milk value chain analysis: industry competitiveness and

Milk value chain analysis:

industry competitiveness and the dairy

policy environment in Pakistan

Sosheel Solomon Godfrey

Submitted in total fulfilment of the requirements for the

degree of

Doctor of Philosophy

School of Animal and Veterinary Sciences

Charles Sturt University

October 2016

DECLARATION

This is to certify that

(i) The thesis comprises my original work towards the PhD except where indicated in the

preface

(ii) Due acknowledgement has been made in the text to all other material used

(iii) The thesis is less than 100,000 words in length, exclusive of tables, maps,

bibliographies and appendices.

Sosheel Solomon Godfrey

I dedicate this research to the hard working farmers of Pakistan, the small ‘dhodhis’ who

live on meagre incomes and to the poor of Pakistan with the prayers that things will

improve one day.

i

ABSTRACT

Dairying is important to Pakistan’s national economy, engaging some 8.8 million small-

scale producer households. Economic comparison of two contrasting agro-ecological

regions, irrigated Okara and rain-fed Bhakkar districts, within Pakistan’s Punjab, revealed

that for dairy enterprises, total costs were often higher than incomes; so many farms (70%

and 60%) were assessed as making losses.

Eighty-two percent of Punjab’s total cultivated area is irrigated and provides the bulk of

Pakistan’s food supply. Further economic analysis of farms in irrigated Okara district,

divided into small milk group (MG1), medium (MG2) and large (MG3) groups based on

their milk production exhibited that all three groups were unprofitable, although the gross

margins were positive for MG2 and MG3. A simulated improved feeding regime of three

times the average concentrate per milking animal showed no improvement in profitability

either. This leads to the important question as to why farmers still produce milk and how

the milk prices are determined at farm gate in the supply chains to which the milk is

supplied.

Informal chains carry 31% of the total production to the final consumer while formal

channels only have 5% market share, yet there is very limited understanding of how these

value chains work. The initial scoping study in this research identified different supply

chain models in both arid and irrigated regions of Punjab. The study highlighted that the

existing large base of milk producers, producing small volumes makes the milk collection

and distribution service extended by middlemen, colloquially known as dhodhi, in the

informal chains, indispensable. The major part of bulk buying by the formal sector comes

from the informal chains. The dairy industry cannot be studied by separating the two

channels. The price setting mechanisms, lack of uniform quantity and quality standards

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and in the irrigated regions, financing function by the informal chains were important

areas identified.

In the scoping phase, a specific rural-urban supply chain identified in irrigated Okara of

Punjab province was further investigated. The chain operated amid a set of unwritten

rules that governed it. Price across the chain was established in an environment in which

margins were low, and technology for milk handling was dated. In irrigated Punjab,

larger milk volumes were handled, and the chain structure was complex with more tiers.

A deeper understanding of these traditional chain subsystems was therefore identified as

an area that required further pursuing.

A value chain analysis framework was further developed through the review of the

literature.

Both qualitative and quantitative techniques were applied for an in-depth study of three

informal rural-urban chains in the irrigated Punjab using this framework. The selection

of these chains was based on the outcome of the scoping study and the need to review

individual cases more thoroughly at the rural–urban fringe where there are burgeoning

populations of milk consumers.

The three chains studied were highly competitive because of the following factors:

relatively low operational costs compared to the formal sector

minimal capital investment

product differentiation in the retail marketplace

nature of human relationships

governance of finances at various levels of the chain

The chains were held together because of the benefits derived from the various partners

through the financing system in the chains that also locked-in each pair of parties involved

in the sequence of transactions. The informal chains can further be characterised as “pro-

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poor” because they create large income generation and employment opportunities. Each

chain had its own quality and quantity standards, which assisted in generating profits. The

margins across the chains were tight, but the chain intermediaries made money by diluting

milk with ice or water. Similarly, the quantity units varied at different tiers and across the

three informal case study chains. Milk was procured in one unit and sold in another. As a

result of these changing volume measures, both producers and consumers consider

themselves financial losers.

The informal chain milk-collectors (‘dhodhis’) provided small-scale dairy farmers, access

to interest-free loans/cash advances. In effect, these chains offered a line of credit to

farmers, which was their regular stream of income and the key reason for farmers

supplying milk to informal channels. This credit is also one of the probable reasons small

dairy holders continue to operate despite losing money on their milk production

operations. To the contrary, formal processors made a delayed payment for the milk

procured and offered no initial cash advances, which are so important to the sustainability

of smallholder dairy producers.

The Pakistani consumers preferred fresh milk and bought it at a lower price, supplied by

the informal chains. Butterfat concentration in milk was the attribute most valued by these

consumers. There was little concern for health and safety, irrespective of socioeconomic

status. The measurement units for milk varied greatly from shop to shop. The consumer

naively facilitated the malpractice of selling milk in variable volumes, thereby enhancing

the profit margins in retail shops. Milk adulteration mostly through the addition of water

along the chains was known by the consumers but a compromise they accepted.

An important policy intervention outcome from this research is the need for uniform

quality and quantity standards and a balanced pricing mechanism across the industry.

Farm gate prices were influenced and controlled by the formal processors who held more

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buying power because of their oligopolistic market structure. The government set the

retail milk prices as a loose benchmark, but these prices were likewise influenced by some

powerful large ‘dhodhis’ who also operated as retailers and were also known to supply

milk to the formal chain.

In future, a platform is needed to advocate the case of farmers, consumers and ‘dhodhis’

alike. There has to be a consultative process to set quality and quantity standards and a

pricing mechanism along the chains while ensuring that the formal sector does not receive

an undue advantage.

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ACKNOWLEDGEMENTS

This PhD journey started with my association with the Australia-Pakistan Agriculture

Sector Linkages Program (ASLP), an Australian bilateral grant aid to Pakistan for the

development of dairy, mango and citrus industries. I managed ASLP in Pakistan from

February 2006 to November 2009, and I am indebted to it.

The job gave me ample opportunities to travel within Pakistan and to Australia, China,

Singapore, and Dubai. It connected me with some lifelong friends and mentors in both

Pakistan and Australia. The list is endless. However, I will mention Christian Roth and

Les Baxter, both my senior colleagues from Australian Centre for International

Agricultural Research (ACIAR), based in Canberra.

I was exposed to value chain thinking though the ASLP mango supply chain project lead

by Ray Collins and Tony Dunne from the University of Queensland. The umbrella

program raised my interest in studying supply chains and end markets. While

coordinating ASLP activities, I became keen to tell my story based on my research. This

interest was raised further by ACIAR’s plan to support a policy project to develop dairy

and horticulture industries of Pakistan. This initiative, however, was not realised but led

me to further interest in the economics of smallholder producers, and policies conducive

to addressing some of the challenges faced by Pakistan.

I meanwhile applied twice for an ACIAR scholarship and despite all the support from my

senior ACIAR colleagues that also did not materialise. I then decided to move on as I

had been granted a skilled migrant visa for United Kingdom (UK). My family and I lived

in London for little over a year until December 2010 while all the processes of admission

and visas were completed. The help and support that I got from my wife’s family settling

vi

in the UK is unforgettable. Living in the UK was a rewarding experience in terms of

knowing a different culture and getting ready for the life ahead in Australia.

The door for this scholarship had opened during my last visit to Australia in November

2009 in my role with ACIAR and endorsed by Peter Horne, the then Programme Manager

with ACIAR. This Ph.D. was made possible through the support of Peter Wynn, a fatherly

figure, to whom I will be indebted forever as he made it happen through support from the

ASLP dairy project in Pakistan, which Peter was leading since 2006. After organising and

attending ASLP 2nd phase planning meeting in Brisbane, I flew to Sydney with the ASLP

dairy project team manager David McGill and was driven all the way to beautiful Wagga

Wagga. We then drove to Orange to meet the smiling and gentle Karl Behrendt with

whom I briefly discussed my initial research proposal.

The support and communication with Peter and David continued, while I was in London

until our arrival in Australia on 5th December 2010. There had been a drought in Australia

for almost ten years, and the recent rains had brought flooding in many places in Australia

including North Wagga, which was all submerged under water when we first arrived.

Despite flooding, the general attitude was of thankfulness and relief as the rains were seen

more of blessing rather that trouble. There was water all over the place and yet we did

not have to worry about anything. Peter Wynn with a bouquet of flowers along with David

McGill and ALSP dairy project in Country Manager Hassan Warriach received us with

broad smiles and open arms at the railway station in Wagga Wagga. David hosted us for

about a month and then moved to our rented accommodation on 7th January 2011. In these

initial months, the love and support by Lyn Wynn were also a great blessing to us.

Coming back to studies after 11 years of work life was not easy and meant going back to

the basics, but thankfully I had all the support and patience of my supervisors, each unique

in their skills.

vii

Karl Behrendt’s constant commitment and guidance as my Supervisor, particularly in

doing farm economic analysis is commendable. Tom Nordblom as my Co-Supervisor

also generously gave his time, whenever needed. Peter Wynn had a deep understating of

the big picture in Pakistan and kept guiding me. In May 2012, Peter Wynn identified

Gavin Ramsay as my Principal Supervisor who took over from Peter in October 2012.

Gavin’s insight and encouragement is immeasurable. He had the vision to see how

valuable my work was. His background and understanding of the qualitative analysis and

supply chains meant a great deal in deciding what and how many times to collect the data

and how best to analyse it. Big thanks is due to Ann Cowling who started giving me

advice on statistical analysis from June 2011.

In November (22-23) 2011, I met Dr Ray Collins and Dr Tony Dunne at an ACIAR

workshop. This meeting started an exchange of ideas and both gentlemen provided

valuable guidance to refine my thinking about fundamental marketing and value chain

concepts and clarity about my research questions. The feedback, guidance, and

encouragement continued with our meeting again mid-June 2012, September 2012 and

2014 and occasionally through emails.

David McGill’s many hours of commitment to guide me through a whole mountain of the

longitudinal survey data that the ACIAR dairy project had collected in Pakistan from

January 2007 to December 2009 is commendable. I used this data to study the economics

of mixed farming systems in Pakistan. Thanks also go to David for reading my thesis

chapters at various stages and giving helpful comments.

Gail Fuller and Deanna Duffy from Charles Sturt University (CSU) Spatial Analysis Unit

(SPAN) were very helpful in developing questionnaires and making maps. The CSU

librarians Karen Mackney, Lee-Anne McInerney and Claudio Dionigi, are thankfully

viii

acknowledged for their support whenever needed. I also would like to thank Liz Anschaw

in helping me with the formatting of my thesis.

Big thanks also go to all the Pakistani ASLP dairy project colleagues including Hassan

Warriach, Hafiz Ishaq, Sajid Latif, Zara Naqvi, Ghulam Mustafa and Karamat Ali for

their support during by first scoping research trip to Pakistan in September 2011. In June

and July 2012, I went back to collect more data. The whole Pakistani team was supportive

again, but Hafiz Ishaq with his local knowledge of rural areas and preparation of

groundwork for me in identifying the case study chains was remarkable. The support of

Punjab livestock department officials is also acknowledged. Similarly, Naveed Aslam my

fellow PhD student from Charles Sturt University (CSU), based in Lahore at that time for

his research, supported me a great deal. His local knowledge of Lahore city and going to

milk retail shops in different parts of the city was very helpful. Naveed lightened up the

stressful moments with his light jokes, as chasing the ‘dhodhis’ and milk retailers was not

easy at times.

Guidance and input of Professors Bill Malcolm, Kevin Parton, and Mark Morrison, whom

I met at various stages of my PhD, are also thankfully acknowledged. I also thank

Jonathan Holland for his support in reading and commenting on my drafts, John Hassall

for reading my draft chapters and Mary Lange for her succinct advice on a few aspects in

terms of clarity. Their selfless support is highly appreciated.

I am also thankful for the many friends made during the PhD journey including Sahibzada

Shafiullah, Naveed Aslam, Riaz Khan, Shoaib Tufail, Vivek Pande, Emmanuel Qunasah,

Vaibhav Gole and many others. We shared our joys and sorrows.

We as a family were also very fortunate to find fellowship and love from Wagga Wagga

Baptist church that has become our second home away from home. David Strong, Andrew

Skewes, and Nick Menzies have been a blessing, great prayer partners, and supporters.

ix

Last but not the least, I am thankful to my wife Cynthia and daughter Eliana for their love

and the sacrifices that they made as I was not able to give them enough time, as a family

and many times they had to bear with me in times of stress. My mother Mrs Veena

Godfrey for her unconditional love and prayers and to my belated father Anwar Godfrey

for his contribution to my studies and his vision for us to work hard and achieve good in

life.

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COMMON LOCAL TERMINOLOGIES, MILK QUANTITY

UNITS, AND QUALITY TESTING

In alphabetical order (most of these and some additional terminologies also explained as

footnotes):

“Burfi” is sweet confectionary made of condensed milk and sugar

“Chokker” is wheat bran fed to the livestock

“Cow” is the mature female of cattle (Bos taurus). Since Pakistan has both cows and

buffaloes (Bubalus bubalis), the term cow in this thesis refers to female cattle only and not

buffaloes. For female buffalo the term buffalo has been used.

“Desi ghee” is clarified butter, prepared by simmering butter and removing the residue.

“Dhodhi,” the colloquial name used for milkmen or middlemen/intermediaries who buy and

sell milk. They have been categorised as small, medium and large based on their position in

the chain(s) and the function(s) they perform.

Foreign currency referred to in this thesis is United States dollar (US$) unless otherwise

mentioned

“Formal processor” for bigger market players with more developed cool chain infrastructure

and selling packaged UHT (Ultra Heat Treated) milk though a few are also selling pasteurised

milk.

Formula used to standardize milk in this research: The formula by International Farm

Comparison Network (IFCN) has been used, which standardises milk to 4% fat and 3.3%

protein using the energy corrected milk formula (ECM):

ECM milk = (milk production * (0.383 * % fat + 0.242 * % protein + 0.7832) / 3.1138)

“Khal” is cotton seed cake a commonly used feed supplement for large ruminants

“Khoya” is milk thickened by heating in an open iron pan. The moisture content may vary

depending on the use

“Kulfi” is traditional ice cream

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“Lassi” is a blend of yoghurt and water, and sometimes fruit is also added. It can be both

salted and sweet.

Local quantity units: Local units used for milk from farm to the final consumer were

complex in the local milk value chains. The following table provides some basic information

about these units for milk:

i. Smaller Unit

– Litre (L) by volume 1L = 1000 ml & by Mass 1L = 1.033 kg

– In local chains, litre was 850 to 1150 ml depending on where it was used

– Kilogram (kg) by volume 1kg = 0.97 ml at 15°C & by Mass 1kg = 1000grams

– In local chains kg was 850 to 1150 grams depending on where it was used

– Seer is a traditional local unit that was used for both mass and volume in British India (Pakistan

was also part of it)

– 1 seer = 0.93310 kg, however, were many local variants

– Gadvi is a local unit of mass and/or volume that has evolved locally as milk used to cross

rivers in round pots that could float

– 1 Gadvi = 800 to 1250 ml or grams as it is not standardised and has many local variants

– Chatank is a local unit of mass and/or volume that has evolved locally

– 1 kg = 16 chatanks and each chatank = 62.5 grams

– Locally, however, a Chatank varied from 50 to 62.5 grams

ii. Larger Unit

– Maund (a local unit) also called panda in the milk chains, which is an anglicised name for a

traditional unit of mass used in British India (Pakistan was also part of it)

Historically: 1 maund = 37.324 kg OR 1 maund = 40 seer

In local chains 1maund = 37kg or seer AND/OR 40kg/40litre at rural end AND/OR 46 litres

at urban end of the market

Data Source: Author’s field research and various websites to confirm official weights

Local milk quality tests in the informal milk chains:

i. Organoleptic test: This is the simplest test: just looking (eyesight) and smelling. If the

milk has a bad smell, or abnormal colour, or contains particles, it should be rejected.

ii. Lactometer (LR) test: Milk has a specific gravity and when adulterated with water

or other materials, the density of milk changes from its normal value to abnormal.

Lactometer test is designed to detect the change in density of milk. Adulterator may

adulterate milk in such a way that the lactometer does show adulteration. It then

becomes important to taste the milk to find out if it is too sweet or salty as well as

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to check unusual sediments at the bottom of milk. Samples of milk from individual

animals as well as buffaloes and cows have different lactometer readings. Feed also

impacts the readings. Carried out together with the Gerber butterfat test, it enables

the buyer to calculate the total milk solids (% TS) and solids not fat (SNF). A small

quantity of milk is poured into a measuring cylinder. Lactometer degrees (ºL) are

associated with the temperature of the milk to get a correct reading.

iii. The Gerber Butterfat test: The fat content of milk and cream is the most important single

factor in determining the price to be paid. Butterfat tests are also done to make accurate

adjustments of the butterfat percentage to standardise milk. Ten mI of sulphuric acid

followed by 11 ml of milk is added to the butyrometer. Next, 1 ml of Amyl alcohol is added,

and the butyrometer is shaken well. The butyrometer is then placed in the centrifuge with

the stem (scale) pointing towards the centre of the centrifuge and spined for a few minutes

and then removed. The top end provides an estimated butterfat percentage in milk.

iv. “Kaan mar kar” test: Another common traditional quality test known as “kaan mar kar”

used by the milk retailers is described in some detail in the thesis. In this test, milk is boiled

to obtain solids.

“Matti” is blue plastic cans of 128 and 160 litres used for collection of milk by the large

dhodhis of Kasur chain while Okara chains large dhodhi also uses them for urban milk supply

“Mixed” milk is both cow and buffalo milk

“Munshi” a record keeper cum milk tester

“Producer” as well as “Farmer” used for milk producers

“Rabri” is condensed sweet milk to which nuts may be added

“Rate” is a common local term used for price

“Rs” has been used for Pakistani Rupee instead of PKR “Retailers” for specialised retail milk

shop operators who sell unpackaged raw fresh milk to the final consumer that is boiled before

consumption

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“Wanda’ is balanced concentrate feed for animals OR concentrate ration

“Yoghurt” locally called “Dahi” is a fermented milk product produced by bacterial

fermentation of milk

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Table of Contents

ABSTRACT ................................................................................................................................. I

ACKNOWLEDGEMENTS ....................................................................................................... V

COMMON LOCAL TERMINOLOGIES, MILK QUANTITY UNITS, AND QUALITY

TESTING .................................................................................................................................... X

TABLE OF CONTENTS ....................................................................................................... XIV

TABLE LIST .......................................................................................................................... XXI

CHAPTER 1. THESIS INTRODUCTION AND STRUCTURE ...................................... 1

BRIEF INTRODUCTION AND BACKGROUND TO THE RESEARCH .................................. 1

RESEARCH PROBLEM AND RESEARCH QUESTIONS ......................................................... 2

THESIS DESIGN, METHODOLOGY, AND METHODS USED ................................................ 2

DELIMITATIONS OF SCOPE AND KEY ASSUMPTIONS ...................................................... 6

CONCLUSION .............................................................................................................................. 7

CHAPTER 2. MILK VALUE CHAIN ANALYSIS: INDUSTRY

COMPETITIVENESS AND THE DAIRY POLICY ENVIRONMENT IN PAKISTAN .... 8

THE WORLD ................................................................................................................................. 8

PAKISTAN .................................................................................................................................. 11

MACROECONOMY, AGRICULTURE, LIVESTOCK AND EMPLOYMENT ............ 11

POPULATION, POVERTY AND UNDERNUTRITION AND INCOMES ................... 12

HOUSEHOLD BUDGETS AND MILK CONSUMPTION ............................................. 13

MILK PRODUCTION IN A MIXED CROP-LIVESTOCK FARMING SYSTEM ........ 15

MILK SUPPLY AND DEMAND ..................................................................................... 18

FOOD SYSTEMS ........................................................................................................................ 23

COMPETITION AND THE ROLE OF FIRMS IN A MARKET ECONOMY, COMPETITIVE

ADVANTAGE, AND THE VALUE CHAIN ...................................................................................... 24

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VALUE CHAINS APPROACH AND ANALYSIS FRAMEWORK ......................................... 26

VALUE CHAINS ACTORS AND THEIR CORE ROLES, TECHNOLOGY AND

INFRASTRUCTURE AND PHYSICAL SPOILAGE RISKS .................................................... 32

PHYSICAL AND FINANCIAL FLOWS AND CAPITAL INVESTED ALONG THE

CHAIN ......................................................................................................................................... 33

PRODUCT SEASONALITY, PRICE DETERMINATION, PRICING DYNAMICS

AND INFORMATION FLOWS .................................................................................................. 37

GOVERNANCE ALONG THE VALUE CHAINS ......................................................... 38

CHAPTER 3. DAIRYING AND WHOLE-FARM ECONOMICS OF CROP-

LIVESTOCK FARMING SYSTEMS; COMPARING ARID AND IRRIGATED

DISTRICTS OF PUNJAB, PAKISTAN ..................................................................................48

MATERIALS AND METHODS: ................................................................................................ 48

RESULTS: ................................................................................................................................... 53

MILK ENTERPRISE ANALYSIS AND COMPARISON FOR THE TWO REGIONS . 57

LIVESTOCK ENTERPRISE AND WHOLE FARM ECONOMIC ANALYSIS ............ 59

CONCLUSIONS: ......................................................................................................................... 61

CHAPTER 4. DAIRYING IN AN IRRIGATED MIXED CROP-LIVESTOCK

FARMING SYSTEM OF PUNJAB, PAKISTAN: ENTERPRISE PROFITABILITY

ANALYSIS FOR SMALLHOLDERS .....................................................................................65


RESULTS .................................................................................................................................... 70

MILK ENTERPRISE ECONOMIC ANALYSIS FOR SEGREGATED MILK

PRODUCTION GROUPS (MG): ................................................................................................ 72

LIVESTOCK ENTERPRISE AND WHOLE FARM ECONOMIC ANALYSIS FOR

MILK PRODUCTION GROUPS (MG): ..................................................................................... 74

DISCUSSION AND CONCLUSION: ......................................................................................... 75

CHAPTER 5. A SIMPLE VALUE CHAIN FRAMEWORK TO HIGHLIGHT

IMPORTANT DAIRY INDUSTRY ISSUES AND PRO-POOR BENEFITS IN A

DEVELOPING COUNTRY CONTEXT .................................................................................78

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BUYING AND SELLING ................................................................................................ 84

FINANCE.......................................................................................................................... 84

STANDARDISATION ..................................................................................................... 84

PRICE DETERMINATION .............................................................................................. 85

TRANSPORT, STORAGE AND PROCESSING ............................................................ 85

RISK BEARING ............................................................................................................... 85

RESULTS: .................................................................................................................................... 86

BUYING AND SELLING: ............................................................................................... 88

FINANCE.......................................................................................................................... 91

CONSUMER VALUE ...................................................................................................... 94

STANDARDISATION ..................................................................................................... 94

PRICE DETERMINATION .............................................................................................. 97

TRANSPORT, STORAGE AND PROCESSING .......................................................... 100

RISK BEARING ............................................................................................................. 101

DISCUSSION:............................................................................................................................ 102

BUYING AND SELLING .............................................................................................. 103

FINANCE AND CONTRACTUAL ARRANGEMENTS .............................................. 103

STANDARDISATION AND CONSUMER VALUE .................................................... 104

PRICE DETERMINATION ............................................................................................ 105

TRANSPORT, STORAGE, PROCESSING AND RISK BEARING ............................. 106

CONCLUSION: ......................................................................................................................... 107

CHAPTER 6. IDENTIFYING PRODUCER, MIDDLEMEN, RETAILER AND

CONSUMER ISSUES FROM A PRO-POOR VALUE CHAIN PERSPECTIVE: A

DAIRY CASE STUDY FROM IRRIGATED PUNJAB OF PAKISTAN .......................... 108

METHODS: ................................................................................................................................ 108

RESULTS: .................................................................................................................................. 113

TECHNICAL SUBSYSTEM AND CONTRIBUTORS TO THE VALUE CHAIN ...... 114

GOVERNANCE IN THE VALUE CHAIN ................................................................... 119

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PRICE SETTING AND INFORMATION FLOWS ALONG THE CHAIN ................. 123

ECONOMIC SUBSYSTEM OF THE VALUE CHAIN ................................................ 124

DISCUSSION AND CONCLUSION: ....................................................................................... 128

CHAPTER 7. INFORMAL MILK VALUE CHAINS FROM THE URBAN

CONSUMER’S PERSPECTIVE: A DEVELOPING COUNTRY SCENARIO ................131

METHODS ................................................................................................................................ 131

RESULTS .................................................................................................................................. 137

DEMOGRAPHICS ......................................................................................................... 138

CONSUMER PREFERENCE AND BUYING BEHAVIOUR ...................................... 139

CONSUMER VALUE .................................................................................................... 143

UNMET NEEDS ............................................................................................................ 145

DISCUSSION AND CONCLUSION ........................................................................................ 146

CHAPTER 8. MILK VALUE CHAIN ANALYSIS: INDUSTRY

COMPETITIVENESS AND THE DAIRY POLICY ENVIRONMENT IN PAKISTAN 152

METHODS ................................................................................................................................ 152

RESULTS .................................................................................................................................. 161

VALUE CHAIN ACTORS, TECHNOLOGY AND INFRASTRUCTURE ALONG THE

CHAIN AND SPOILAGE RISKS ............................................................................................. 161

CONSUMER VALUE, QUALITY DETERMINATION AND GRADING AND

QUANTITY MEASUREMENTS ALONG THE CHAIN AND GROSS MARGINS .............. 162

PRODUCT SEASONALITY, PRICE DETERMINATION, PRICING POWER

DYNAMICS AND INFORMATION FLOWS ......................................................................... 168

FACILITATING FUNCTIONS OF FINANCING AND PAYMENT SCHEDULES,

RELATIONSHIPS AND POWER DYNAMICS ...................................................................... 171

DISCUSSION AND CONCLUSION: ....................................................................................... 174

KASUR-LAHORE CHAIN IMPROVED STATE IMPLICATIONS ............................ 178

OKARA-LAHORE CHAIN IMPROVED STATE IMPLICATIONS ........................... 181

PAKPATTAN-LAHORE CHAIN IMPROVED STATE IMPLICATIONS .................. 186

QUALITY STANDARD AND INDUSTRY WIDE COMPETITION .......................... 189

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CHAPTER 9. CONCLUSION: ........................................................................................ 193

REFERENCES ........................................................................................................................ 202

APPENDICES.......................................................................................................................... 215

CHAPTER 3: APPENDIX A (DETAILS OF EQUATIONS / FORMULAS USED): ...................... 215

CHAPTER 3: APPENDIX B (KEY ASSUMPTIONS): .............................................................. 224

CHAPTER 4: APPENDIX C (DETAILS OF EQUATIONS / FORMULAS USED): ...................... 231

CHAPTER 4: APPENDIX D (KEY ASSUMPTIONS): .............................................................. 240

CHAPTER 5 AND 6: APPENDIX E QUESTIONNAIRES .......................................................... 246

CHAPTER 8 APPENDIX F: RESULTS: CASE STUDY 1: KASUR-LAHORE FRESH

UNPACKAGED MILK VALUE CHAIN ..................................................................................... 261

F8.1 INTRODUCTION OF KASUR-LAHORE VALUE CHAIN ACTORS, TECHNOLOGY

AND INFRASTRUCTURE ALONG THE CHAIN AND SPOILAGE RISKS ........................... 262

F8.2 CONSUMER VALUE, QUALITY DETERMINATION; GRADING AND QUANTITY

MEASUREMENTS ALONG THE KASUR-LAHORE CHAIN AND GROSS MARGINS ....... 270

F8.2.1. FINAL CONSUMERS ........................................................................................... 275

F8.2.2. PRODUCERS, SMALL DHODHIS, LARGE DHODHI AND FORMAL

PROCESSOR ..................................................................................................................... 276

F8.3 PRODUCT SEASONALITY, PRICE DETERMINATION, PRICING POWER

DYNAMICS AND INFORMATION FLOWS ............................................................................. 285

F8.3.1. FINAL CONSUMER’S RESPONSE TO PRICE CHANGES ............................... 290

F8.3.2. RETAIL URBAN PRICING .................................................................................. 290

F8.3.3. PRICE BETWEEN SMALL DHODHI AND LARGE DHODHI .......................... 291

F8.3.4. FARM GATE RURAL PRICING .......................................................................... 292

F8.4 FACILITATING FUNCTIONS OF FINANCING AND PAYMENT SCHEDULES,

RELATIONSHIPS AND POWER DYNAMICS.......................................................................... 293

F8.4.1. PRODUCER AND SMALL DHODHI .................................................................. 295

F8.4.2. SMALL DHODHI AND LARGE DHODHI .......................................................... 297

F8.4.3. LARGE DHODHI AND RETAILERS .................................................................. 298

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CHAPTER 8 APPENDIX G: RESULTS: CASE STUDY 2: OKARA - LAHORE FRESH,


G8.1 INTRODUCTION OF VALUE CHAIN ACTORS, PRODUCT PHYSICAL FLOWS AND

SPOILAGE RISKS ....................................................................................................................... 301

G8.2 CONSUMER VALUE, QUALITY DETERMINATION; GRADING AND QUANTITY

MEASUREMENTS ALONG THE OKARA-LAHORE CHAIN AND GROSS MARGINS ...... 306

G8.2.1. FINAL CONSUMERS ................................................................................................. 311

G8.2.2. PRODUCERS, SMALL DHODHIS, MEDIUM DHODHI, LARGE DHODHI AND

RETAILERS .............................................................................................................................. 311

G8.3 PRODUCT SEASONALITY, PRICE DETERMINATION, PRICING POWER

DYNAMICS AND INFORMATION FLOWS ALONG OKARA-LAHORE MILK CHAIN ... 320

G8.3.1. FINAL CONSUMER’S RESPONSE TO PRICE CHANGES .................................... 325

G8.3.2. RETAIL URBAN PRICING ........................................................................................ 325

G8.3.3. FARM GATE RURAL PRICING BETWEEN LARGE DHODHI, MEDIUM

DHODHI, SMALL DHODHIS AND PRODUCERS ................................................................ 326

G8.4 FACILITATING FUNCTIONS OF FINANCING AND PAYMENTS, RELATIONSHIPS

AND POWER DYNAMICS ......................................................................................................... 329

G8.4.1. PRODUCER AND SMALL DHODHI ........................................................................ 333

G8.4.2. SMALL AND MEDIUM DHODHI ............................................................................ 334

G8.4.3. MEDIUM AND LARGE DHODHI ............................................................................. 337

G8.4.4. LARGE DHODHI AND RETAILERS ........................................................................ 337

CHAPTER 8 APPENDIX H: RESULTS: CASE STUDY 3: PAKPATTAN - LAHORE FRESH,


H8.1 INTRODUCTION OF VALUE CHAIN ACTORS, PRODUCT PHYSICAL FLOWS AND

SPOILAGE RISKS ....................................................................................................................... 341

H8.2 CONSUMER VALUE, QUALITY DETERMINATION; GRADING AND QUANTITY

MEASUREMENTS ALONG THE PAKPATTAN-LAHORE CHAIN AND GROSS MARGINS

346

H.8.2.1 FINAL CONSUMERS ................................................................................................. 350

xx

H8.8.2. PRODUCERS AND SMALL DHODHIS .................................................................... 350

H8.2.3. SMALL AND LARGE DHODHI AND RETAILER................................................... 351

H.8.3 PRODUCT SEASONALITY, PRICE DETERMINATION, PRICING POWER

DYNAMICS AND INFORMATION FLOWS ............................................................................. 357

H8.3.1. FINAL CONSUMER’S RESPONSE TO PRICE CHANGE ....................................... 362

H8.3.2. RETAIL URBAN PRICING ........................................................................................ 362

H8.3.3. FARM GATE RURAL PRICING BETWEEN LARGE DHODHI, SMALL DHODHI

AND PRODUCERS AND THE ROLE OF FORMAL PROCESSORS .................................... 362

H8.4 FACILITATING FUNCTIONS OF FINANCING AND PAYMENTS, RELATIONSHIPS

AND POWER DYNAMICS ......................................................................................................... 364

H8.4.1. PRODUCER AND SMALL DHODHI ........................................................................ 368

H8.4.2. SMALL AND LARGE DHODHI AND RETAILER1 ................................................. 370

CHAPTER 8 APPENDIX I: LARGEST FORMAL PROCESSOR IN THE DAIRY INDUSTRY ...... 372

CHAPTER 8: APPENDIX J QUESTIONNAIRES ..................................................................... 374

xxi

Table List

Table 1: Farm scale and the number of farms, livestock and associated household (HH) numbers

in Pakistan and Punjab. Punjab’s proportion is indicated in parenthesis (Number in millions). .16

Table 2: Mean physical and economic attributes of agricultural land and livestock for farm survey

data. Standard error of mean (SE) indicated in parentheses. Results of t-tests comparing means

.....................................................................................................................................................55

Table 3: Mean production and economics of milk enterprise. Mean with Standard error of means

(SE) indicated in parentheses. Results of t-tests comparing means .............................................58

Table 4: Mean economic attributes for livestock and whole livestock activity. Mean with Standard

error of means (SE) indicated in parentheses. Results of t-tests comparing means .....................60

Table 5: Mean physical attributes, average standard error of difference (SE) and p-value of

agricultural land and livestock for farm survey data segregated into milk production classes for

the irrigated Okara district ...........................................................................................................70

Table 6: Mean economics of milk enterprise, average standard error of difference (SE) and p-

value for farm survey data of irrigated Okara segregated into milk production classes ..............73

Table 7: Mean economic returns for meat production and whole livestock activity. Mean with

Standard error of means (SE) indicated in parentheses. Results of t-tests comparing means. .....74

Table 8: Chain actors studied at various tiers in Pakistan’s dairy industry. .................................80

Table 9: Data collection and analysis framework for milk value chain scoping study ................82

Table 10: Capital assets, time and product volumes along the chain ...........................................89

Table 11: Contractual arrangements and cash advances along the chain ....................................92

Table 12: Criterion to assess milk quality at various tiers and within formal and informal milk

chains of two regions ...................................................................................................................95

Table 13: Nutritional facts per 100 ml mentioned on UHT packaged milk of three major

processors .....................................................................................................................................96

Table 14: Average price range at farm gate and retail end formal and informal chains in the two

regions ..........................................................................................................................................98

Table 15: Cow and buffalo milk composition ...........................................................................110

Table 16: Functions of participants, geographical location, time input and technology used to

handle milk along the chain .......................................................................................................116

Table 17: Governance along the milk value chain .....................................................................120

Table 18: Physical and financial flows along the milk value chain ...........................................126

xxii

Table 19: Purposive sample of 35 consumers from 7 retail milk shops at the end of three rural-

urban milk value chains. ............................................................................................................ 134

Table 20: Quality cues and quality attributes for foods (Oude Ophuis & Van Trijp, 1995) .... 137

Table 21: Demographics of consumers (n=35) ......................................................................... 138

Table 22: Consumer’s priority ranking on scale of 1 (highest importance) to 3 (lowest importance)

for the preferred form and source of milk purchase (n=35) ...................................................... 140

Table 23: Aggregate of the priority ranking on a scale of 1 (highest in importance) to 5 (lowest in

importance) for consumer’s experience quality attributes, intrinsic quality cues and credence

quality attributes. Extrinsic quality cues while buying fresh, unpackaged milk, ranked on a scale

of 1 (highest) to 3 (lowest) for consumers (n=35). .................................................................... 143

Table 24: Price, unit, quantity (authors’ field research) and quality (Aslam, 2015) for each shop

of the seven retail milk shops at the end of the three rural-urban milk value chains................. 148

Table 25: Number of rural-urban milk value chains participants interviewed and the number of

tiers of each chain and the formal milk processors/companies ................................................. 157

Table 26: Physical and financial flows along the Kasur-Lahore fresh, unpackaged milk value

chain .......................................................................................................................................... 165

Table 27: Physical and financial flows along the Okara-Lahore fresh unpackaged milk value chain

................................................................................................................................................... 166

Table 28: Physical and financial flows along the Pakpattan-Lahore fresh, unpackaged milk value

chain .......................................................................................................................................... 167

Table 29: Financial flows based on actual quantity and quality on the basis of improved chain

state along the Kasur-Lahore milk value chain ......................................................................... 180


state along the Okara-Lahore milk value chain ......................................................................... 184


state along the Pakpattan-Lahore milk value chain ................................................................... 188

Table 32: Technology and infrastructure, labour and time along the rural Kasur-urban Lahore

milk value chain ........................................................................................................................ 268

Table 33: Kasur-Lahore milk quality attribute perspective of various chain actors from farm to

final consumer ........................................................................................................................... 272

Table 34: Physical and financial flows and capital invested by each actor along the Kasur-Lahore

milk value chain ........................................................................................................................ 281

xxiii

Table 35: Punjabi and Gregorian calendar and buffalo & cow milk production / supply for Kasur

Lahore milk value chain .............................................................................................................287

Table 36: Technology and infrastructure, labour and time along the rural Okara-urban Lahore

milk value chain .........................................................................................................................305

Table 37: Okara-Lahore milk quality attribute perspective of various chain actors from farm to

final consumer ............................................................................................................................308

Table 38 : Physical and financial flows and capital invested by each actor along the Okara-Lahore

milk value chain .........................................................................................................................317

Table 39: Punjabi and Gregorian calendar and buffalo & cow milk production / supply along

Okara-Lahore milk chain ...........................................................................................................322

Table 40: Attributes important to seller farmer and all other buyers of milk in the rural Okara-

urban Lahore milk value chain: .................................................................................................332

Table 41: Technology and infrastructure, labour and time along the rural Pakpattan-urban Lahore

milk value chain .........................................................................................................................345

Table 42: Pakpattan-Lahore milk quality attribute perspective of various chain actors from farm

to final consumer........................................................................................................................348

Table 43: Physical and financial flows and capital invested by each actor along the Pakpattan-

Lahore milk value chain .............................................................................................................355

Table 44: Punjabi and Gregorian calendar and buffalo & cow milk production / supply for

Pakpattan Lahore chain ..............................................................................................................359

Table 45: Attributes important to seller farmer and all other buyers of milk in the rural Pakpattan-

urban Lahore milk value chain: .................................................................................................367

xxiv

Figure List

Figure 1: Seasonal changes in milk production and the related practices ................................... 18

Figure 2: Fresh raw milk flows from rural and peri-urban producers to urban consumer ........... 20

Figure 3: Value Chain Analysis Framework ............................................................................... 32

Figure 4: Governance continuum from open markets to vertical integration .............................. 38

Figure 5: Governance external to the chain and internal chain governance for an array of firm’s

dealings from open markets to vertical integration ..................................................................... 39

Figure 6: Governance of relationship and their patterns ............................................................. 42

Figure 7.a. Maps of Pakistan and Punjab; b. Map of Punjab showing Okara and Bhakkar districts.

..................................................................................................................................................... 49

Figure 8. Linear regressions for (a) average milk production per milking animal per farm for the

concentrates fed, and (b) total milk production per farm and land allocation for green fodders in

irrigated Okara and arid Bhakkar districts of Punjab .................................................................. 56

Figure 9: Milk gross margin comparison between irrigated Okara and arid Bhakkar districts of

Punjab .......................................................................................................................................... 58

Figure 10: Milk profit & new milk profit comparisons between irrigated Okara and arid Bhakkar

districts of Punjab ........................................................................................................................ 59

Figure 11: Livestock and whole farm gross margin comparison between irrigated Okara and arid

Bhakkar districts of Punjab ......................................................................................................... 60

Figure 12: Whole farm operating and net profit comparison between irrigated Okara and arid

Bhakkar districts of Punjab ......................................................................................................... 61

Figure 13 a. Maps of Pakistan and Punjab; b. Map of Punjab showing irrigated Okara district. 67

Figure 14: Milk production per milking animal in relation to concentrates fed for each of the three

milk groups .................................................................................................................................. 71

Figure 15a. Map of Pakistan and Punjab; b. Map of Punjab showing rural Bhakkar district and

D.I. Khan city (D.I.Khan is in Khyber Pakhtunkhwa province) in the arid region and Okara and

Pakpattan districts and Sahiwal and Lahore cities in the irrigated region of Punjab ................. 79

Figure 16: Various milk value chain models from rural producer to final consumer.................. 87

Figure 17: Pyramid of the relationships between participants in the irrigated Okara-Lahore fresh

unpackaged milk value chain .................................................................................................... 114

Figure 18a. Maps of Pakistan and Punjab; b. Map of Punjab showing rural arid Bhakkar and rural

irrigated Pakpattan, Kasur and Okara districts supplying milk to metropolitan urban Lahore city

................................................................................................................................................... 132

xxv

Figure 19: Distribution of total daily milk purchased by consumer households standardised to

litres at each of the seven shops (different units used by the seven retailer milk shops are explained

further in Table 24). ...................................................................................................................140

Figure 20: Percentage of consumer’s (n=35) a) preferred fresh milk source, b) claim to be able to

differentiate buffalo and cow milk, and c) understanding of units of milk purchased. ..............142

Figure 21: Milk attributes preferred by the consumers (n=35) ..................................................144

Figure 22: Distribution of years for milk purchased by consumer households from specialised

milk retail shops (n=35) .............................................................................................................145

Figure 23a. Map of Pakistan highlighting the Punjab province; b. Map of Punjab showing Kasur

district and Lahore city ..............................................................................................................154

Figure 24: Multiple case study procedure ..................................................................................155

Figure 25: Changes in milk composition and extent of dilution assessed at each level of the Kasur-

Lahore milk value chain : a. Added water percentage, b. Fat percentage and c. Protein percentage

Data Source: (Aslam, 2015) .......................................................................................................179

Figure 26: Changes in milk composition and extent of dilution assessed at each level of the Okara-

Lahore milk value chain : a. Added water percentage, b. Fat percentage and c. Protein percentage

...................................................................................................................................................183

Figure 27: Changes in milk composition and extent of dilution assessed at each level of the

Pakpattan-Lahore milk value chain : a. added water percentage, b. fat percentage and c. protein

percentage ..................................................................................................................................187

Figure 28: Kasur-Lahore chain model and product physical flows ...........................................261

Figure 29: Quantity and quality along the Kasur-Lahore chain .................................................274

Figure 30: Pricing mechanism along the Kasur-Lahore chain ...................................................288

Figure 31: Price information flows along the Kasur-Lahore chain ............................................289

Figure 32: Financing, relationships and power dynamics along the Kasur-Lahore chain .........294

Figure 33: Okara-Lahore chain model and product physical flows ...........................................300

Figure 34: Quantity and quality along the Okara-Lahore chain ................................................310

Figure 35: Production and pricing mechanism in Okara - Lahore chain ...................................323

Figure 36: Price information flows along the Okara -Lahore chain ..........................................324

Figure 37: Financing, relationships and power dynamics along the Okara - Lahore chain .......330

Figure 38: Pakpattan-Lahore chain model and product physical flows .....................................341

Figure 39: Quantity and quality along the Pakpattan - Lahore chain.........................................349

xxvi

Figure 40: Production and pricing mechanism in Pakpattan - Lahore chain ............................. 360

Figure 41: Price information flows along the Pakpattan - Lahore chain ................................... 361

Figure 42: Financing, relationships and power dynamics along the Pakpattan-Lahore chain ... 365

1

Chapter 1. Thesis introduction and structure

Brief introduction and background to the research

Agriculture is important to Pakistan’s economy. It has a 21% share in the gross domestic

product (GDP), and more than half of agriculture’s contribution is derived from livestock

(Ahmad, 2013) (FAOSTAT 2013). Thirty percent of the country’s estimated 29 million

households depend on livestock for their livelihoods (Mazhar, 2013). Milk is the most

valuable output from livestock1. It crucial to meet the nutrient needs and maintaining

regular cash flows for small dairy holders in a mixed crop-livestock farming system

(Afzal, 2010) and for the nation as a whole that spends half the household income on

food, a quarter of which goes for dairy products (Government of Pakistan, 2013a). Milk

(fresh, packed & dry powder) provides 10.6% and 18.7% of the total protein intake per

capita per day (Government of Pakistan, 2011, 2013a). The country is experiencing rapid

urbanisation, and densely-populated cities provide a huge demand base for milk and

markets that have economies of scale (United Nations, 2012b), creating pro-poor

opportunities for small-scale rural producers and micro-enterprises associated with

domestic supply chains.

The dairy industry has shown resilience and strong growth despite the dominance of small

holders and a huge informal dairy sector (Anjum, Lodhi, Raza, Walters, & Krause, 1989;

Staal, Pratt, & Jabbar, 2008). Processed dairy products are less than 5% of the total

production whereas more than 31% of the fresh, unpackaged milk goes to consumers

through value chains that operate with minimal cool chain technology (Burki, Khan, &

1 The combined value of buffalo and cattle milk and meat is US$ 17.2 billion of which milk is worth US$ 12.9 billion. This is still

larger than the US$ 10.9 billion combined value of the four major crops of Pakistan namely wheat, rice, sugarcane and cotton.

http://faostat.fao.org/site/339/default.aspx


2

Bari, 2004; Zia, Mahmood, & Ali, 2011), yet little is known about these chains and the

industry as a whole.

Research problem and research questions

This thesis is primarily about the structure of the Pakistan dairy industry and the impact

of this structure on the performance of the industry and in particular the performance of

sub-groups of the industry – the pro-poor.

The key research question is:

How do we adapt traditional value chains in a developing country to address the important

national challenges of sustaining profitable smallholder dairy farm operations and at the

same time providing high-quality milk for final consumers?”

This leads to further questions:

Q1. Is milk production a profitable and reliable source of income for smallholder dairy

farmers in a mixed crop-livestock farming system? (Chapters 3 & 4)

Q2. How does the fresh, unpackaged informal rural-urban value chain system function in

the Pakistani context (Chapters 2, 5, 6, 8 & Appendices F, G, H, I)

Q3. What is the perspective of final consumers who buy milk from these chains? (Chapter

7)

Q4. What are the policy issues of public concern based on this value chain analysis?

(Chapter 9)

Thesis design, methodology, and methods used

The key question was answered using a value chain approach as a diagnostic or theoretical

framework that evolved as the research progressed. The research path followed was based

3

on the learning cycle that has been explained along with the sequence of the chapters in

the steps below:

Step 1: To answer 1st question farm economic analysis was carried out to ascertain the

cost of milk production in mixed crop-livestock farming systems of arid Bhakkar and

irrigated Okara districts of Punjab. The choice of the districts was based on the access to

data from a two-year longitudinal survey. The data were collected by an Australian Centre

for International Agricultural Research (ACIAR) funded dairy project. The quantitative

analysis focused on milk and whole farm profitability and made a comparison of the two

districts.

This analysis which partly answers question 1, forms Chapter 3 of the thesis.

Step2: In conjunction with farm economic analysis, a scoping study using the approach

of Collins and Dunne (2007) was carried out in the two regions of Punjab to collect

preliminary data on the milk value chains. The data were collected for this thesis by the

author’s interviews with value chain actors. The study identified what functions are

performed and who does what along the informal milk value chains.

To summarise the findings from this study, a simple value chain framework was

developed based on functional and institutional approaches (Kohls & Uhl 2002;

Schaffner, Schroder, & Earle, 2003). Underpinning the analytical framework was action

research (Olsen, 2012) an approach that uses principles of systematic inquiry and is

focused on resolving practical issues.

This scoping study partly addressed question 2 and has been presented in Chapter 5 of

the thesis.

4

Step3: The scoping study also led to the identification of a specific rural-urban fresh milk

value chain model. This chain was analysed in some detail using the preliminary

framework from step 2. The model stood out as it had complex quantity and quality

determination mechanisms and the dhodhi operators were extending interest-free cash

advances/loans to participants downstream.

As part of the scoping study, another informal fresh milk chain model was also identified

that was using a better-refrigerated chain infrastructure compared to other chains.

The scoping study and specific rural-urban chain models highlighted the need to study

similar information-rich models in irrigated Punjab. The chains in irrigated Punjab were

supplying relatively larger quantities of milk compared to the arid region. The chains

originating from irrigated districts catered to the urban market of Lahore that had a

burgeoning population of milk consumers.

This preliminary analysis of a specific case partly addressed question 2 and forms Chapter

6 of the thesis. It also led the researcher on the path of using a case study method of

analysis. This case was later studied in detail and has been attached as Case Study 2 in

Appendix G of the thesis. The other better-refrigerated chain infrastructure model was

also studied later in detail and attached as Case Study 3 in Appendix H.

Step 4: Based on the renewed focus on irrigated Punjab as an outcome of the scoping

study, further economic analysis of farms in irrigated Okara district was carried out using

the same ACIAR data used earlier in Chapter 3. To analyse the impact of size on

profitability the farms were segregated into three milk production groups (MG) on the

basis of total farm milk production as follows:

• MG1 Low < 2,300 kg/yr

• MG2 Medium 2,300 to 3,700 kg/yr

5

• MG3 High 3,700 to 10,100 kg/yr

The results derived from the economic analysis of milk production led to important

questions such as why are farmers producing milk despite incurring losses and why are

large-scale farmers obtaining a slightly higher price for their milk sold than small-scale

producers. The research also provided an estimate of the cost and price at the farm gate.

Farms similar in size to the ones analysed using ACIAR data were the entry point for the

next step i.e. farm to market research. The support from the ongoing ACIAR dairy project

staff was an important consideration while choosing rural districts as the entry point for

value chain analysis.

The economics of farms in the irrigated region of Punjab based on this analysis has been

presented in Chapter 4 of the thesis, providing further insight to answer question 1.

Step 5: A preliminary finding from the scoping study (Steps 2 & 3) led to further

examination of complex information-rich rural-urban value chain cases in irrigated

Punjab. The theoretical value chain framework was further developed on the basis of

work performed in the initial scoping study. The refined framework guided the analysis

for the three specific rural-urban fresh, unpackaged milk chains studied. A large formal

processor was also interviewed.

Yin’s (2009) case study method was used to carry out this in-depth research using

qualitative and quantitative techniques to collect and analyse data (Bergman, 2008;

Creswell, 2010a, 2010b; Creswell & Plano Clark, 2011). Interviews and personal

observations (Patton, 2002; Yin, 2009) were the key data collection tools. The qualitative

methods dominated the research due to qualitative nature of the inquiry.

6

The refined value chain framework forms Chapter 2 of the thesis. Chapter 8 summarises

the milk value chain case studies that have been attached as Appendices F, G, H, I of the

thesis. These Appendices present comprehensive results from the value chain analysis.

Step 6: Understanding of consumer behaviour was developed in the scoping study phase

of the research such as a common preference for high-fat content buffalo milk.

Consumers were later studied in detail at seven fresh, unpackaged milk retail shops that

were supplied by the three rural-urban case study chains. The findings highlight the

attributes valued by urban consumers when buying milk and how the milk quality is

assessed by them.

This step addresses question 3 and is compiled in Chapter 7. The results from these

consumer evaluations have also been used in Chapter 8 and Appendices F, G, and H.

Step 7: All the earlier thesis chapters and their results contribute to answering the final

question. The concluding Chapter 9 integrates these studies with the development of

recommendations for the future management of milk marketing to service the needs of

smallholder dairy farmers, consumers, and the wider industry. This summary formed

Chapter 9 of the thesis and addresses question 4.

Delimitations of scope and key assumptions

The dairy industry in Pakistan is very large. This means the value chains are quite diverse,

regarding the number of participants involved in a chain and the milk exchange and

transaction methods adopted by them. This study has been carried out with the hope that

information shared by the chain actors was factual, which is very hard to guarantee due

to milk adulteration practices that start even at the farm level. Milk is measured in many

7

ways using various utensils and units including litres, kilogrammes and ‘gadvi’ (a local

measure); and there is limited understanding of how to standardise these various

measures.

Also in the local mixed farming system, milk and meat go hand in hand and are integrated

with crops. Therefore, ideally, and in light of learning from this project, a meat value

chain should have also been analysed, but this will have to be a task for the future.

More importantly, the value chain analysis in this thesis that has used the case study

approach is extended to identify macro-level policy issues. Such a methodology, though,

is more relevant to each chain as a case, which has varied dimensions, and is therefore

restricted in terms of its benefits.

Conclusion

This introduction has laid the foundation for my research and has provided a stepwise

approach taken to answer the research questions s. Each chapter is designed and

written in a way to be independent although they build together to answer the research

questions.

8

Chapter 2. Milk value chain analysis: industry

competitiveness and the dairy policy environment in

Pakistan

This chapter develops a value chain analysis framework from the literature and uses it as

a lens to examine the Pakistani dairy industry by studying three rural-urban milk value

chains. The research also keeps a focus on the broader structure of the Pakistani dairy

industry and the impact of this structure on the performance of the industry and in

particular the performance of an important sub-group of the industry, the poor and

disadvantaged.

Initially, the chapter provides an overview of the global situation. It then focuses on

Pakistan and its dairy industry to further understand the challenges that it faces. The

chapter then briefly discusses food systems before analysing parent literature on industrial

organisation and value chains to understand the role of corporate entities in a capitalist

economy. The last section delves further into value chain theory to provide a framework

to design the questionnaires required for this research.

The world

The world population reached 7.2 billion in mid-2013. Eighty-two percent (5.9 billion)

of the world’s population reside in the developing countries (United Nations, 2013). An

estimated 2.6 billion of the world’s population live on less than US$ 2 a day, and Asia

harbours the majority of the poor (Otte et al., 2012).

For many developing economies the agriculture sector contributes as much as 30 percent

to gross domestic product (Food and Agriculture Organization, 2013a). Ninety percent of

the world’s extremely poor are small-scale farmers dependent on agriculture and livestock

for their livelihoods (Otte et al., 2012). Similarly, three-quarters of a billion are urban

9

poor. The share of poor as a proportion of the urban population is highest in South Asia

(J. Baker, 2008).

Poverty is intimately associated with under-nutrition (Otte et al., 2012). Recent estimates

suggest that 868 million people are chronically undernourished, and 98% of them live in

developing countries (Food and Agriculture Organization, World Food Programme, &

International Fund for Agricultural Development, 2012). Hunger and malnutrition are

most prevalent in South Asia where four out of five people live in extreme poverty

(United Nations, 2012a). Diets in developing countries are deficient not only in

quantitative terms but even more so in terms of quality (Otte et al., 2012).

In the developing world, an average household spends half of its total budget on food

(Asian Development Bank, 2011). Cereals account for a larger share of the food budget

(Andrew, Seale, Meade, & Regmi, 2013), but an increasing trend in disposable incomes

has stimulated demand for livestock products such as milk and meat (Moir & Morris,

2011). The average per capita energy intake is still lower2, however, compared to the

developed world (Gerosa & Skoet, 2012). These brief facts make a strong case to study

rural incomes and urban nutrition, particularly sourced from animals.

Consumers in the developing world largely rely on traditional food systems to buy

cheaper calories and affordable food, such as livestock products, delivered through

traditional and informal marketing systems (Food and Agriculture Organization, 2013c).

Effective value chains are essential in meeting the evolving needs of the poor. These

typically represent small-scale production and marketing systems, which offer the means

to increase access to animal sourced foods for poor consumers, and present opportunities

2 2651 calories/person/day is developing countries and around 3400 calories/person/day in developed countries

10

for poor producers and marketers: thus they have a pro-poor value chain focus

(Echeverría, Solh, Seré, & Hall, 2011).

These traditional food chains create more opportunities in domestic markets. Food

exports from developing countries account for only 1.9% and 8.4% of domestic

production in raw tonnage and value, respectively. The local markets also generate greater

economic gains through follow-on multiplier effects that help reduce poverty, for

example through employment generation and spending on local products. In addition, the

international markets exhibit a higher price risk because of fluctuating exchange rates,

trade barriers, and more stringent food safety standards (Gómez et al., 2011).

Urbanisation also provides economies of scale for markets closer to home and

opportunities for a local production base from farmers whose livelihoods depend on

related food systems (Food and Agriculture Organization, 2013c).

It is increasingly apparent that a value chain approach is essential to understand effective

nutrition delivery to the poor and socially marginalised. Policies and development

strategies in many countries often fail to recognise and provide adequate support to

smallholder production systems and value chain development, focusing instead on

higher‐profile industrial production (Echeverría et al., 2011). Therefore, this research will

focus on domestic farm to market milk value chains in Pakistan to identify the benefits

and bottlenecks hampering the growth of the local dairy industry.

11

Pakistan

Macroeconomy, Agriculture, livestock and employment

This section briefly portrays a picture of the macroeconomy of Pakistan before studying

the agriculture and livestock sectors.

Pakistan faces numerous domestic and external challenges. The country’s economic

performance, in the last several years, has been affected adversely by devastating floods

and rains, internal security hazards, and a severely crippling energy crisis that has led to

large-scale power outages and depressed output. The economic growth rate in the last five

years on average has been three percent per annum. This growth trend is well below that

needed to provide jobs for the rising labour force and to reduce ever-increasing levels of

poverty (Ahmad, 2013; International Monetary Fund, 2013a, 2013b). Agriculture has a

21 percent share of GDP in 2012-13 and is important to the country’s economy and

livestock makes up 56% of that (Ahmad, 2013). Milk is the most valuable output from

livestock production, the monetary value3 of which exceeds the combined value of the

four major crops in Pakistan (Afzal, 2010; Food and Agriculture Organization, 2013b).

The Global Competitive Report (Schwab & Sala-i-Martín, 2013) ranks Pakistan 124th out

of 144 world economies. This means the country is at the first of the three stages of

development and among other aspects, needs better infrastructure and a more vibrant

macroeconomic environment for growth. Pakistan is a factor-driven economy and

competes based on factor endowments, primarily natural resources and low-skilled

labour. Firms compete on the basis of price and sell basic products or commodities, with

their low productivity reflected in low wages.

3 The combined value of buffalo and cattle milk and meat is US$ 17.2 billion of which milk is worth US$ 12.9 billion. This is still

larger than the US$ 10.9 billion combined value of the four major crops of Pakistan that is wheat, rice, sugarcane and cotton.


12

Pakistan also has the world’s ninth largest labour force with 57 million people available

for work and an official unemployment rate of 6% (Government of Pakistan, 2013b). The

agriculture sector is the major employer absorbing 45% of the total labour force (Mazhar,

2013). Agriculture engages half the country’s households (51%), and 59% of those

households are in Punjab (Government of Pakistan, 2010). The sector is categorised as

non-wage employment. The value added to the economy per worker in the primary sector

is low at US$ 1,187 whereas in Australia it is US$ 70,416 per worker (World Bank,

2012).

Population, poverty and undernutrition and incomes

This section studies the existing state of poverty in Pakistan amidst its rising population,

the share of milk in consumption expenditures and the impact of inflation on household

incomes. This helps put the Pakistani consumer in the context of this research.

Pakistan’s population of 184 million people is growing at two percent per annum and is

projected to reach 275 million by 2050, making it the fifth most populous nation (Mazhar,

2013; United Nations, 2012b; World Bank, 2014). There are an estimated 29 million

households4 in Pakistan and an average household consists of 6.4 members (Government

of Pakistan, 2013a).

This research was carried out in Punjab, which is the largest of the country’s four

provinces with 53% of the total population. Currently, 36% of the country’s population

is urban based with a high rural-urban migration trend, and it is projected that by 2050

this will increase to 56% of the population. Six out of the nine most populated cities are

4 Authors estimate where 184m divided by 6.41

13

currently and will continue to be in Punjab province (Mazhar, 2013; United Nations,

2012b; World Bank, 2014).

The research focused on milk supply chains located in irrigated rural districts supplying

urban Lahore city, which is the capital of Punjab. Lahore is the second most populous

city in Pakistan and the thirtieth in the world (Government of Pakistan, 2011; Government

of the Punjab, 2012; Mazhar, 2013).

Per capita incomes by purchasing power parity (PPP) for Pakistan stood at US$ 2,880 in

2012 (World Bank, 2014). According to a 2008 survey, 21% of the country’s population

was below the extreme income poverty measure of US$ 1.25 a day, while 60% have

incomes of less than US$ 2 a day (World Bank, 2013). The Multidimensional Poverty

Index (MPI) provides an index of overlapping deprivations in health, education, and

standard of living. Using this criterion Pakistan ranks as the second highest in South Asia

with 49% of the population living in multidimensional poverty (Malik, 2013).

Poverty is closely linked with undernourishment assessed by energy intake (Food and

Agriculture Organization, 2013c). Pakistan’s annual development plan 2013-14,

disclosed that 33% of the country’s children under five years of age and 18% of mothers

are underweight (Planning Commission, 2013). These facts highlight the issue of

undernutrition in Pakistan and studying the diets of average Pakistanis.

Household budgets and milk consumption

An average Pakistani household spends eleven percent of the household budget on milk

and milk based products5 (Government of Pakistan, 2013a). Milk (unpackaged fresh,

5 HIES 2011-12 shows that an average Pakistani household spends 45.01% on food (Table 2.7). Of that 20.59% goes to fresh milk

and 25.21% to all dairy products combined (Table 16). Therefore in the total consumption expenditure

the share of fresh milk 9.3%=45.01÷100×20.59

& milk and milk based products is 11.3%=45.01÷100×25.21

14

packaged and powdered) provides 10.6% of the 1700 calories and 18.7% of the 45 grams

of protein consumed per capita per day (Government of Pakistan, 2013a; Wynn et al.,

2006). Milk consumption per capita, quoted by various reports, varies a great deal and

ranges from 81 to 230kg/capita/annum. Despite this inconsistency, the country is still

ranked high for its consumption trend, among other developing countries (Government

of Pakistan, 2011; Hemme & Otte, 2010). The high volumes of fresh milk consumed also

highlight a general consumer preference for fresh milk (Anjum, 1978; Government of

Pakistan, 2013a) despite the common knowledge of product dilution (Burki et al., 2004).

Despite, the significant importance of fresh milk in the human diet and high production

base, consumption per capita has shown a decreasing trend in the last ten years. The fresh

per capita milk consumption has fallen by about 5% since 2007 (Government of Pakistan,

2011, 2013a).

This pattern can be linked directly to inflation and food price escalation in particular.

Pakistan has experienced double-digit inflation for five consecutive years averaging 14%

from the fiscal year 2007 to 2012. Analysis of Consumer Price Index (CPI) suggests that

a basket of goods that cost Rupees (Rs) 100 in the base year 2000-01 escalated to Rs 256

by the end of the fiscal year 2011-12 (A. Khan, 2012a). Food inflation in the same period

averaged 14 %, which has resulted in phenomenal food price increases. The nominal price

of fresh milk has risen by 91% from 2007 to 2012 although the real prices have remained

stagnant at Rs 20 per litre since fiscal year (FY) 2000 (A. Khan, 2012a, 2013). Average

own price elasticity of demand for dairy products in Pakistan is inelastic (-0.571) or less

responsive to a price change (United States Department of Agriculture [USDA], 2005).

This food price inflation disproportionately affects the poor, as food constitutes 60% of

the lowest income quintile average household consumption budget. This steep rise in

prices is an enormous challenge in particular as real household incomes have been

15

stagnant since FY 2000 (Asian Development Bank, 2011; Siddique, 2011). Demand for

dairy products in Pakistan is income inelastic (0.779), a common occurrence with basic

necessities (Andrew et al., 2013; United States Department of Agriculture [USDA],

2005).

These data emphasise the high levels of poverty found. It also highlights how important

milk and particularly fresh milk is in the diet of an average Pakistani household. The

rising urban population merits studying further consumer perception of milk quality and

demand for fresh milk.

Milk production in a mixed crop-livestock farming system

Livestock is a crucial and increasing component of Pakistan’s mixed crop-livestock

farming system. South Asia’s share in global milk production is 23 percent mainly from

India and Pakistan (Hemme & Otte, 2010). Pakistan ranks as the second and eleventh

largest country for whole fresh buffalo and cow milk production respectively (FAOSTAT

2011). Overall, the country is ranked the third largest milk producer in the world (Hemme,

2010).

Milk production in the country’s mixed crop-livestock farming system cannot be

examined in isolation from other farm activities (Devendra & Thomas; Kurosaki, 1995,

1997). Punjab has 63% of the total cultivated area of Pakistan of which 82% is irrigated

and provides the bulk of the national food supply (Byerlee & Hussain, 1992; Government

of Pakistan, 2010). The average land and livestock holdings both in Pakistan and in

Punjab are small (Table 1)Error! Reference source not found., with 89% of the farm

households having less than 12.5 acres of land and 97% having less than 15 animals.

16

Table 1: Farm scale and the number of farms, livestock and associated household (HH) numbers in Pakistan and Punjab. Punjab’s proportion is indicated in

parenthesis (Number in millions).

Agriculture Livestock

Number of

HH-

associated

with farms

Number of HH-associated with

buffalo and cattle

Administrative

Unit

Farm

area

in

acres

Number

of farms

Average size

(Acres)

Number

of

Buffaloes

Number

of Cattle

Total Farm

households

Non-farm

households

Pakistan 52.9 8.3 6.4

8.3 33.7 38.3 8.8 5.5 3.3

Punjab 29.3

(55%)

5.3

(64%)

5.5

5.3

(64%)

22.9

(68%)

21.1

(55%)

5.5

(63%)

3.7

(55%)

1.8

(68%)

Sources: Agricultural Census 2010, Pakistan Bureau of Statistics. Numbers of buffalo and cattle based on Economic Survey of Pakistan 2012-13

and Punjab percentages estimates based on Agricultural Census 2010, Pakistan Bureau of Statistics

17

Milk production in Pakistan has grown at 3.3 % per annum in the last decade and is on a

steady rise (Food and Agriculture Organization, 2013a). The fresh milk production6,

however, is insufficient to meet the local demand, given rapid population growth (Burki

et al., 2004; Wynn et al., 2006). The country continues to be a net importer of dairy

products7. Despite a huge production base, there is negligible value addition with a small

proportion of raw product being converted into butter and ghee (Food and Agriculture

Organization, 2013a). The country raises buffalo and cattle for milk and meat remains a

by-product of these animals (Wynn et al., 2006). FAO data for 2011 suggest milk from

buffalo and cattle is the most valuable of all the agricultural commodities produced in the

country. If the value of meat from these large ruminants is added, the economic value far

exceeds any other cash crop (Food and Agriculture Organization, 2013a).

Punjab has a 63% share of milk production followed by 23% produced in Sindh (Fakhar,

Fakhar Law International, & Walker, 2006). In the Punjab, the three major production

systems are, irrigated, rainfed (Barani) and desert, with buffalo and cattle production

systems classified into rural-irrigated, rural-Barani, progressive or commercial and peri-

urban (Wynn et al., 2006). Small dairy holders dominate the sector, however. Milk is also

crucial to meet the nutrient needs of dairying communities and to maintain regular cash

flows. Livestock also acts as a buffer to mitigate risk from damage to crops (Afzal, 2010;

Fakhar et al., 2006; Farooq, 2012; Teufel & Gall, 1999). Approximately 80 percent of

milk is produced in rural areas with urban and peri-urban areas accounting for 20% of the

total production. Approximately 60% of the milk produced in rural farms is consumed at

the household level, and the rest is sold (Zia et al., 2011). Despite decades of livestock

6According to the national statistics, the gross milk production estimates also include milk from camel and sheep. Milk for human

consumption, however, is derived by subtracting 20% (15% wastage in transportation and 5% in calving) of the gross milk production

of cows and buffalo. The local demand and supply primarily based summer and winter seasons do not match either. 7 Dairy imports of value added products have increased by 256% between 2000 and 2010 whereas export have only increased by 74%

in the same period

18

rearing the productivity remains low at 1290 kg per annum per animal compared to 5773

kg per cow per annum in Australia (Fakhar et al., 2006) for the country, although it varies

among production systems and regions (Wynn et al., 2006).

Pakistan’s first and only farmers’ milk co-operative was formed in 1992 and named Idara-

e–Kissan (IK) and had some 19,000 farmers. The cooperative used ‘Halla’ as the trade

name. This development sprouted from a German Technical Co-operation Programme

(GTZ) funded in the early eighties. (Staal et al., 2008).

Milk Supply and demand

Domestic milk supply is seasonal and inversely related to demand. Milk demand peaks

in summer due to increased usage of milk based drinks and yoghurt, whereas supply

declines with decreased production in winter (Figure 1Error! Reference source not

found.).

Figure 1: Seasonal changes in milk production and the related practices

Data Source: Adopted from Anjum et al. (1989)

50

60

70

80

90

100

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Index

of

pro

duct

ion &

consu

mpti

on

Seasonal change in milk supply and demand

Supply

Water

Demand

Excess demand met by recostituted, powder and diluted milk

Excess supply that is converted to powder and other processed products

Milk supply

Dilution

(milk + water)

Demand

19

Production of milk falls to 55% of peak production at its lowest point in mid-June, while

the demand increases 60% during this time compared to December when the milk supply

is ample. The supply of buffalo milk decreases in the summer months of May-June and

increases by an estimated 88 % in winter during January-February. For buffalo, winter is

widely recognised as the period of flush production whereas heat stress is linked to the

decline in summer.

Cows, on the other hand, are more productive during the summer with high milk

production in May-June and low production in November-December. This offsets the

buffalo yield pattern to maintain a more constant milk supply in addition to the wide use

of reconstituted powdered milk by the formal sector. During the lean season, when the

availability of the milk is limited, the prices increase (Anjum et al., 1989; Fakhar et al.,

2006).

Modern processing plants were introduced to Pakistan in the 1960s, to meet the growing

urban demand for milk. The 23 milk pasteurisation plants were located around the major

cities of Islamabad, Lahore and Karachi. These plants have all closed which signalled

poor acceptance of reconstituted milk by consumers. In 1977, ultra heat treated (UHT)

milk was introduced by a local packaging company and later taken over by Nestlé

Pakistan. Currently, there are twelve large-scale dairy processing plants in Pakistan that

on average operate at 50 percent of their capacity. The operational capacity goes down

particularly in summer when production is low, and demand is high (Anjum et al., 1989;

Zia et al., 2011).

Although the country’s formal processing industry segment has negligible (less than five

percent) market share, there has been strong overall industry growth (Staal et al., 2008).

Milk is supplied to the consumers by two main types of chains that can be defined as

informal and formal chains. The main differences between the two are cool chain

20

infrastructure and logistics, hygiene and handling practices and packaging (Zia et al.,

2011).

Quality remains a concern in these informal chains. Milk adulteration is associated with

dilution by up to 60% with poor quality water as well as the use of penicillin, formalin,

hydrogen peroxide, milk productivity hormones and many other potentially harmful

preservatives and residues (Staal et al., 2008). Informal milk value chains operate with

minimal technology and infrastructure but remain a dominant link between millions of

urban consumers and predominantly smallholder dairy producers. The function of milk

collection, transport, and distribution is performed by different tiers of small, medium and

large vendors, colloquially known as dodhis. The milk is sold by specialised retail milk

shops to final consumers (Figure 2) (Burki & Khan, 2007; Burki et al., 2004).

Figure 2: Fresh raw milk flows from rural and peri-urban producers to urban consumer

Source: Author’s depiction based on various FAO reports and dairy industry research

papers

Domestic milk

production

• 80% rural (60%

consumed at source)

• 20% urban & peri-

urban

40% of rural production

• 85% procured by small, medium

and large dhodhis

• 10% goes to dairy processors

• 5% to bakers or confectioner

Urban fresh

unpackaged milk

consumption (39.5%

of total production)

• Specialized retail

milk shops

• Home delivery by

retail shops and

dhodhis

• Self pick up by

consumers from peri

urban dairies

Whole urban & peri-urban production

• 85% sold directly to urban

consumers

• 15% sold to specialized retail milk

shops

Supply Chains

52% of total

production

Total production

(0.8% imports and 0.02%

exports)

44.5% of total

production

Urban & rural total

packaged fresh milk

consumption is (4.75% of

total production)

21

The World Bank’s analysis of the milk-processing sector revealed that Pakistan has an

internationally competitive cost of production of milk at the farm. Losses in the collection,

however, due to a large number of geographically dispersed small-scale farmers and

rudimentary chilling methods reduces its competitiveness by the time the milk has been

delivered to the processors. Also for the Pakistani dairy industry, the terms of trade

heavily favour subsidised dairy products imported from the EU, US, and Canada. This

means any production increases are more likely to be absorbed by the domestic fresh milk

market rather than being exported (F. Shah, 2006). An important issue that is an

impediment to the industry’s competitiveness and export penetration for processed dairy

products is the inadequate system for quality assurance and health safety standards. The

practice of combining imported milk from the formal sector with milk from the informal

sector makes quality control and traceability even more complex (World Bank, 2006).

The fragmented food safety laws that exist in Pakistan are not aligned with international

quality standards. These laws are inadequate for meeting market demands and are poorly

enforced. Lack of hygiene, poor handling practices, and almost non-existent cold chains

lead to an inferior product. Existing regulations do not prohibit or limit the use of harmful

preservatives, including bacteria inhibitors such as penicillin and formalin as well as other

substances such as urea, sugar, and glucose (Zia et al., 2011). The Punjab Government’s

‘Pure Food Laws’ (Government of the Punjab, 2011f) stipulate that milk from dairy

animals be allowed to undergo standardisation and reconstitution. For cow and buffalo

milk the standard is set at 12% milk solids (3.5% fat and 8.5% Solids not fat: SNF) and

14% milk solids (5.0% fat and 9.0% SNF) respectively. Overall, the law requires milk to

have no less than 34% of milk protein and 46% of lactose in milk solids other than SNF.

Government by-laws also control and fix retail prices of fresh milk under the pretence of

protecting the public interest. The District Coordination Officer (DCO), a senior

22

bureaucrat, sets up a District Price Review Committee comprising representatives from

the livestock department, dairy farmers, milk retailers, consumers and various

stakeholders in the milk trade. This price review committee, under the overall leadership

of the DCO, reviews and sets the price of milk and thus plays a significant role in the

fresh milk market (Zia, 2007). These prices are not based on the cost of production and

favour urban consumers. Although not strictly enforced, these prices act as a disincentive

to investors to improve and invest in the production of better quality milk (Ministry of

Food, 2007).

The livestock sector has long been identified by the government as being of crucial

importance to support the pro-poor growth (Amjad, 2010). There exists a national

livestock development policy initiated in 2007 and approved by the then prime minister.

The policy has not been approved by the parliament to make it a national document. The

policy recommends rationalisation of milk and meat prices. It also raises the need for easy

access to credit on softer terms for small livestock farmers, who currently fail to meet the

collateral requirement for financial institutions. The policy highlights the need for the

provision of liberal credit availability for the commercialization of the livestock sector

from production, processing through to marketing. Another important point that the

policy raises is the provision of a level playing field for the local dairy industry by

imposing duty and taxes on imported milk powder and other dairy products equivalent to

the production and export subsidies provided by the exporting countries. The current

practices adversely affect the local dairy industry (Ministry of Food, 2007).

Despite the importance of fresh, unpackaged milk supply chains, very little is known

about them and how and why they have been operating over so many decades and still

continue to operate. The work done on these chains so far, very broadly identifies

traditional milk marketing channels and role of chain actors (Ali, 2006; Anjum et al.,

23

1989; Fakhar et al., 2006; Raja, 2001b; Sharif & Farooq, 2004; Zia, 2007; Zia et al.,

2011). Therefore, this research project aims to examine these chains from a developing

country’s pro-poor value chain perspective.

Food systems

Food systems encompass all the people, institutions and processes by which agricultural

products are produced, processed and brought to consumers. Today the modern and

traditional food systems coexist and evolve as economies grow and urbanisation increases

(Food and Agriculture Organization, 2013c).

A food system implies interconnections between; (1) biological processes to produce

food, (2) economic and political aspects which imply power and control different groups

exert over different parts of the system and (3) social and cultural elements including the

personal relations, community values and cultural traditions which affect people’s use of

food (Tansey & Worsley, 1995).

The “systems approach” applied to a specific food product supply chain, treats it as a

single entity consisting of individual businesses, focused on the delivery of quality

desired by consumers (Florkowski, Shewfelt, Brueckner, & Prussia, 2009) more

efficiently than the competing chains (USAID Microlinks, n.d.).

The greatest influence on consumer food behaviour comes from nationality and race. It

also depends on consumer knowledge and awareness that leads to concerns about

nutrition, food safety and the social and environmental issues (Schaffner et al., 2003).

24

Competition and the role of firms in a market economy, competitive

advantage, and the value chain

In a free market economy, the private sector is recognised as the engine of growth. The

prices hypothetically are determined by the forces of supply and demand and are

decentralised. The firms in these markets compete to maximise profits and to satisfy and

create value for the final consumers. Consumers derive value or satisfaction from their

use and monetarily reward the firms that please them. Efficient allocation of scarce

resources improves living standards of society as a whole. Price efficiency is dependent

on the capability of the whole system, and competition plays a key role in achieving lower

prices (Kohls & Uhl 2002; Schaffner et al., 2003).

“The process of competition – is the search for a new combination to allow entrepreneurs

to escape the tyranny of the normal rate of profit, and the subsequent bidding away of the

economic rent by competitors – fuels the innovation which drives capitalism forward.”

(Kaplinsky, 2001, 2004).

The behaviour of a firm is influenced by the environment and structure of the industry in

which it operates. The way in which they respond to industry variables determines their

performance, which may vary with the competitive structure. Structure refers to the

number and size of buyers and sellers in the industry. Their characteristics and

organisation determines the nature of competition that can be viewed as Horizontal

competition; that is rivalry between firms at the same level e.g. processors or wholesalers

or retailers and Vertical competition that is comprised of bargaining relationships between

buyers and sellers of agriproducts and how the margins within the consumer food dollar

are divided (Kohls & Uhl 2002; Schaffner et al., 2003).

The question, therefore, arises as to how to study the competitiveness of industry and

where value chains impact on industry efficiency in a developing country. The theoretical

25

basis for these is now explored based on the original literature before proceeding to a

value chain framework for the present analysis.

Bain (1968) developed the industry structure-conduct and performance (S-C-P) model to

examine the efficiency of the industry. The model suggests classification of industries

according to their characteristics that provide a framework to test the influence of market

structure on market conduct and performance. Bain describes market economies, as a

multitude of privately owned enterprises that produce goods and services. These

enterprises determine what and how much of each commodity is produced and how they

distribute it to the end users. The Government’s role is as referee and rule maker to put in

place certain minimal restraints in the public interest otherwise a laissez-faire8 approach

would be the rule.

Porter (1998a) built on the industrial organisation theory and put firms at the centre of

focus to understand competitiveness, that is the ability of a firm to develop and maintain

an edge over rivals in the industry. Two key sources of competitive advantage are cost

leadership and differentiation. Competitive advantage to cope with rivals is achieved

through one or a combination of two main strategies namely:

1) Cost advantage; producing and delivering goods and services more efficiently and at a

price acceptable to the final consumer, and

2) Product Differentiation: This describes the uniqueness of the product or service in

terms of price-quality ratio, relative to other competitive products or services (Porter,

1980).

To diagnose competitive advantage, it is necessary to define a firm’s value chain in

relation to a particular industry. A value chain is a basic tool that examines all the

8 French, literally "let (people) do (as they think best),"

26

activities performed by a firm, and their interactions help establish their competitive

advantage. Every firm undertakes a collection of activities performed to produce, market

and deliver its product thus forming a value chain. The structure of these chains may

differ between competitors thus acting as the key source for competitive advantage.

Potential interrelationships among the value chains and business units within an

enterprise are widespread and have a powerful influence on cost structures or product

differentiation. The structure of an industry both shapes the value chain of a firm and is a

reflection of the collective value chains of competitors. Structure determines the

bargaining relationships with buyers and suppliers that are reflected in both configuration

of a firm’s value chain and how the margins are divided (Porter, 1998a).

This S-C-P model and the value chain theory are the geneses of this research’s analysis

framework. From here onwards, the review will delve deeper into the value chain theory

to develop a basis for the analysis.

Value chains approach and analysis framework

This section will analyse the literature on the value chain as a concept, value chain

management (VCM) and value chain analysis (VCA) to be used as a framework to guide

the analysis of milk value chains in Pakistan.

The dynamics of competitive advantage are no longer about suppliers and customers

treated in isolation as independent entities but inextricably linked throughout the entire

sequence of events to bring raw material from source of supply to the ultimate customer.

Success is no longer measured by a single transaction; competition is, in many instances,

evaluated as a network of co-operating firms competing with other firms along the entire

chain (Spekman, Kamauff Jr, & Myhr, 1998).

27

The traditional view of competitiveness has been challenged by an alternative view that

sees a firm as part of a chain that links the production of goods and services to the final

consumers, referred to as the value chain. The competitiveness is thus influenced by inter-

firm interactions (Collins, 2009). In any value chain approach, the competition or rivalry

debate shifts from that among the firms and industry to value chains and firms within

those chains competing against each other to get a larger share of the final consumers’

expenditure on food (Boehlje, 1999).

The value chain approach looks at the complex range of activities implemented by various

chain actors or organisations. The chain starts from the production system of the raw

materials and will move along the linkages with other enterprises engaged in trading,

assembling, processing and marketing (Purcell, Gniel, & van Gent, 2008). Customers are

businesses that are the next links in the chain to which the product is sold while consumers

are the final users of the finished product (Fearne, 2009b).

For developing countries, the challenge is to strengthen value chains that incorporate an

ever growing workforce while increasing productivity and incomes and at the same time

endeavouring to be equitable to all (Altenburg, 2006a). Value chains and the way they

are governed have important development implications for developing countries and

therefore need to be understood. The chains have different patterns of organisation and it

is important to recognise these differences to identify the inherent risks and opportunities

arising from these patterns, especially for poor people. This is required to form policies

that optimise social inclusiveness without sacrificing long-term competitiveness

(Altenburg, 2006c). Although much of the value chain debate has been focused on global

chains, most value chains in developing countries serve domestic consumers. This applies

to chains, which are dominated by local firms as well as for those dominated by

multinationals as they seek a market share. How different forms of an industrial

28

organisation impact on the availability, quality and price of products is, therefore, a

development issue, especially if the goods concerned make up a substantial share of the

poor households’ consumption basket (Altenburg, 2006b).

The basic principle of value creation is to produce or provide a product or services that

will create sufficient value for customers and end users (Boehlje, 1999), as customer value

is a singly major source of competitive advantage (Woodruff, 1997). The term value from

a chain’s perception refers to those attributes that are valued by the next customer

downstream or the final consumers who use the finished product supplied by a specific

chain (Collins, 2009) and hence the term value chain rather than supply chain. The

concept of value is framed by the perspective of the user or consumer looking back to the

chain that produced and delivered the product or service with the consumer as the ultimate

target of the activities of a chain (Collins, 2006).

In effect functional chains are not linear but a complex with many linkages to and from

many other chains: this provides the researcher with a challenge on how best to map

these complex pathways (Kaplinsky & Morris, 2001). A chain has primary members that

carry value adding activities and supporting firms such as banks that lend the money to

businesses to facilitate primary members. This product based distinction helps identify

the point of a chain’s origin where no previous suppliers exist and the point of

consumption where no further value is added (Lambert & Cooper, 2000).

This research focuses on the farmer as the primary milk producer and source of the

product’s origin to the final consumer purchasing the product from a retail shop. A few

key definitions of value chains that will guide this value chain analysis framework are as

follows:

29

Collins (2009) defines “Food value chains as systems driven by the interaction of their

technical (production, processing, transport etc.), economic (profitability), information-

related (communication) and governance (human relationships) systems”.

Boehlje (1999), makes a case for the structural realignments in agricultural industries that

relate to transactions between various tiers of firms, require an understanding of

relationships and information flows as well as physical and financial flows, best

described by taking a value chain approach (Boehlje, 1999). He thus advocates using

VCA as an industry-wide tool. Boehlje suggested that the conceptual framework to study

the structural changes in an agricultural industry would come from various fields or

disciplines. The challenge is to integrate the appropriate concepts into a comprehensive

analytical framework (Boehlje, 1999).

Altenburg (2006a) linked VCA to industry analysis that focuses on the impediments to

growth, studying upstream and downstream operations as a relevant framework

influencing an industry’s core competitiveness.

Value chain theory suggests simplicity and clarity of focus although in reality, the

commercial world is much more complex, so arbitrary decisions on what to map will have

to be made (Kaplinsky & Morris, 2001). Chain analysis also requires selection of a

specific chain(s). VCA offers both the micro and macro aspects of production and

exchange activities and offers an insight into the organisational structures and strategies

of different actors and core processes that link to economics. The number of actors and

employment opportunities are quantifiable. At the heart of chain mapping is the wider

industry and key linkages (Purcell et al., 2008).

VCA plays a key role in understanding the need and scope for systemic competitiveness.

The analysis focuses on the dynamics of inter-linkages within the productive sector, and

the way firms are integrated. VCA is also useful as an analytical tool in understanding the

30

policy environment, which provides for the efficient allocation of resources within the

domestic economy as well as linkages with the global economy. A powerful feature of

VCA is that it goes beyond the level of the corporate entity (Kaplinsky & Morris, 2001).

An important question is to what extent changes in agribusiness chains affect the

prospects for economic growth and poverty reduction. This leads to policy makers giving

more consideration to the development of less demanding local markets (Humphrey,

2006).

VCA is a process for understanding the systemic factors and conditions under which a

value chain and its firms can achieve higher levels of performance while fostering growth

and reducing poverty. It is a huge undertaking and has two interlinked components; (1)

understanding end-market opportunities and the constraints to these opportunities and (2)

chain analysis to identify key constraints to sustained competitiveness and to envision

ways to address those constraints (USAID Microlinks, n.d.).

From above literature, VCA will broadly be used for the following:

Micro-level analysis of specific chains recognising that each chain is unique and has

its distinctive dynamics.

Macro-level analysis as a tool to understand how the industry works and identify

bottlenecks that possibly hinder the growth and competitiveness of an industry.

From the above few definitions and those by Collins (2009) and Boehjle (1999) in

particular, a framework can be built by pulling apart the intertwined microeconomic or

chain level and macro / industry / policy aspects depicted in Figure 3Error! Reference

source not found.. Important functional aspects inherent to food systems and marketing

based on Kohls et al. (2002) and Schaffner et al. (2003) will be used too. Moreover, this

research will draw on VCM literature to identify key building blocks for a VCA

31

framework based on which questionnaires will be developed to carry out this research

and its analysis, focusing on the following four key areas:

1. Actors and their core roles along the chain, which includes buying and selling;

technology used and physical functions of production, storage and cooling,

processing and transport and the time associated with these physical functions; risks

associated with handling a perishable product.

2. Physical flows based on consumer value; product volumes handled; quantity and

quality standards and financial flows linked to the chain standards associated with

price, costs and margins.

3. Information flows both micro or internal to the chain and macro or industry level with

a focus on price

4. Governance both micro or chain level and macro or industry level and closely linked

to information flows: focusing on price information flow only:

For macro level governance industry-wide price setting associated with

product demand and supply and who holds the power to set the farm gate

and retail prices were studied

For micro level governance along the value chain(s); financing in the

absence of formal contracts; relationships; power to stop supplying or

buying or payments; conflict resolution and problem solving were studied

32

Figure 3: Value Chain Analysis Framework

Source: Authors own depiction based on Boehlje (1999), Kohls et al. (2002), Schaffner

et al. (2003) and Collins (2009)

Value chains actors and their core roles, technology and infrastructure and

physical spoilage risks

Food systems have various business structures and contributors that have various roles

(Tansey & Worsley, 1995). Value chains can be complex and lengthy; so the point of

entry is based on the subject of enquiry. The very first step is to define the point of entry

and then systematically map the actors from production to the point of final sale for a

particular product to assess the characteristics of actors along with product flows

(Kaplinsky & Morris, 2001).

A range of physical activities are performed in the food chains that create value for the

final consumer. These functions can be broken down into different activities or processes

such as product handling, movement and physical change to answer time, form and place

of the food marketing (Gunderson, Wysocki, & Stern, 2009; Kohls & Uhl 2002; Schaffner

et al., 2003). Mapping the product flow along the chain identifies the product

transformation from raw material to final product and creates a clear picture of what forms

4. Governance (micro i.e. chain level and macro i.e. industry level)

& Information Flows (both chain and industry level)

Farmer Middlemen Processor Retailer Consumer

2. Physical Flows (quantity, quality and standardization)

3. Financial Flows (economics: profits & margins)

Exchange Functions: buying & selling, time, risk bearing

1. Value chain actor and their roles

Physical Functions: collection & transport, storage & cooling, processing

33

of products are handled, transformed and transported at each stage of the value chain

(Purcell et al., 2008).

Transport is required to move products from where they are produced to consumption

centres. The speed and flexibility of transportation affect inventory. It also influences

storage costs and capacity needed in the food system (Kohls & Uhl 2002).

Storage and cooling is required to buffer day-to-day variations in supply and demand,

which are seldom in balance (Kohls & Uhl 2002; Schaffner et al., 2003). Fresh produce,

in particular, is highly perishable and ideally requires cool chain infrastructure to maintain

a certain temperature, which is often a costly endeavour (Gunderson et al., 2009). Smart

firms customise logistics according to the requirement and profitability of the customer

segment (Anderson, Britt, & Favre, 2007).

Processing of fresh produce adds value and is essentially a form changing activity such

as the conversion of milk to yoghurt (Kohls & Uhl 2002; Schaffner et al., 2003).

Risk bearing is another component of a fresh produce supply chain. Product deterioration

or spoilage is a major risk, which can result in substantial losses to the firm holding the

product title (Gunderson et al., 2009; Kohls & Uhl 2002).

Physical and financial flows and capital invested along the chain

In the contemporary production systems, the primacy is the product characteristics pulled

by the final market (Kaplinsky & Morris, 2001). Commercial product standards should

be set by the government or else the private systems of coordination within a chain

implement their own standards. VCA identifies how information about applicable rules

and standards are transmitted through the value chain and its impacts, both at the industry

level and internally through the lead firm via its coordination system (Purcell et al., 2008).

34

Quantity or product volume flows can be identified and volumes estimated at different

stages of the chain (Purcell et al., 2008). Applying the value chain approach conveys full

information concerning attributes such as quantity and quality of a product coordinated

by chain actors as opposed to spot markets (Boehlje & Schiek, 1998).

Quality is driven by attributes valued by the final consumer. At the retail or final

consumption point, fresh food products have specific attributes such as taste, freshness

and overall sensory experience that consumer loosely integrates into what is termed

quality. The final consumer weighs price and quality to determine whether the product is

good value for money or not. The challenge for the chain is, therefore, to understand and

deliver this value profitably (Collins, 2009). Consumer value links marketing strategy

back to the biological production process. In terms of the dairy industry, this means, the

milk composition that meets specific needs of the market. With respect to attributes, price

structures can give economic signals to appropriate parties leading to the development of

a system that rewards those who meet these specific component contents (Boehlje &

Schiek, 1998).

Value chains and linkage concepts explain the whole process of value creation from

primary production to final consumption (Altenburg, 2006a). In order to capture value

from a chain, a firm first needs to create the value along the chain and then capture a

sufficient share from the various partnerships to make it financially viable (Stych &

Gulati, 2008). In commodity markets, such as raw fresh milk, the sum of value created is

often fixed. The value lies in the eyes of the ultimate consumer and is created by various

activities at each stage of the chain that focuses on consumer wants to create the product

demanded. This total value of the product is often referred to a pie or the final sum paid

by the ultimate consumer that has then to be divided among the chain participants in their

margins (Fearne, 2009b; Keeffe & Fearne, 2009; O’Keeffe, 1998). The monetary flows

35

at every step of the chain can be analysed by studying economic parameters of revenue,

cost structures, profit, and return on investment (Purcell et al., 2008).

A new price is determined, each time product exchanges hands and value judgment sets

into play. Price agreement between buyer and seller leads to transfer of ownership. A

product title may exchange several hands from primary producer through to the final

consumer. The exchange only happens if an arbitrage opportunity exists that is a profit

opportunity of buying at low prices and moving to plentiful demand areas at higher prices

(Gunderson et al., 2009; Kohls & Uhl 2002). Price determination in fresh produce

industries is much less transparent compared to other agricultural supply chains. Price is

either negotiated between a buyer and seller, or the two parties may negotiate a contract

that sets a price for a specified quantity and/or length of time. At the retail level again,

various forces are into play that set the prices. Food price inflation, for example, puts

pressure on authorities to keep prices under control (Gunderson et al., 2009; Kohls & Uhl

2002; Schaffner et al., 2003).

Cost control is critical in any production system, a systems approach focused on the end

user, recognises total costs for production and distribution systems as well as cost at each

stage of the value chain (Boehlje & Schiek, 1998). Firms collaborate to reduce costs and

improve the response to consumer needs (Boehlje, Schrader, & Akridge, 1998).

Each firm focuses on costs and revenue (P × Q) while agreeing on the price, which leads

to profit. This difference in prices at each level of the chain leads to margins along the

chain. Margin represents payments, including profits made and costs incurred, for all

functions performed in assembling, processing, transporting, and retailing food to the

final consumer. All this action is to provide time, place, form and possession utility to the

final consumer (Kohls & Uhl 2002; Schaffner et al., 2003). A systematic mapping of any

chain identifies the profits and cost structures along with final product’s destination and

36

volumes. The analysis of margins and profits within the chain identifies who benefits

from participation in the chain (Kaplinsky & Morris, 2001).

Margins, however, can be unreliable indicators of value accruing to different actors as

they suggest that the higher the margin on sales, the higher value that any participant

derives from the chain. This measure is though flawed as price margins themselves mean

very little unless they are related to the volume of transactions as well as to the activities

that underlie the increments in price (Gereffi, Humphrey, Kaplinsky, & Sturgeon, 2001).

37

Product seasonality, price determination, pricing dynamics and information

flows

The biological production processes are associated with variability. For the dairy

industry, seasonality of milk production and associated utilisation is the biggest challenge

(Boehlje & Schiek, 1998). A change in price reflects changes in demand or supply of a

commodity. Price is a highly effective communication signal capable of inducing change.

Both consumers and producers respond independently to price changes in order to

maximise utility and profitability (Williamson, 1991). Along the chain, the response at

each stage can be initiated only after price signals the need for change in quantity or

quality. The ability to respond quickly to economic changes is critical to maintaining

profit margins. Quick recognition of erroneous decisions, followed by appropriate

adjustments and corrections, are essential to survival and success (Boehlje & Schiek,

1998).

Information mapping in the value chain involves showing the flow of information

between actors at each tier of the chain (Purcell et al., 2008). An integrated value chain

requires continuous information flows that help makes best product flows possible with

the final consumer being the primary focus of all the chain activities. The kind of

information passed among chain members and its frequency has a strong influence on a

chain’s efficiency (Lambert & Cooper, 2000). Information is a significant force in

industries characterised by negotiated or personal linkages. The firms or individuals with

unique and accurate information and knowledge exercise increasing power and control in

the agricultural production system that garners better profits from and transfers risk to

others with less power (Boehlje & Schiek, 1998).

38

Governance along the value chains

Governance conceptualises complex value chain structures with a range of patterns of

industrial organisation that occurs between the two extremes of spot markets or arm’s

length trade and vertical integration (Figure 4) (Altenburg, 2006c).

Figure 4: Governance continuum from open markets to vertical integration

Source: Authors own depiction based on (Williamson, 1971)

Governance refers to both the official rules that directly relate to management of the

commercial environment to ensure the preservation of competition between firms: it

involves unofficial instruments that range from contracts between chain actors to

unwritten norms or understandings. There are potential key actors within and outside the

value chain that influence the governance structure and they may establish their own set

of wider rules which have broader implications for the wider industry (Purcell et al.,

2008). VCA highlights the role of governance, which can be internal or external to the

chain (Kaplinsky & Morris, 2001).

External governance is important from a policy perspective and identifies the

institutional arrangements that may need to be targeted to improve wider capabilities of

value chains operating in the industry. These may be very specific commercial rules

including the association of quality grades with the pricing of the product (Kaplinsky &

Morris, 2001; Purcell et al., 2008). Governance in a macro sense external to the chain

(Figure 5) means regulations that influence activities required to bring a product from

Markets(arms-length dealing)

Vertical Integration(relationship-specific investments)

39

inception to its end use (USAID Microlinks, n.d.) and the government in determining

both product and process parameters in value chains is important (Gereffi et al., 2001).

Figure 5: Governance external to the chain and internal chain governance for an array of firm’s

dealings from open markets to vertical integration

Source: Authors own depiction based on Altenburg (2006c), Kaplinsky and Morris

(2001) and Purcell et al. (2008)

Similarly, there are dominant firms in the industry that promulgate practices that constrain

economic and social development. These firms may choose to impede competition or

abuse market power to squeeze the margins of other firms upstream and/or downstream

in the value chain. These dominant firm(s) have common interests with their suppliers as

far as the overall efficiency of the supply chain is concerned, but pursue different policies,

which favour their commercial profitability when it comes to negotiating purchasing

prices and quality standards. These leaders try to gain monopsonistic market power by

creating competition among suppliers to enhance their bargaining power (Altenburg,

2006b). These dominant firms set the parameters of industrial organisation and engage in

quasi-hierarchical relationships with firms upstream and downstream in the value chain

that are legally independent but nevertheless to a high degree reliant on their decisions

Governance (external to

the chain)

Governance (external to

the chain)

Governance (internal to the chain)MarketsVertical

Integration

40

(Kaplinsky, 2001). Sexton et al. (1994) highlighted the need to consider the

monopsony/oligopsony issues in the policy debate, particularly in the agricultural markets

to promote competition.

In the formal sector, processors have to maintain adequate processing capacity to handle

milk during the peak supply season, but plants are often idle during the off-season. This

excess capacity adds substantial system costs for processors (Boehlje & Schiek, 1998).

Demand and supply conditions in agricultural chains vary with seasons and influence the

governance and power of different chain actors (Purcell et al., 2008). Price fluctuation is

a risk associated with variation in supply and demand, which can lead to changes in the

governing rules. The risk associated with pricing volatility is borne by the product title

owners, and the ability to manage this risk associated with changes in supply and demand

is a key factor in the sustainability of chain function (Gunderson et al., 2009; Kohls &

Uhl 2002).

Internal value chain governance is process control through non-market mechanisms to

coordinate economic activities along the chain. It refers to the structure of relationships

and coordination mechanisms that exist between actors along the value chain to monitor

the activities of supplier firms. The management of risk across the chain is important to

ensure that no one essential contributor fails financially thereby leading to major

disruption to the marketing of the product. Governance takes various forms and differs

significantly with respect to how strongly governance is exercised, how much it is

concentrated in the hands of a single firm, and how many lead firms exercise governance

over chain members (Gereffi et al., 2001; Kaplinsky & Morris, 2001). Effective chain

governance minimises transaction costs and enhances efficiency (Dyer & Singh, 1998).

Relationships between sellers and buyers are important, defined as a social connection

between two parties, where trust provides social capital that enables efficient linkages

41

through the reduction of transaction costs (Purcell et al., 2008). The relationships a lead

firm has with suppliers can either be helpful to improve the competitiveness of the

industry based on long term commitments or can be predatory with a focus on realising a

quick profit in the short-term (USAID Microlinks, n.d.). Firms reduce price risks using

coordination and control mechanisms, which are different to the open market pricing

system. A common business strategy is to reduce the risk of high input prices by

contracting for supplies combined with contracting product sales (Boehlje & Schiek,

1998).

The success of a business, in a competitive environment, depends on its ability to manage

its intricate network of business relationships with multiple firms (Lambert & Cooper,

2000). Dyer and Singh (1998) link relationships in which a firm is committed to a source

of competitive advantage. Effective inter-firm relationships are crucial to the performance

of value chains and enhancing industry competitiveness over time. The value chain

approach provides a framework to capture and analyse these complex and often

adversarial relationships logically categorised by two extremes of supportive to

adversarial (Campbell, 2008).

Adversarial relationships increase costs whereas cooperation and teamwork along with

rapid and continuous information exchange reduce them (Hobbs, 1996). Relationships

between different stakeholders, coupled with effective information flows enable

economic optimisation of product flows (Fearne, 2009a). Since the value in commodity

chains is fixed, inevitably conflict will lead to winners and losers along the chain as a

result of antagonistic relationships (Fearne, 2009b; Keeffe & Fearne, 2009; O’Keeffe,

1998).

The relationships are the lifeblood of chains as firms rely on their suppliers to reduce

costs and improve quality although these relationships are not easy to build and manage

42

(Liker & Choi, 2004). Relationships crossing firm’s boundaries and governance of these

relationships can broadly be classified into 1) legal contracts and 2) self-enforcing

agreements (Figure 6) (Dyer & Singh, 1998).

Figure 6: Governance of relationship and their patterns

Source: Authors own depiction based on citations in the next few paragraphs

a.Business dealings that can either be managed through legal contracts or self-enforcing agreements. The

self-enforcement can take the form of either captive or relational chains. Within relational chain, there can

be either dependence or interdependence.

While formal written contracts offer some specific benefits and have historically been

required by many firms as a part of legal considerations, their use is not universal, and

the complex and dynamic nature of alliances make detailed written contracts difficult to

develop and maintain (Whipple & Frankel, 1998).

Therefore governance mechanisms such as financial formal safeguards and investment

hostages (Figure 6) are created by firms to control opportunism (Dyer & Singh, 1998).

Opportunism is defined as self-interest seeking with guile. Businesses and individuals

often seek to exploit a situation to their own advantage. Although not all those involved

in transactions act opportunistically all of the time but the risk of opportunism is often

present (Williamson, 1979).

Governance

of

Relationships

Legal

Contracts

Self

Enforcing

Agreements

Formal Safe

Guards such as

financial

hostages

Captive Chains

Informal Safe

Guards such as

goodwill and trust

Relational Chains

Dependence

Interdependence

43

In captive value chains relationships, smaller suppliers are captive since they are

dependent on larger buyers and face significant costs to switch to an alternative vendor.

Such networks are controlled closely by these buyers to firstly lock in suppliers and then

subordinate operators in the chain to render it financially unattractive for them to leave

(Gereffi, Humphrey, & Sturgeon, 2005).

Informal safeguards such as goodwill and trust (Figure 6) are most effective and least

costly to enforce (Dyer & Singh, 1998). Informal social contracts serve a more critical

role in developing long-term commitment and require a shift away from traditional

mechanisms of power and control to place a greater emphasis on human elements,

highlighting the need for co-operation and trust to ensure mutual engagement in their

relationship. Social contracts bind the key contacts together, and these relationships

illustrate the importance of co-operation, trust, and loyalty and represent the commitment

between both parties (Whipple & Frankel, 1998).

Trust and linkages are inextricably intertwined within a value chain. Trust and level of

trust can be studied by exploring the length of trading relationship, price setting

mechanism, product quality control and inspection procedures and the nature of

contractual arrangements that can be written or oral in nature (Purcell et al., 2008).

Networks with complex interactions between buyers and sellers often create mutual

dependence (Figure 6) and high levels of asset specificity, managed through reputation,

or family and ethnic ties. Mechanisms are implemented that impose costs on the party

that breaks a contract. Tacit knowledge is exchanged between buyers and sellers, and

suppliers provide a strong motivation for lead firms to outsource, given the

complementary nature of supplier firms. The exchange of complex information is most

often accomplished by frequent face-to-face interaction and governed by high levels of

coordination, which makes the costs of switching to new partners high (Gereffi et al.,

44

2005). Successful lead firms slash the number of suppliers they do business with and

maintain long-term relationships based on trust with a smaller number of suppliers. They

also make their suppliers responsible for quality, costs and timely delivery (Kaplinsky &

Morris, 2001; Liker & Choi, 2004).

Dependence if smartly managed (Figure 6), through inter-organisational relations, can

boost the overall pool of value to be distributed. Joint dependence fosters more cohesive

exchange in relationships and triggers a higher quality of information flow that translates

to superior value creation and a larger pool of value available for partners to share. When

it comes to claiming value, a firm that has its partners more dependent on it, is in a better

position to claim a greater piece of the pie without squeezing the business partners to the

point that triggers negative reactions, thus hurting relationships and overall value creation

(Stych & Gulati, 2008).

Interdependency and a social bond (Figure 6) is built between the seller and buyer based

on a customer service-oriented philosophy. Positive experiences and satisfaction then

follow by a commitment to the relationship as both parties benefit. The buyer is satisfied,

and the seller gains customer loyalty; repeat purchase and positive feedback spreads

throughout the market. The relationship building process requires adaptations on the part

of both parties and certain changes and concessions are made by both sides to help the

relationship grow (Cann, 1998). One of the major outcomes of this relationship building

process is a commitment on the part of both parties involved to cooperate and continue

the relationship for the long-term. However, a major disadvantage to a dyadic relationship

achieving this level is that it has very high termination costs (Morgan & Hunt, 1994).

The relational exchanges will always have disagreements or conflict (Morgan & Hunt,

1994) between two or more parties that arise when at least one of the parties perceives

the other as engaging in behaviour designed to harm it (Goldman, 1966). Conflict among

45

chain members can have a strongly negative impact on an alliance (Bucklin & Sengupta,

1993) if not resolved and can lead to relationship dissolution. On the contrary, if the

disputes are resolved amicably, these are referred to as ‘functional conflicts’ as they

provide a medium through which problems are discussed, and solutions are found

(Morgan & Hunt, 1994). The firm that possesses an efficient conflict resolution

mechanism such as fiat compared to litigation, to settle minor conflicts, are more efficient

(Williamson, 1971). Inter-firm cooperation can reduce transaction costs thus leading to

improved efficiencies. Firms downstream though have little incentive to act in good-faith

as suppliers, when participants upstream engage in predatory or non-transparent

behaviour (Kula, Downing, & Field, 2006).

The lead firm or firms, engaged in quasi-hierarchical relationships with firms upstream

and downstream in the value chain, exercise power and exert control by setting and/or

enforcing parameters under which others in the chain operate. The other firms in the chain

are dependent on the lead firm (Altenburg, 2006b; USAID Microlinks, n.d.).

Power is the ability of a firm or organisation to exert influence and control over other

firms in the chain. Within a value chain, power comes from and is held by lead firms

(USAID Microlinks, n.d.). In local markets of developing countries official standards

defining product quality, grading, and business practices are weak and poorly enforced.

Intermediaries, traders or retailers who may serve as de facto lead firms within the chain,

therefore, enforce their own rules at the chain level. These rules, quality standards, and

norms may not be written and vary within and across markets and chains (Purcell et al.,

2008). These lead firms fulfil a prominent role in the value chain as they explore dynamic

rent opportunities and assign different roles to other firms along the chain (Kaplinsky,

2001).

46

Governance involves the ability of one firm in the chain to influence or determine the

activities of other firms in the chain. This influence can extend to defining standards for

products to be produced by suppliers and those from whom they obtain the product

(Gereffi et al., 2001).

Power is directly related to the level of concentration and access to key assets that may

be in the hands of a limited number of actors. Key assets can be both physical resources

e.g. capital, land, credit and intangible resources such as market information, knowledge,

personal relationships, and reputation. Actors who have exclusive access to key assets

and resources are more powerful and have the capacity to influence others in the chain

(Purcell et al., 2008). Apart from concentration or market share of the firm(s) and control

over key resources needed in the chain, power is exercised through the lead firms'

decisions. These decisions may influence entry to and exit from the chain, monitoring,

and control of suppliers and their positioning in the chain that helps the lead firm to create

and/or appropriate higher returns (Gereffi et al., 2001). This structural dimension of

positioning in a chain means that firms with the direct relationship with the end consumer

hold most power (Lambert & Cooper, 2000).

Value chains have complex systems with manifold implications for development as they

entail many stakeholders with partly rivalling interests and asymmetric power relations.

Policy makers in developing countries need to focus on making value chains more

socially inclusive to strengthen the competitiveness, profits and wages of those involved

in the chains (Altenburg, 2006b). It is important for policy makers to recognise the

differences in buyers and markets and match the capabilities of local producers with the

requirements of the market (Humphrey, 2006).

Governments are primarily for developing food and nutrition policies that are in the best

interests of their nation. Power, influence, and control of resources largely determine who

47

derives the most benefits from food. A balanced government strategy on food economy

should take into account the interrelationships within the food sector and between it and

the rest of the national and international economy. Laws are to protect honest firms from

unfair competition and to help equalise the “David and Goliath” relationship between

small and very large firms (Tansey & Worsley, 1995). Reardon et al. (2009) highlighted

the importance of competition-based prices and fair commercial practices at the heart of

public policy. The price war is an important point of conflict between these giants and

traditional firms who cannot match their economies of scale. Two basic conflict sources

are inequality of power and the practices or use of that power in terms of pricing, quality,

location, payment and contracting to their advantage (Reardon & Hopkins, 2006).

This VCA framework above was used to interpret the finding from the three case studies

for this research. The next section will briefly define the methodology.

48

Chapter 3. Dairying and whole-farm economics of crop-

livestock farming systems; comparing arid and irrigated

districts of Punjab, Pakistan

The chapter studies the whole farm profitability of small agricultural households, with a

specific focus on milk production. It compares two contrasting agro-ecological regions

within Pakistan’s Punjab, irrigated Okara and rain fed-Bhakkar.

Materials and Methods:

The data from a two-year longitudinal survey planned by an Australian Centre for

International Agricultural Research (ACIAR) funded project entitled “Improving dairy

production in Pakistan through improved extension services” (Wynn, Unpublished), was

used. The survey was conducted from January 2008 to December 2009 and included 230

farms from 17 and 14 villages in Okara and Bhakkar districts (Figure 7 a & b) of Punjab

respectively. In addition to support from Government of Punjab livestock department’s

district extension staff in both the districts, the farmers in Okara were selected from those

recommended by Idara-e-Kissan, the only dairy farmer’s cooperative in the country (that

no longer exists), while in Bhakkar, the collaboration of National Rural Support Program

(NRSP), a nationwide non-governmental organization (NGO) providing micro credit to

farmers, was sought.

49

Figure 7.a. Maps of Pakistan and Punjab; b. Map of Punjab showing Okara and Bhakkar districts.

Source: City and border data spatial from 2012 ESRI data & maps

50

The irrigated Okara district lies between the rivers Ravi and Sutlej and is part of the

Southern Irrigated Plains with calcareous clayey soils. The climate is arid subtropical and

continental with hot summers and mild winters. In the hottest summer months, maximum

temperatures reach 44 °C, and minimums of 2°C occur during winter. Average annual

rainfall is 500 mm and the majority of farmers use tube wells for irrigation to supplement

canal-sourced water. The main crops grown are wheat, rice, maize, sugarcane, and cotton,

with potato being a popular vegetable crop. The district is famous for rearing local

Sahiwal cattle and Nili-Ravi water buffalo breeds (Dost, 2002, 2003; Government of the

Punjab, 2011e, 2012; Pakistan Meteorological Department, 2013; Small and Medium

Enterprises Development Authority).

The rain-fed Bhakkar district on the western bank of the river Indus has two zones within

it, with well-cultivated lands in the west and dry and sandy lands in the east. The district

has calcareous sandy soils and dunes. The climate is semi-arid with hot summers and cold

winters and with a short dry season in early summer. The maximum temperature in

summer reaches 47°C with winter minimums of 3°C. Mean annual rainfall is 400 mm.

Sugarcane, gramme, wheat, guar seed and cotton are the main crops, with cattle and

buffalo also reared by farmers (Dost, 2002, 2003; Government of the Punjab, 2011e,

2012; Pakistan Meteorological Department, 2013).

The longitudinal survey data aimed to establish a comprehensive picture of the operations

of smallholder crop-livestock producers. A key farmer selection criterion was to include

farmers with at least one or two milk animals, some surplus milk production to be

marketed, and some cultivable land. There was no limit on the maximum number of milk

livestock held, or the size of the land holding, although small dairy holders remained the

main focus. An easy to understand herd book was used to gather data and collection

frequency varied for different variables. Weekly data was recorded on milk volume per

51

buffalo and/or cow, type and quantity of feed for the whole herd at each farm,

expenditures on animal health and revenue from sale or cost of livestock purchase.

Monthly data recorded land allocation for different crops grown as well as the number

and composition of livestock kept, including milking animals.

From this survey, data for one cropping year from June 2008 through May 2009 was

extracted for 115 and 97 farms each in Okara and Bhakkar districts. The farms with

incomplete data and the very large farm units, in terms of land area, which were outliers

skewing the normal distribution, were excluded.

The key focus was dairy enterprise and profitability from milk, livestock (milk and meat),

though all other major farm enterprises were also brought in to allow whole farm analyses

(Kay, Edwards, & Duffy, 2008; Malcolm, Makeham, & Wright, 2005; Wilson, Charry,

& Kemp, 2005).

The following are the terms used to define elements of our whole farm economic analysis

(detailed equations used along with an in-text citation of secondary data sources outlined

in Appendix A and B). (same framework applies to the next farm economic analysis

chapter)

Gross margins (GM), defined as the gross income from an enterprise minus the

variable costs were estimated for crops, green fodders, milk, and meat, for each farm.

The cost of manual labour was excluded for all enterprises and accounted as fixed cost.

Crop gross margin (GMC) was gross income (GIC) from a crop enterprise based on

market value less its variable costs (VCC).

Green fodder gross margin (GMF) was taken as zero that is gross income (GIF) from

each fodder crop was equated to its variable cost of production (VCF) as this cost was

charged to livestock enterprise feeding green fodders grown at the farm.

52

Whole livestock activity (milk and meat) gross margin (GMWLA) was gross income

(GIWLA) from the livestock activity and included the value of total milk produced, plus

livestock trading income (TIL ), less total variable costs (TVCWLA ) of rearing livestock

that included feed, health and breeding costs. These costs were divided between milk

and meat enterprise by allocating all female buffalo and cattle costs to milk enterprise

and males to meat. As milking buffaloes and cows are ultimately culled for meat

(Wynn et al., 2006), one-fourth of their total variable cost has been allocated to meat

enterprise.

Milk gross margin (GMMk) was gross income (GIMk) from milk production that

included sales, home consumption and 5% to suckling calves, less variable cost (VCC)

allocated to milk enterprise.

Meat gross margin (GMMt) was gross income (GIMt) from livestock trading (TIL), less

variable costs (VCC) allocated to meat enterprise.

Total fixed cost (TFC) was taken as the labour (L) assumed to be provided by the

farmer owner and / or his household. These manual and casual labour costs had been

excluded from all enterprise GM estimates. There were no other fixed costs.

Analysis of milk production per kilogram to estimate average variable cost

(AVCMk/kg), average fixed cost (AFCMk/kg), total cost (TCMk/kg) and marginal cost

(MCMk/kg) was carried out using the variable costs allocated to milk enterprise while

labour was brought in as fixed cost.

Operating profits (OPWF) for the whole farm was calculated by subtracting total

labour costs taken as the only fixed cost (TFCWF ), from whole farm gross margins

(GMWF).

53

Net Profit (NPWF) for the whole farm was OPWF less finance cost (FCWF) for the whole

farm. FCWF was calculated by applying an annual interest cost on the value of land and

livestock utilised as key farm assets (their opportunity cost). The cost of finance was

based on the long-term average national savings rate of 9% and that used by the

government of Punjab in its crop gross margin estimates for the fiscal year 2008-09

(Government of the Punjab, 2011c; National Savings Organization, 2000).

Statistical analysis was carried out using t-tests to compare means of physical and

economic attributes for the two districts. A two sample t-test with 95% confidence

interval and the district as group factor was applied to compare sample farms variables in

the irrigated Okara and arid Bhakkar districts of Punjab.

Linear regression was used to explore associations between milk production and two key

variables; land allocated for fodders and concentrates fed to milking animals.

Results:

Average land holding was the same in the two districts though more land was being more

intensively cultivated in Bhakkar for different crops, during the two cropping seasons, in

rain-fed Bhakkar compared to irrigated Okara (Table 2). There was a significant

difference (p < 0.001) between the mean number of buffalo and cattle kept per farm in

the two districts with more buffalo in Okara and more cattle in Bhakkar, which conforms

to the national statistics (Government of the Punjab, 2012). A significant difference (p <

0.001) was found in green feed and roughages fed to livestock with Okara higher on both

accounts.

Linear regressions used to investigate associations between

i. total farm milk output and land allocated for growing different fodders, and

54

ii. average milk output per animal and concentrates fed,

showed a significant difference (p < 0.001) between the two districts of Okara and

Bhakkar.

The slope for Bhakkar showed a higher increase in milk production for both variables

(Figure 8 a & b) of green fodders per farm per annum and the use of concentrates for

milking animals.

55

Table 2: Mean physical and economic attributes of agricultural land and livestock for farm survey

data. Standard error of mean (SE) indicated in parentheses. Results of t-tests comparing means

Measure Okara Bhakkar t df9 p

Total sample size (n) 115 97

Land (Acres)

Total land 9.04 (0.66) 9.47 (0.91) -0.38 181 0.702

Total cultivated area

(summer and winter crops)

16.15 (1.11) 21.77 (1.81) -2.65 163 0.009

Land cultivated for fodder crops 5.44 (0.35) 5.18 (0.38) 0.51

210

0.612

Land cultivated for other crops 10.71 (0.85) 16.59 (1.51) -3.40 154 < 0.001

Livestock (kept for milk and meat)

Herd size (hd) 10.93 (0.48) 10.50 (0.57) 0.59 210 0.555

Buffalo (hd) 7.67 (0.34) 4.19 (0.35) 7.09 210 < 0.001

Cattle (hd) 3.27 (0.31) 6.30 (0.44) -5.63 177 < 0.001

Milking cows and buffaloes (hd) 3.71 (0.18) 3.77 (0.27) -0.20 210 0.840

Total milk production

(kg/annum/farm)

3,400 (181) 3,453 (278) -0.16

169

0.875

Average milk production

(kg/annum/milking

animal/farm)

999 (44)

916 (54) 1.19 210 0.234

Milk sold (kg/annum/farm) 658 (73)

29% of total

1558 (334)

37% of total

-2.63 50 0.011

Source: 2008-2009 Australian Centre for International Agricultural Research (ACIAR) farm survey data

from Wynn (Unpublished) Where 1 acre = 1 ac = 0.4047 ha or 4,047m2 and 1hectare = 1 ha = 2.471

acres

9 While comparing average land held by the farmers in the two districts. Based on F-test, the variances for Okara and Bhakkar were

not equal.

Okara 𝑠12 = 50 & n1=115

&

Bhakkar 𝑠22 = 81 & n2=95

A two-sample t-test without assuming the equality of variances was used. To calculate the degrees of freedom (d.f.) the formula is as

follows:

𝑑𝑓 =(

𝑠12

𝑛1+

𝑠22

𝑛2)

1

𝑛1−1 (

𝑠12

𝑛1)

2

+ 1

𝑛2−1(

𝑠22

𝑛2)

2

The above formula gave df=181

GenSTAT statistical software was used to carry out the statistical tests for the economic analysis in the thesis. The software estimated

degrees of freedom (df) for total land, for example, to be 181.

While performing the two sample t-test, the option of automatic was used to the estimate of variance and degrees of freedom for three

land and three livestock variables and hence the result provided in the table.

Imposing equal variance in the t-test would have given 210 degrees of freedom for the total land variable, for example, but the variance

was 50 for Okara and 81 for Bhakkar i.e. not equal.

56

Source: 2008-2009 ACIAR farm survey data from Wynn (Unpublished)

Figure 8. Linear regressions for (a) average milk production per milking animal per farm for the

concentrates fed, and (b) total milk production per farm and land allocation for green fodders in

irrigated Okara and arid Bhakkar districts of Punjab

y = 1.3837x + 747.68

R² = 0.4045

y = 1.9195x + 556.66

R² = 0.33

0

500

1000

1500

2000

2500

3000

3500

0 200 400 600 800 1000 1200

Av

era

ge

Mil

k (k

g /

An

ima

l /

farm

)

Average concentrates fed per milking animal (kgs)

a.

Okara Bhakkar Linear (Okara) Linear (Bhakkar)

y = 167.08x + 2491.4

R² = 0.1023

y = 453.36x + 1104.2

R² = 0.3772

0

3000

6000

9000

12000

15000

18000

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0

To

tal

Mil

k P

rod

uct

ion

p

er F

arm

(k

g)

Land allocated to Green Fodders per Farm (Acres)

b.

Okara Bhakkar Linear (Okara) Linear (Bhakkar)

57

Milk enterprise analysis and comparison for the two regions10

Average milk enterprise gross margin (GM) was positive in both the districts though

Bhakkar showed better results (Table 3). A cumulative relative frequency distribution

(CRFD), however, revealed that 30% and 20% of farms in Okara and Bhakkar

respectively, were making losses and that these farms had average variable costs (Rs/kg)

higher than farm gate milk prices (Table 3 and Figure 9).

The total cost of milk production, after taking labour costs into account, was almost

double the price of milk in both districts and made the milk enterprise loss bearing for

70% and 60% of the farmers in Okara and Bhakkar districts (Table 3 and Figure 10). A

marginal cost analysis, assuming a hypothetical scenario of 50% increase in milk

production with an associated 30% increase in total variable costs, relating to overall

better animal husbandry practices (Burki et al., 2004; Teufel, 2007), revealed a reduction

in economic losses, but not to the point where milk production became profitable. Even

with such improvement, milk enterprises remained unprofitable for 50% and 40% of the

farms in the Okara and Bhakkar respectively (Table 3 and Figure 10).

10 The analysis was performed to estimate economic and not accounting profits. The variable costs for crops and livestock, whole farm

labour costs and the finance costs to estimate net farm profits are treated as follows: 1. Variable costs (explicit or out of pocket costs such as purchase of fertilizer) for estimating gross margins for milk, meat, livestock

and crop enterprise.

2. Labour costs have been used to estimate operating profits. These costs have been treated as fixed costs on actual basis assuming that the farmer and/or his household is providing all the labour and no contractual labour is hired. These cost are therefore

explicit and not implicit as in accounting.

3. Implicit costs have only been used to estimate net farm profits. It has been assumed that farmer could have earned 9% interest on land and livestock assumed to be the only assets held.

58

Table 3: Mean production and economics of milk enterprise. Mean with Standard error of means

(SE) indicated in parentheses. Results of t-tests comparing means

Measure Okara Bhakkar t df P


Milk Economics

Milk prices (Rs/kg) 22.99 (0.24) 21.14 (0.31) 4.81 210 <0.001

Milk average variable cost

(Rs/kg)

19.93 (1.47) 16.26 (1.73)

1.63 210 0.105

Milking animals gross margin

(Rs from milk enterprise)

5,902 (1,196) 9,011 (1,077) -1.90

210 0.059

Milk GM (Rs from milk

enterprise)

25,797 (3,734) 37,416 (4,691) -1.96 210 0.051

Milk average fixed cost (Rs/kg) 18.52 (1.23) 20.94 (2.31) -0.93 148 0.356

Milk total cost (Rs/kg) 38.45 (2.39) 37.20 (4.00) 0.27 159 0.789

Milk production profit (Rs

from milk enterprise)

-25,427 (3,776) -9,598 (3,947) -2.89 210 0.004

Milk Economics (marginal cost analysis)

New Milk average variable cost

after increase (Rs/kg)

17.27 (1.27) 14.09 (1.50) 1.63 210 0.105

New Milk average total cost

after increase (Rs/kg)

35.80 (2.21) 35.04 (3.77) 0.17 158 0.862

Source: 2008-2009 ACIAR farm survey data from Wynn (Unpublished) and a range of secondary sources

referred in Appendix 2

Note: 1USD = 70.1 PKR, Official exchange rate from State Bank of Pakistan as an average of the fiscal

year 2007-08 and 2008-09 (State Bank of Pakistan, 2013)


Figure 9: Milk gross margin comparison between irrigated Okara and arid Bhakkar districts of

Punjab

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-100000 -50000 0 50000 100000 150000 200000 250000

Cu

mu

lati

ve

Fre

qu

ency

Rupees

Okara Milk GM Bhakkar Milk GM

59

Figure 10: Milk profit & new milk profit comparisons between irrigated Okara and arid Bhakkar

districts of Punjab


Livestock enterprise and whole farm economic analysis

In all surveyed farms livestock trading income was a loss. In addition whole livestock

activity GMs that included both milk and meat enterprises, was negative on average for

both districts and CRFD’s indicate that 40% and 50% of the farmers in Okara and

Bhakkar were making losses (Table 4 and Figure 11). Gross margin per Rupee invested

in livestock activity showed negative returns on investment in livestock for both districts

(Table 4).

Whole farm GM was 90% and 80% positive for farms in Okara and Bhakkar and

mitigated the negative effects of livestock activity losses (Table 4 and Figure 11). Overall,

Okara district farms performed better than Bhakkar due to the higher productivity of the

irrigated district.

Operating profits after accounting for labour costs showed 30% of Okara farms having

losses and 40% of Bhakkar. Although after deduction of finance costs, which relates to

the opportunity cost of capital invested in the farms, 90% of the farms were loss bearing

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-200000 -150000 -100000 -50000 0 50000 100000 150000 200000 250000 300000

Cu

mu

lati

ve

Fre

qu

ency

Rupees

Okara Milk Profit Bhakkar Milk Profit Okara-New milk Profit Bhakkar-New milk Profit

60

in both districts (Table 4 and Figure 12) at the net profit level. The return on assets (RoA)

was higher for Okara than Bhakkar.

Table 4: Mean economic attributes for livestock and whole livestock activity. Mean with Standard

error of means (SE) indicated in parentheses. Results of t-tests comparing means

Measure Okara Bhakkar t df p


Livestock trading income

(Rs)

-9,687 (20,311) -16,057 (15,124) 0.25 202 0.802

Meat GM (Rs) -51,369 (20,449) -45,567 (14,885) -0.23 200 0.819

Milk GM (Rs) 25,797 (3,734) 37,416 (4,691) -1.96 210 0.051

Livestock activity GM (Rs) -25,572 (20,549) -8,151 (15,495) -0.68 203 0.499

GM return per Rs invested

in livestock activity

-0.015 (0.01) -0.028 (0.01) 0.79

183

0.428

Crop GM (Rs) 355,164 (28,462) 231,545 (20,067) 3.55 198 <0.001

Whole farm GM (Rs) 329,593 (36,416) 223,394 (27,849) 2.32 204 0.022

Operating profit (Rs) 202,062 (32,548) 84,625 (21,901) 2.99 194 0.003

Net profit (Rs) -294,271

(28,313)

-324,547

(29,568)

0.74 210 0.462

Return on assets (%age) 2.78 (0.708) 0.53 (0.704) 2.24 210 0.026

Source(s): ACIAR farm survey data from Wynn (Unpublished) and a range of secondary sources referred

in Appendix 2




Figure 11: Livestock and whole farm gross margin comparison between irrigated Okara and arid

Bhakkar districts of Punjab

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-1500000 -1000000 -500000 0 500000 1000000 1500000 2000000

Cu

mu

lati

ve

Fre

qu

ency

Rupees

Okara Livestock GM Bhakkar Livestock GM Okara Whole Farm GM Bhakkar Whole Farm GM

61

Figure 12: Whole farm operating and net profit comparison between irrigated Okara and arid

Bhakkar districts of Punjab


Conclusions:

Whole farm profitability is negative in net terms when accounting for farm households’

labour and capital costs, which indicates that the factors of production, particularly labour

and capital are not getting appropriate returns. The return on farm assets (Table 4) is lower

than the interest rate on national savings (9%) (National Savings Organization, 2000).

Gross margins are positive for both milk and farm enterprise as a whole though meat is a

loss-bearing enterprise and made the livestock (milk & meat) rearing unprofitable even in

the short-run ( Table 3 and Table 4).

Milk enterprise total costs, taking assumed labour costs into account, are almost double

the price of milk. Milk production is not profitable, even with a production increase of

50% per farm (Table 3). This raises the specific question as to which producers are

making profits from milk production. What should be the milk farm gate price and how

is it fixed? How much should the final consumers be paying to make dairying viable for

the producers? This also relates to the question of margins along the milk value chains

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-2000000 -1500000 -1000000 -500000 0 500000 1000000 1500000

Cu

mu

lati

ve

Fre

qu

ency

Rupees

Okara Whole Farm Operating Profits Bhakkar Whole Farm Operating Profits

Okara Whole Farm Net Profits Bhakkar Whole Farm Net Profits

62

and farmers share of consumers’ rupee spent on milk. These questions suggest the need

for a study of milk markets and value chains to inform pro-poor policy development.

Significant losses from livestock enterprises, both as a whole and from livestock trading

incomes, are suspected to be linked to low reproductive rates and high mortality rates

(Table 4) (Teufel, 2007; Teufel & Gall, 1999; Wynn et al., 2006). These losses, in turn,

are possibly linked to widely acknowledged, constrained nutrition of the herd and green

fodder shortages, particularly during peak summer and winter (Raja, 2001b; Teufel, 2007;

Wynn et al., 2006). Our hypothetical improved practices (Table 3) scenario though did

not make all the farms profitable.

Livestock and crops compete for limited land, initially complementing each other but then

become extremely competitive for limited land and labour, adversely affecting

profitability and causing inefficiencies. As a limited resource, over allocation of labour

to livestock also adversely affects the farm productivity, livestock rearing being highly

labour intensive must be considered in the trade-off for crops grown (Erenstein, Thorpe,

Singh, & Varma, 2007). The logical explanation for keeping livestock in these mixed

farming systems includes the other tangible and intangible benefits not explored here in

detail. These benefits include regular cash flows and milk for household consumption,

manure as fertilizer (its prices accounted as cost to crop and fodder enterprise in this

analysis) fuel, and livestock as a liquid asset for quick disposal (Kurosaki, 1995; Otte et

al., 2012; Staal et al., 2008; Upton, 2004).

The structure of Pakistan’s dairy industry at the level of farmer producers and the

challenges they face are those identified by Bain (1968); excessive competition within a

concentrated industry (8.8 million small households) that is economically inefficient.

Bain suggested government intervention to move redundant resources from distressed

63

industries to other occupations and to ensure optimal resource allocation and equity in

income distribution.

However, in Pakistan’s current situation, it is not a practical proposition, given that 45%

of the country’s labour force and 51% of it’s households are associated with agriculture

and livestock, with a low skill base. The official unemployment rate is 6.2%. Though

lower than perceived, the official explanation is that the scarce public social safety nets

mean people are obliged to engage in any sort of economic activity, irrespective of reward

considerations, to make ends meet (Government of Pakistan, 2013b, p. 31; Mazhar,

2013). As for low return on capital (Table 4), given a high double digit inflation averaging

11.8% for the last five years (A. Khan, 2012a, 2013), it seems sensible to hold on to assets

such as land and livestock whose value does not depreciate over time.

A fundamental need for Pakistan’s dairy industry is to raise the productivity given that

8.8 million households (37% of total households) depend on it for their livelihoods, with

89% land and 91% livestock owner households falling into the analysed sample

(Government of Pakistan, 2010). Their prosperity depends on the industry’s long-term

productivity; that is, efficient use of the local factors of production, linked to their

microeconomic competitiveness (Porter, 1998b, n.d.). Porter (1980) suggests that the

benchmark for profitability is long-term government securities. Therefore the farms

earning lower returns will eventually have to go out of business.

This study established descriptive economic estimates of milk, meat, and whole farm as

part of an integrated mixed farming system, based on the data available. Given the

importance of the dairy industry and agriculture sector, there is a need however to

benchmark costs, yields and prices to estimate farm profitability for various districts in

the country on a regular basis. Understanding the economics of this complex integrated

64

system in detail may lead to specialised crop, fodder, meat or milk producers having a

comparative advantage in production and thus increasing industry’s overall efficiency.

Dairy enterprise turned out to be unprofitable for 50% and 40% and whole farm enterprise

unprofitable for 80% and 90% of the farms in Okara and Bhakkar respectively. This leads

to the important question of what land and livestock combination is profitable and

commercially viable for both districts? This question requires further breakdown and

analysis of these farms to find the optimal land and livestock combination. Those that are

inefficient will ultimately have to exit the industry but given limited off-farm work

opportunities; this also remains a challenge.

65

Chapter 4. Dairying in an irrigated mixed crop-livestock

farming system of Punjab, Pakistan: Enterprise

profitability analysis for smallholders

This chapter analyses economics of 115 farms in irrigated Okara district of Punjab. The

farms are divided into small (MG1), medium (MG2) and large (MG3) groups, based on

their milk production to ascertain the most profitable group.


The data from a two-year longitudinal survey supported by the Australian Centre for

International Agricultural Research (ACIAR) funded project entitled “Improving dairy

production in Pakistan through improved extension services” (Wynn, Unpublished) were

used to compile both biophysical and financial data. The survey was conducted from

January 2008 to December 2009 and included 127 farms from 17 villages in the Okara

region of Punjab (Figure 13a). The surveyed farmers were identified using support from

Government of Punjab livestock department’s district extension staff and those

recommended by Idara-e-Kissan11, the only dairy farmer’s cooperative in the country. It

no longer exists.

The irrigated Okara district (Figure 13b) lies between the rivers Ravi and Sutlej and is

part of the southern irrigated plains with calcareous clayey soils. The climate is arid

subtropical and continental with hot summers and mild winters. In the hottest summer

months, maximum temperatures reach 44 °C, and minimums of 2°C occur during winter.

Average annual rainfall is 500 mm and the majority of farmers use tube wells for

11 Urdu word which means organization of farmers

66

irrigation to supplement canal-sourced water. The main crops grown are wheat, rice,

maize, sugarcane, and cotton, with potato being a popular vegetable crop. The district is

well-known for rearing local Sahiwal cattle and Nili-Ravi water buffalo breeds (Dost,

2002, 2003; Government of the Punjab, 2011e, 2012; Pakistan Meteorological

Department, 2013; Small and Medium Enterprises Development Authority).

67

Figure 13 a. Maps of Pakistan and Punjab; b. Map of Punjab showing irrigated Okara district.

Source: City and border data spatial from 2012 ESRI data & maps.

68

The longitudinal survey data aimed to establish a comprehensive description of the

operations of smallholder crop-livestock producers. A key farmer selection criterion was

to include farmers with at least one or two milk animals, some surplus milk production to

be marketed, and some cultivable land. There was no limit on the maximum number of

milking animals, the number of livestock, or the size of the land holding, although small

dairy holders remained the main focus. An easy to understand herd book was used to

gather data with collection frequency varied for different variables. Weekly data were

recorded on milk volume per buffalo and /or cow, type and quantity of feed for the whole

herd at each farm, expenditures on animal health and revenue from sale or cost of

livestock purchase. Monthly data recorded land allocation for different crops grown as

well as the number and composition of livestock kept, including milking animals.

From this survey, data for one cropping year from June 2008 through to May 2009 was

extracted for 115 smallholder farms in the Okara districts. The farms with incomplete

data and the very large farm units, in terms of land area exceeding 50 acres were excluded.

The largest remaining farm was 38 acres.

The key focus of the analysis was the dairy enterprise and profitability from milk and

livestock (milk and meat) production, though all other major farm enterprises were also

brought in to allow analysis at the whole farm level. Minor enterprises such as potatoes,

tomatoes, onions and other vegetable were treated as a single enterprise and given a

category of vegetable and horticulture crops (Kay et al., 2008; Malcolm et al., 2005;

Wilson et al., 2005).

The following are the terms used to define elements of our whole farm economic analysis

(detailed equations used along with an in-text citation of secondary data sources outlined

in Appendix C and D).

69

Statistical analysis was carried out using ANOVA to compare means of physical and

economic attributes for three milk groups (MG). The farms were segregated equally into

three groups and then divided into low (MG1), medium (MG2) and high (MG3) milk

production groups (MG) based on total production per farm rather than production per

head or number of head. Multiple linear regression was used to explore associations

between milk production and three key variables; green feed, concentrates, and roughages

fed to milking animals. A simulated improved feeding regime of three times the average

concentrate per animal, based on the regression analysis, was then used to estimate

changes in the profitability of milk production as an enterprise for the three milk

production groups.

70

Results

The average land holding for 115 farms surveyed was 9 acres and ranged from 1 to 36

acres. The average herd size was 11 animals and ranged from 3 to 29 animals. The survey

farms ran more buffaloes than cattle (2.4:1), which conforms to the national statistics for

the region (Government of the Punjab, 2012), and there were more milking buffaloes than

milking cows (1.8:1). There were statistically significant differences in the herd sizes,

milking animals and total and average milk production for the three milk production

groups (Table 5).

Table 5: Mean physical attributes, average standard error of difference (SE) and p-value of

agricultural land and livestock for farm survey data segregated into milk production classes for the

irrigated Okara district

Measure Milk Production Groups

Total sample size (n) 39 38 38

MG1 Low

< 2,300

kg/yr

MG2

Medium

2,300 to

3,700 kg/yr

MG3 High

3,700 to

10,100

kg/yr

Avg. SE

of diff.

p

Land (Acres)

Total land 7.12 8.82 11.24 1.58 0.035

Livestock (kept for milk and meat)

Herd size (hd) 8.11

10.86

13.91

1.06

<0.001

Milking cows and

buffaloes (hd) 2.45

3.84

4.88

0.38

<0.001

Total milk production

(kg/annum/farm) 1572 3131 5547 237 <0.001

Average milk

production

(kg/annum/milking

animal/farm)

780 990 1234 99.4 <0.001


from Wynn (Unpublished) Where 1 acre = 1 ac = 0.4047 ha or 4,047m2 and 1hectare = 1 ha = 2.471

acres

Multiple linear regression showed there was no association between milk output per

animal and green feed or roughages fed per head per annum. However, the association

between milk output per animal and concentrates was highly statistically significant (p <

71

0.001). The association between milk output and concentrates was the same for each milk

group.

The final model was as follows:

𝑂𝑢𝑡𝑝𝑢𝑡 = {

602.6 + 1.84 × 𝐶𝑜𝑛𝑐, 𝑀𝑖𝑙𝑘 𝐺𝑟𝑜𝑢𝑝 1736.4 + 1.84 × 𝐶𝑜𝑛𝑐, 𝑀𝑖𝑙𝑘 𝐺𝑟𝑜𝑢𝑝 2873.1 + 1.84 × 𝐶𝑜𝑛𝑐, 𝑀𝑖𝑙𝑘 𝐺𝑟𝑜𝑢𝑝 3

The linear equation showed that one kilogramme per annum increase in concentrates fed

per milking animal would lead to a 1.184 kg increase in milk production per milking

animal per annum for each of the three milk production groups (Figure 14).

Figure 14: Milk production per milking animal in relation to concentrates fed for each of the three

milk groups

72

Figure 14 illustrates all three milk groups have the same rate of response to concentrates

fed. None of the three groups was feeding concentrates to the point where the marginal

returns that is milk output from their use would diminish.

Milk enterprise economic analysis for segregated milk production groups

(MG)12:

For the low producers group (MG1) the average variable cost (AVC) of milk production

was higher than the price of milk, and hence the milk enterprise gross margin (GM) was

negative (Table 6). The average total cost (ATC) of milk production was higher than the

price of milk for all three groups, and more than double the price for low producers,

making dairy a loss-bearing enterprise.

12 The analysis was performed to estimate economic and not accounting profits. The variable costs for crops and livestock, whole farm

labour costs and the finance costs to estimate net farm profits had been treated as following: 1. Variable costs (explicit or out of pocket costs such as purchase of fertilizer) for estimating gross margins for milk, meat,

livestock and crop enterprise.

2. Labour costs have been used to estimate operating profits. These costs have been treated as fixed costs on actual basis assuming that the farmer and/or his household is providing all the labour and no contractual labour is hired. These cost are

therefore explicit and not implicit as in accounting.

3. Implicit costs have only been used to estimate net farm profits. It has been assumed that farmer could have earned 9% interest

on land and livestock assumed to be the only assets held.

73

Table 6: Mean economics of milk enterprise, average standard error of difference (SE) and p-value

for farm survey data of irrigated Okara segregated into milk production classes


from Wynn (Unpublished)



A marginal cost analysis of milk production was conducted; using the derived relationship

between concentrates fed and milk production per milking animal by applying the

marginal revenue (MR) equal to marginal cost (MC) rule.

For MG1, an increase in the use of concentrates (Table 6) per farm per animal per annum

slightly lowered the AVC and ATC, but farms remained unprofitable. For MG2 and MG3

however, the increased use of concentrates (Table 6) did not lower the costs. More

importantly, overall losses were curtailed for all three groups.

Measure Milk Production Groups

Total sample size (n) 39 38 38

MG1 Low

< 2,300

kg/yr

MG2 Medium

2,300 to 3,700

kg/yr

MG3 High

3,700 to

10,100

kg/yr

Avg. SE

of diff.

P

Milk Economics

Milk prices (Rs/kg) 22.89 22.84 23.25 0.60 0.752

Milk average variable cost (Rs/kg) 30.76 16.65 12.10 3.13 <.001

Milk average fixed cost (Rs/kg) 26.29 17.01 12.06 2.70 <.001

Milk average total cost (Rs/kg) 57.05 33.66 24.15 4.94 <.001

Milk production profit (Rs from

milk enterprise)

-43,072 -32,064 -679

8,355

<.001

Milk Economics (marginal cost analysis)

Number of times increase in

concentrates 2.37 2.37 1.93 - -

Percentage increase in milk

production 36.3% 40.5% 32.5% - -

New milk average variable cost

after increase (Rs/kg) 29.29 18.08 14.69 2.69 <.001

New milk average total cost after

increase (Rs/kg) 55.59 35.09 26.75 4.56 <.001

New milk production profit (Rs

from milk enterprise) -42,750 -31,540 -601 9,717 <.001

74

Livestock enterprise and whole farm economic analysis for milk production

groups (MG):

Livestock trading income was loss bearing for MG1 and MG2 and meat GM turned out

to be negative for all three production groups. Similarly, the GM for whole livestock

activity that included both milk and meat enterprises was positive only for MG3 with

negligible positive returns on investment made in livestock (Table 7). Whole farm GM

and operating profit was positive for all three groups although net profit after deduction

of finance costs was negative in all three scenarios. This finance cost though relates to

the opportunity cost of capital invested by the farms. The total return on these assets was

also lower, compared to the national interest rate.

Table 7: Mean economic returns for meat production and whole livestock activity. Mean with

Standard error of means (SE) indicated in parentheses. Results of t-tests comparing means.

Measure Milk Production Class

Total sample size (n) MG1 Low

< 2,300

kg/yr

MG2

Medium

2,300 to

3,700 kg/yr

MG3 High

3,700 to

10,100 kg/yr

Avg. SE

of diff.

P

Meat & Livestock Enterprise (includes fodders)

Milk GM (Rs) -6,271 20,123 64,383 6,289

<.001

Meat GM (Rs) -37,014 -74,387 -43,083 50,395 0.730

Livestock activity GM (Rs) -43,285 -54,264 21,300

50,200 0.273

GM return per Rs invested

in livestock activity

-0.018 -0.034 0.007 0.024 0.225

Whole farm

Total crops GM 271,487

353,346 442,862 68,443 0.047

Whole farm GM (Rs) 228,202

299,082

464,162 89,724 0.019

Whole farm fixed costs (Rs) 93,551 129,053 160,881 13,696 <.001

Operating profit (Rs) 134,651 170,029 303,281 78,667 0.082

Whole farm finance costs

(Rs)

401,817 489,926 594,840 77,836 0.049

Net profit (Rs) -267,166 -319,896 -291,559 70,390 0.755

Return on assets % 3.27 1.37 4.24 1.84 0.290


from Wynn (Unpublished)



75

Discussion and Conclusion:

In the short-run, milk production was satisfactory for MG2 and MG3 as P >AVC but the

farms producing less than 2300kg threshold (MG1) were making losses (P<AVC). In the

long-run, once labour costs were taken into account, all three groups became unprofitable

(P < ATC), making dairying unviable for the smallholder producers.

The marginal cost scenario slightly lowered AVC for MG1 but total costs remained higher

than the price for all three production groups (Table 6). The recommendation for lactating

animals is one kg of concentrates for every two litres of milk and 40 to 50 kg of green

fodder per day (S. I. Shah, Bashir, & Bantel, 2005). The three milk groups were feeding

0.32kg, 0.48kg and 0.70 kg of concentrates and 28, 22 and 21 kg of green feed

respectively, which is less than half the recommended dietary intake (Burki et al., 2004;

S. I. Shah et al., 2005; Teufel, 2007). Substantially improved concentrates feeding

benefitted the lowest production groups (MG1) more than the medium and high, due to

the poor livestock nutritional intake. Improving nutritional intake did not, however, turn

losses into profits. This point towards the existing very low base of milk production across

the three milk groups.

The three groups, based on total livestock holdings represent 68% of Pakistani farmers13

(Table 5). The percentage goes as high as 84% if accounted for land holdings14

(Government of Pakistan, 2010). These farmers, categorised as the rural market oriented

(Raja, 2001a; Zia et al., 2011) have not shown promising results.

The analysis does not take into account the short-term gains in animal reproduction and

long-term flow on effects in reproductive performance associated with better feeding

regime. The benefits attained from farmyard manure, its use as fuel and animal draught

13 As the ACIAR survey data ranged from 3 to 29 animals per farm 14 As the ACIAR survey data ranged from 1 to 36 acres per farm

76

power also needs to be studied further to be accounted for. Additionally the analysis has

been done from an economic profit perspective but these farmers may not necessarily

only be driven by profits. There may be other motives for keeping dairy animals in a

mixed crop-livestock farming system that need to be studied further.

Economies of scale effects (Dunne, 1999) were visible with lowest variable costs in the

highest production group MG3. This points to the need to develop a dairy industry with

a more profitable production base than the current structure (Bain, 1968) of mainly small-

scale producers (Government of Pakistan, 2010), which is not feasible in the long-run.

Given the importance of dairying in the irrigated region, a cluster of competitive

production base (Porter, 2000) with a focus on increasing productivity of farms best

utilising the local factors of production (Porter, 2008) is the way forward. A study looking

at farms, which are more competitive in the range studied, is a possible future research

avenue.

In the long-run, there will have to be scaled-up economies with a focus on increasing

productivity or specialisation in more profitable farm enterprises. The smaller

unprofitable producers will eventually have to exit.

The common argument of low opportunity cost for labour (Government of Pakistan,

2013b) will have to be rejected if the policy goal is the best interest of rural producers.

Currently, the producers are not getting a decent return on their labour, which is linked to

the farm gate milk prices taking account of all production costs including labour.

MG3 getting a relatively higher price for milk (Table 6) leads to the question whether

higher volumes lead to higher prices but more importantly, how the milk farm gate prices

are fixed by the marketing channels and supply chains, which these smallholder producers

cater.

77

The livestock enterprise gross margins (Table 7) were negative and the gross margin

return per Rupee invested in livestock was negligible even for MG3. For the whole farm,

short-run gross margins were positive, taking into account variable cash costs. The long-

run net profit, however, accounting for both labour and capital was negative for all three

production groups. Similarly, the return on assets was lower than the national interest rate

on national savings (9%) (National Savings Organization, 2000). For whole farm part of

the research, there is a lack of accuracy in crop gross margin estimates, which are based

on wholesale market prices rather than the farm gate prices (Appendix D). There is a dire

need, therefore, to carry out more detailed studies at each district level in various agro-

ecological zones of Pakistan to benchmark prices and cost of production and understand

smallholder farming systems.

Given the enormous importance of agriculture and livestock production and the

prevalence of small farms throughout Pakistan, such future research is closely linked to

poverty alleviation and would be the first step to guide the development of pro-poor

policy.

78

Chapter 5. A simple value chain framework to highlight

important dairy industry issues and pro-poor benefits in a

developing country context

This chapter studies the industry using a simple value chain framework and borrows from

industrial organisation theory to capture various farm to market functions. A number of

cases were studied and face-to-face interviews conducted with chain actors in arid and

irrigated regions of Punjab.


The study originated from irrigated Okara and arid Bhakkar districts of Punjab. The rural

Pakpattan district and urban Sahiwal and Lahore in the irrigated region and Dera Ismail

Khan city of Khyber Pakhtunkhwa (KPK) province in an arid region, were also studied

(Figure 15a & b) because of their proximity to the key study areas. Field research and

data collection was performed in September 2011. The choice of the districts studied was

based on farm economic analysis of the data of a two-year longitudinal survey collected

by an Australian Centre for International Agricultural Research (ACIAR) funded project

entitled “Improving dairy production in Pakistan through improved extension services”

(Wynn, Unpublished).

79

Figure 15a. Map of Pakistan and Punjab; b. Map of Punjab showing rural Bhakkar district and D.I. Khan city (D.I.Khan is in Khyber Pakhtunkhwa province) in the

arid region and Okara and Pakpattan districts and Sahiwal and Lahore cities in the irrigated region of Punjab


80

Collins et al. (2007) raise the need to scope the performance of the whole supply chain as

a dynamic system and provide a framework for rapid supply chain appraisal. Such

scoping studies identify how the farmer to consumer system works, the actors and their

roles, and value creation along the chain through case studies. For this research, Collin’s

approach was used to develop a simple value chain lens to study these chains and the

wider industry.

A purposive sampling method was used for the field work to ensure the sample adequately

represented the particular interest of the study (Patton, 2002). Face to face interviews

were carried out using four questionnaires (attached as Appendix E), designed for the key

actors including the milk producers, dhodhis, retailers and consumers. Table 8 details the

number of chain respondents at different levels.

Table 8: Chain actors studied at various tiers in Pakistan’s dairy industry.

Value Chains /

Respondents

Okara District (rural), rural

Pakpattan & urban Sahiwal and

Lahore

Bhakkar district (both rural

and urban) & urban Dera

Ismail Khan district

Milk Producers 13 14

Dhodhis (collectors

& distributors) Small

Small

6 5

Medium 5 3

Large 3 2

Formal Processors 1 1

Retailers 12 10

Consumers 8 3

Data Source: Author’s field research

For this preliminary industry investigation, a simple framework (Table 9) (Altenburg,

2006a; United Nations Industrial Development Organization, 2009) was developed and a

pro-poor value chain analysis approach applied. The data was collected by exploration of

the most logical functions performed by each link in the chain (Kohls & Uhl 2002;

81

Schaffner et al., 2003). These activities were dissected into small components and then

reassembled to explain the whole system. The dynamic framework development

continued with the analysis of the raw data, and this process allowed understanding and

summarising of various models of domestic fresh milk chains and the interactions

between the chain actors. This research was iterative action learning (Olsen, 2012) that

borrowed key concepts from the social sciences to support the method. Action research

primarily addresses key problems in communities and involves creating positive change.

It has been described by Reason and Bradbury (2008) as, “Action research is a

participatory process concerned with developing practical knowing in the pursuit of

worthwhile human purposes. It seeks to bring together action and reflection, theory and

practice, in participation with others, in the pursuit of practical solutions to issues of

pressing concern to people, and more generally the flourishing of individual persons and

their communities.”

82

Table 9: Data collection and analysis framework for milk value chain scoping study

What? i.e.

Functional

Approach

(Exchange,

Facilitating &

Physical Functions)

&

Who does what?

i.e.

Institutional

Approach

a. Buying and Selling (volumes and time along the chain)

b Financing (Contract, cash advances & payment mode) closely linked to buying

and selling arrangement

Consumer Value1 i.e. what the final consumer’s value?

c. Standardisation (quantity measurement and quality assessment)

d. Price Determination (price at farm gate & retail level, seasonal i.e. summer

and winter price change, who gives the price?

e. Transport, Storage and Processing

f. Risk bearing

Source: Authors fresh produce value chain analysis framework adopted from Kohls & Uhl (2002) and

Schaffner et al. (2003) 1 Consumer value used in this analysis framework is not part of the original functional and institutional approaches to study food

marketing system, hence not numbered in the table above

This section will explain the framework in some detail using literature on which the

scoping study was based. The questionnaires combined fixed-choice and open-ended

questions for quantitative and qualitative inquiry respectively. Standardisation of units of

quantity and quality assessment, price fixation mechanism and financing were not directly

explored but emerged as important wider industry issues.

Before explaining the value chain framework used for this scoping study some

background of industrial organisation theory is necessary to make sense of the wider

context in which the firms operate at different tiers of the Pakistani dairy industry.

Economic theory recognises that the behaviour of firms is influenced by the structure of

the industry (Bain, 1968) in which they operate. This structure is described by the

following three key characteristics:

1. The degree of the seller (or buyer) concentration: This includes the number of

firms (one, few or many) and the size distribution of firms in the market. Competition

83

within an industry is determined by the degree of concentration within groups of

competing firms.

2. The degree of product differentiation: The extent to which a product is

differentiated and how this differentiation is perceived by the buyer.

3. The barriers to entry / exit: The relative ease or difficulty with which firms may

enter or exit the market.

Eight different types of market structures, four on the selling and the buying side are

widely recognised.

Pure Competition (buyers & sellers) – there are many buyers and sellers; the products

produced are the same and the firms are ‘price takers’. There is perfect information about

product supply and demand, and there is freedom of entry and exit from the industry.

Pure Monopoly (seller) / Pure Monopsony (buyer) Competition – there is only one

buyer or one seller, which theoretically allows the firm to be ‘price maker’. The firm

protects this position by prohibitive barriers to others’ entry into the market. These

barriers may include access to key inputs, extremely high capital requirements or

technology.

Oligopoly (sellers) / Oligopsony (buyers) Competition – there are few buyers or sellers

in a market selling identical or differentiated products. The firms are mutually

interdependent in terms of pricing, market share and marketing practices. There are

effective but not prohibitive barriers to entry such as fairly high plant and equipment

costs.

Monopolistic (sellers) / Monopsonistic (buyers) Competition – there are many buyers

or sellers, not enough to be no effect as perfect competitors and not so less as to make

them interdependent as oligopolists. The products are differentiated, though very close,

they are not perfect substitutes and competition amongst firms is often vigorous on

84

attributes other than price. Market information is not perfect, and entry to and exit from

the market is relatively easy.

Buying and selling

Buying and selling function identifies the quantity of product flowing through the value

chain to enable estimation of volumes at different stages (Purcell et al., 2008). Timelines

along the chain point to continuous and efficient product flows, on a day to day basis, to

minimise wastage or avoid unusable inventory (Bonney, Clark, Collins, Dent, & Fearne,

2009).

Finance

Financing is needed by firms to perform various functions for the system to operate and

access to financial capital is the lifeblood of any business (Gunderson et al., 2009; Kohls

& Uhl 2002).

Consumer value

Consumer value was ascertained as the value chain perspective says that chains are driven

by the final consumers who ultimately determine where the value lies in the product

(Fearne, 2009a, pp. 8-10) and have specific attributes bundled as quality (Collins, 2009).

These final markets drive the product standard and quality specifications (Kula et al.,

2006, p. 17).

Standardisation

Standardisation establishes uniform qualitative and quantitative measurements. It

simplifies buying and selling and ensures the flow of uniform products on a mass scale.

Only adequately defined quantity and quality units can allow price quotation to work well

(Kaplinsky & Morris, 2001). In the dairy industry context, quality means milk

composition and attributes valued by the final consumer (Boehlje & Schiek, 1998).

85

Price determination

Price determination is a process whereby once a product leaves its point of origin, transfer

of title takes place and value judgment comes into play. The product exchange only

happens if an arbitrage opportunity exists, that is, a profit opportunity of buying at low

prices and moving to plentiful demand areas where higher prices prevail. A product title

may change several hands from primary producer through to the final consumer and each

time it changes hands; a new price is determined. The price is either negotiated, or the

two parties may enter into a contract that sets a price for a specified quantity and/or length

of time (Gunderson et al., 2009; Kohls & Uhl 2002; Schaffner et al., 2003).

Transport, storage and processing

The movement of farm products from where they are produced to consumption centres

creates place utility. The speed and flexibility of transportation affect inventory (Kohls &

Uhl 2002). Supply and demand are seldom in immediate balance in the food system.

Storage is required to act as a buffer for day-to-day variations. It makes a product

available at the desired time, creating time utility (Kohls & Uhl 2002; Schaffner et al.,

2003). The fresh agricultural products are processed to a greater or lesser degree to create

form utility (Kohls & Uhl 2002; Schaffner et al., 2003). Mapping the product flows

identifies the product’s transformation and creates a clear picture of what forms of

products are handled at each stage of the chain (Purcell et al., 2008).

Risk bearing

Risk bearing is another component of fresh produce chains. The physical risk of product

deterioration or spoilage can result in substantial losses to the firm holding the title

(Boehlje et al., 1998; Gunderson et al., 2009; Kohls & Uhl 2002).

86

Results:

A number of models of milk value chains existed in both the districts and are depicted in

Figure 16.

87

Figure 16: Various milk value chain models from rural producer to final consumer

Rural milk producers

Rural

neighbour

consumer(s)

Small

dhodhi

Village

grocery

shop

Urban retailer /

direct to

consumer

household

Local dhodhi(s)

& sweet shop

owners in

nearby town /

city

Urban

consumer (s)

Cheese

maker(s)

Local

wholesale

dhodhi&

supplier

Urban

retailer

Rural

consumer(s)

City / small

town

consumer(s)

Small

dhodhi

City / small

town

consumer(s)

Small

dhodhi

Small

dhodhi

Medium

dhodhi

Large

dhodhi

Metrop-

olitan

city

urban

retail

shops

Urban

consumer(s)/

tea stalls

Large milk

processor’s rural

collection centre

Large milk

processor’s

plant

in

nearby

city

Rural & urban

retail grocery

stores

&

super markets

Small &

medium

dhodhi

Large

dhodhi /

contactor

Rural &

urban

consumer(s)

Mega

dhodhi

/contactor

Small

dhodhi

a b c d e f g h

88

Buying and selling:

Key function of buying and selling will be explored here while introducing farmers,

dhodhis, processors and retailers. Table 10 summarises major capital investments made

by the businesses, time along the chain and volumes traded.

89

Table 10: Capital assets, time and product volumes along the chain

Regions Producer Small dhodhis In Irrigated Region only Retailers

Medium dhodhis Large dhodhis

Both regions

Capital assets

invested

Land & livestock Cash advance

extended to farmer

suppliers

A few collection pots

transport i.e. either

bicycle or motorcycle

Cash advance extended

to Small Dhodhi suppliers

transport i.e.

motorcycle or Toyota

Hilux

Collection pots

Cash advance extended

to small dhodhi & medium

dhodhi suppliers

Credit supply to some

regular retail buyers

transport i.e. truck(s)

collection pots

Varied with scale and

size mainly

Cash advances

extended to the

suppliers

Deep freezers.

Bigger businesses

owned

the shop as in

property and

milk chillers

Time of the day

along the chains

morning &

evening milking

5 to 11am

&

6 to 9pm

Varied with the nature of

operation

5am to 12midnight

5am to midnight while

some operated round

the clock

Informal in

Irrigated

Region

Volumes per

day

2 to 12 L 45-320 L 600 - 1500 L 2800-16000 L 20 to 25,000L

Informal in

Arid Region

Same as above 40-150 L

20 to 800L

Formal

Processors in

both regions

All above actors selling various quantities at rural chillers 25,000 to 150,000L


90

At the rural level, there were 5 to 10 small dhodhis in each village, some of whom were

themselves, small farmers. These small dhodhis were the key collectors of milk at the

farmers’ doorstep. Their collection was supplied to a range of businesses. At the urban

level of the irrigated region, small dhodhis were buying from specialised retail milk shops

and delivering to households. Though only observed in metropolitan Lahore as in smaller

cities, small dhodhis from adjacent rural areas were delivering directly to households.

Some medium dhodhis collected milk from farmers’ doorsteps whereas others were

buying from small dhodhis. Some were selling to large dhodhis and others sold directly

to retail shops and/or the formal processors. Large dhodhis were collecting from medium

dhodhis and supplying either to specialised urban retail milk shops in Lahore and/or

Sahiwal. Quite a few large dhodhis had their own shops, set up as a family business that

is vertically integrated downstream. Almost all dhodhis admitted to be supplying excess

winter supply during the production flush to large formal processors either directly or

through large contractors. This was their cushion as demand in the fresh milk market was

said to go down while supply increased.

Milk retailers in both regions ranged from small rural grocery shops, local khoya and

cheese makers, traditional sweet makers, bakers and confectioners to specialised milk and

milk product retailers. In the irrigated region, shops were commonly buying milk from a

medium or large dhodhi. Some bigger urban retail shops were more vertically integrated

upstream and were buying directly from farmers. One particular retailer15 was the

exception and was completely vertically integrated from production to final sale. In the

arid region, most shops purchased either directly from the farmers working as a

cooperative along the Indus river belt or from small dhodhis.

15 JTRYK Dairies. The name of the dairy has changed to hide the identity of the entrepreneur

91

In both regions, retail customers were the final consumers although some big traditional

shops had small dhodhis buying milk to resell to households. In the irrigated region, shops

even claimed to be supplying milk to formal processors when in excess supply or winter.

Quite a few retailers were also supplying khoya (thickened milk) and sweet milk to

wedding functions.

Formal processors had set up their own collection centres in various villages where

farmers were delivering milk directly, though supply from small dhodhis was also a

common occurrence. In the arid region, Nestlé was the only formal processor though in

the irrigated region some processors were collecting milk. These processors can be

divided into two groups, namely the big multinational and national companies such as

Nestlé, Engro and Haleeb and smaller ones such as Adam’s Cheese. The collection

between these two groups varied by a wide range, increasing in winter, which is the

season of oversupply. Bigger companies had installed chillers at their respective rural

collection points, whereas the smaller processors were using ice for cooling milk before

carrying it to the plant. All large processors were said to be bulk buying from very large

contractors, who collected milk from the large collectors of traditional chains. These

processors were selling packaged and processed products through more organised grocery

shops that stocked a variety of retail products.

Finance

In this section, we will study the contractual arrangements along the chains and cash

advances extended by various chain actors that have been summariszed in Table 11.

92

Table 11: Contractual arrangements and cash advances along the chain

Sector Regions Services Written

Contracts

Cash Advance

Cash Advance Practice Guarantee Basis of cash advance

Informal

Sector

Irrigated

Region

Small dhodhi or

medium dhodhi

supplies to

farmers:

Feed for

animals

Fertilizer

household

grocery

No Yes

cash advance to most farmers

irrespective of size

Interest-free loans to small

dhodhis

milk on credit to retailers

For small dhodhis a personal

guarantee

or a signed cheque in some

cases

Upstream, at each tier, the

amount of cash advance

extended is based on the

volume of milk supplied i.e. for

farmer, small dhodhi, medium

dhodhi & large dhodhi

Downstream for retailers it is

based on the volumes of milk

purchased

Arid Region Same as above No Yes but

cash advance not for farmers &

retailers extending to dhodhis

No NA

Formal

Sector

Irrigated &

Arid Region

Some larger

processors only

awareness

raising materials

informal

trainings

No Yes some large formal processors

but only to big farmers

Some smaller local small

processors

but only to medium and large

dhodhi suppliers

Have sufficient collateral NA


93

In both regions, there was no formal written seller-buyer contract at any tier in either

sector (Table 11). Milk was being sold solely on the basis of verbal commitments. The

small dhodhis were supplying cotton seed cake, rice bran, and concentrate ration, bags of

fertiliser and in some instances even groceries as payments for milk, to the farmer’s

household.

In the irrigated region, a cash advance was a common practice extended by the buyer to

the seller from the farmer through to the retailer. Effectively the seller had an investment

in the business. The amount of advance extended was based on the volumes of milk

supplied; i.e. the higher the volume, the higher the cash advance payment. A personal

guarantee or a signed cheque was taken as an assurance in some cases, against the advance

taken. Farmers, in addition, borrowed money on a need basis from their small dhodhi

buyers. Medium dhodhis were extending cash advances as interest-free business loans to

their small dhodhi milk suppliers. Large dhodhis claimed to have extended millions of

rupees in cash advances to medium dhodhis and small dhodhis and in some instances

were supplying milk on short-term credit to the retail buyers. Most retailers also claimed

to be extending cash advances to their milk suppliers. In the arid region, a cash advance

practice was prevalent only in few specific farmer cum small dhodhi models, receiving a

lump sum amount from retailers for a six monthly verbal milk supply contract.

The formal processors did not use the cash advance payment system and were only

extending short-term loans to more organised commercial farmers with collateral

infrastructure and supplying at least 40L of milk per day. To qualify they also needed

dedicated bank accounts for processors to deposit payments whereas the dealing for

informal chains was in cash.

94

Consumer value

Consumers of fresh, unpackaged milk, interviewed at various retail shops in four urban

centres (Figure 15b and Table 8) were buying 0.5 to 12 L of fresh milk. Higher butterfat

content and sweetness of taste were attributes commonly valued. Fresh milk was boiled

before use and cream set on the top, firmness of yoghurt made from it and the taste of tea

were quality indicators. There was confusion among consumers on units of fresh milk

purchased. These consumers occasionally bought packaged ultra-heat treated (UHT) milk

as well at almost double the price of fresh milk.

Standardisation

In this section, we will explore the quantity measurement and quality assessment criteria

that varied a great deal within the various chain models in the absence of a uniform

industry-wide standard.

Quality Assessment: In the informal milk chains the key quality criterion was butter fat.

Formulae used to assess quality at various tiers and within chains varied a great deal and

are summarised in Table 12.

95

Table 12: Criterion to assess milk quality at various tiers and within formal and informal milk chains of two regions

Irrigated region informal chains Arid region informal chains Formal processors in both

regions

Farm gate

buyers

Small dhodhi mainly buying on the basis of Organoleptic test i.e. visual

appearance, taste & smell

Being present at the time of milking or self-milking

Some medium dhodhis buying directly from farmers doing LR test

Same as irrigated region but in addition

small dhodhis commonly used a small

flotation metal instrument, about two inches

long containing a standard volume of the

heavy metal mercury to check viscosity of

milk

At village milk collection

centres

Organoleptic

Solid Not Fat (SNF) %

Total Solids (TS)%

Lactometer reading (LR)

Larger processors claimed to

carry out more tests at sub-

centres and main centres /

processing plants

Medium

dhodhi and

large dhodhi

buyers

Medium dhodhi and/or large dhodhi buying on fat basis using Gerber

method. A small sample of milk was taken in butyrometer, mixed with

sulphuric acid and Amyl alcohol and centrifuged in a manual machine that

gave an average fat reading. Fat standard at this tier was set at 6% for sellers

and reward penalty system in place. Lactometer reading (LR) was also taken

Some large dhodhi who very vertically integrated at retail end checking

SNF and TS as formal processors

NA

Retailer

buyers

Organoleptic test

Dipping of hands in milk to check viscosity

Firmness of yoghurt produced from milk

Consumer feedback is also important.

Yield of khoya (thickened milk) from the boiled milk sample

Same as irrigated region but in addition the

practice of checking viscosity of milk using

the heavy metal instrument as done by small

dhodhi


96

At the farm gate, in both regions, milking testing at the farmer’s doorstep was culturally

unacceptable hence, the practice of organoleptic16 testing was prevalent. At the rural milk

collection centres of formal processors17 (Table 12), however, where the farmers from

same villages / communities were selling milk, in addition to the organoleptic test, fat

content, SNF, and TS percentage tests were performed to check the quality of milk.

Product labelling was non-existent in informal channels and the information provided

through labelling by the milk processors, on the packaged milk by both national and

multinational companies, was also vague. For example, Table 13 describes the labelling

of UHT packaged milk by Nestlé, Engro and Haleeb, the three larger formal processors.

There was no mention of fat, which was highly preferred by the final consumers and a

key quality aspect in informal chains.

Table 13: Nutritional facts per 100 ml mentioned on UHT packaged milk of three major processors

Energy Protein Calcium Carbohydrates, Lactose, iron, Vitamin A, C and

phosphorus

64

kilocalories

3 to 3.2

grams

132 mg Various quantities variably mentioned

Data Source: Information obtained from the packaging

Measurement units for quantity: In both regions, the survey results indicated that different

units of the sale were used in different tiers of the chain. The formal processors and their

sellers used litres as their standard unit. The final product was also being sold in litres.

In informal arid region chains, far less confusion was observed in units. Farmers, dhodhis

and retailers commonly mentioned kg (1000grams) or the larger local unit of maund

(40kg), though undersized measures at retail level cannot be ruled out.

16 Organoleptic test is a simple test and requires just looking (eyesight) and smelling. If the milk has a bad smell, or abnormal colour, or contains particles, it should be rejected. 17 In rural pockets, formal processors’ milk collection centres were not as widespread as the informal dhodhi networks.

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In informal irrigated region chains, however, there was enormous confusion due to the

variation in the measurement units used from farm to the final consumer. The weights

and units varied between the local units of gadvi or seer, kilogramme and litres. The actual

quality and weights for these measuring units varied depending on who the buyer/seller

was and their position in the chain. For example, the same term gadvi had different sizes

depending on who was using it. A gadvi was 1100 to 1130ml rather than the actual litre

for small dhodhis, thus buying from the farmers resulted in a gain for them of 4 to 5L per

40 litres purchased. The same gadvi at retail shops was around 900ml when selling to the

consumer. At the rural central collection point in the chain, the conversion to actual units

by the large dhodhi resulted in a gain of 100 to 130ml per litre and then the fat

standardisation resulted in either a loss or gain of another 100ml per litre. At this stage

around 160 to 170 grams of ice was added per 1L of milk, higher in the summer season,

which increased the milk volumes by around 5 to 6L for each 40L collected: this was

called the Lahori maund of 46 litres. The unit conversion at different points of the chain

was possibly used deliberately to gain undue advantage.

Price determination

In this section, we will describe the farm gate and retail price fixation mechanism and its

link to seasonality in milk production. Table 14 gives a price range from the two regions.

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Table 14: Average price range at farm gate and retail end formal and informal chains in the two

regions

Regions/Formal

& Informal

Average

existing farm

gate milk prices

Dhodhis Average retailers prices raw of fresh milk

Informal in

Irrigated Region

35 to 40 Rs/L 2 to 5

Rs/L

margin

42 to 75 Rs/L

50 Rs/L city/district government price fixed

for the whole year

Informal in Arid

Region

30 to 45 Rs/L 45 to 60 Rs / L

40Rs/L city / district government price fixed

for the whole year

Packaged UHT longer shelf life milk

Formal Processors

in both regions

30 to 40 Rs/L 80 to 100 Rs/L for various brands


Farm Gate Prices: Overall milk production was said to decrease in summer and increase

in winter but the demand was opposite to the production cycle. Farm gate prices in both

regions were said to be changing seasonally. In informal chains, particularly in the

irrigated region, the prices would increase and regularly fluctuate in summer, based on

market demand and supply, and decrease in winter. The formal processors were said to

absorb excess winter supply from informal chains.

In the irrigated region, the chains with more intermediate participants were offering

relatively lower farm gate prices (Table 14). In the arid region, the lowest price was

observed at a Nestlé’ chiller and the highest was observed for a farmer cooperative model

selling milk directly to an urban specialised milk shop.

In both regions in informal chains, farm gate milk prices were negotiated to some degree

between the seller and buyer. A higher price was offered for buffalo versus cow milk due

to higher butterfat content in it. In the arid region, small dhodhis were being offered a

price by their retail buyer(s) while in the irrigated region, medium dhodhis & large

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dhodhis were giving a price based on urban market demand and supply. In irrigated

regions, the prime farm gate price setting mechanism and its fluctuation were stated to be

based on the Pakistan Dairy Association’s (PDA) formal notifications issued at the rural

central collection points. The PDA was said to do this in consultation with the large

formal processors. Overall, the farm gate price set by the largest buyer, Nestlé, was used

as the ultimate benchmark.

Retail prices: In both regions, the retail prices of fresh, unpackaged milk varied a great

deal among retailers and localities. The city district government fixed the retail milk price

once every year in the month of May, which is at the start of the summer season. The

purchase price paid per unit by the milk retailers to their sellers was the same as or higher

than the retail price fixed by the government. The prevailing retail prices, on the other

hand, were observed to be both lower and higher than the government’s fixed retail price.

It is assumed that in the case of lower prices, the quality was inferior, and/or the quantity

sold was less than the volume stated by the government or both. The specialised milk

retailers in both regions were well aware of the government fixed prices, prevailing

market prices and those being charged by their competitors although they stated that they

were still establishing their own price independently.

In the irrigated region, some very large urban retailers who were also large dhodhis,

including the PDA members, played an important role in establishing the price. The

buying price paid to milk suppliers was said to fluctuate based on supply and demand

although retail prices were fixed for the whole year and were difficult to change because

of the sensitivity of final consumers to prices. In the arid region, the price was set by

mutual agreement between the dodhi supplier and the retailer and changed every six

months, increasing 2 to 5 Rs/L. Formal processors were selling packaged milk at almost

double the government’s fresh milk price.

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Transport, storage and processing

In this section, we study the key physical functions of transport, storage and processing

that had been customised based on the local demand and profitability of the targeted

market segment.

Transport: In both regions, the majority of farmers did not have to use any means of

transport because milk was being collected at their doorstep. A few farmers were

delivering their produce to the collection centres of the formal processor(s) on foot or

using bicycles or motorcycles. Small dhodhis were using bicycles and/or motor cycles

and in some cases local rickshaws and public transport to collect/deliver the milk. The

small dhodhis were using 46 to 50-litre steel containers called dabbas or pandas to collect

milk. An average of 50km radius was covered by each small dhodhi to collect and/or

deliver the milk.

Medium dhodhis were using motor cycles or mini trucks based on the nature of their

operation, and some did not need transport because they were merely facilitating the

transactions between small and large dhodhi and working on a commission basis. Large

dhodhis had relatively bigger trucks fitted with either a non-refrigerated steel tank or large

plastic cans (128 to 160 litres each). Most urban retailers did not require any transport

because milk was being delivered on vans/trucks or traditional horse or push carts. A few

shops were delivering milk to households on motorcycles, or a shop worker would deliver

on foot.

Storage: In both regions, some farmers were storing small quantities of milk from the

evening milking to be sold the next day. Small, medium and large dhodhis were collecting

and delivering milk to their next customer downstream within a few hours of collection

on the same day and did not store the milk. Ice in different quantities, depending on the

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stage of dhodhi in the chain, was being added to maintain lower milk temperatures.

Specialised milk retailers were storing milk overnight and most commonly sold milk

within 24 hours of delivery to ensure the continuous flow of milk into their shop reached

the consumer promptly. Specialised milk retailers owned deep freezers, and bigger

retailers and retail chains had chillers, particularly in the large metropolitan Lahore. The

small cheese and khoya makers did not have any storage facility. In the arid region, some

shops did not have a storage facility and were setting yoghurt from the left over milk

overnight for use the next day.

Processing: At the farm gate there was no processing for commercial purposes, and lassi

(a yogurt-based drink), yoghurt, butter and desi ghee (clarified butter) were being made

for home use only. Similarly, the small, medium and large dhodhis were not conducting

any form of processing. Only the specialised retail shops were making yoghurt followed

by lassi. Other common milk based products were khoya (thickened milk), butter, desi

ghee, sweet milk, kulfi (traditional ice cream), rabri (condensed sweet milk with nuts)

and a range of traditional local sweets such as burfi (sweet confectionary made of

condensed milk and sugar). In the arid region, a few specialised shops in Dera Ismail

Khan city were making sohan halwa, a local milk-based sweet which is quite popular

nationwide. Similarly, formal processors were making a range of dairy-based products

such as cheese and ice creams in addition to processing milk and making yoghurt.

Risk bearing

For small dhodhi, the collection and delivery times and distances covered were relatively

shorter and thus lesser spoilage risk. The risk was prevalent, however, for small dhodhis

too, particularly in hot summer as the commercial buyer dhodhi discouraged dilution by

offering a reward based on higher fat percentage method. The risk of spoilage increased

with larger volumes collected downstream. Once the milk exchanged hands, it became

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the responsibility of the buyer. Apart from common spoilage risks, the supply disruption

due to riots or flooding was also highlighted as an important risk factor.

Discussion:

The application of this simple value chain framework approach to study the Pakistani

dairy industry provided information on its structure (Bain, 1968; Kohls & Uhl 2002; Seitz,

Nelson, & Halcrow, 2002) in terms of the number of sellers and buyers and production

differentiation at various tiers and its impact on the performance of the industry, which is

as following:

Upstream at the rural production end, the dairy industry has 8.8 million milk producer

households and a few hundred thousand dhodhis, particularly the smaller and medium

dhodhis. These actors buy and sell raw fresh milk as a homogenous commodity and

have no influence on the prices. These actors face formal processors (Zia et al., 2011)

that represent an oligoposony market structure as buyers and oligopoly model as

sellers. These processors are mainly selling their own differentiated brands of UHT

milk and exercise the substantial power to set the farm gate price and charge a high

price for the final product.

Downstream at the retail end, there are a small number of emerging informal chains

that are vertically integrating and represent the characteristics of monopolistic

competition. These chains have established their own brand names at their specialised

milk shops in the final markets, particularly observed in Sahiwal and Lahore cities

within irrigated Punjab. This branding gives them product differentiation and the

ability to set retail prices.”

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Buying and selling

Buying and Selling: Given this dairy industry structure, the research has highlighted the

important function of collection and distribution of milk being performed by the dhodhis

and a greater appreciation of their role. These actors free up producers to focus on

production and consumers for other pursuits thereby saving time. It is unimaginable for

8.8 million farm households to find specific buyers among 185 million consumers in

Pakistan (Mazhar, 2013). The transaction costs of linking sellers and buyers and

negotiating exchanges are borne by the dhodhis.

The farm level industry structure of very small holdings with the national average of 6.4

acres land holding, and 91% households having less than 10 animals (Government of

Pakistan, 2010) leads to small volumes produced and sold. These quantities are not

commercially viable in the long-run although in the short-run they seem to meet farm

household nutrition needs and provide a quality product not available to general

consumers in the market. The middlemen and retailers in informal domestic chains are

performing collection and distribution more efficiently than their formal sector

competitors using their extensive network of collection and distribution that has evolved

with time. The formal sector is largely dependent on informal channels unless specialised

farmers with economies of scale enter the market. Larger volumes per farmer may also

benefit the middlemen, particularly the small dhodhis as product volumes handled by

them, and therefore profits, are very small.

Finance and contractual arrangements

Cash advance mechanism and needs based borrowing, particularly in the Punjabi irrigated

region, is a unique strength of these informal chains. The small dhodhis work as banks to

meet the day-to-day need of their farmer suppliers. The medium dhodhi provides interest

104

free loans to small dhodhi to establish their own business to earn a livelihood. Large

dhodhi supplies milk on credit to retailers. These loans are extended without any formal

written contract.

Standardisation and consumer value

Any industry where mass scale buying and selling takes place has to have effective

standards that are also the basis of an effective pricing process. If a lesser quantity is being

sold for a given price per unit and the retailer is charging a certain price per litre but

selling 900ml, or if the diluted milk is being sold at the price of pure milk, then the retail

price fixed by the government becomes meaningless. Standardisation of quantities at

different tiers of the informal chains is an important area that needs to be addressed at the

policy level. The current practices benefit the middlemen and retailers but incur huge

losses to the producer and consumer which, when aggregated, make up billions of rupees

in both monetary terms and milk volumes. On the other hand, these mechanisms give

some leverage for the middlemen to adjust margins, which may be non-existent in the

absence of such clandestine manipulation.

Similarly, as for quality, in the absence of uniform industry standards and grading, each

actor has his own formula for buying milk. In informal chains, the actors downstream are

more organised but the small dhodhis are merely buying on the basis of experience. The

quality judgment criterion from farm to market varies a great deal and leads to an

environment of mistrust. The formal processors though are organized and have their own

quality testing formulas. A third party, as an independent authority should be formed to

ensure the best interest of local producers, informal chain actors, particularly small

dhodhis, and consumers. For milk as a commodity, a single pricing system based on

specific quality attributes could be used as a value indicator. This mathematical formula

105

sets the price and in more developed economies is based on the cost of production at one

end and consumer price index at the other end. The formula is often established in

consultation with government authorities, with the main challenge being to maintain

realistic pricing in the face of fluctuations in supply and demand (Schaffner et al., 2003).

Unlike the current practice, a single quality assessment formula should be used across the

whole industry and at various tiers of the milk chains.

More importantly, the policy needs to ensure that the milk meets the nutritional needs of

Pakistani consumers who spend one tenth of their households income on milk

(Government of Pakistan, 2013a) in a country where 60% of the population lives below

the poverty line of US$ 2 a day (World Bank, 2013). Poverty is closely associated with

under-nutrition (Otte et al., 2012). The challenge is to educate the uninformed public of

the nutritional virtues of milk and its components. The damage done to the product by

boiling it also needs to be highlighted.

Price determination

The milk price setting mechanism is a crucial aspect linked to the future development of

the industry and a policy issue. At the farm gate level, the research revealed that formal

sector players, who primarily buy from the informal chains, have the main say in price

fixing in the absence of any formal mechanism set by the government. The current price

mechanism is linked to the structure of the dairy industry. A large number of smallholder

farmers and dhodhis, that supply or trade in small volumes, cannot influence price or sale

volume of larger enterprises and therefore are price takers. The formal processors,

however, handle a large enough proportion of output to affect price or sale volume of

other firms, and that leads to price-output interdependence. These commercial industry

leaders are sufficiently influential to facilitate collusion and control of milk price setting

at the farm gate (Bain, 1968). Rogers and Sexton (1994) highlighted the need to consider

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the monopsony/oligopsony issues in the policy development debate, particularly in the

agricultural markets, to promote competition. The aim of regulatory policy should be to

improve market performance by encouraging a competitive environment free of collusive

or predatory activity (Bain, 1968).

Similarly, at the retail end, retailers who are large contractors as well as supplying formal

processors, negotiate milk prices with the city government during the course of annual

price reviews for fresh, unpackaged milk. In the markets we have observed, each retailer

had set his own price with very little regard for the government price. This retail price

fixation was also noticed by the Pakistani government price regulatory body (Competition

Commission of Pakistan, 2012). Another complexity is that the farm gate prices fluctuate

with summer and winter seasons and even within any specific season based on market

demand and supply. However, the government retail price is fixed for the whole year, so

the question remains as to how the quality of the product is ensured.

Transport, storage, processing and risk bearing

The informal chains use unrefrigerated transport but the distances covered are far lower

when compared to formal processor chains. The lower carbon footprint of these chains

may be important in a country where environmental control mechanisms are not well

developed. Similarly, the absence of proper storage along the informal chains means an

efficient mechanism to deliver fresh milk to the final consumer is required. It also means

high risk borne by the intermediaries and retailers downstream. Dilution with ice becomes

unavoidable despite the best intentions of those who want to avoid it. Anderson et al.

(2007) state that firms customise these logistics according to the requirement and

profitability of the customer segment. To establish proper cool chain infrastructure to

maintain a certain temperature is a costly endeavour (Gunderson et al., 2009) in a country

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where 60% of the population lives on less than US$ 2 a day (World Bank, 2013).

Therefore, the question is, “will the average consumers be able to afford to pay for this

through a higher retail price?”

Conclusion:

The simple analytical method developed and used to study the industry and reported

herein revealed some insightful findings. The discussions that originated from this

analysis have raised further questions that require further research and a more rigorous

analytical framework. There is a further need, however, to review individual case studies

more carefully at the rural–urban fringe where there are pressures on land-use and

burgeoning urban populations of milk consumers.

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Chapter 6. Identifying producer, middlemen, retailer and

consumer issues from a pro-poor value chain perspective: A

dairy case study from irrigated Punjab of Pakistan

This chapter focuses on one specific value chain as a case study in the irrigated region of

Punjab. The chains originated from rural Okara district and supplied milk to the urban

consumers of metropolitan Lahore city. The reason for going back to this specific chain

will be described further in the methods section. This case study will be reviewed in

further detail in Chapter 8 and its Appendix G to fill the missing details.

Methods:

Collins (2009, 2007 ) defined food value chains as systems driven by the interaction of

their technical (production, processing, transport, etc.), economic, information-related

and governance subsystems. This study uses this definition to examine the four chain

subsystems of a specific fresh milk chain from rural producer to urban consumer. It

describes a set of unwritten rules, which govern the chain and price fixing and sharing

mechanisms.

Fresh produce chains require physical transport, storage and some processing that is

customised to the requirement of consumers and profitability for vendors (Anderson et

al., 2007; Kohls & Uhl 2002; Schaffner et al., 2003). The firms in chains assimilate across

organisational boundaries through the provision of products and services that add value

for their customers (Lambert & Cooper, 2000).

Governance of value chain activity comes from a combination of public sector regulations

and the commercial imperatives of the private sector (Kaplinsky & Morris, 2001). In

markets of developing countries, official regulations are either weak or poorly

implemented. Local traders often located closer to the consumers, therefore, are in a

109

position to provide their own interpretation of the rules, which give them a commercial

advantage. Their demands can, therefore, influence the practices adopted by chain

members upstream by offering lower prices which relate to the quality and quantity of

product they are able to buy from producers and sell to consumers (Kula et al., 2006;

Purcell et al., 2008).

The primary driver of internal value chain governance is provided by non-market

mechanisms which co-ordinate the flow of finance along the chain. In the absence of

formal contracts, safeguards are set by participants through holding their commercial

contacts as “economic hostages” as they adjust transaction costs to their advantage

(Gereffi et al., 2001, Altenburg, 2006).

Price offered and paid for product is an effective means of communicating the economic

principles involved in any marketing chain (Williamson, 1991). These are a reflection of

the flow of information between participants along the chain (Purcell et al., 2008). In the

absence of clear public information, the lead private sector processors often behave

opportunistically by distorting the market by manipulating pricing for their own benefit

(Boehlje, 1999; Boehlje & Schiek, 1998).

Product exchange takes place only if an arbitrage opportunity exists whereby profit is

obtained by moving produce to communities with higher demand and willing to pay

higher prices (Gunderson et al., 2009). While the product exchanges hands, its ownership,

price, and the level of risk borne by each handler also changes. Income and its distribution

are gauged by mapping financial transactions along the chain (Kaplinsky & Morris, 2001;

Schaffner et al., 2003).

110

Milk as a product, its attributes and handling

Milk is regarded as being nature's most complete food (Mahony, 1998). The type of

animal (breed and species) and its diet can lead to differences in the taste and fat content

of milk. The average percentage composition of cow and buffalo milk provided in Table

15 demonstrates the higher fat content of buffalo milk:

Table 15: Cow and buffalo milk composition

Species Water Fat Protein Lactose

Cow 87.2 3.7 3.5 4.9

Buffalo 82.8 7.4 3.6 5.5

Data Source: FAO (Fellows & Hampton, 1992)

The price and quality of milk are usually dependent upon three factors namely milk-fat,

protein content and microbial quality. Milk is a perishable commodity and spoils very

quickly unless a temperature is maintained that slows microbial growth. Dilution of milk

with water or ice will reduce the quality by diluting the key measures of fat and protein

and increase the risk of microbial contamination (Harding, 1995).

This research was carried out in two stages during September 2011. In the first stage, a

rapid appraisal approach was used to identify the structures of various milk supply chains

(Collins & Dunne, 2007). In the second stage, based on the initial data gathered, a more

detailed evaluation was carried out of one particular chain by carrying out further

observations, cross-checking initial data, interviewing more chain participants and

walking the chain from the farmer to the final consumption point. This chapter outlines

the results from the second stage.

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As outlined in chapter 5, in the 1st phase, face-to-face interviews were conducted to

develop a broad understanding of informal milk chains and markets, using a purposive

sampling method (Patton, 2002; Robson, 2002) to ensure the sample adequately

represented the particular focus of the study.

The four questionnaires designed for the first phase (attached as Appendix E) were used

one for each of the four groups: namely seven producers; three small, one medium and

one large dhodhi middleman, one retailer who refused to cooperate. The data from

consumers is based on the larger first phase study. The questionnaires still combined

fixed-choice and open-ended questions and collected both quantitative and qualitative

data.

Quantitative data collected included physical aspects such as milk volumes produced and

traded along with associated technical aspects of production and handling practices such

as transport, storage, cooling and processing. The addition of ice was a sensitive topic and

was explored by showing an understanding of the need to do so in hot summers. The

linked financial or economic costs and margins were investigated for the various physical

functions performed by the chain participants.

A number of factors influence governance mechanisms and the formulation of unwritten

rules operating along the chains. These include the backgrounds of buyers and sellers,

quality assessment, contractual arrangements, levels of satisfaction with business

agreements and the extent of borrowing and lending between participants. Some crucial

elements relating to volume measurements upon which purchases and sales were based,

and fat standardisation practices were not part of the structured questionnaires and came

to the fore through informal discussions that flowed from semi-structured questions.

Similarly, the price information and setting mechanisms were identified by enquiring

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about the basis of price fixation, seasonal price changes and sources of price information.

The consumers’ preferred attributes for fresh milk were also ascertained.

Interviews with each respondent, took between fifteen minutes to an hour depending on

the respondent’s place in the chain. The difference in time taken depended on the level of

complexity and number of questions asked: for example, the questionnaire for the

consumer was brief compared to those used for farmers, middlemen and retailers in the

chain. All questionnaires included an explanation of the purpose of the research to all

respondents.

Of the many chain models initially identified in chapter 4, one specific traditional rural-

urban milk value chain was selected for further research. A case study approach by Yin

(2009) was used in this empirical inquiry to investigate and understand this real life case

in its local context. This chain was selected for its larger number of intermediaries and

larger milk collection volumes compared to other informal channels and the detail on

transaction mechanisms such as the statement of volume measures and milk quality

assessments.

The study commenced at the chain’s origin in rural Okara and followed the chain to the

point of final consumption at a market in metropolitan Lahore city. In doing so, additional

participants were interviewed and observations made to further understand and validate

earlier study findings. A snowball sampling method was used to identify the chain

contributors based on the information provided by participants from other parts of the

chain (Patton, 2002; Robson, 2002). Thus, producers identified their small buyers or

dhodhis, which led to the identification of medium and large buyers, and then the milk

retailers. The information from each step of the chain was pieced together; for example,

the small collector dhodhi provided details of product exchange with medium dhodhis

and this was corroborated with comparable information obtained from the medium sized

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dhodhi. Very often further information became known with this second interview, which

lead to a more accurate reflection of the nature of transactions occurring along the chain.

The retailer at the end of this chain refused to be interviewed and so details of his

transactions are based on prices and units displayed at his shop and information provided

by his major supplier.

Results:

This section describes the case study from the second stage of field research using the

diagnostic framework introduced earlier in the introduction based on the definition of

value chains.

Among the various chains model identified in Chapter 5 (Figure 16 f and h), the Okara-

Lahore rural-urban informal fresh, unpackaged milk chain illustrated in Figure 17

supplies fresh milk to consumers in Lahore city. The chain had five tiers from farm to

final consumer. Figure 17 provides an estimate of the number of farmers, small medium

and large dhodhis18, retailers and consumers contributing to the chain. These estimates19

are derived from the chain’s milk collection averages.

18 Milk collectors and distributors 19 Producer household estimates as large dhodhi collects milk 6700L÷8medium dhodhis=836.5 → 836.5 ÷ 11small dhodhis=76 → 76

÷ 10Ps =7.6 therefore 6700L ÷ 7.6 6LperP = 882 Ps approx.

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Figure 17: Pyramid of the relationships between participants in the irrigated Okara-Lahore fresh

unpackaged milk value chain

The estimate of the number of consumers20 is based on a household income economic

survey (HIES) 2011 in which the per capita milk consumption in the urban centres of

Pakistan was requested. The milk chain created more than a hundred employment

opportunities from farm to final consumer. The results focus on one participant at each

step of the chain.

Technical subsystem and contributors to the value chain

This section introduces specific participants, their functions, geographical location as well

as providing a time course for movement of product down the chain to the consumer

20 Consumer household estimates are based on 2010-11 Household Income Economic Survey (HIES) average per capita fresh milk consumption and average household size → 6.76L per month÷30day = 0.225Lper day× 6.38 member per household=1.4L → 6700 ÷

1.4 = 4785 households approx.

882 Farmer Producers

8 Medium Dhodhis

88 Small Dhodhis

16 Retail shops

4785 Consumer Households

1Large Dhodhi

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(Figure 17 and Table 16). The table also highlights the technology and infrastructure,

transport, storage, cooling and processing facilities along the informal rural-urban chain.

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Table 16: Functions of participants, geographical location, time input and technology used to handle milk along the chain

Actors Producer Small

Dhodhi

Medium

Dhodhi

Large Dhodhi Milk retail shop

Exchange Function

Production Buying and selling Exchange facilitation on

commission basis

Buying and selling Sale to final consumers

Geographical location Rural i.e. a village in

Okara

Rural i.e. local villages in

Okara

Rural i.e. a central collection

points between few villages

Linking between rural

and urban markets

Urban i.e. metropolitan

city

Time along the chain 5 hours for milking

and animal husbandry

practices

4 hours from 6:00 to

10:00am

3 hours from 10:00 am to

1:00pm

18 hours from 5:00am

to 11:00pm

17 hours from 6:00am to

10:00pm

Technology and

Infrastructure

Hand milked Steel pots Open top steel tank available

but not used

Plastic containers

Freezers and milk sold in

polythene bags

Transport

Nil Motorcycle

(35 km)

Nil Truck (350 km) Nil

Storage and

Cooling

Nil Nil Nil Ice (7.3 milk: 1 ice)

added during

transportation

Refrigerators and ice also

added

Processing Nil for commercial

purpose

Nil Nil Nil Yogurt


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As outlined in Table 16 the milk was collected and transported with minimal use of

refrigeration technology. The functions performed by each level of participants are now

described in more detail from the perspective of those interviewed.

The Producer was located in a village in rural Okara. He owned five acres (2ha) of land

and five dairy animals of which one cow and one buffalo were lactating. The farmer was

milking twice a day by hand. He was selling almost 4.5 gadvi21 of his mixed cow and

buffalo milk to the small dhodhi, with the remainder used by his household. He was

selling morning milking only whereas the evening milking was kept for home usage.

Small Dhodhi collected a total of 49 litres22 of milk from ten farmers. The small dhodhi

only collected the morning milk. The milk was collected at each farmer’s doorstep and

delivered to a central collection point once every morning, a process that took four hours.

The Small Dhodhi used his motorcycle and steel pots to collect milk and travelled 35

kilometres daily. In addition, the small dhodhi delivered groceries or agricultural inputs

to farmer’s household as required.

Medium Dhodhi’s operation was located at a bus stand called an adda, which was

located at a midpoint between a few villages. His three-hour morning operation did not

require travel as 660 litres23 of milk was delivered to his centre by eleven small dhodhi

suppliers. A big open top steel tank was available but not used. Medium Dhodhi had a

hired hand, locally called Munshi, whose job was to check fat content of milk supplied

by each small dhodhi. The milk was then transferred directly from the small dhodhis’ pots

21 Gadvi is a local traditional unit of mass and/or volume that has evolved locally as milk used to cross rivers in Punjab in round steel

pots that could float and hence the term gadvi. 1 Gadvi = 900 to 1100 ml or grams and varies along the chain as it is not standardized.

Farmer’s total production per day was 4.5 gadvi that included both morning and evening. He was storing part of evening milking and mixed it with the morning milking next day to sell it.

22 41 gadvis that becomes 45 litres as small dhodhi’s 1 gadvi = 1.1 kg therefore 41 × 1.1 = 45 kg approx. Now with large dhodhi’s

standardisation formula and 6.5% fat in milk the milk volume further increases to 50 litres i.e. (456×6.5%fat) ÷ 6 = 49L 23 660 litres based on fat content premium / penalty for small dhodhi awarded by large dhodhi i.e.

Premium Paid = [(Milk in 𝑙𝑖𝑡𝑟𝑒 × %actual fat) ÷ 6%base target fat content] × Base Price per 𝑙𝑖𝑡𝑟𝑒

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to the Large Dhodhi buyer’s blue plastic container. The Large Dhodhi measured the milk

quantities for each small dhodhi, which were recorded by the Munshi in order to calculate

and deduct the commission owed by small dhodhis for their milk supplied.

Large Dhodhi was from a powerful Gujjar clan that dominates the Lahore milk market.

He was collecting 6,700 litres24 of milk from 8 medium dhodhis and supplying to 16

different retail shops in Lahore including his own shop. He made a 350 km return trip

between urban Lahore and rural Okara on a daily basis for milk collection and delivery.

This was an 18-hour operation seven days a week. This was a basic operation with blue

plastic containers holding 138 litres each used to transport milk. Ice was added to the milk

to assist in its preservation.

Milk Retailer was selling an estimated 465 gadvi25 of milk daily to urban consumers in

an impoverished area of Lahore city (the large dhodhi stated that he own this shop).

Retailer’s operation required two refrigerators to store milk overnight, the only use of

refrigeration in the chain. Ice was added to milk when electricity supply was disrupted,

which was a common occurrence. The only value adding activity undertaken by retailer

was making yoghurt from the milk supplied. Milk and yoghurt were both sold in

transparent polythene bags26.

The consumers at retail shops in Lahore milk market preferred fresh, unpackaged milk.

The main choice criterion was taste, which was defined by sweetness and thickness. That

is, the more cream found in the purchased product after boiling, the happier the consumer

was. This evaluation is based on interviews carried out in the scoping study where

24 6,700 litre that includes 5,970 litres of milk and 820 kg ice (7.3milk:1ice) 25 465 gadvis based on 900ml sold for each litre i.e. 418÷0.9=465 approx.

26 Using polythene bags is a common method of selling fresh milk and yoghurt at retail shops in Pakistan.

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consumers rated fat content followed by taste and aroma to be of high importance while

buying milk.

Governance in the value chain

Operators in the marketing chain conduct their business under the guise of strict unwritten

rules in the absence of formal written contracts and industry-wide product standards. The

two rules operating within the chain investigated are related to financing functions and

quality and quantity standards and are detailed in Table 17.

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Table 17: Governance along the milk value chain

Producer Small Dhodhi Medium Dhodhi Large Dhodhi Milk Retailer

Rule1: Financing

Function

Cash advance Advance taken from

small dhodhi for

milk

Advance extended to

Producer to secure

milk supply

Nil Nil Nil

Loans Nil Nil Interest-free loans

extended to small

dhodhis to secure milk

supply

Nil Nil

Credit Nil Nil Nil Gives milk on credit to

some retail shops

Nil

Rule 2:

Standards

Quantity units Ps’ 1 gadvi = small

dhodhi’s 1.1 kg

Gains 100 grammes

extra per gadvi of milk

Small Dhodhi’s milk fat

%age check only for

Large Dhodhi

Nil Assumed to sell lower

volumes for the price

paid (1gadvi =900ml)

Quality Nil Collects mixed cow

and buffalo milk

without any quality

check at the farm gate

Nil Pays a premium to small

dhodhis based on 6% fat

standard

Adds ice to milk (7.3

milk: 1ice)

Nil


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Rule 1): Financing functions: There was no formal written contract at any tier of the

chain. Upstream, at the rural end, the Medium Dhodhi extended a loan of 0.1 million Rs

on average to almost all small dhodhi suppliers and “took a cheque as a guarantee” for

the amount of the loan given.

The loan enabled small dhodhis to buy a motor cycle to collect milk and to provide a

monetary payment to their farmer suppliers who demanded a cash advance for the milk

sold. The Producer mentioned, “I take 2000 to 3000 [Rs] cash advance every two weeks”.

The cash advance was based on the milk volume sold to small dhodhi: that is the more

milk supplied, the higher the cash advance demanded by the farmer. Small Dhodhi said,

“A chung [farmer supplier] supplying 2 kg asks for 10,000 [Rs] cash advance”. The small

dhodhi was not, however, happy with this arrangement and said, “our money gets blocked

by the farmer, whereas we have to pay back all the loan to the dealer [medium dhodhi] if

we change buyer”.

Downstream, at the retail end, the large dhodhi was supplying milk to some of his

customers on credit.

Contrary to the practice of cash advance by farmers associated with the informal chain,

the formal processors buying milk from the same village did not offer any cash advance

to the farmers. The payment for the milk procured was also made every eighth day. The

money was paid for five days of milk supply only with three days of payment rotating.

Rule 2): Quantity and quality standards: Several factors impacted on milk quantity

and quality with those factors often interacting. The ways in which milk was measured

and preserved and the evaluation of quality was confusing and complex. Firstly, the

quantity and measurements are explored. Inconsistent units were prevalent all along the

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chain. The small dhodhis collected 1100 grammes27 per gadvi instead of the standard

1000 grammes of milk but paid the farmer for 1000grams. Thus the small dhodhis got an

incentive of 100g per litre of milk purchased. This was then sold as a litre at the Medium

Dhodhi’s central collection point (Table 17).

The most important commercial quality attribute in this chain was fat content in milk as

it was readily sought after by the urban consumer. Thus high fat buffalo milk was

important in that it could be diluted more prior to sale. The small dhodhis preferred

buffalo milk due to its higher fat content but was buying mixed cow and buffalo milk as

farmers owned both species. There was no formal quality check at the farm gate as milk

testing was not culturally acceptable to the farmers. The Small Dhodhi said, “I come at

the time of milking”, if there was some doubt about the farmer’s integrity in maintaining

the purity of milk.

The Large Dhodhi had placed a reward / penalty system in place to ensure delivery of

milk with a 6% minimum fat standard. The following formula was used as a tool to

encourage the supply of undiluted high-fat content buffalo milk.

Premium Paid = [(Milk in 𝑙𝑖𝑡𝑟𝑒 × %actual fat) ÷ 6%base target fat content]

× Base Price per 𝑙𝑖𝑡𝑟𝑒

The Small Dhodhi stated that this quality control occurred at the level of the Large

Dhodhi, with the Medium Dhodhi performing the fat content tests on behalf of the higher

volume collector large dhodhi. Fat content was recorded using the Gerber method with

the help of a manual centrifugal machine present at the central collection point.

The Large Dhodhi then diluted milk through the use of ice added at the rate of

approximately 1kg per 7.3litres of milk in a total volume of 40 litres, termed colloquially

27 The units varied at farm gate and central collection point. As Small Dhodhi was selling in litres the units at farm gate should be

referred to as millilitre but the Small Dhodhi mentioned that kilograms change to litres at the Medium Dhodhi’s central collection

point. To add to the complexity the Medium Dhodhi mentioned seers as a traditional local unit for milk collected by Small Dhodhi’s.

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as a maund. The ice was added directly to the milk to avoid spoilage on its way to the

Lahore market, which was a three to four-hour journey. Cooling the milk was important

in extremely hot weather with temperatures reaching over 40 degrees Celsius.

Thus after dilution with melted ice, each 40litre maund actually consisted of 46 gadvi of

milk. The milk was then on sold by the retail shop to the consumer in gadvi that contained

only 900ml. It meant a lower quantity given to the final consumers for the price paid. In

this case, as the shop in this study was owned by the large dhodhi, there was no quality

check at the point of sale. The Large Dhodhi, however, stated that some retail milk shops

in Lahore made khoya28 to check the quality of milk supplied by him, to ensure that

consumers were being supplied the high fat content milk they were paying for.

Price setting and information flows along the chain

Different mechanisms and processes were used to set the price along the chain. The

consensus among chain operators was that the larger multinational and national milk

companies established the farm gate price for milk at the district level that others simply

follow. The price is then used by all the rural local informal chains’ central collection

points such as that operated by medium dhodhi. The price was adjusted every few weeks

based on supply and demand, but the major change occurred with summer and winter

seasons. A difference of 2Rs/litre was noted between the price offered to farmers from

dhodhis in this chain and that offered by big processing companies, with the latter offering

a higher price and using accurate litre measuring cylinders when buying milk.

While the price of milk received by the producer was set by the small dhodhi, this

invariably was subject to negotiation, with producers often consulting with neighbouring

farmers on the prevailing price being offered by other dhodhis.

28 Milk thickened by heating in an open iron pan. The higher the milk solids the better is the quality.

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The small dhodhis were offered a fixed price by the Medium Dhodhi at the central

collection point as the Small Dhodhi interviewed said, “the rate [price] is given by our

dealers [Medium Dhodhi]”.

The Medium Dhodhi operated under a different business model, by charging a fixed

commission per litre of milk he handled. This commission was based on loans extended

to the small dhodhis, and therefore price change did not influence the profitability of their

business.

The urban retail price for fresh milk in the Lahore city market, paid by the final consumer,

was fixed by the city district government on an annual basis. At the time of this study, the

fresh, unpackaged milk price was set at Rs50/litre. The retailer at the end of this chain

was selling milk at 42Rs/gadvi.

Other specialised fresh retail milk shops were selling milk in litres, kilogrammes and

gadvi that is different units and at different prices that varied from the equivalent of 40 to

70 Rs. The ultra-heat treated (UHT) packaged milk processed by large companies was

being sold at around Rs85/litre.

Economic subsystem of the value chain

One way to examine any value chain is to evaluate the price margins achieved by each

participant. These margins for each participant are detailed in Table 18 and provide an

estimate of the capital invested by each participant. The estimation excludes owner-

operators’ opportunity cost of labour and provides a crude estimate of their financial

viability. The measuring units for milk sales also differ along the chain. The statistics

were obtained on the day(s) of the survey and are representative of transactions that

occurred during the end of the Monsoon season in September 2011.

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The analysis indicated that the milk producer was making losses from milk production

despite having the second highest capital investment in the chain. All other chain

participants recorded positive gross margins. The Small Dhodhi’s margin comprised of

the volume adjustments and milk standardisation formula that increased the volumes

collected in the absence of which he would have been making a loss of Rs 18 per day.

Similarly, the retailer’s margins would have curtailed to Rs 236 per day if not for selling

900 ml instead of one litre in the gadvi purchased by consumers. The Large Dhodhi

earned the highest gross margin due to economies of scale. He, however, was taking

substantial risks with the potential for spoilage of large milk volumes handled and

transported without proper cooling. Similarly, the Medium Dhodhi had the highest capital

invested and was taking a considerable financial risk by extending interest-free loans to

his small dhodhi suppliers without any formal contractual arrangements.

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Table 18: Physical and financial flows along the milk value chain

Producer Small dhodhi Medium dhodhi Large dhodhi Milk Retailer

Volumes sold per

day

4.5 gadvis

41 gadvis that becomes 45

litres as small dhodhi’s

1 gadvi = 1.1 kg therefore

41 × 1.1 = 45 kg approx.

Now with large dhodhi’s

standardisation formula and

6.5% fat in milk, the milk

volume further increases to 50

litres i.e. (456×6.5%fat) ÷ 6 =

49L

660 litres based on fat

content premium / penalty

for small dhodhi awarded

by large dhodhi

6,700 litre that includes 5,970

litres of milk and 820 kg ice

(7.3milk:1ice)

465 gadvis based on 900ml

sold for each litre i.e.

418÷0.9=465 approx.

Average price at

each step

30 Rs/gadvi 32 Rs/kg 35 Rs/litre 40 Rs/litre 42/gadvi

Estimated Revenue

/ day (P×Q)

135 Rs a

= 30×4.5

1,568 Rs

= 49×32

1,980Rs

= 3Rs margin or

commission / litre×660

268,000Rs

= 6,700×40

19,530Rs b

= 465×42

Average variable

cost per unit

39Rs a as

1price :1.3cost

26Rs 0.6Rs 33Rs/litre 37Rs/litre

Estimateda

Variable costs / day

175.5 Rs 1,330 based on

1,230Rs milk purchase

100Rs/day motor cycle fuel

400 Rs/day based on

8000Rs/month to record

keeper

2000Rs shop rent &

utility bills

2000Rs for

miscellaneous such as

entertainment of shop

guests

221,687 Rs/day based on

208,950 Rs for the milk

purchased

2,460 Rs for 820kg ice @

3Rs/kg

8,000Rs/day truck fuel

267 Rs based on

8,000Rs/month truck

driver’s salary

17,320 Rs/dayc based on

16,720 Rs milk purchased

167 per day shop rent

based on 5000Rs/month

200Rs based on

6000Rs/month gas and

electricity bills

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Producer Small dhodhi Medium dhodhi Large dhodhi Milk Retailer

2,010 Rs based on 270 to

400 Rs daily wage of 6

loaders

133 Rs based on

4000Rs/month shop

helper’s salary

100 Rs based on

3000Rs/month polythene

bags for selling milk

Gross margins per

participant

-40.5 Rs/day 238 Rs/day 1,580Rs/day 46,313Rs/day 2,243 Rs/day

Capital Investment 2.56 million Rs

(0.31 million for

livestock and

2.25 million for

land)

0.1 million Rs

(50,000 Rs for motor cycle

and pots. 50,000Rs approx.

advances to farmer producers)

3.5 million Rs as loans to

small dhodhis

Truck worth 1.4 million Rs

and 1 million Rs as milk on

credit to some retail

customers

50,000 Rs as refrigerator(s)

for milk storage

Note: 1USD = 85.47 PKR or Rs, Official exchange rate from State Bank of Pakistan http://www.sbp.org.pk/ecodata/HER-USDollar.xls

1USD = 86.99 PKR or Rs, Unofficial exchange rate from OANDA http://www.oanda.com/currency/historical-rates/ a. Producer’s cost price estimates based on author’s detailed farm economic analysis as part of PhD research (Chapter 3, Table 6). Assuming that the producer studied, produces

less than 2,300litres per year. The revenue and cost of milk used by the household has been excluded

b. Retailer sells yogurt 55Rs/kg, which is ignored in the calculation above to simplify the results

c. The cost estimates for the retailer are not actual and are best estimates based on the larger study of other chain models

http://www.sbp.org.pk/ecodata/HER-USDollar.xls

http://www.oanda.com/currency/historical-rates/

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Discussion and conclusion:

The research provides an insight into the operations of a rural-urban informal fresh,

unpackaged milk value chain in Pakistan, which has not been described previously. The

chain is pro-poor because it creates a number of employment opportunities while using

minimal technology to collect, transport and sell fresh, unpackaged milk at a low price,

amid low gross margins. It offers financing, loans and credits where needed. Given that

it offers a number of benefits in addition to selling milk, it would appear to be a part of

the social fabric of local communities.

The chain has its own governance mechanisms in the absence of formal contracts at any

tier. The arrangements for financing retains cohesion in the chain but some contributors

are entrapped by the need for loans to remain a viable member of the whole operation.

The analysis conducted here shows clearly that the producers and small dhodhi vendors

are significantly disadvantaged by the arrangements.

Despite making a loss from every litre sold to the chain, the producer preferred to sell his

milk through the informal milk chain because of the additional benefits on offer by doing

so. These included obtaining an advance for milk supplied, maintaining a regular cash

flow and having access to other services such as agricultural inputs not provided by large

companies. This is inspite of the higher price offered by the formal sector. The producer

described in this case study is representative of the typical smallholder Pakistani farmer

because 65% of them have less than 5 acres (2 ha) of land and 91% have less than 10

animals based on the Agricultural Census (2010). The Small Dhodhi obtains interest-free

loans to operate and earn a livelihood while the Medium Dhodhi generates viable returns

on his capital. The Small Dhodhis, however, is in part trapped, by both the producers to

whom he extends cash advances, and the Medium Dhodhis from whom he borrows the

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money. The term “economic hostages” best describes the position of the small dhodhis

(Williamson, 1991). It is assumed the Large Dhodhi is locked in with his customers too,

as he supplies milk on credit at the retail end.

Activity along the chain distorts the units of measurement of milk volume and decreases

milk quality as there is no enforcement of any regulatory standards. However, the ensuing

lower prices help the chain gain a competitive advantage despite the lower quality of the

product.

These distortions are important elements for the sustainability of this chain; however,

both the producer and endpoint consumer are the losers. Both, however, seem to live with

these market distortions: the consumer is happy as he purchases milk with fat content

possibly higher than or equal to the 3.5% found in packaged milk, while he has little

understanding of the importance of the protein content of the product for human nutrition.

The average Pakistani consumer household spends eleven percent of their budget on milk

and milk products (Government of Pakistan, 2013a) and nutritional qualities of the

product should be given higher importance in community education programs. However,

there is a good commercial reason not to pursue this as consumer resentment would build

if it became common knowledge that inadequate protein was being provided in the final

product. On the other hand, income from dairy produce is minor in the family budget

relative to income from crops. Therefore, the producer simply accepts a price for a

commodity that varies in quantity according to the volume consumed by the extended

family.

In the bigger picture, the price setting mechanism by the city government in the urban

centres requires further review as there is a trade-off between price and quantity / quality.

Similarly, farm gate price setting and possible collusion by the large processors having

monopsony powers to set these prices (Rogers & Sexton, 1994) also requires further

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investigation. There is a need to explore linkages between the formal and informal sector

to understand how the earlier affects, the later and vice versa.

Despite the producer losing money and small dhodhi making a marginal profit, the

question that must be asked is why these personnel participate in the chain. The provision

of cash advances and loans provides the answer in part, but it would seem more direct

access to the endpoint vendor would be advantageous to all three of them. Could this be

achieved through the development of co-operative producer groups organising their own

milk transport modes?

The chain operates in an industry environment, which is complex and competitive. There

are a large number of small producers and final consumers catered for by a large number

of dhodhis and retailers. More rural-urban chain models will have to be studied before

making concrete recommendations on improving the livelihoods of those associated with

the Pakistani dairy industry.

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Chapter 7. Informal milk value chains from the urban

consumer’s perspective: a developing country scenario

This chapter identifies the product characteristics the Pakistani consumer values when

buying milk, their buying behaviour, their demographics, and any unmet needs of the

urban consumer.

Methods

The study of informal milk value chains originated from the irrigated Okara and arid

Bhakkar districts of Punjab in Pakistan (Figure 18 a & b). The choice of the districts

studied was based on the farm economic analysis of a two-year longitudinal survey data.

The data was collected as part of an Australian Centre for International Agricultural

Research (ACIAR) funded project entitled “Improving dairy production in Pakistan

through improved extension services” (Wynn, Unpublished). For the first phase of this

research, a scoping questionnaire was developed, and face-to-face interviews were carried

out in September 2011 with eleven randomly selected consumers buying fresh,

unpackaged milk at retail milk shops.

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Figure 18a. Maps of Pakistan and Punjab; b. Map of Punjab showing rural arid Bhakkar and rural irrigated Pakpattan, Kasur and Okara districts supplying milk

to metropolitan urban Lahore city


133

The scoping study informed the second and final phase of data collection. Of the arid and

irrigated regions, the latter was focused based on preliminarily scoping study, which

indicated that rural-urban informal fresh milk chains in the irrigated region carry larger

milk volumes and maintain complex structures with many tiers. These chains also cater

to a large number of consumers as they supply milk to large and densely population cities

such as Lahore. The milk chains in the arid region had less tiers and were carrying smaller

volumes to smaller cities situated in that region.

Four specific rural-urban fresh, unpackaged milk value chains were identified in the

second phase with the support of ACIAR project colleagues to guide the purposive

sampling of informal chains. The selection criterion was chains carrying larger volumes

and each having a different point of origin or district. One chain each, originating from

rural Kasur, Okara and two from Pakpattan district of irrigated Punjab (Figure 18b and

Table 19) and supplying milk to its provincial capital city of Lahore were selected. The

large milk collector of one of the two chains from Pakpattan, however, refused to

cooperate later, and the chain, therefore, had to be dropped.

The final study was conducted in June and July 2012, which represents the peak milk

demand and decreased supply period during Pakistan’s hot summer. Using a case study

approach (Yin, 2009), the physical flows of milk from initial production to final point of

sale was followed for the three milk chains. Face-to-face interviews were carried with 35

fresh, unpackaged milk consumers buying milk from seven different specialised retail

milk shops in different areas of Lahore city (Table 19).

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Table 19: Purposive sample of 35 consumers from 7 retail milk shops at the end of three rural-urban

milk value chains.

Milk Value

Chains

Chain origin

Value chain 1:

Kasur-Lahore chain

Kasur is 85km south-east of

Lahore

Value chain 2:

Okara-Lahore chain

Okara is 135km

south-east of Lahore

Value chain 3:

Pakpattan-Lahore

chain

Pakpattan is 190km

south-east of Lahore

Retail shops for

each chain

Kasur-

Lahore

Retailer1

Kasur-

Lahore

Retailer2

Kasur-

Lahore

Retailer3

Okara-

Lahore

Retailer1

Okara-

Lahore

Retailer2

Pakpattan-

Lahore

Retailer1

Pakpattan-

Lahore

Retailer2

Number of

consumers

interviewed at

each shop

4 5 5 6 5 5 5

Shop’s socio-

economic

locality

C D C C C B C

Source: Author’s field research

Note: The socio-economic categorization is based on author’s interpretation and is based on the local

knowledge of city areas, where

Category: A is very well

off or rich

B is well to do

C is mediocre

D is

marginalised

poor

E is extremely

poor

Interviews with consumers were only conducted at the shops that were cooperative and

amenable for the interviews to be conducted. At the end of each chain of the Kasur-

Lahore, Okara Lahore and Pakpattan Lahore chains; 14, 11 and 10 milk consumers were

interviewed respectively (Table 19). A purposive sampling technique was used to study

the final consumers which supported the logical representation of consumers at the

concluding end of the chains (Patton, 2002; Robson, 2002).

The questionnaire (attached as Appendix J) consisted of both structured and semi-

structured questions with both Likert and rank-order scales used to clarify the motive of

respondents. The questionnaire evolved during interviews, as the sequence of questions

and the way they were asked had to be modified to attain clear responses. At the beginning

of the interview, the purpose of the study was explained to the consumers. The interview

was carried out in the local language. They were interviewed during the evening, which

represents the peak daily sale time. Each interview was designed to last for ten to fifteen

135

minutes. A voice recorder was used, and pictures were taken with the consent of the

consumer and retailer. The sample size is smaller than anticipated due to a number of

other urban milk retail shops identified from the three chains, being unwilling to

participate in the research, and those that did participate were not agreeable to a large

number of consumers being interviewed.

Quantitative data was collected on demographics while both quantitative and qualitative

data was gathered for consumer preferences and buying behaviour, attributes valued in

milk, and unmet needs.

Demographic data included age, gender, education, household size, residential address

and monthly income. The income brackets were based on the five income quintiles in

“household income economic survey (HIES)” of the Pakistan Bureau of Statistics

(Government of Pakistan, 2011). Wismer (2009) links demand for products to

demographics, incomes and awareness of consumers. The groups of individuals with

similar values and demographics represents consumer segments with similar expectations

of quality. The market aspects such as the number of people, where and how they live as

households, their age, education and incomes along with general availability and variety

of foods available, all have an effect on how food is marketed and consumed (Kohls &

Uhl 2002; Schaffner et al., 2003). Responsive firms tailor their chains to the nature of

product market and supply according to consumer demand or segments (Lee, 2004) that

enables them to develop services tailored to the needs of customers (Anderson et al.,

2007).

Consumer preference for buffalo or cow milk and preferred source and form of purchase

was explored. Otte et al. (2012) suggested that consumers in developing countries have

traditional preferences for fresh produce, sourced from markets that do not conform to

the idea of sophisticated and technologically up to date supply chains.

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Buying behaviour was ascertained by asking the time, quantity and unit of milk purchased

and changes in consumption pattern along summer and winter seasons. This was to

understand the final market; that drives the product standard and quality specifications

(Kula et al., 2006).

What the urban consumers value in milk was studied by asking the consumers to rank

five attributes of milk, as well as being asked to explain milk quality in their own words.

According to Fearne (2009a), for a chain to have a comparative advantage it is important

that in its activities, the consumer comes first as the final consumer ultimately determines

where the value lies in the product. In fresh produce chains, the sources and drivers of

value may include freshness, overall sensory experience, food-safety and nutrition. Each

of them plays an important role in a consumer’s food purchase decision. When these

attributes are loosely bundled together as ‘quality’, it is the interaction between price and

quality that can be evaluated as what buyers regard as ‘value for money’. A chain is

challenged to understand and deliver this value profitably while meeting the needs of

consumers (Collins, 2006, 2009).

Product quality was explored using a framework given by Ophuis et al. (1995). This work

defined the quality concept from a consumer perspective, with a particular reference to

foods by using cues and attributes (Table 20) although only a few local market relevant

cues and attributes were chosen. Quality cues are determined by the use of senses, prior

to consumption, and are observable product characteristics that can be intrinsic or

extrinsic. Quality attributes are abstract, post product consumption aspects, and are based

on experience or perceived benefits. These quality dimensions are woven together to

understand what consumers perceive as quality.

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Table 20: Quality cues and quality attributes for foods (Oude Ophuis & Van Trijp, 1995)

Intrinsic quality cues

appearance

colour

shape

size

structure

Extrinsic quality cues

price

brand name

country of origin

store

nutritional information

production information

Experience quality attributes

taste

freshness

convenience

Credence quality attributes

healthfulness

naturalness

animal friendliness

environmental friendliness

wholesomeness

exclusiveness

way of production

Source: Ophuis et al. (1995)

Unmet consumer needs were explored by asking whether consumers were satisfied with

the quality and final comments were garnered to allow consumers to suggest

improvements in the existing milk markets. Baker et al. (2009) suggested the

characterization of satisfaction or dissatisfaction of the consumers demanding products

delivered by the chain, allows for identification of entry points for improvement.

Results

The first scoping phase of research (Chapter 5) helped establish the general consumer

preference of high fat content and sweet taste while buying fresh milk. The results

described here are from the third and final phase and focus on demographics of consumers

interviewed at the specialised retail milk shops. It will then examine their preferences and

buying behaviour, what they value while buying milk and unmet needs if any.

138

Demographics

There was considerable variation between the consumers interviewed in relation to their

age, the size of their households, education and household incomes (Table 21). Fifty-one

percent of the consumer households interviewed were in the middle-income quintile

range with 12% in the lowest and 37% in the highest national income quintiles. High-

income households were also residing in marginalised residential areas. Consumers from

A and B category residential areas were buying milk from shops in C and D category

residential areas (Table 21). These consumers claimed that shops, which had established

a brand name in well off category A localities, were selling the same quality at a higher

price. A proportion (14%) of the consumers were buying from shops that were on their

way home from work. Apart from one woman, all consumers interviewed were men.

Table 21: Demographics of consumers (n=35)

Average Minimum Maximum

Age (years) 38 16 61

Household size 6 1 12

Education (years of formal education attained) 10 0 21

Percentage

Gender

Male 97%

Female 3%

Consumers categorised by residential address

Category E: extremely poor 0%

Category D: marginalised poor 14%

Category C : mediocre 49%

Category B: well to do 34%

Category A: very well off or rich 3%

Monthly household incomes

up to 11,500 Rs (up to 122USD) 12%

11,501-15,500Rs (122-164USD) 6%

15,501-20,000Rs (164-212USD) 24%

20,001-35,000Rs (212-372USD) 21%

Above 35,000Rs (Above 360USD) 37%

Notes: 1USD = 94.2 PKR or Rs, Official exchange rate from State Bank of Pakistan as an average of June

and July 2012 (State Bank of Pakistan, 2013)

-Monthly household income brackets based on Household Income Economic Survey (Government of

Pakistan, 2011)

-Consumer’s residential address categories are author’s own interpretation based on the local knowledge of

city areas

139

The consumers buying milk from shop in low-income localities (Table 21) were price

conscious. A consumer (Kasur-Lahore Retailer2-Consumer4), who worked as a daily

wage labourer said: “I work as a labourer and carry bricks and get 2 Rs [Rupees] per trip

[from the ground floor to multi-storey roof top]. It is really hard to make money but when

it comes to spending it just vanishes29”, which illustrates low purchasing power amidst a

high inflation environment. Another consumer (Okara-Lahore Retailer1-Consumer4)

said, “Price matters for good quality but hard...for poor consumers to buy expensive milk,

especially for salaried class”, pointing to the underlying issue of consumers not being able

to pay a higher price.

Consumers buying milk at retail shops selling at a higher price in upper middle-class

localities were relatively less price sensitive as a consumer (Pakpattan-Lahore Retailer2-

Consumer2) said, “Price of milk is ok as there is generally very high inflation”, suggesting

the price being charged is justified.

Consumer preference and buying behaviour

The average milk consumption per household per day was 3.1 litres, which equates to an

average of 0.52 litres30 per person per day. The minimum purchase per household was

0.35 litres, and the maximum was 6.5 litres per day (Figure 19). The milk was generally

purchased twice a day, once in the morning and once in the evening. It was observed that

the main income earners or occasionally the younger male members of the family were

buying milk.

29 Referring to high inflation and very low purchasing power of Rupee 30 Litre as a unit does not represent the units at the seven retails shops, which were all using different units. It has been used here only for the sake of consistency while explaining the average consumption in this section.

140

All of the consumers interviewed scored fresh milk as their most preferred source,

followed by packaged milk and then powdered milk (Table 22). Packaged milk was only

bought if fresh milk was not available and to make tea. Some consumers were using

packaged and powdered milk at their work places to make tea. The preferred source of

milk was the retail shops at the end of the rural-urban milk value chains followed by home

delivery. Some retail milk shops were delivering milk to the consumer’s doorstep for no

additional charge.

Figure 19: Distribution of total daily milk purchased by consumer households standardised to litres

at each of the seven shops (different units used by the seven retailer milk shops are explained further

in Table 24).

Table 22: Consumer’s priority ranking on scale of 1 (highest importance) to 3 (lowest importance)

for the preferred form and source of milk purchase (n=35)

Form of milk Ranking

Fresh loose milk 1.0

Packaged milk 2.2

Powdered milk 2.8

Source of milk

This specialised retail milk shop 1.1

Home delivery by milk man 2.4

Packaged milk from grocery shop 2.5

141

In conversation with the consumers, it became evident that the general consumer

perception was that the packaged milk was more adulterated than the fresh, unpackaged

milk. A consumer said, “…cooking oil, washing powder and urea being mixed in the milk

that is sold [by suppliers selling to formal processors]”. The general sense was that fresh

milk is relatively better than the packaged milk.

Sixty-six percent of consumers preferred buffalo milk because of its high fat content

(Figure 20a). Eighty-six percent claimed to be able to differentiate the two forms of milk

(Figure 20b). The main attributes explained by customers that allowed them to compare

the two forms of milk were that buffalo milk is thicker and is white when compared to

cow milk, which is yellowish and its aroma was suggested to be not very pleasant. Based

on open-ended questions, most consumers indicated that they were buying buffalo milk.

Only a small number of the consumers were aware that the milk being sold in the market

was mixed.

The retail shops were selling milk in three different units and at different prices that

included litres, kilogrammes and gadvi. Each consumer had a slightly different

understanding of these units. A kilogramme (kg) was rightly understood to be 1,000

grammes, although there was confusion on the use of litre and gadvi. For milk, 1 litre

equals 1.033kg, whereas the gadvi is a local traditional unit of measure for which the

standard weight is not clearly defined. The understanding of consumers varied for these

two units. A consumer (Kasur-Lahore Retailer3-Consumer2) said, “Litre is 900grams and

gadvi is 1.25 kg or 1250grams”. Another consumer (OK Retailer2-Consumer5) said,

“Gadvi is same as kg and only 50 grammes more”. Another consumer said, “Litre and

gadvi are the same. This shop is selling milk in litres which are same as kg [whereas the

shop was selling in kg]”. The consumers were equally divided (Figure 20c) between the

142

three measures while 12% admitted to being unaware of the difference between the three

units.

When questioned on the change in milk consumption patterns between the summer and

winter season, 37% of consumers indicated that their household consumption decreases

in winter.

Figure 20: Percentage of consumer’s (n=35) a) preferred fresh milk source, b) claim to be able to

differentiate buffalo and cow milk, and c) understanding of units of milk purchased.

66%

26%

9%

Prefer-Buffalo milk No preference Prefer-Cow milk

a) 86%

9%6%

Yes No Somewhat

b)

38%

26%

24%

12%

kg litre gadvi Not Sure

c)

143

Consumer Value

Consumer value was explored with consumers quantifying and describing what they

valued most in milk while buying it. The consumers ranged from those who were unable

to explain what they valued when buying milk to those who were clear in what they

wanted in their milk. The summation of consumer remarks in Table 23 made evident that

consumers gave the highest value to fat, followed by sweet taste and then good aroma in

fresh, unpackaged milk.

Table 23: Aggregate of the priority ranking on a scale of 1 (highest in importance) to 5 (lowest in

importance) for consumer’s experience quality attributes, intrinsic quality cues and credence quality

attributes. Extrinsic quality cues while buying fresh, unpackaged milk, ranked on a scale of 1

(highest) to 3 (lowest) for consumers (n=35).

Attributes & cues Score

Experience quality attributes

Thickness (higher fat content) 1.6

Taste (sweetness) 2.4

Aroma 2.8

Intrinsic quality cues Visual appearance (colour) 3.7

Credence quality attributes Safety and health benefits 3.8

Extrinsic quality cues

Trust and loyalty with seller 1.5

Convenience of buying 2.1

Price 2.2

Sixty-eight percent of the consumers (Figure 21) had higher fat content as their top

priority while only 9% consumers ranked safety and health as their first priority while

buying milk.

144

Figure 21: Milk attributes preferred by the consumers (n=35)

Comments from a few consumers further described what is valued most in milk among

consumers. A consumer (Kasur-Lahore Retailer1-Consumer4) at one retail shop said,

“There should be cream on top of milk, no matter how many times it is boiled”. The only

woman (Kasur-Lahore Retailer1-Consumer2) interviewed said, “This milk has a nice

aroma, and I get lots of cream after boiling from which I make butter. Smell and taste

both are very nice. The colour of the milk is good as well. I like the tea of this milk.”

Another consumer (Pakpattan-Lahore RetailerI-Consumer4) said, “Milk should have

(butter) fat, taste and good aroma and (it should be) white in colour”. These statements

and the aggregated results (Table 23) show that fat is important to the consumer with little

consideration for health and safety.

The most important criterion for buying milk from these respective retail milk shops was

trust and loyalty with the seller, followed by the convenience of buying (Table 23).

Quality was even more important than price for the consumer while making a buying

decision. One consumer (Kasur-Lahore Retailer3-Consumer2) commented, “Price does

not matter as it is hard to find pure milk even if the desired price is paid”. The time period

Safety and

health

benefits

9%

Visual

appearance

(colour)

3%

Taste

(sweetness)

17%

Smell

3%

Thickness

(higher fat

content)

68%

145

that the consumers had been buying from each of their respective milk shops ranged from

3 days to 30 years (Figure 22). Most of the consumers had been buying for a long time

from the same milk retail shops. The duration was linked to trust with retailers in terms

of milk quality.

Figure 22: Distribution of years for milk purchased by consumer households from specialised milk

retail shops (n=35)

Unmet needs

The level of satisfaction among the consumers was explored by asking if they were

getting the desired attributes of milk in terms of quality for the price paid. The responses

revealed a general dissatisfaction from consumers, which meant they often compromised

on the quality of milk they purchased to meet the price they could afford. A consumer

(Okara-Lahore Retailer1-Consumer3) answered, “[This fresh unpackaged] milk is ok for

the price paid, although I am not satisfied”. Another consumer (Pakpattan-Lahore

Retailer2-Consumer5) responded, “Milk is diluted, and we do not really have many

options” to buy beter quality milk elsewhere. Another consumer (Pakpattan-Lahore

146

Retailer1-Consumer5) replied, “Yes it [milk] is satisfactory, and we just have to get along

[with whatever we get]”. These responses show consumers awareness of the price and

quality trade-off and acceptance of the fact that it is not possible to find the desired quality

of fresh milk. The degree of dissatisfaction varied between consumers and shops. The

consumers sought better quality pure milk but knew that the milk they were getting is

diluted. A consumer (Kasur-Lahore Retailer2-Consumer2) said, “The milk should be

purer. Their [retailers’] milk's quality went down a few months ago…” Another consumer

(Okara-Lahore Retailer1-Consumer2) said, “Sometimes the quality is not good, and we

come and complain...” indicating that the quality varies on a regular basis.

Discussion and Conclusion

At all the seven retail shops for the three rural-urban milk value chains studied,

consumers, regardless of their income and education demographics, valued higher fat

content buffalo milk with health and safety their least concern (Table 21 and Table 22).

Consumers buying cheaper milk from low socio-economic localities or in the low-income

bracket were relatively more price conscious based on the quotes provided by these

consumers while describing demographics. Despite a high inflation, lower incomes and

poverty, consumers were lesser concerned about prices when buying fresh milk, and more

importance was given to quality associated with the trust upon milk retailers, which

reflects the general scarcity of high-quality milk.

The consumers had their set preference for specialised retail outlets of fresh, unpackaged

milk purchased, which is linked to trust. This retail outlet preference is possibly due to

the common practice of dilution in milk that is sold fresh. Most fresh, unpackaged milk

consumers expressed doubts and were not sure what they were buying in terms of quality,

147

but still preferred it as opposed to packaged milk based on the perception that large

contractors supplying to large processing companies, add adulterants harmful to health

and are able to deceive the laboratory testing.

In the larger study, it was derived from conversations with the large milk collector

suppliers and retailers of these milk value chains that the retail shops in Lahore milk

market sell the mixed cow and buffalo milk. Consumers in this study, however, mainly

perceived they were buying fresh, unpackaged buffalo milk. The fresh, unpackaged milk

suppliers claimed that the fresh, unpackaged milk had a fat content of 4 to 5%, which is

the prevailing unwritten standard in the Lahore market. This fat percentage was believed

to be higher than Ultra Heat Treated (UHT) packaged milk sold by the formal sector,

which is understood to be 3.5% fat, although this is not labelled on the packaging. The

packaged milk was being sold at double the price of fresh milk, which makes fresh milk

better value for the money spent by the consumer resulting in its higher demand.

Table 24 illustrates a clear picture of price, units, quantity and linked quality aspects. The

retail price of fresh milk during the research period was 57 Rs per litre, which is fixed

annually by the city government with no regard for milk production seasonality and the

cost of bringing the product to the market. The packaged UHT milk was being sold from

80 to 100 Rs per standard litre, depending on the brand. The effective price per standard

litre has been worked out for the seven retails shops. The big variation in prices and the

use of illicit unit conversions was possibly used deliberately to gain undue advantage and

to get around the price set by the city government. Consumers’ ignorance of appropriate

units of purchase and the right weight for each unit, made this clandestine manipulation

possible.

148

Table 24: Price, unit, quantity (authors’ field research) and quality (Aslam, 2015) for each shop of the seven retail milk shops at the end of the three rural-urban milk

value chains.

Milk Value Chains Value chain 1:

rural Kasur- urban Lahore chain

Value chain 2:

rural Okara-urban Lahore

chain

Value chain 3:

rural Pakpattan - urban Lahore

chain

Formal

Processors

Nestlé, Engro

& Haleeb

Retail shops for each chain Kasur-Lahore

Retailer1

Kasur-Lahore

Retailer2

Kasur-Lahore

Retailer3

Okara-Lahore

Retailer1

Okara-Lahore

Retailer2

Pakpattan-

Lahore

Retailer1

Pakpattan-

Lahore

Retailer2

NA

Price per sold unit31 50Rs/litre 52Rs/litre 55Rs/litre

&

60 Rs/gadvi

48Rs/gadvi 48Rs/gadvi 57Rs/kg 57Rs/kg 80 to

100Rs/litre

Different units and actual

quantity per unit sold

950 ml 950 ml 900 ml

&

1200ml gadvi

925 ml 925 ml 1000

grams

1000

grams

standard

1000ml

Units standardised into ml

950 950 900 925 925 970 970 1000

Effective price per actual

litre (1000ml)

53 55 61 52 52 59 59 9032

Price per 100 Calories (Rs) 10 13 12 12 11 11 11

14

Price per 100 kJ

(Rs) 2.4 3.0 2.5 2.6 2.4 2.6 2.6 3.4

31 The retail fresh milk prices are fixed for the whole year in the Lahore urban market. 32 Average of 80 and 100 Rupees

149

Milk Value Chains Value chain 1:

rural Kasur- urban Lahore chain

Value chain 2:

rural Okara-urban Lahore

chain

Value chain 3:

rural Pakpattan - urban Lahore

chain

Formal

Processors

Nestlé, Engro

& Haleeb

Quality

(Aslam,

2015)

ECM33 per

standard 1 litre

0.78

0.69 0.76 0.70 0.74 0.81 0.83 NA

Calories34 per

100 ml

50 41 53 44 48 52 53 64

kJ35 per 100 ml 210 173 220 185 200 217 222 267

Fat% 3.3 2.9 3.4 2.9 3.4 3.2 3.4 NA

SNF% 5.7 4.4 6.0 5.0 5.3 6.4 6.1 NA

Protein% 2.1 1.6 2.2 1.9 2.0 2.4 2.3 NA

Added water % 33.5 42.8 29.8 42.0 38.8 24.7 27.8 NA

Note: The milk composition for retailers is based on whole year average recorded by Aslam (2015). The formal processors do not mention fat and SNF percentages on the

packaging

33 IFCN Net ECM milk = [gross milk production * (0.383 * % fat + 0.242 * % protein + 0.7832) / 3.1138]. The database standardises milk to 4% fat and 3.3% protein using the above formula. Now making the existing Nestlé formula of 13 total solids (TS) equivalent to IFCN meant →

Net ECM milk= (gross milk production × (0.22 × 4% fat + 0.72 + 6.5SNF+ 4% fat) /13 where 6.5 in the formula is SNF = 26LR÷4 34 1g of fat = 9 calories; 1g of protein = 4 calories; 1g of carbohydrates or lactose = 4 calories. Therefore 9×5.8+4×2.9+4×4.1=80 35 1 Calorie = 4.184 kJ and 1 kJ = 0.239 Cal

150

The quality of milk is also closely linked to price. Table 24 illustrates that the 4 to 5% fat

unwritten fat standard, claimed by the value chain operators, does not mean much as an

average fat percentage is actually around 3% (Aslam, 2015). Energy-corrected milk

(ECM) shows that apart from the misuse of units, even if we assume a standard litre

packaging, the consumers are getting less per litre at all seven shops. The nutritional

value of fresh milk is slightly lower than the packaged milk supplied via the formal chain,

but it is negligible relative to the price difference between milk from the two channels.

The packaged milk supplied through the formal chains also does not mention fat

percentage on its label, which causes doubt on the source of energy contained within the

milk, and which is possibly cheap imported powdered milk. An ECM analysis, therefore,

would not have been uniform and meaningless for the two forms of milk.

Table 24 demonstrates that the domestic chains are a source of cheaper calories for urban

domestic consumers (Food and Agriculture Organization, 2013c), particularly those in

the lower socio-economic group. These informal fresh milk chains are not ideal but still

offered relatively better value for money (Collins, 2009). The quality of milk does,

however, remain a concern and Pakistan being a higher consumption country, it has to be

addressed and improved.

Consumer awareness of both milk quality and quantity is of critical importance to bring

a positive change in the practices in these fresh milk value chains. More importantly, the

consumers need to be aware of the virtues of better nutrition for the benefit of their

household in a developing country scenario where calories are very precious. The

awareness by end consumer will lead to a demand for milk with appropriate nutrition as

well as volume for which they are charged. Consumer awareness backed by enforcement

of standards by the government authorities are expected to change the current illicit

practices prevalent in the milk value chains.

151

High-fat content buffalo milk is currently of the highest value to the final consumers who

gauge milk quality by the cream set on the top of milk after boiling. Overall nutrition and

safety are of little concern to consumers who are also generally unaware of the effective

units of milk purchased, which provides opportunities for retailers to misuse their power

within the informal chains.

The study points to the need of uniform price, quality and quantity standards across the

industry with clear labelling for both formal and informal channels. As the price of the

final product is closely associated with quality and quantity sold, it is worthwhile studying

how it is determined from farm gate to final consumer, among and across the chains and

in the industry as a whole.Milk value chain analysis: industry competitiveness and the

dairy policy environment in Pakistan

152

Chapter 8. Milk value chain analysis: industry

competitiveness and the dairy policy environment in

Pakistan

This chapter builds on the research conducted and presented so far. It includes methods

for this final part of the research. The value chain analysis framework is provided in the

detailed literature review Chapter 2 of the thesis. This chapter summarises three rural-

urban milk value chain case studies an interview with the senior manager of an industrial

milk processing company i.e. formal processor. The conclusion of the chapter is based on

improvement scenarios for these domestic rural-urban milk value chains and the industry

as a whole.

Methods

The study originated from the irrigated Okara and arid Bhakkar districts of Punjab (Figure

23 a & b). The choice of the districts studied was based on the availability of farm

economic analysis data from a two-year longitudinal survey (Wynn, Unpublished) for

these two districts.

The study involved two stages. The first stage involved a scoping study which used a

purposive sampling method (Patton, 2002) to identify and sample fresh, unpackaged milk

informal and formal chains in both districts. Twenty-seven producers, 11 small, eight

medium and five large dhodhis, 22 retailers, two formal processors and 11 consumers

(Chapter 5, Table 8) were interviewed personally, using four different questionnaires

(attached as Appendix E). In total twenty-five, informal chains and two formal processor

chains were studied. The questionnaires were developed using a simple value chain

analysis framework to identify key functions being performed along the chain. The initial

rural participants were identified with the help of the Australian Centre for International

153

Agricultural Research (ACIAR) project team (Wynn, 2010) and their buyers were then

tracked and subsequently interviewed. Some dhodhis and retailers were also randomly

surveyed to provide greater cross-sectional perspectives. During this research the Okara-

Lahore chain model (Chapter 6) stood out because of its complexity and author did some

preliminary analysis of the chain. Similarly, a better cool chain supply chain model of

Pakpattan-Lahore chain (Case study 3, Appendix H) was also identified to be of interest

that required further investigation.

154

Figure 23a. Map of Pakistan highlighting the Punjab province; b. Map of Punjab showing Kasur district and Lahore city


155

In the second stage, four fresh, unpackaged rural-urban fresh milk value chains were

identified in the irrigated Punjab (Figure 23b). Although a number of chain models

existed (Figure 16), the choice of rural-urban chains was based on the outcome of the

scoping study and the need to review individual cases more thoroughly at the rural–urban

fringe where there are burgeoning urban populations of milk consumers. Quantity and

quality assessment, price fixation mechanisms and financing emerged as important wider

industry issues for further exploration. The chains identified for further study were

complex and information rich with more tiers carrying higher product volumes from farm

to the consumer.

Yin’s (2009) case study method was used for this research. The use of case study

approach for an empirical inquiry allows the researcher to investigate a contemporary

phenomenon that is the “case” in depth and within its real life context. Furthermore, the

use of multiple cases (Figure 24) allows substantial analytical benefits as they provide

more compelling evidence and the overall study is, therefore, more robust.

Figure 24: Multiple case study procedure

Source: Yin (2009)

Develop

theory

Select cases

Designing data

collection protocol

Conduct 1st case

study

Conduct 2nd case

study

Conduct

remaining case

studies

Write individual

case report

Write individual

case report

Write individual

case reports

Draw cross-case

conclusions

Modify theory

Develop policy

implications

Write cross-case

report

Define and Design Prepare, Collect and Analyse Analyse and Conclude

156

The selection of specific villages and districts was based on author's close association

with and support from the ongoing ACIAR dairy project (Wynn, 2010) presence in these

areas, whose staff had good standing with the smallholder producers, the entry point for

this study.

The number of participants interviewed for each chain are provided in Table 25, which

also describes the number of tiers for each chain. Only the Okara-Lahore chain had a

Medium Dhodhi operator. Of the four cases, the Large Dhodhi operator of one of the two

Pakpattan-Lahore chains initially identified refused to cooperate and therefore the case

had to be dropped (Table 25). A senior official of a multinational formal processor was

also interviewed. The four case studies are attached as Appendices F, G, H and I.

157

Table 25: Number of rural-urban milk value chains participants interviewed and the number of tiers of each chain and the formal milk processors/companies

Milk Producers Small Dhodhi Medium Dhodi Large Dhodhi Retail milk shops Consumers

Value chain 1:

rural Kasur-

urban Lahore

chain

Four including

Producer1 &

Producer2

One Small Dhodhi NA One that included father

and two sons

All seven retail buyers

were introduced but

detailed interviews with

the three retailers

Retailer1 4

Retailer2 5

Retailer3 5

Value chain 2:

rural Okara-

urban Lahore

chain

Producer1

&

Producer2

Small Dhodhi 1

&

Small Dhodhi 2

One Medium

Dhodhi

One Large Dhodhi (two

brothers)

Five of the eight retail

buyers were

approached. Two

retailers outside the

family did not

cooperate

Retailer1 5

Retailer2 6

Value chain 3:

rural Pakpattan -

urban Lahore

chain

Producer1 One Small Dhodhi NA Large Dhodhi (two

senior managers and one

senior most milk tester)

Retailer1 (owner’s

brother i.e. managing

shops at retail end)

5

Retailer2 (franchised

shop)

5

Value chain 4:

rural Pakpattan -

urban Lahore

chain

Two milk

producers

One Small Dhodhi NA One Large Dhodhi who

refused to introduce his

urban retail buyers

Formal Processor and multinational Nestlé’s senior collection manager interviewed. Engro & Haleeb, however, are also big players in the domestic milk market and have

frequently been referred to by the informal chain participants

Source: Author’s field research (Please refer to Figure 28, Figure 33 and Figure 38)

158

The research was underpinned by mixed methods that are qualitative and quantitative

techniques to collect and analyse data. The method combines the use of both quantitative

and qualitative methodologies within the same study to address a single research question.

The integration of these two approaches to collect data helps develop a complete

understanding of the research problems than what either one by itself would net. These

studies can later be brought together and integrated, by casting them within a larger

theoretical framework (Bergman, 2008; Creswell, 2010b; Creswell & Plano Clark, 2011;

Jupp, 2006).

The quantitative data collected for each value chain case study will give a clear picture of

a) Physical flows including product quantity, quality and time to transfer product

along the chain

b) Financial flows represented by costs and margins and value creation and

distribution

c) Technology and infrastructure used in transport, storage, cooling and

processing and its economic value

The qualitative data collected for each value chain case study identified

a) Value chain participants and their functions (who?), roles (what?) and rules

(how / why?)

b) Governance internal to the chain that is relationships, power dynamics, conflict

and problem solving. External governance in terms of government and dominant

market players and their influence on price, quality and price information flows.

c) Information flows with a particular focus on price to understand the type,

direction, timing, completeness, accuracy and distortion if any in these flows.

d) Consumers and their buying behaviour, preferences and unmet needs, what they

value and their demographics (Chapter 7).

159

For this research, field observations were made, and in-depth face-to-face interviews were

carried with milk value chain participants using four questionaries (attached as Appendix

J) that included fixed-choice and open-ended questions. The questionnaires from the first

stage were further refined to go deeper using the framework developed in the literature

review to both collect and analyse the data. The purpose of the research was explained to

each respondent to gain the trust.

Patton (2002) and Yin (2009) point towards the use of interviews and personal observations

as the key tools for data collection in the qualitative case study research. Clarke (1999),

describes interviews as a conversation with a purpose. He describes that in a structured

interview, questions are asked in a systematic and consistent order while semi-structured

interviews follow a less rigid format and include open-ended questions.

For this research, structured questions were asked to get the numbers. Both Likert scale

and ranking scale were used to determine the priorities of respondents. The semi-

structured questions were used to understand how and why the chain participants do what

they do. The semi-structured questions generated more in-depth responses although often

the structured questions also lead to further discussions and insight. USAID (2005)

qualitative interview manual was also used as a guide for doing the research in a

developing country setting. The author tested the questions with a colleague with several

years of fieldwork experience in the dairy sector of Pakistan. The sequence of questions

was refined several times after each case study.

The practices and understanding of two keys aspects of milk quality and quantity varied

for chain participants and across the milk value chains. Evidence related to these practices

was gathered through direct observation of their participation and practices at various

tiers of the chain. Apart from taking occasional field notes outside the formally designed

160

questionnaires, pictures and voice recording were extremely valuable tools for the

analysis of data collected later on.

In this research, validity aspect was addressed by collecting data from multiple sources.

This approach to construct validity is consistent with Patton (2002) and Yin (2009) who

recommend multiple sources of evidence in case studies.

The primary data sources were milk producers, dhodhis at different tiers, retailers and

final consumers of milk whose statements were cross-examined. Various government

reports and local research publications on the dairy industry of Pakistan also helped make

better sense of the local industry although it was somewhat generic and biased against the

local milk chains.

Secondly, interviews with a Pakistani Professor who had done research on the dairy sector

of Pakistan, a senior bureaucrat from the Punjab Livestock Department Punjab and

discussion with extension officers from both Punjab and ACIAR dairy project field also

added more depth to author’s understanding of the local milk marketing context, although

this second source did not inform the analyses.

The most important advantage presented by using multiple sources of evidence is the

development of converging lines of inquiry or triangulation, a technique to ensure that an

account is rich, comprehensive and well developed (Patton, 2002; Yin, 2009). The author

relied on the triangulation through matching and cross-examining the response of chain

participants about the same thing to check the consistency. Finally, the milk quality collected

by Aslam (2015) at each tier of the three milk value chain case studies identified by the

author was a key source of validation and has been used to develop an even deeper

understanding of the chains studied and the dairy industry of Pakistan.

161

Results

The Kasur-Lahore, Okara-Lahore and Pakpattan-Lahore fresh, unpackaged rural-urban

milk value chains in this study originated in separate villages of Kasur, Okara and

Pakpattan districts in Punjab province (detailed case studies in Appendices F, G, H and

I). They were situated 85, 135 and 190 kilometres respectively south-west of metropolitan

Lahore city to which the milk was being supplied. All chains were supplying milk to

formal processors as well. The Kasur-Lahore chain’s origin used to be the source of

product for Pakistan’s only milk cooperative that had recently ceased to operate.

Value chain actors, technology and infrastructure along the chain and

spoilage risks

The three informal fresh milk chains had four, five and four tiers respectively (Table 25)

from farm to retailer before the milk was sold to the final consumer. The large dhodhis

and retailers gave the most time to their business operations. The Kasur-Lahore, Okara-

Lahore and Pakpattan-Lahore chains generated 407, 979 and 3,486 employment

opportunities respectively from milk producers to the retailers.

Large dhodhis followed by the milk producers had made the highest investment in the

chains. Apart from the Pakpattan-Lahore chain that had a proper cool chain, all other

equipment used along the chains was unrefrigerated. Trucks used to transport milk in all

three chains were unrefrigerated. The retailers used refrigerators for overnight storage.

Similarly, apart from Pakpattan-Lahore chain retailers that made more processed products

from milk, the other retailers in other two chains only made yoghurt for sale purposes.

The physical spoilage risks of milk varied amongst the three chains due to their different

geographical structures. For example, the Small Dhodhi in the Kasur-Lahore chain was

162

collecting milk from his own village and did not face the risk of spoilage whereas for

Okara-Lahore and Pakpattan-Lahore chains; the small dhodhis faced significant spoilage

risk as they were covering a wider milk collection area. Overall, the spoilage risk then

increased downstream for large dhodhis and retailers in all three chains.

In the Kasur-Lahore chain, Nestlé was the formal processor that had established its village

milk collection centre 10 km from the village where milk producers and Small Dhodhi

interviewed reside. For the Okara-Lahore chain, the formal processors did not have a

chiller in the Producer1’s village. These processors, however, had their representatives

who collected milk on bicycles at the same price as the informal Okara-Lahore chain’s

Small Dhodhi did. The village where Producer2 lives had a collection centre for the

multinational Nestlé with a chiller installed. However, he was offered a relatively better

price for higher fat content buffalo milk from his Small Dhodhi buyer. Similarly, for

Pakpattan-Lahore’s chain village where farmers were interviewed, Nestlé had installed a

collection chiller in the adjacent village, which was approximately ten km distant.

Consumer value, quality determination and grading and quantity

measurements along the chain and gross margins

Fat content associated with buffalo milk followed by sweet taste and then aroma were of

prime importance in all the chains for the final consumers. The higher fat, therefore,

became key quality attribute sought by all three chains. Large dhodhis in all three chains

preferred collection of buffalo milk associated with higher fat and diluted it with ice for

the urban retail market to gain volume. Kasur-Lahore and Okara-Lahore large dhodhi

used the same formula of 6% fat standard in milk to assess milk quality, which is as

following:

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Okara-Lahore chain’s Large Dhodhi was offering an extra 0.7% for fat to each small

dhodhi for the milk collected in summer. This was because average fat percentage for

small dhodhis’ collection was less than the 6% standard. This was confirmed by the

author’s observation of the use of 5.7% fat average as the minimum standard used by

Kasur-Lahore chain’s Large Dhodhi for his total rural collection.

Substantially Large Dhodhi operator in the Pakpattan-Lahore chain, however, had

adopted the multinational milk processor Nestlé’s standard of 13% total solids:

0.22 × Actual Fat + 0.72 + SNF + Actual Fat = (TS per liter × Gross volume) ÷ 13%TS

= Net volume

where TS (Total solids) = Fat + SNF (Solid Not Fat)

and SNF (Solid Not Fat) = LR(lactometer reading) × 0.25

The large dhodhis of Kasur-Lahore and Okara-Lahore chains claimed to be supplying

milk at around 4.8% and 4.5% fat to retail shops in the urban Lahore market. The Large

Dhodhi for Pakpattan-Lahore chain was selling milk at around 4.5 to 4.6% fat. He aimed

to sell at 5% fat but was unable to do so given that Nestlé had lowered its quality standard

to 13 total solids from 14 at the farm gate. This lowering of the standard by Nestlé meant

small dhodhi suppliers operating in the Pakpattan-Lahore chain gained volumes and had

to be paid more for the milk procured. Formal processors also imported and use powdered

milk in their packaged UHT milk product as the Nestlé manager said, “…milk collection

drops substantially in summer…imported milk powder is blended with fresh milk as a

part of the manufacturing process…”, which gives them further advantage over the

informal chains.

There was no grading at any tier of the three fresh milk chains apart from the Kasur-

Lahore chain. Small Dhodhi separated buffalo and cow milk in this chain. He sold cow’s

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milk to the formal processors and buffalo milk to the informal Kasur-Lahore chain’s

Large Dhodhi, who offered an incentive for higher fat associated with buffalo milk.

The units of volumes to buy milk at the farm gate and sell at retail shops varied across

and along the three chains (Table 26, Table 27 and Table 28). The variation in unit volume

was possibly due to the social acceptance of these practices by the producer and lack of

awareness of consumers.

Table 26, Table 27 and Table 28 illustrate gross margin estimates per actor based on the

milk quantity units and quality standards used by each chain. The estimates exclude

owner operator’s opportunity cost of labour and disregard interest foregone on the capital

invested. Milk processed into yoghurt and other forms have not been included, and

accordingly the costs associated with processing have been excluded from the

calculations.

165

Table 26: Physical and financial flows along the Kasur-Lahore fresh, unpackaged milk value chain

Kasur-Lahore chain

Kasur-

Lahore

Producer1 Small Dhodhi Large Dhodhi Retailer1, Retailer2 and Retailer3

Volumes 3 gadvi 32litre where

27gadvi ×1.1=29.5 L

→

(29.5×6.5)÷6=32 L

1400litre where

1200 L milk and 200kg ice

Retailer1: 230 L÷0.95= 242litre

Retailer2: 450 L÷0.95= 474litre

Retailer3: 1,380 L÷0.95= 1,453litre

Quantity

&

Quality

1 gadvi = 1.1 litre 1.1L

(1.1×6.5)÷6=1.2 L

(6milk:1ice) Litre

1 L= 950ml

Price 40 Rs/gadvi 43.75 Rs/litre 47.5 Rs/litre Buying

Retailer1:47Rs/L

Retailer2: 49 Rs/L

Retailer3: 50 Rs/L

Selling

Retailer1: 50 Rs/L

Retailer2: 52 Rs/L

Retailer3: 55 Rs/L

Gross

Margin

-36Rs1

180 Rs 6,607 Rs Retailer1: 575 Rs

Retailer2: 930 Rs

Retailer3: 8,586 Rs

Capital

invested

4.1 million Rs 0.8 million Rs 5.2 million Rs Retailer1: NIL as Large Dhodhi’s invested 0.2 million Rs

Retailer2: 0.5 million

Retailer3: 1 million Rs

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Table 27: Physical and financial flows along the Okara-Lahore fresh unpackaged milk value chain

Okara-Lahore chain

Okara-

Lahore

Producer1

&

Producer2

Small Dhodhi1

&

Small Dhodhi2

Medium Dhodhi Large Dhodhi Retailer1

&

Retailer2

Volumes Producer1: 10 gadvi

Producer2: 1 gadvi

Small Dhodhi1: where 66.7 gadvi ×

1.073 = 71.6 ÷ 0.925 =

(77.4×6.2%fat)÷6 = 80 litre

Small Dhodhi2: 31 gadvi × 1.073 =

33.3 ÷ 0.925 = (36×6%fat)÷6 = 36

litre

570 litre 2,350 litre where

2056L milk and 294kg ice

(8milk:1ice)

Retailer1: 511litre

Retailer2: 277litre

Quantity

&

Quality

1 gadvi = 1.073 litre 1.073 litre ÷ 0.925

=1.16litre×6.2%fat)÷6 = 1.20litre

NA as commission only (8milk:1ice) Litre

1 L= 925ml

Price Producer1: 35 Rs /

gadvi

Producer2: 35 Rs / kg

Small Dhodhi1: 38 Rs / L


40 Rs/L 44.5 Rs / L

Retailer1: 48 Rs / gadvi


Gross

Margin

Producer1: 170 Rs1

Producer2: 10 Rs1

Small Dhodhi1: 100 Rs


510 Rs 4,300Rs Retailer1: 3,500Rs

Retailer2: 1,900Rs

Capital

invested

Producer1: 27 million

Rs

Producer2: 12 million

Rs

Small Dhodhi1: 0.55million Rs

Small Dhodhi2: 0.15 million Rs

1 million Rs 4.4 million Rs Retailer1: 0.2 million Rs

Retailer2: 0.15 million Rs

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Table 28: Physical and financial flows along the Pakpattan-Lahore fresh, unpackaged milk value chain

Pakpattan-Lahore chain

Pakpattan-Lahore Producer1 Small Dhodhi Large Dhodhi Retailer1

Volumes 14 kg standard 1×0.9681= 0.9681 litres 23,387 L

(16milk:1ice)

1,527kg

Quantity & Quality Standard kg Litre (16milk:1ice) Litre Standard kg

Price 36.25 Rs/kg 41.50 Rs/L 50 Rs/L 57 Rs/kg

Gross Margin 250.4 Rs1 2,762 Rs 67,907 Rs -3,322 Rs

Capital invested 12 million Rs

2.5 million Rs

Estimated36 100million 1.7 million Rs

Data Source: Author’s field research 1Based on author’s detailed farm economic analysis as part of his PhD research (Chapter 4). The price & cost ratios are based on the description of land and livestock holding provided by the respondents in this research. These ratios indicate that

the average annual variable cost of production is higher than price for some small-scale farmers

& the average annual variable cost of production is less than price for some large-scale farmers

More specifically, it is assumed that for Kasur-Lahore chain the producer produces less than 2,300 litres per year (1price:1.3cost); for Okara-Lahore chain Producer1 produces

3,700 to 10,100L per annum (1.9price:1cost); whereas Producer2 produces 2,300 to 3,700L per annum (1.4price:1cost); and for Pakpattan-Lahore chain Producer1 produces

3,700 to 10,100kgs per annum (1.9price:1cost).

These average price and average cost estimates are on single basis although the prices and costs may change seasonally.

36 Authors’ estimate based on the milk volumes purchased and sold, compared to other chains studied

168

Producers had invested substantially in land and livestock that is 4 to 27 million Rupees

(Table 26, Table 27 and Table 28) but their margins were negligible in all three chains.

The small size Producer1 in Kasur-Lahore chain was making losses on milk as an

enterprise, and his variable costs were higher than the price paid for milk.

Large dhodhis had made the largest capital investments in Kasur-Lahore and Pakpattan-

Lahore chains, whereas the producers in the Okara-Lahore chain had made a bigger

investment than the large dhodhi.

Small dhodhis would have been losing money if it was not for the biased measurement

units and fat incentives offered by the large dhodhis. The Pakpattan-Lahore chain was

exceptional as Small Dhodhi was losing volumes due to the kg to litre conversion

assumed to be a safeguard against the lower 13% TS standard, as the conversion deprived

the Small Dhodhi of some volume. The large dhodhis and retailers of the Kasur-Lahore

and Okara-Lahore chains earned higher margins, except Retailer1 of Pakpattan-Lahore

chain, who was losing money.

Similarly, the unit alterations allowed the retailers to make some money amid tight

margins.

Product seasonality, price determination, pricing power dynamics and

information flows

Demand and supply associated with product seasonality: The 35 consumers

interviewed at the seven retail shops stated that their household consumption was highest

in summer and decreased in winter.

However, this demand did not coincide with peak supply. In the Kasur-Lahore chain, the

producers responded that their milk production for both buffalo and cow species started

169

decreasing in mid-April that is the start of summer37 when demand for milk and other

dairy products was increasing.

Okara-Lahore chain producers said that milk production peaks in winter when there is an

abundance of green fodders. The lactation cycle for cows depends on the breed animal

and can be both the same as or different to buffalo.

While in the Pakpattan-Lahore chain, milk production for both buffaloes and cows starts

decreasing in mid-April when demand for milk and other dairy products starts to increase.

Some producers, however, had cows producing more milk in summer and less in winter.

This production cycle of cows, as opposed to buffalo, helped meet some of the increased

summer demand.

Consumer response to retail prices: The responses of consumers to price changes and

urban retail prices varied at the seven retail shops and appeared to be linked to their socio-

economic status. The Pakpattan-Lahore shops charging higher prices were located in

areas where consumers had a higher purchasing power and were not that concerned about

price.

Price determination-Retail urban prices: The retail price in urban markets is fixed on

an annual basis by the city district government before the start of summer season. For

2012, a price of 57 Rs per litre had been fixed. There was no logical rationale used to

determine this benchmark government retail milk price for fresh milk. Some large

dhodhis cum retailers influenced the price setting mechanism, which meant they held

substantial power in the urban markets.

However, the fixed price was not strictly followed by the retailers and worked as a loose

benchmark around which prices fluctuated. Depending on the nature of their business,

some retailers acted independently to set their retail price based on the unit used while

37 Pakistani summer starts mid-May

170

others relied on the large dhodhis’ business acumen in recommending a suitable price.

The units for milk volume also varied widely across the chains and at various tiers of each

chain.

Price determination-Farm gate rural prices and pricing power dynamics: The formal

processors controlled the farm gate milk prices and thus were the key price brokers. These

prices were associated with supply or production. The formal processor who said, “Nestlé

reviews farm gate milk prices paid on a weekly basis”, verified this. He further said, “The

price is based on estimated domestic milk supply, competitors’ demand, the international

price of powder milk. The average farm gate or contractor price range this year will vary

from a minimum of Rs 37.5 to a maximum of Rs 50”.

The major farm gate price change is associated with summer and winter seasons. Minor

price changes did, however, occur on a regular basis and were either absorbed by the large

dhodhis or in some cases passed on to the small dhodhis. The price offered by the chain

to small dhodhis was higher than that offered by the formal processors. The data gathered

did not indicate minor regular price changes were passed to the producers, but seasonal

market prices were.

Kasur-Lahore chain’s Large Dhodhi demonstrated a fair degree of independence in price

fixation with his Small Dhodhi supplier although the latter did observe factory prices and

was constantly lobbying his Large Dhodhi buyers for price increases.

The Okara-Lahore chain’s Large Dhodhi and Medium Dhodhi were strictly following the

formal processor prices. The same applied to the Large Dhodhi of Pakpattan-Lahore

chain. This farm gate price determined by the formal processors worked as a benchmark,

and the chain could not offer a price less than that to their Small Dhodhi suppliers.

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The large dhodhis absorbed the fluctuation in rural milk prices to a large degree. Their

small dhodhi buyers informed the producers of prices, but these producers also consulted

other dhodhis and neighbours.

The key source of price information for all three chains in the urban market was the

government price and in rural markets, it was the formal processors’ prices. The rural

actors that is large, medium and small dhodhis were well aware of the rural prices.

Facilitating functions of financing and payment schedules, relationships

and power dynamics

There was an intricate set of facilitating functions in the chain that enabled it to function

in the absence of formal contracts. This section describes the financing and various

services provided in the chain. It examines the duration and description of relationships,

conflict and problem-solving mechanisms. The interaction between sellers and buyers at

various tiers of the chain that was studied.

Producers and small dhodhis: In all three chains, the small dhodhis provided services

such as the supply of fertilisers, feed supplements and even household groceries to the

producer households. More importantly, the small dhodhis extended initial cash advances

to the producers to procure milk. Farmers used these advances to meet their household

needs. The producers also borrowed money from their small dhodhi buyer whenever a

need arose. The accounts between the two were settled once each month although the

producer kept the advance until all conditions of the financial dealing came to a complete

halt. This arrangement turned the balance of power in the producers’ favour as he could

hold the small dhodhis’ money if an animal went dry until the time it started milking

again. In some cases, the producers did not return this money even if the business dealings

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ended with the small dhodhi. Similarly, the producer had more power in peak summer

demand due to milk supply shortages.

There was a relational aspect to the dealings between producers and small dhodhis

although the duration of dealings varied among the individuals and chains. Often both

parties were from the same village or same baradari38. Conflicts if any were resolved with

the involvement of other locals. There was often friction and mistrust at this tier of the

chain as both parties suspected each other of diluting milk.

Small, medium and large dhodhis and formal processors: In the Kasur-Lahore and

Pakpattan-Lahore chains the large dhodhis extended interest-free loans or cash advances

to his small dhodhi suppliers. In the Okara-Lahore chain, this function was performed by

the medium dhodhi.

This arrangement locked in both parties. It provided the surety of supply to the buyer and

guarantee of purchase to the seller in the peak summer season when there was higher

demand and less supply. The large and medium dhodhi for the Okara-Lahore chain also

continuously met any other financial need of their small dhodhi suppliers.

In some instances, lender dhodhis took a bank cheque from some but not all small dhodhi

recipients, which was a guarantee for cash advance extended. This security was a risk

mitigating approach, particularly applicable to those small dhodhis who were not from

the same rural vicinity or to those who could not be trusted. The frequency of payment

for milk varied in the three chains.

In all chains, books with small dhodhis were settled every eighth day. In the Kasur-Lahore

chain, the mechanism varied slightly as the small dhodhi were paid every twelfth-day

making payment for eight days that the milk was supplied, keeping four days of payment

38 Kinship

173

in abeyance. Formal processors followed the same mechanism for their milk suppliers.

Formal processors Nestlé maintained accounts on a weekly basis for all farmers. It made

payment for eight days of milk supplied and held three days payment as a surety.

The business dealings at this tier of the informal chain were more professional compared

to dealing upstream. There was a higher level of trust and longer lasting relationships.

The balance of power was seasonal. The small dhodhi suppliers had more power in

summer because there was a higher demand and reduced supply and vice versa for winter,

whereas the opposite was strue for farmers.

The large dhodhis in all three chains were supplying milk to formal processors as well,

which provided a mechanism for winter milk sales when the urban demand at retail milk

shops decreased.

Large dhodhi and retailers: The Large Dhodhi in the Kasur-Lahore and Pakpattan-

Lahore chains extended milk on credit to some retail buyers who were either close family

members or vendors operating in retail outlets owned by them. The accounts were settled

at the conclusion of business dealings. The Pakpattan-Lahore chain’s Large Dhodhi used

a more professional business model where he owned four shops while a further nine were

franchised. The relationships at this tier of the chains were longer term compared to

relations upstream. There was a high level of trust on Large Dhodhi, particularly evident

in the Kasur-Lahore chain.

On the balance of power, both parties were free to part ways and change buyer and/or

supplier.

Working together long-term was beneficial, however, as in the of peak summer, it was

hard to find suppliers and buyers in winter. In both Kasur-Lahore and Okara-Lahore,

chains the large dhodhis were also vertically integrating at the retail end and either

opening their own shops or operating through shops owned by close relatives. The

174

changing of buyers or sellers in this situation was not suitable for either party due to better

terms of trade.

Discussion and Conclusion:

The study has used a value chain approach as a lens to study the dairy industry of Pakistan.

This work is unique in Pakistani dairy industry’s context, as it has not been investigated

in the past. The research has provided a deeper insight into the operations of informal

rural-urban chains and their interactions with the formal sector to make sense of why the

industry works the way it does. The irrigated region of Punjab, where the study was

conducted, is both the food bowl as well as the most densely populated demand hub of

Pakistan.

The informal milk chains were pro-poor, and they together generated an estimated 4,872

employment opportunities from farm to market. Job creation is one of the key policy

instruments for any government. These chains have therefore to be empowered and

improved so that finance generated locally not only flows back to the local producers but

has a trickle-down effect on the broader economy (Gómez et al., 2011).

Governance through financing at various tiers of the chain and interdependent

relationships were key strengths of the chains, apart from low operational costs and

product differentiation, which was occurring at the retail end.

The financial arrangements along the chains held them together. Regular cash flows were

passed to the producers upstream, interest-free loans to dhodhis at the middle tier and

credit downstream to the retailers. These financing mechanisms locked-in the two parties

involved in a transaction along the chain, at almost all times. The small dhodhis were

captive to producers due to their cash advance arrangement in all three chains. Further,

along the chain the large dhodhis in Kasur-Lahore and Pakpattan-Lahore chains were

175

ensuring consistent milk supply by locking in the small dhodhis through their provision

of interest-free loans. In Okara-Lahore chain, the medium dhodhi exercised a fair degree

of control on small dhodhi suppliers through loans extended. On the other hand, the small

dhodhis by using these loans were not only able to then extend cash advances to the

farmers and buy a motorcycle for their business, but they also secured a source for their

milk supply. The cash advances and loans made exiting the chain an unattractive option

for most receivers (Gereffi et al., 2005) as there was a high degree of interdependence

between operators (Stych & Gulati, 2008).

The strong relationships designed to establish shared competitive advantage (Dyer &

Singh, 1998) along the chains and the unique conflict resolution mechanism, in the

absence of formal contracts, was another of their key strengths. This was important, as

operators were unable to pursue costly and potentially unpredictable litigation.

Smallholder producers preferred to sell milk to the informal chains for the following

reasons:

Farming is labour intensive and time-consuming. The small dhodhis collected

milk at the producers’ doorstep, which saved them time and transportation costs.

Although the formal channels offered one rupee per litre higher or the same price

to the producers, compared to dhodhis, it was negligible given the small quantities

produced and sold by the farmers.

The formal processors did not offer any advance cash incentive for fat content, or

at least the producer did not see any visible incentive offered for providing milk

with a higher fat: a pricing incentive was offered through the informal channels

for high-fat buffalo milk. The quality standards set by the formal processors were

not clearly understood by the small producers, and thus there was hesitation in

dealing with them.

176

Formal processors made a delayed payment for the milk procured and also did not

offer any initial cash advances, nor did they meet the regular needs of producers

as the small dhodhis did, which was extremely important for the producer.

Small dhodhi supplied feed supplements regularly or on demand to the producers

The informal chains relied on strong human relation aspects, which was one of its

key strengths contrary to the impersonal dealings of formal processors.

The informal chains and in particular the participants downstream faced physical and

market-related price risks (Kohls & Uhl 2002). The chains operated with minimal cool

chain infrastructure, which limited large dhodhis to collect morning milking in the Kasur-

Lahore and Okara-Lahore chains. The lack of cool chains increased the spoilage risks

downstream and these physical risks (Boehlje, 1999) were mainly borne by the large

dhodhi who also bore the price risks associated with regular price fluctuations, which are

assumed to be dealt with, by dilution of milk. Handling and dealing in cash was another

risk taken by large dhodhis, amidst very fragile law and order practices in the country.

Inconsistent energy supply made the use of ice to preserve milk a necessity.

These informal chains have both a competitive cost advantage over the formal processors

and are differentiating their product by branding at the retail end (Porter, 1980). The

chains had invested far less capital in their operations than the formal processors. The

Pakpattan-Lahore informal chain had better, although not seamless, cool chain

infrastructure and was catering to a relatively more affluent clientele and accordingly

charging a higher price. The margins along all three chains were tight. The lesser capital

investment in the cool chain also meant a greater need for relatively cheap labour to

handle the product along the chains. Proper cool chains, if installed, will require capital

investment and the costs will have to be borne by the final consumer in terms of higher

177

milk prices. The question is: is it feasible given the current levels of poverty (World Bank,

2013) amongst the clientele in the markets that the chain caters to?

All three chains were vertically integrating at the retail end. The large dhodhis were

establishing their own shop names as brands. The Pakpattan-Lahore chain marketed

through a well-established brand name associated with better quality in the Lahore

market. The large dhodhis of both Kasur-Lahore and Okara-Lahore chains were

developing brand names too for the milk supplied to the same urban market. Final

consumers preferred cheaper milk with higher fat. The large dhodhis and retailers were

well aware of this buying behaviour of consumers. Large dhodhis were focusing on

procuring higher fat buffalo milk valued by the final consumer and had checks in place

to ensure this happens.

In the absence of government industry standards and labelling regulations (Purcell et al.,

2008), each chain had its own standards for quality and quantity measures, which assisted

in providing positive gross margins for all operators in the chains, except farmers. The

business owners, however, had to forego the opportunity cost of their labour and the

interest rate on the capital invested.

As for milk quality, the important question is what the minimum fat percentages set by

the large dhodhi at the rural and urban level factually mean in terms of milk quality and

what impact dilution has on the nutritional status of the final consumer. In the present

study, actual milk composition data (Aslam, 2015) gathered along the three chains was

used to estimate the Energy Corrected Milk (ECM)39 yields which predict fat content.

The study also monitored protein content.

39 IFCN Net Energy Corrected Milk (ECM) = [gross milk production * (0.383 * % fat + 0.242 * % protein + 0.7832) / 3.1138]. The

database standardises milk to 4% fat and 3.3% protein using the above formula. We then aligned it with the current Nestlé’s of PL chain’s formula on standardisation

178

Kasur-Lahore chain improved state implications

For the Kasur-Lahore chain, the data in Figure 25 revealed that the milk was diluted by

producers at the rate of 6.3 & 7.5% and by retailers by 0.9% & 2.2% in the summer and

winter seasons respectively.

The producers most likely dilute milk because of the low price cost margins at the farm

gate. The two Kasur-Lahore chain Retailers 1 and 2 have fixed tight margins with the

Large Dhodhi supplier and dilution allows for an increase in gross margin: this is also

achieved through the use of ice to avoid spoilage. The Large Dhodhi is the one who dilutes

milk the most both summer and winter (18.7% and 24.6%) respectively (Figure 25a).

Despite the higher production in winter, the greater incidence of dilution is most probably

attributable to the lower farm gate prices on offer directed by the large formal milk

processing companies. The milk composition data also closely validates the author’s

original estimates of dilution by Large Dhodhi, which we are now able to approximate to

be one part ice to seven parts milk40 in the summer season (Figure 25a).

40 Figure 25a is based on Aslam (2015) PhD data. In summer, there was 30.5% added water in the milk when it reached the final

consumers at the fresh milk urban retail shop.

Milk to ice (and/or water) ratio as a result of the actions of Large Dhodhi has been estimated as: → 29.6 – 10.9 – 6.3 = 12.4 (Percentage of ice added by Large Dhodhi between rural collection outlet & retail shop)

→ 100 - 12.4 = 87.6 (Ratio of milk to ice without Large Dhodhi’s dilution)

→ 87.6: 12.4 = 7.1 milk : 1 ice (milk to ice ratio based on Large Dhodhi’s dilution)

179

Figure 25: Changes in milk composition and extent of dilution assessed at each level of the Kasur-

Lahore milk value chain41 : a. Added water percentage, b. Fat percentage and c. Protein percentage

Data Source42: (Aslam, 2015)

42 Of the eight producers, three small dhodhis, one large dhodhi and three retailers studied by Aslam (2015), the author picked three

producers, one actual small dhodhi, one large dhodhi and two retailers R1&R2. The aim was to narrow down on those participants

that were supplying milk to this chain in order to get a clearer picture of added water percentages, fat and protein from farm to consumer.

180

For the Kasur-Lahore chain, the implementation of trading on actual volume of milk with

natural fat content without adjustments by the Large Dhodhi will undoubtedly improve

returns to the milk producer (Table 29). In this case, all contributors to the chain will lose.

Retailer 3 will still have positive gross margins due to a higher price margin and larger

volumes traded, but the gross margin would be halved.

Table 29: Financial flows based on actual quantity and quality on the basis of improved chain state

along the Kasur-Lahore milk value chain

Producer1 Small Dhodhi Large Dhodhi Retailer1,

Retailer2 and Retailer3

Current state

Volumes

sold

Three gadvis

based on Small

Dhodhi’s 1.1-

litre collection

pot

32Lof buffalo milk

sold to Large

Dhodhi

where

27gadvi×1.1=29.5L

→

(29.5×6.5)÷6=32L

i.e. based on extra

volumes procured

from the producers

and 6.5% fat

Large Dhodhi’s

1400L total

collection

includes 1200L

milk and 200kg

ice (6milk:1ice)

Retailer1 230 L÷0.95= 242 L as

selling 950 ml i.e. a

smaller litre to the final

consumer

Retailer2

450 L÷0.95= 474 L as

selling 950

Retailer3’s 1,380L÷0.95= 1,453 as

assumed to be selling 950

ml too though did not

disclose the actual

volumes on his units

Price at

each step

40 Rs/gadvi 43.75 Rs/litre 47.5 Rs/litre Buying

from

Large

dhodhi

Retailer1: 47 Rs/L

Retailer2:

49 Rs/L

Retailer3:

50 Rs/L

Selling to

final

consumer

Retailer1: 50 Rs/L

Retailer2:

52 Rs/L

Retailer3:

55 Rs/L

Estimated

Revenue /

day (P×Q)

120Rs 1400 Rs

66,500Rs

Retailer1: 12,105 Rs



Estimated

variable

costs per

day

156Rs 1,220 Rs

60,433 Rs Retailer1: 11,530 Rs



181

Gross

margins

per day

from milk

loses 36Rs


Retailer2: 930 Rs

Retailer3: 8,586 Rs

Improved state

If correct

volumes

traded

3.3 litres 27 litres43

1200L44 Retailer1: 230 L

Retailer2: 450 L

Retailer3: 1,380 L

Gross

margins

per day

from milk

Total loss

curtailed to

24Rs1

i.e. 12Rs lesser

than the original

36Rs

-39 Rs -3,433Rs Retailer1: -30 Rs

Retailer2: -301 Rs

Retailer3: 4,952 Rs

Data Source: Author’s field research 1Based on detailed farm economic analysis for farms in irrigated regions presented in Chapter 3.

Please refer to Table 34 for detailed economic estimations and Figure 29 for quantity and quality

conversions along the chain.

The final consumers would also be better off in terms of purchasing a product of higher

nutritional value with a guaranteed accurate volume with each purchase (Table 24).

Okara-Lahore chain improved state implications

Similarly, for the Okara-Lahore chain, the dilution started at the farm gate (Figure 26),

albeit negligible in both summer and winter at the rate of 3.4 % and 5%. Dilution by small

dhodhis is negligible, possibly due to the butterfat and extra volume incentives offered

by the Large Dhodhi. The figure shows that dilution occurs at the retail end too. In this

case, it is assumed that the Large Dhodhi is primarily responsible for this dilution (24.1%

and 16.7%) including the bar graph at the retail end (Figure 26). He adds ice in his blue

plastic pots while pouring milk into them after buying milk from small dhodhis at the

rural end. He then possibly adds more ice on the way to the Lahore market where the milk

composition was again tested. The composition also validates the author’s original

43 Actual without deceiving farmer & no fat incentive 44 without ice

182

estimates of dilution by Large Dhodhi, which we are now able to calculate accurately to

be one part ice to eight parts milk 45 in summer.

45 Figure 26a is based on Aslam (2015) PhD data. In summer, there was 41.2% added water in the milk when it reached the final consumers at the fresh milk urban retail shop.

Milk to ice (and/or water) ratio as a result of the actions of Large Dhodhi has been estimated as:

→ 41.2 - 17.1 - 9.5 - 3.4 = 11.2 (Percentage of ice added by Large Dhodhi between rural collection outlet & retail shop) → 100 - 11.2 = 88.8 (Ratio of milk to ice without Large Dhodhi’s dilution)

→ 88.8:11.2 = 7.9 milk: 1 ice (milk to ice ratio based on Large Dhodhi’s dilution)

183

Figure 26: Changes in milk composition and extent of dilution assessed at each level of the Okara-

Lahore milk value chain46 : a. Added water percentage, b. Fat percentage and c. Protein percentage


With respect to the Okara-Lahore chain, trading in actual volumes and without fat

standardisations used by the large dhodhi, milk producer 1 and 2 became more profitable

(Table 30).

46 P=Producer, SD = Small Dhodhi, LD= Large Dhodhi, R1=Retailer1 and R2=Retailer2 47 Of the eight producers, three small dhodhi, one large dhodhi and three retailers studied by Aslam (2015), the author picked three

producers, one actual small dhodhi, one large dhodhi and two retailers R1&R2 that is those specially supplying to this chain to get a clearer picture of fat, protein and added water percentages

184


along the Okara-Lahore milk value chain

Producers Small Dhodhis Medium

Dhodhi

Large

Dhodhi

Retailers

Current state

Volumes

sold

Producer1

10 gadvi morning

mixed cow and

buffalo milk based

on Small

Dhodhi1’s 1.073L

collection pot

Producer2

One gadvi to Small

Dhodhi2’s based

on later 1.073L

collection pot

Small Dhodhi1

collects 80 litres

where

66.7 gadvi ×

1.073 = 71.6 ÷

0.925 =

(77.4×6.2%fat)÷6

= 80L

Small Dhodhi2’

collects 36 L

where 31 gadvi ×

1.073 = 33.3 ÷

0.925 =

(36×6%fat)÷6 =

36L

Medium

Dhodhi is

supplied

570L milk

Large

Dhodhi

collects

2,350L

(6 to

8milk:1ice)

Retailer1

460L÷0.925=

511L as

selling 925ml

i.e. a smaller

litre or gadvi

to the

consumer

Retailer2

256÷0.925=

277L i.e.

same as

Retailer1

Average

price at

each step

Producer1: 35 Rs /

gadvi

Producer2: 35 Rs /

kg

Small Dhodhi1:

38 Rs / L

Small Dhodhi2:

38 Rs / L

40 Rs/L

44.5 Rs / L

Retailer1: 48

Rs / gadvi

Retailer2: 48

Rs / gadvi

Estimated

Revenue

per day

(P×Q)

Producer1: 350 Rs

Producer2: 35 Rs

Small Dhodhi1:

3,040 Rs

Small Dhodhi2:

1,368 Rs

1,140 Rs 104,575Rs Retailer1:

23,870 Rs

Retailer2:

13,284 Rs

Estimated

variable

cost per

day

Producer1:18.4×10

=184Rs

Producer2: 25×1

=25Rs

Small Dhodhi1:

2635Rs

Small Dhodhi2:

1,205 Rs

613Rs 96,465 Rs Retailer1:

23,870 Rs

Retailer2:

13,284 Rs

Gross

margins

per day

from milk

Producer1: 170 Rs

Producer2: 10 Rs

Small Dhodhi1:

100 Rs

Small Dhodhi2:

31 Rs

510 Rs 4,300Rs Retailer1:

3,500Rs

Retailer2:

1,900Rs

Improved state

If correct

volumes

traded

Producer1:

10.73 litres

Producer2:

1.073 litres

Small Dhodhi1:

66.7 litres

Small Dhodhi2:

31 litres

570 litres

2056 litres

Retailer1:

460 litres

Retailer2:

256litres

Gross

margins

per day

from milk

Producer1: 192 Rs

Producer2: 12.6

Rs

Small Dhodhi1:

-60 Rs

Small Dhodhi2:

-12 Rs

367 Rs -8,650Rs Retailer1:

860Rs

Retailer2:

373Rs

185

Data Source48: Author’s field research 1Based on author’s detailed farm economic analysis as part of his PhD research



Again, the quality of milk reaching the consumer would improve (Table 24), but all of

the operators in the chain beyond the farm gate apart from the Medium Dhodhi who

operates on a fixed margin, will have to absorb the loss.

48 Of the eight producers, three small dhodhis, one large dhodhi and three retailers studied by Aslam (2015), the author picked three

producers, one actual small dhodhi, one large dhodhi and two retailers 1 & 2 that is those supplying milk specifically to the Okara-Lahore chain. This was done to get a clearer picture of added water percentages, fat and protein in milk at different tiers of the chain.

186

Pakpattan-Lahore chain improved state implications

For the Pakpattan-Lahore chain, the milk dilution was modest at the farm gate, being as

low as 6.6 & 4% for summer and winter (Figure 27). The Small Dhodhi also diluted milk

in both summer (11.4%) and winter (9.6%) possibly due the inconsistent volumes in

which milk was traded. The dilution perpetrated by the Large Dhodhi was lower in

summer (9.2%) but higher (19.3%) in winter possibly due to the low farm gate prices and

thus lower margins on offer. Thus in this chain, the overall dilution by Large Dhodhi was

lower with one part of ice combined with 38 parts49 of milk in summer. Water addition,

in this case, is negligible in fact reduced at the retail outlet. There is a suspicion that total

solids were boosted with the addition of powdered milk to maintain fat50 content.

49 Figure 27a is based on Aslam (2015) PhD data. In summer, there was 26% added water in the milk when it reached the final

consumers at the fresh milk urban retail shop.

Milk to ice (and/or water) ratio as a result of the actions of Large Dhodhi has been estimated as: → 27.2 - 18 - 6.6 = 2.6 (Percentage of ice added by Large Dhodhi between rural collection outlet & retail shop)

→ 100 - 2.6 = 97.4 (Ratio of milk to ice without Large Dhodhi’s dilution)

→ 97.4: 2.6 = 38milk: 1ice (milk to ice ratio based on Large Dhodhi’s dilution) 50 Although Figure 27b and c show declining fat and rising proteins but this is due to some missing fat% value in the data due to the

spoilage of milk sample

187

Figure 27: Changes in milk composition and extent of dilution assessed at each level of the Pakpattan-

Lahore milk value chain51 : a. added water percentage, b. fat percentage and c. protein percentage


51 P=Producer, SD = Small Dhodhi, LD= Large Dhodhi, R1=Retailer 1 and R2=Retailer 2 52 Of the eight producers, three small dhodhi, one large dhodhi and three retailers studied by Aslam (2015), the author picked three

producers, one actual small dhodhi, one large dhodhi and two retailers R1&R2 that is those specially supplying to this chain to get a clearer picture of added water percentages, fat and protein at different tiers of the chain.

188

The Pakpattan-Lahore was the only chain selling milk in standard kg whereas the

government’s urban retail milk price was set on a volume basis in litres, in this case 57Rs

per litre. Trading in actual volumes and without the Large Dhodhi’s fat standardisations

(Table 31), the farmer Producer1’s gross margin does not change as the farmers had been

using the right kg units. The Small Dhodhi will make more money, and he does not have

to convert kg to litres. The margin of Large Dhodhi becomes negligible, and Retailer1’s

loss will rise.


along the Pakpattan-Lahore milk value chain

Producer1 Small Dhodhi Large Dhodhi Retailer1

Current state

Volumes

(units as

mentioned

by each

actor)

14 kg

810kg×0.9681=784

litres.

22,000 litres total

net collection

Retailer1

1577×0.9861=1,527kg

Average

price at

each step

36.25 Rs/kg

41.50 Rs / L

50 Rs / L 57 Rs / kg

Estimated

revenue

per day

(P×Q)

508 Rs

34,000 Rs

1,134,235 Rs 89,889 Rs

Estimated

variable

cost per

day

257.6Rs

31,200 Rs

1,1066,328 Rs 95,501 Rs

Gross

margins

per day

from milk

250.4 Rs 53

2,762 Rs

67,907 Rs -3,322 Rs

Improved state

If correct

volumes

traded

14 kg 876kg with standard kg

bought from the farmers &

quality incentive

22000kg & without

dilution

1527kg bought and

sold

Gross

margins

per day

from milk

250.4 Rs i.e. no

change

5,497 Rs 672 Rs -5,762 Rs

Data Source: Author’s field research 1Based on author’s detailed farm economic analysis as part of his PhD research



53

189

Quality standard and industry wide competition

An important aspect of competition distortion mentioned by Large Dhodhi/Retailer1 of

Pakpattan-Lahore chain was the lowering of the farm gate quality standard to 13% total

solids from 14% recently adopted by Nestlé (Appendix I). The aggregate of data on milk

composition (Aslam, 2015) revealed that to be the correct measure as the total solids for

24 farmers surveyed is 13.1% that is 5.2% fat plus 7.9% solid not fat (SNF). This change

in total solids is possibly due to the change in the composition of the dairy herd in

Pakistan.

The question remains as to how to ensure the welfare of all chain participants from

producer to final consumer is sustained. Clearly, the producers are supplying more than

what they are paid for, and consumers are receiving substantially less than what they pay

for per litre, leaving the lower quantity aside, which makes them, even more, worse off.

The need is to clearly define and implement industry-wide standards for milk quantity

and quality. The current standards are vague and do not address the milk butterfat content

directly. Although the current standard is 12% milk solids for cow milk (3.5% fat and

8.5% Solids not fat: SNF) and 14% milk solids for buffalo milk (5.0% fat and 9.0% SNF)

but the law also allows for the use of reconstituted milk powder, which gives undue

advantage to the formal processors (Government of the Punjab, 2011f). The informal milk

chains are disadvantaged because the consumer prefers fresh milk with higher fat content

and the informal chains endeavour to supply this, although the addition of powdered milk

by them cannot be rule out. The local industry and farmers are at a loss if the use of

powdered milk by the informal channels also becomes a norm.

The producers and consumers then need to be educated on these standards. At the farm

end, this will address the level of distrust between producers and small dhodhis, as

190

illustrated in the Kasur-Lahore and Okara-Lahore chains. At the retail end, it will give

confidence to the consumers who need to be made aware of the nutritional virtues of milk

and the losses associated with dilution of the product they are purchasing, protein in

particular.

There is another issue of price linked to the quality and quantity. The control of farm gate

prices by the formal processors due to the oligopsonistic market structure needs to be

addressed. Antitrust laws are required to address this situation.

In his concluding remarks on the challenges facing the industry Small Dhodhi from

Kasur-Lahore chain said, “...firstly better farm gate prices have to be given by the

factories54”, so the power and practices of large processors have to be addressed. He

further said, “...and secondly processors and small players [dhodhis] have to be brought

at a level playing field. The companies are buying [same] milk [as informal chains] at

6%fat and selling at 3% fat for 88 Rupees per litre [that is almost double the price of fresh,

unpackaged milk supplied by this chain]...the packaged milk is three times what is

collected; that is one litre is made into three litres...”. This highlights the need for a level

playing field for both sectors. This is a policy issue that has to be addressed for the local

industry to flourish.

The Medium Dhodhi of the Okara-Lahore chain stated that,“ [there has to be] more

factories55 that buy milk...at the moment we have less buyers... the existing ones have less

production capacity and don’t buy enough milk...they rely on the powdered milk

...[formal processors] store milk in winter and sell that in summer....presently when we

have more milk supply [in winter] we don’t have enough buyers ”. This statement points

to the dominating power held by the large processors.

54 formal milk processors who control farm gate prices 55 Formal processors

191

Furthermore, the Small Dhodhi of the Pakpattan-Lahore chain concluded that: “...the milk

in our area is good...our Government should care for its own producers. It should stop the

purchase of powdered milk from abroad which makes our milk worthless...Pakistani

producers should be taken care of...they [farmers] work [hard] day and night”.

Importation of cheap powdered milk not only suppresses the local prices but distorts

competition in favour of formal processors”. Along the same line, Large Dhodhi of the

Pakpattan-Lahore chain stated, “The importation of powdered milk spoils the market and

price and should be stopped. Nestlé and Engro for example...were not buying milk and

the rate went down by 5 Rs”.

These statements make it clear that the importation of cheap powdered milk not only

suppresses the local prices but distorts competition in favour of formal processors. It has

to be either totally banned or strict import quotas attracting high duties have to be set, to

allow the domestic industry to come out of its infancy.

The producers are unaware of their costs of production and their productivity per animal

is quite low56 despite a high capital invested: this is an extremely inefficient use of

resources. Producers will have to understand their costs and adopt production practices

that earn profits in a complex mixed crop-livestock farming system. Milk production has

to meet peak summer demand, which will happen with the correct pricing signals

appearing from the retail end and passing to the producers57. The existing retail milk price

setting practice by the government authorities is counterproductive. These prices are

56 Kasur-Lahore chains’ Producer 1 held 14 dairy animals. He was producing only 7.7 litres of milk per day from only one lactating

cow. Okara-Lahore chain’s Producer1 held 16 dairy animals. He was producing only 23 litres of milk per day from four lactating buffaloes

and cows that averages 5.75litres a day.

Similarly, Papattan-Lahore chain’s Producer1 held 24 dairy animals. He was producing only 22 kgs of milk per day from 3 lactating buffaloes and one cow that averaged 5.5kg per animal per day. 57 In addition to price issue, the Punjabi months overlap with the Gregorian calendar (Table 35, Table 39 and Table 44 of the thesis).

The local farmers use the traditional Punjabi calendar whereas various extension messages developed by the government and other projects that aim at increasing productivity use Gregorian calendar months. This inconsistency needs to be addressed to make

communication with farmers more effective.

192

influenced by some powerful large dhodhis who also operate as retailers and are known

to supply milk to the formal processors (Competition Commission of Pakistan, 2012). If

the policy goal is rural poverty alleviation and better nutrition for consumers, the milk

retail pricing mechanism will have to account for the costs of milk production and all

other costs associated with bringing the product to the final market.

The Pakpattan-Lahore chain, on the contrary, is challenged, however, by a market

dominated by the supply of low cost, inferior quality milk to their retailers. Large Dhodhi

cum Retailer1 in this chain stated, “We are trying to collect better quality milk. We are

the ones facing most trouble as we try to maintain better quality... [a shop nearby selling

milk at] 33Rs/kg...and people are buying. We have invested millions and it is not really

profitable and customers do not realize it. Around 30 shops in this area and the customer

base is so much segmented. Although the customer is happy with our quality but is also

comparing it with the very low prices prevailing in the market.” The statements points to

the need for minimum quality standards and price.

The milk value chains, their operations and interactions between formal and informal

sectors are complex. This research has highlighted some of the challenges facing the dairy

industry of Pakistan. There is a need to build on this research and further understand cost

of milk production in different regions of Pakistan; cost associated with bringing milk to

the final markets and time series price data to further study forces that influence milk

prices. The role of the local processor in controlling milk pricing deserves further

investigation. This study is expected to be the foundation stone for key future work to

understand and support informal milk value chains that are of immense importance to

Pakistani farmers, middlemen, retailers and consumers.

193

Chapter 9. Conclusion:

The key research question58 explored in this research was “How do we adapt traditional

value chains in a developing country to address the important national challenges of

sustaining profitable smallholder dairy farm operations and at the same time providing

high quality milk for final consumers?” This key question has not been answered as a

whole but in parts through the sub-questions, which are as follows:


farmers in a mixed crop-livestock farming system? (Chapters 3 & 4)

Q2. How does the fresh unpackaged informal rural-urban value chain system function in

the Pakistani context? (Chapters 2, 5,6, 8 & Appendices F, G, H, I)


7)

Q4. Can this value chain analysis assist in addressing policy or strategy issues of public

concern? (Chapter 9 coalesces all studies)

A particular focus of the analysis was the impact on the poor and whether the industry

can be considered to be pro-poor. At the heart of this research was the structure of the

Pakistani dairy industry and the impact of this structure on the performance of the industry

with a particular focus on the performance of sub-groups of the industry that is poor.

The milk value chain actors studied from production through to final consumption

represent the following participants:

58 The research has generated sufficient information to simulate alternative value chain models upon which interventions to enhance

market efficiencies in developing countries could be based. This is an area that can be explored further.

The characterisation of existing value chains have enabled simulations of proposed interventions. These can be tested and developed more in-depth by applying to other studies of similar nature.

194

8.8 million Smallholder dairy farmer households. Eighty-nine percent of these

farm households have less than 12.5 acres of land and 97% have less than 15

animals.

Several hundred thousand middle men, colloquially known as dhodhis (31%

market share), who deal in relatively small quantities of fresh milk compared to

the formal processors ( > 5% market share & rest of the milk consumed at source)

Estimated 28 million consumer households, 60% of them live on less than US$ 2

a day with rising urban population. An average household spends 45% of the total

household budget on food and 11% on milk and milk products (9.3% on fresh

milk). Milk is an important source of calories (11%) and protein (19%) for

Pakistani families.

The participants illustrate that many of them are poor, but the involvement of the poor in

an activity does not demonstrate that the activity is pro-poor. The following paragraphs

summarise the outcome this research and a few possible future research areas.


farmers in a mixed crop-livestock farming system?

The first question was initially answered through whole farm economic analysis. The

farm economic analysis for the irrigated region, from which the three detailed case study

chains originated, revealed that the smallholder dairy producers are not generating any

economic profits from milk, making milk production as a single activity unviable for the

producers. The present dairy industry structure with a huge smallholder base appeared to

be unsustainable if we focus on milk as the only output from dairy production. There were

other reasons, however for producing milk, which were not purely economic. The

questions that then arise are that if dairy production is unprofitable then firstly why are

195

the smallholders producing and selling milk and secondly why are they involved in the

informal chains? These questions are examined in the next section.

Smallholder producers raise dairy animals to secure pure milk for home consumption in

the absence of the availability of quality milk. These animals are also a source of pride

and social status in the rural communities. In a complex mixed farming system within

village communities, farmers have little idea of the level and sources of profitability.

From a purely monetary aspect, however, in the long-run, there has to be a combination

of productivity increase and scaled up economies and perhaps commercial farming

focused on the specialised production of milk, meat, fodders or crops to generate

commercially viable farm enterprises.

The research pointed to the further future research need of dairy industry and agriculture

as a whole being benchmarked to measure the farm financial performance in different

regions of Pakistan. The producers need to understand and know their costs and

profitability to make more informed decisions.

Q2. How does the fresh, unpackaged informal rural-urban value chain system function in

the Pakistani context?

The current structure of the dairy industry, with a huge smallholder production base,

makes the milk collection and distribution service extended by middlemen, indispensable.

The very nature of milk as a commodity, which is diluted to increase profit margins,

allows markets to function. There is no market failure, albeit inefficient markets in terms

of social welfare gains.

These fresh milk value chains handle 31% of production as the formal sector share is less

than 5% and the rest is consumed domestically. The majority of milk purchased by the

formal sector is also obtained from mid-sized milk collectors in the informal chains.

196

These informal fresh chains are not ideal but still offered relatively better value for

money. The quality of milk, does, however, remain a concern and Pakistan, being a higher

consumption country relative to other developing countries (Government of Pakistan,

2011; Hemme & Otte, 2010), it has to be addressed and improved.

The three informal rural-urban chains studied in the irrigated region provided evidence to

explain why small-scale dairy farmers continue to operate despite losing money on their

milk production operations. The three chains are highly competitive because of the

following factors:

relatively low operational costs compared to formal sector

minimal capital investment

product differentiation in the retail marketplace

nature of human relationships

governance of finances at various levels of the chain

The chains are held together because of the benefits derived from the various partners

through the financing system in the chain. The chains provide regular cash flows to the

producers upstream, interest-free loans to dhodhis operating in the middle tier and credit

downstream to the retailers. These financing mechanisms lock-in the two parties involved

in a transaction along the chain. Thus tangible incentives cement the chain actors together

despite low margins and inequitable income distribution.

Being part of the informal chain confers many advantages on the small producer with

those advantages being:

Ability to access interest-free loans / cash advances offered by the chain dhodhis.

In effect, these chains offer a line of credit to farmers, which is their regular stream

197

of income. In contrast, formal processors make a delayed payment for the milk

purchased and also do not offer any initial cash advances, which are so important

to the sustainability of smallholder dairy producers.

Operators in the informal chain purchase on the basis of fat content and reward

the farmers for a higher butterfat, generally associated with buffalo milk. On the

other hand, the quality standards set by the formal processors are not clearly

understood by the small producers and the producers do not see any visible

incentive: thus, there is hesitation in dealing with them.

Farming is labour intensive and time-consuming. The acquisition of milk from the

farm doorstep by dhodhis saves the farmer both time and money. The formal

channels offer similar or slightly higher prices to the producers, compared to

informal chains’ dhodhis. The convenience of product collection provided by

dhodhis and the additional financial services, however, outweighs any slight

improvement in returns from a higher milk price. The formal sector also does not

have as extensive a collection network as the informal chains.

The small dhodhi collecting milk directly from producers, supplies them feed

supplements regularly or on demand.

The informal chains can further be characterised as “pro-poor” because they generate

large income and employment opportunities for many families operating at or just above

the poverty line. The three case study chains generated an estimated 4,872 employment

opportunities from farm to market.

Each chain had its own quality and quantity standards, which assists in generating profits.

The margins across the chains are tight, but the chain intermediaries make money by

diluting milk with ice or water. Similarly, the quantity units varied at different tiers and

across the three informal case study chains. The local unit, the gadvi along with kg and

198

litre were being used, and each weighed differently. Milk is procured in one unit and sold

in another. As a result of these changing volume measures, both producers and consumers

are financial losers. The variation of the unit is possibly due to the social acceptance of

these practices by the producer and lack of awareness consumers.


7)

The Pakistani consumers prefer fresh milk and can buy it at a lower price if it is supplied

by the informal chains. This milk is approximately half the price of packaged ultra-heat

treated (UHT) packaged long life milk.

Although consumers acquire cheaper milk from informal chains, they are unaware of

nutritional virtues of fresh milk. Nor are they aware of the system of measuring volumes

in the commercial marketplace. Fat in milk is the attribute most valued by these

consumers. There is little concern for health and safety, irrespective of socioeconomic

status.

The measurement units for milk varied greatly from shop to shop. The consumer naivety

facilitates the malpractice of selling milk in variable volumes to enhance profit margins

in retail shops. Milk adulteration, mostly through the addition of water along the chains

is known by the consumers but a compromise they are prepared to accept.

These findings merit raising awareness of consumers on the nutritional virtues of

untainted milk with clear labelling from both formal and informal channels as well as on

the standard units of milk volume sales.

Q4. Identification of and addressing policy issues of public concern based on this value

chain analysis?

199

The challenges that the dairy industry faces cannot be addressed by separating the

informal and formal channels of milk collection and supply to the final consumer as the

two channels are deeply integrated.

An important policy intervention outcome from this research is the need for uniform

quality and quantity standards and a balanced pricing mechanism across the industry.

The formal processors and the larger informal chain operator studied, for example,

measure milk solids and solids not fat, whereas the other two case study chains were only

testing butterfat content in milk. Dilution is a common practice at different tiers of the

informal chains, where water or ice is added to milk to gain financial advantage. The large

dhodhis argued that the formal processors also do the same when they standardise the

milk to 3.5 fat, and they also use powdered milk. The fat, protein and lactose of milk

along the three chains studied (Aslam, 2015) was not as bad as generally perceived by the

general public and projected by other research studies. The fat59 percentage was almost

at par with the packaged milk sold by the formal processors (Table 24).

The identification of current price setting mechanisms is an important policy requiring

attention. The current mechanism does not transmit the right market signals from final

market to the producer.

Farm gate prices are influenced and controlled by the formal processors who hold more

buying power because of their oligopoly market structure. There has to be an antitrust law

in place to address these monopsony practices.

Furthermore, importation of cheap powdered milk not only suppresses the local prices

but distorts competition in favour of the formal processors. It has to be either totally

banned or strict import quotas with high tariff rates have to be set, if the importation is

unavoidable to meet domestic demands. This may be necessary until the Pakistani

59 Although not mentioned on the packaging in Pakistan but understood to be 3.5% based on the standard energy corrected milk (ECM) formula; albeit using powdered milk

200

industry is able to meet the ever-increasing volume demand of consumers. The viability

of imported powdered milk and its impact on the industry and local milk prices does,

however, require further research.

The retail milk prices are set by the government as a loose benchmark, but they are

likewise influenced by some powerful large dhodhis who also operate as retailers and are

also known to supply milk to the formal chain. The final retail milk prices though vary a

great deal in the final market.

In future, perhaps a consultation platform is needed to advocate the case of farmers,

consumers and dhodhis alike. As identified through this research, one of the key elements

of the domestic milk value chains is a flow of goods and services up and down the chain.

These chains, therefore, offer a huge potential to increase the productivity of milk at the

farm. One possible area, for example, is the use of these chain networks of dhodhis to

distribute animal husbandry extension messages/ information and products that would

increase productivity. More importantly, these informal dhodhi networks already have a

financial dimension that offers a possibility for additional microfinance facilities directed

at increasing productivity.

Dhodhis are business people. They will need the appropriate incentives to implement

productivity-enhancing policy. Incentives could be in the form of increased profits from

handling larger volumes of milk up the chain. There may also be incentives attached to

providing additional animal husbandry products and information down the chain and for

providing microfinance if that is feasible.

In terms of policy development, the networks of value chains appear to be suited to

trialling productivity-enhancing policy interventions on a small scale to see which ones

work in practice.

201

There has to be a consultative process to set quality and quantity standards and a pricing

mechanism along the chains while ensuring that the formal sector does not receive an

undue advantage. In addition being businessmen, these dhodhis are part of the Pakistani

society and if their trust is gained and they are convinced of the need to ensure provision

of better quality product to supply our future generations, it is assumed they would be

willing to help.

202

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APPENDICES

Chapter 3: Appendix A (Details of Equations / Formulas used):

The following equations for this analysis have been applied to the Pakistani mixed farming system scenario

but are based on Kay et al. (2008) and Malcolm et al. (2005):

Crop gross margin, GMC, has been calculated as follows:

GMC = GIC − VCC

where GIC is crop gross income and VCC is crop variable cost of production that includes land preparation

and nursery costs where applicable, seed and sowing, irrigation, chemical fertilisers and farmyard manure

costs, pesticides and sprays, and harvesting costs.

The cost of manual labour has been excluded from all enterprise gross margins and assumed to be fixed

cost.

Green fodder gross margin, GMF, on the farm, has been calculated by making GIF that is fodder gross

income, equal to VCF variable costs of fodders, as all green fodders are assumed to be produced and

consumed on the farm and are charged to livestock enterprise. The fodder variable cost components are

assumed to be the same as those for crops.

Whole livestock activity gross margin, GMWLA, on the farm has been calculated as follows:

http://aslpdairy.pk/en/

216

GMWLA = GIWLA − TVCWLA

where GMWLA is whole livestock activity (milk and meat) gross margin, GIWLA is gross income from the

livestock activity (including milk plus livestock trading income), and TVCWLA is the total variable costs of

feed (green fodders, concentrates and roughages), health and breeding.

Total variable costs for whole livestock activity, TVCWLA, on the farm has been calculated as follows:

TVCWLA = VCH + VCF + VCB

where VCH is actual health costs, VCF is the cost of all the feed fed and recorded by the survey data. It has

been calculated as cost per kg of green fodder estimated from gross margin per acre of fodder grown at

the farm. Roughages cost per kg is estimated from a value per kg of rice and wheat straw produced from

these crops. Concentrates per kg feed cost are based on an estimated market price. VCB is an estimate of

breeding costs.

Gross margin per Rupee invested in livestock, GM per RsL, on the farm has been calculated as follows:

GM per RsL =GM L

(𝐴𝑉𝐿 + 𝑉𝐿𝐹)

where GML is whole livestock activity gross margin, AVL is the average value of livestock obtained from

taking an average of opening and closing value estimates, and VLF is the value of land allocated to produce

green fodders for the consumption of livestock.

Milk gross margin, GMMk, on the farm has been calculated as follows:

GMMk = GIMk − VCMk

where GIMk is gross milk income. GIMk is calculated as follows:

GIMk = (HMk + SMk + 5%CMk) PMk

where HMk is consumption of milk by household, SMk is milk sales, CMk is 5% milk going to suckling calves,

and PMk is farm gate price of milk recorded by the data, and VCMk is variable cost allocated to the milk

enterprise, including feed (green fodders, concentrates and roughages), health and breeding costs.

Variable cost of milk production, VCMk, on the farm has been calculated as follows:

217

VCMk = TVCWLA ( FL

TL

)

where TVCWLA is total variable costs for whole livestock activity, that is milk and meat production; FL is

number of female livestock in the whole herd and TL is total livestock number for each farm.

Milk animal gross margin, GMMkA, on the farm has been calculated as follows:

GMMkA =GMMk

NMkA

where GMMk is gross margin from milk and NMkA is number of milking animals.

Meat gross margin, GMMt, on the farm has been calculated as follows:

GMMt = TIL − VCMt

where GIMt is meat gross income obtained as livestock trading income TIL and VCMt is variable cost

allocated to meat enterprise and includes feed (green fodders, concentrates and roughages), health and

breeding costs.

Livestock trading Income, TIL, on the farm, has been calculated as follows:

TIL = CVL − OPL + ILS − ELP

where CVL is closing value of livestock, OPL is opening value of livestock; ILS is Rupees of income from

livestock sold, and ELP is total Rupee value of livestock purchased.

Variable cost of meat production, VCMt, on the farm has been calculated as follows:

VCMt = TVCWLA (ML

TL

)

where TVCWLA is total variable costs of livestock for meat and milk production, ML is number of male

livestock in the whole herd, and TL is total livestock number for each farm.

Whole farm gross margin, GMWF, on the farm has been calculated as follows:

GMWF = GMC&𝐹 + GMWLA

where GMC&F is gross margin for crops and fodder grown on the farm and GMWLA is whole livestock activity

gross margin.

218

Total fixed cost, TFCWF, for the whole farm has been equated to LWF , that is, the cost of whole farm manual

labour allocated to livestock, fodder and crop enterprises.

Fixed cost for crops, TFCC, for other crops cultivated by each farm has been calculated as follows:

TFCC = TFCTA (TCA

TTA

)

where TFCTA is total fixed cost for total acres cultivated, TCA is total cultivated acres for crops and TTA is

total cultivated acres.

Fixed cost for fodders, TFCF, for green fodders cultivated by each farm has been calculated as follows:

TFCF = TFCTA (TFA

TTA

)

where TFCTA is total fixed cost for total acres cultivated, TFA is total cultivated acres for green fodders and

TTA is total cultivated acres

Total fixed cost for milk production, TFCMk, for the farm has been calculated as follows:

TFCMk = TFCWLA (FL

TL

) + TFCF (FL

TL

)

where TFCWLA is total fixed cost for whole livestock activity, FL is total estimated female livestock and TL

is total livestock owned. TFCF is total fixed cost of green fodder cultivation allocated to milk enterprise.

Total fixed cost for meat production, TFCMt, for the farm has been calculated as follows:

TFCMt = TFCWLA (ML

TL

) + TFCF (ML

TL

)

where TFCWLA is total fixed cost for whole livestock activity, ML is total estimated male livestock and TL is

total livestock owned. TFCF is total fixed cost of green fodder cultivation allocated to meat enterprise.

Milk average variable cost per kilogram, AVCMk/kg, for milk production has been calculated as follows:

AVCMk/kg =TVCMk

OMk

where TVCMk is total variable of milk production and OMk is milk production.

219

Milk average fixed cost per kilogram, AFCMk/kg is:

AFCMk/kg =TFCMk

OMk

where TFCMk is total fixed cost of milk production and OMk is milk production.

Milk total cost per kilogramme,TCMk/kg, is:

TCMk/kg = AFCMk/kg + AVCMk/kg

where AFCMk is average fixed cost of milk production and AVCMk is average variable cost of milk

production

Profit for milk production, πMk, is calculated as follows:

πMk = TRMk − TCMk

where TRMk is total revenue from milk production and TCMk is total cost of milk production.

An increase in milk production, Mkkg, by % increase in milk production each group based on the

regression analysis calculated as follows:

↑ Mkkg = (OMk )%age increase based on regression analysis + OMk

where OMk is actual milk production per farm from primary survey data. The percentage increase is based

on widely acknowledged understanding that improved nutritional management, supply of higher quality

green feed and simple interventions, such as ad libitum access to water, can substantially increase milk

production (Burki et al., 2004; S. I. Shah et al., 2005; Teufel, 2007).

An increase in total variable cost of milk production, TVCMk, by 30% calculated as follows:

↑ TVCMk = (TVCMk )30% + TVCMk

where TVCMk is actual total variable cost of milk production from primary survey data.

Increased milk average variable cost per kilogram, AVCMk/kg, after 50% increase in milk production and

30% variable cost is calculated as follows:

220

↑ AVCMk/kg = ↑ TVCMk

↑ OMk

where TVCMk is increased total variable cost of milk production and OMk is increased milk production.

Increased milk total cost per kilogram, TCMk/kg, after increase is calculated as follows:

↑ TCMk/kg = ↑ AVCMk/kg + AFCMk/kg

where AVCMk/kg is increased average variable cost of milk production and AFCMk/kg is average fixed cost of

milk production that remains unchanged.

Milk marginal cost per kilogram, MCMk/kg ,after increase in productivity is as follows:

MCMk/kg =∆TVCMk

∆OMk

where ΔTVCMk is change in total variable cost of milk production and ΔOMk is change in milk production.

Increased gross Income from milk production, GIMkΔ, after increase is calculated as follows:

↑ GIMk∆ =↑ OMk × PMk

where OMk is total milk output after increase and PMk is price per kg of milk

Increased total cost of milk production, (TCMkΔ), after increases is calculated as follows:

TCMk∆ = (TCMk/kg × Acutal OMk) + ( ↑ OMk × MCMk)

where OMk is total milk output or production and PMk is price per kg of milk.

Profit from milk production, πMk, after the increases / changes is calculated as follows:

πMk∆ = TRMk − TCMk

where TRMk is total revenue from milk production after changes and TCMk is total of milk production after

changes.

My original model applied (Malcolm et al., 2005) to this analysis to estimate operating and net profits

and return on assets is as follows:

𝐺𝐼 − 𝑇𝑉𝐶 = 𝑇𝐺𝑀

and

𝑇𝐺𝑀 − 𝑂𝐻 = 𝑂𝑃

221

where GI is gross income, TVC is total variable costs, OH is total overhead or fixed costs, TGM is total

gross

margin, OP is operating profit. Operating profit is the return on all the capital used in the business, and is

the

reward to all who have contributed the capital used in the business.

𝑂𝑃 − 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑝𝑎𝑖𝑑 𝑡𝑜 𝑐𝑟𝑒𝑑𝑖𝑡𝑜𝑟𝑠 − 𝑙𝑒𝑎𝑠𝑒 𝑐𝑜𝑠𝑡𝑠 = 𝑁𝑒𝑡 𝐹𝑎𝑟𝑚 𝑃𝑟𝑜𝑓𝑖𝑡

Interest is paid out of operating profit to creditors. Operating profit minus interest is the reward to the

farmer’s own capital. This is called net farm income or net profit. Lease payments are also a financing

expense and a reward to the owners of the assets that are being leased.

Profit does not indicate economic efficiency until it is related to the amount of capital used to produce it,

expressed as the percentage return on total capital (operating profit/total capital). This indicates the rate of

earning of the total capital relative to the rate of earning of that capital if it were employed in some other

income-producing activity.

𝑅𝑒𝑡𝑢𝑟𝑛 𝑡𝑜 𝑎𝑠𝑠𝑒𝑡𝑠 =𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑝𝑟𝑜𝑓𝑖𝑡𝑠

𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑡𝑜𝑡𝑎𝑙 𝑐𝑎𝑝𝑖𝑡𝑎𝑙 (𝑊𝐼𝑊𝑂) × 100

For this analysis due to data limitations, to estimate operating and net profits and return on assets,

assumptions have been made on the following basis:

The formula for profit is

𝑃𝑟𝑜𝑓𝑖𝑡(𝜋) = 𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑣𝑒𝑛𝑢𝑒 (𝑇𝑅) − 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡 (𝑇𝐶)

From the equation above, Total Cost (TC) is the sum of total variable costs and total fixed costs.

𝑇𝑜𝑡𝑎𝑙 𝑐𝑜𝑠𝑡(𝑇𝐶) = 𝑇𝑜𝑡𝑎𝑙 variable costs (𝑇𝑉𝐶) + 𝑇𝑜𝑡𝑎𝑙 fixed c𝑜𝑠𝑡𝑠 (𝑇𝐹𝐶)

a. Variable costs (also called direct costs, explicit (E) or out of pocket costs) vary with the level of

production. These costs incur in the current period per unit of output, and the manager has control

over them in the short run. Examples include costs of seeds, fertilizers, pesticides, contract labour…

b. Fixed costs (also called overhead and include both implicit (I) & explicit (E) costs) do not vary with

the level of production. These costs are associated with owning a fixed input such as land or labour.

Examples include:

i. Explicit (E) costs: interest on farm mortgages, property taxes, insurance…

ii. Implicit (I) costs: potential income from employment opportunities foregone and rental rate for

owned assets

Economic profit includes both explicit and implicit costs:

𝐸𝑐𝑜𝑛𝑜𝑚𝑖𝑐 𝑃𝑟𝑜𝑓𝑖𝑡(𝜋𝐸) = 𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑣𝑒𝑛𝑢𝑒 (𝑇𝑅) − Total 𝐶𝑜𝑠𝑡 (𝑇𝐶𝐼+𝐸)

Accounting profit only includes explicit costs:

𝐴𝑐𝑐𝑜𝑢𝑛𝑡𝑖𝑛𝑔 𝑃𝑟𝑜𝑓𝑖𝑡(𝜋𝐴) = 𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑣𝑒𝑛𝑢𝑒 (𝑇𝑅) − Total 𝐶𝑜𝑠𝑡 (𝑇𝐶𝐸)

For this analysis:

Operating Profit (OPWF ) for the whole farm is calculated by assuming all farm household labour costs

(variable and fixed) to be explicit (i.e. not opportunity costs).

222

Operating Profit, OPWF, for the whole farm, has been calculated as follows:

OPWF = GMWF − TFCWF

where GMWF is gross margin for the whole farm and TFCWF is total fixed cost for the whole farm which is

labour cost.

TFCWF is the cost of whole farm manual labour allocated to livestock, fodder and crop enterprises,

assumed to be provided by the farmer owner and / or his household. The manual and casual labour costs

are excluded from all enterprise GM estimates. The farmer owner also provides the managerial labour.

There is no other fixed cost.

The managerial labour provided by the farmer is implicit cost. The casual or contractual labour hired by

farmer/farm household is both explicit & implicit as the casual labour is often hired in peak sowing and

harvest

seasons and for taking care of livestock as well. Given the low opportunity cost of farm household labour,

the

implicit labour costs should be zero. However, the analysis assumes that these costs are being paid that is

explicit while calculating operating profits.

Similarly, Net Profit (NPWF) for the whole farm is calculated by applying an annual interest

cost on the value of land and livestock utilized as key farm assets (their opportunity

cost).

Net Profit, NPWF, for the whole farm, has been calculated as follows:

NPWF = OPWF − FCWF

where OPWF is operating profit for the whole farm and FCWF is finance cost for the whole farm, which is

estimated at 9% of the value of land and livestock per annum. The percentage on finance costs is based on

the average national savings rate and that used by the government of Punjab in its crop gross margin

estimates for the fiscal year 2008-09 (Government of the Punjab, 2006-13; National Savings Organization,

2000).

Total value of farm assets, VTFA, for the whole farm, that is land and livestock, is assumed to be owned by

the farmer and calculated as follows:

VTFA = VLd + VLs

where VLd is the market value of land, and VLs is the value of livestock. VLs is calculated as follows:

VLS =(OVLs + CV

Ls)

2

223

where OVLs is opening value of livestock and CVLs is the closing value of livestock.

Return on Assets, RoAWF, for the whole farm has been calculated as follows:

RoAWF = (OPWF

VWFA

) 100

where OPWF is operating profit for the whole farm and VCWFA is the average value of whole farm assets.

224

Chapter 3: Appendix B (Key Assumptions):

The questionnaire used to collect data from the two-year longitudinal survey by Australian Centre for

International Agricultural Research (ACIAR) funded project entitled “Improving dairy production in

Pakistan through improved extension services.”

Dairy Farmer Record book

Agriculture Sector Linkages Program, Pakistan-Australian Dairy Improvement Project

Basic Information:

Farmer number: Farmer’s name and father’s name

Address: Phone number:

Agriculture Information

Total area cultivated__________________

Land owned __________________ Land leased__________________

Important Crops/Fodders

Khariff area


Rabi area

Dairy Animal Information

Buffaloes

Number of buffaloes

Number of buffalo heifers

Male calves

Female calves

Bulls (Breeding)

Cows

Number of cows

Number of cow-heifers

Male calves

Female calves

Bulls (Breeding)

Total number of animals __________________

Month (Weekly)

Milk Production

Animal identity number Morning (kg) Evening (kg) Total (kg)

Buffalo

Cow

Reproduction information (Weekly)

Animal

identity

number

Dry Pregnant Heat Disease AI Natural Other

Buffalo



225

Cow

Nutrition (Daily)

Details Green Fodders (kg) Straws Concentrates

Type

Quantity

Health (Weekly)

Details Vaccination Deworming Medicine Other

Type

Number of

Animals

Cost

Marketing (Weekly)

Details Quantity Price (Rs) Comments

Milk

Animals

Other

Management (Weekly)

Details Quantity Cost (Rs) Comments

Water

Animals

purchased

Buildings

226

B3.1 MAJOR CROPS grown in the two districts extracted from the data were wheat

(Triticum spp.), rice (Oryza sativa), cotton (genus Gossypium) and sugarcane (Saccharum

officinarum L.). In the Bhakkar district two other major crops, moong lentil (Vigna

radiata) and chickpeas (Cicer arietinum) were also taken into account. All other minor

crops such as potatoes, tomatoes, onions, etc. were treated as a single enterprise and

summed up as vegetable/horticulture crops.

The average yield for the fiscal year 2008-09 varied for wheat, rice, sugarcane and cotton

in the two districts and figures were taken from Punjab Agriculture Department’s final

estimates (Government of the Punjab, 2011d). Yields for moong lentil and chickpea in

Bhakkar were based on district-wide estimates by the Punjab government (Government

of the Punjab, 2011b, 2011c). Yield estimates of vegetable/horticulture category were

based on the average of Punjab government’s final summer and winter estimates,

differentiated by taking a 5% lower yield for rainfed Bhakkar due to its semi-arid climate,

which also conforms with major crop actual district wise estimates (Government of the

Punjab, 2011d).

Market prices: Market prices for wheat, rice and maize were the average of June 2008

and 2009 prices (Government of the Punjab, 2009). The price of sugarcane was taken as

an average of reported price for the season (Baig & Bashir, 2008; Elahi, 2008). The price

of cotton was an average of 2008-09 monthly prices quoted by APTMA (All Pakistan

Textile Mills Association, 2013). Price estimates for vegetable/horticulture crop category

were based on the average of June 2008 and 2009 market price of potato, tomato and

onion crops grown as main vegetable crops in Okara. For Bhakkar, since the prices were

unavailable. Therefore prices for the closet situated Sargodha district were taken instead

(Government of the Punjab, 2009).

227

Variable cost of production estimates for major crops of wheat, rice, sugarcane, cotton,

maize and averages for horticulture/vegetable crops for the Pakistani fiscal year 2008-09

were adopted from Punjab’s government estimated costs and assumed to be same for the

two districts due to lack of any credible sources to differentiate (Government of the

Punjab, 2006-13). The gross margin estimates for moong lentil and chickpea were based

on expert opinion (S. S. Khan, 2012b).

B3.2 MAJOR FODDERS were berseem (Trifolium alexandrinum), maize (Zea mays),

lucerne (Medicago sativa), millet (Pennisetum typhoides), sorghum (Sorghum bicolor)

and sugarcane tops (Saccharum officinarum L.) (Top one foot or one-sixth of the total

yield) allocated as fodder. Millet, sorghum and maize were taken as fodder crops only.

Smaller land allocation to other fodders grown was categorised as fodder mix.

Average yield estimates for all the green fodders was based on averages of Punjab

Agriculture department’s estimates (Government of the Punjab, 2013), and expert opinion

from Pakistan (S. S. Khan, 2012b; Zahid, May 2011).

Price for green fodder(s) per kilogramme was taken as the total variable cost of

production for each fodder divided by average yields.

Variable cost of production for fodders was based on expert opinion from Pakistan (S.

S. Khan, 2012b; Zahid, May 2011).

B3.3 LIVESTOCK PRODUCTION (MILK & MEAT): The average milk production

per buffalo and / or cow and the number of milking animals per farm were extracted from

the survey data, and 5% output was added for that going to suckling calves (Farooq, 2012,

2013). The data also distinguished buffalo and cattle and classed them by sex and age.

Female animal were allocated to milk and male to meat enterprise, while one fourth of

228

milking buffaloes and cows that are culled for meat were allocated to meat enterprise

(Wynn et al., 2006). Average live weights (S. S. Khan, 2012b; Teufel, 2007) were

assigned to each class of animal to calculate annual meat production. Livestock

reconciliation gave an animal count at the closing of the year that gave a closing asset

value of livestock.

Livestock (milk, meat and per animal) Prices: The farm gate price of milk sold was

recorded by the survey. For meat, the average market beef price for the fiscal year 2008-

09 in Punjab was used to estimate the production value (Government of the Punjab,

2011a, 2011e).

Variable cost of production: The three variable costs for rearing livestock were 1) feed

that is green fodders, roughages (mainly rice and wheat straw), concentrates purchased

(mainly compound feed, cotton seed cake and wheat bran), 2) health care and 3)

breeding costs.

The total feed cost was calculated by assigning a Rupee value to each kilogramme of feed

fed to livestock that was recorded by the primary data along with health and breeding

costs.

B3.4 FIXED OR OVERHEAD COSTS: All the manual labour was taken as fixed cost

for all the farm enterprises. Crop and fodder manual labour estimates60 were excluded

from gross margin estimates and brought in later as fixed costs.

Similarly, livestock labour was based on estimates61 from a study of small dairy holders

in Punjab (Teufel, 2007) and minimum wage rate for the fiscal year 2008-2009 was

60 All manual labour costs, that is man hours for the estimation of per acre gross margin budgets, such as labour for bund making,

sowing, canal irrigation and tube well, fertilizer and chemical application, harvesting costs (a range of operations that varied with the

crops) were taken as fixed costs i.e. assuming that these functions are being performed by the owner-operator. 61 For this analysis the livestock classes were as follows:

229

determined from the government of Punjab production costs (Government of the Punjab,

2006-13). Operating profit, for the whole farm, was estimated by including whole farm

labour costs for crop, fodder and livestock (milk and meat) enterprises that had earlier

been excluded from GM estimates.

Net farm profit for the whole farm enterprise was estimated by applying an annual

interest cost on the value of land and livestock assets, which were assumed to be the only

major farm fixed assets owned by the farmer(s) and utilised as farmer’s equity for

production activities. The annual interest rate was subtracted from the operating profit.

The land prices per acre were recorded by the data, and missing values were estimated

taking averages of village data. For livestock, an assumed market value was assigned to

each class of animal in the herd, based on consultation with ACIAR dairy project staff

and expert opinion from Pakistan (S. S. Khan, 2012b; Wynn, 2010; Wynn, McGill,

Warriach, & Agriculture Sector Linkages Program (ASLP). Pakistan, n.d). The interest

was based on the long-term average national savings rate of 9%, and that used the

Class of cattle

aTotal

Adult

Cows

aTotal

Adult

Buffalo

Total

Heifer

s

Male

Calves

Femal

e

Calves

bCattl

e

Bulls

Total

B

Heifer

s

Male

B

Calve

s

Femal

e B

Calves

bBuffa

lo

bulls

Labour

Requirements

(hr/hd/annum) 438 438 412 58 58 219 412 58 58 219

Labour Costs

(Rs/hd/annum) 10950 10950 10300 1450 1450 5475 10300 1450 1450 5475

Based on Teufel (2007), page 56 annual labour requirements of

i. average and high-yielding adult female buffalo are 412 hours & 464 hours respectively ii. heifer 438 hours and

iii. calf 58 hours

The same hours were allocate to heifer and calves to calculate annual labour requirements, apart from iv. Adult cowsa and buffaloesa, where an average of 412 & 464 hours i.e. 438 hours was estimated per annum as not all of

them were milking and it was not possible to distinguish between average and high yielding.

v. For both cattleb and buffalob bulls, 438 hrs was halved as these bulls do not require milking

Labour charges per day in 2008-09 were 200 Rs/day, which comes to 25Rs/hour. This amount was multiplied by the labour

requirements per animal per farm to obtain labour costs for livestock. –

For example, an average adult cow needs 438hr/hd/annum and so the cost of labour is as follows:

438×25=10950Rs/annum (3rd row and 2nd column of the table above)

230

government of Punjab in its crop gross margin estimates for the fiscal year 2008-09

(Government of the Punjab, 2011c; National Savings Organization, 2000).

231

Chapter 4: Appendix C (Details of Equations / Formulas used):

The following equations for this analysis have been adopted to the Pakistani mixed farming system scenario

but are based on Kay et al. (2008) and Malcolm et al. (2005)

Crop gross margin, GMC, has been calculated as follows:

GMC = GIC − VCC

where GIC is crop gross income and VCC is crop variable cost of production that includes land preparation

and nursery costs where applicable, seed and sowing, irrigation, chemical fertilisers and farmyard manure

costs, pesticides and sprays, and harvesting costs.

The cost of manual labour has been excluded from all enterprise gross margins and assumed to be fixed

cost.

Green fodder gross margin, GMF, on the farm, has been calculated by making GIF that is fodder gross

income, equal to VCF variable costs of fodders, as all green fodders are assumed to be produced and

consumed on the farm and are charged to livestock enterprise. The fodder variable cost components are

same as those for crops.

Whole livestock activity gross margin, GMWLA, on the farm has been calculated as follows:

GMWLA = GIWLA − TVCWLA

where GMWLA is whole livestock activity (milk and meat) gross margin, GIWLA is gross income from the

livestock activity (including milk plus livestock trading income) and TVCWLA is the total variable costs of

feed (green fodders, concentrates and roughages), health and breeding.

where, Total variable costs for whole livestock activity, TVCWLA, on the farm has been calculated as

follows:

TVCWLA = VCH + VCF + VCB

where VCH is actual health costs, VCF is cost of all the feed fed and recorded by the survey data. It has

been calculated as cost per kg of green fodder estimated from gross margin per acre of fodder grown at

the farm. Roughages cost per kg is estimated from value per kg of rice and wheat straw produced from

these crops. Concentrates per kg feed cost is based on an estimated market price. VCB is an estimate of

breeding costs.

232

Gross margin per Rupee invested in livestock, GM per RsL, on the farm has been calculated as follows:

GM per RsL =GM L

(𝐴𝑉𝐿 + 𝑉𝐿𝐹)

where GML is whole livestock activity gross margin, AVL is the average value of livestock obtained from

taking an average of opening and closing value estimates, and VLF is the value of land allocated to produce

green fodders for the consumption of livestock.

Milk gross margin, GMMk, on the farm has been calculated as follows:

GMMk = GIMk − VCMk

where GIMk is gross milk income. GIMk is calculated as follows:

GIMk = (HMk + SMk + 5%CMk) PMk

where HMk is consumption of milk by household, SMk is milk sales, CMk is 5% milk going to suckling calves,

and PMk is farm gate price of milk recorded by the data, and VCMk is variable cost allocated to the milk

enterprise, including feed (green fodders, concentrates and roughages), health and breeding costs.

where, Variable cost of milk production, VCMk, on the farm has been calculated as follows:

VCMk = TVCWLA ( FL

TL

)

where TVCWLA is total variable costs for whole livestock activity, that is milk and meat production; FL is

number of female livestock in the whole herd and TL is total livestock number for each farm.

Milk animal gross margin, GMMkA, on the farm has been calculated as follows:

GMMkA =GMMk

NMkA

where GMMk is gross margin from milk and NMkA is number of milking animals.

Meat gross margin, GMMt, on the farm has been calculated as follows:

GMMt = TIL − VCMt

233

where GIMt is meat gross income obtained as livestock trading income TIL and VCMt is variable cost

allocated to meat enterprise and includes feed (green fodders, concentrates and roughages), health and

breeding costs.

where, Livestock trading Income, TIL, on the farm has been calculated as follows:

TIL = CVL − OPL + ILS − ELP

where CVL is closing value of livestock, OPL is opening value of livestock, ILS is Rupees of income from

livestock sold and ELP is total Rupee value of livestock purchased.

and, Variable cost of meat production, VCMt, on the farm has been calculated as follows:

VCMt = TVCWLA (ML

TL

)

where TVCWLA is total variable costs of livestock for meat and milk production, ML is number of male

livestock in the whole herd, and TL is total livestock number for each farm.

Whole farm gross margin, GMWF, on the farm has been calculated as follows:

GMWF = GMC + GMWLA

where GMC is gross margin for crops grown on the farm and GMWLA is whole livestock activity gross

margin.

Total fixed cost, TFCWF, for the whole farm has been equated to LWF, that is, cost of whole farm manual

labour allocated to livestock, fodder and crop enterprises.

Fixed cost for crops, TFCC, for other crops cultivated by each farm has been calculated as follows:

TFCC = TFCTA (TCA

TTA

)

where TFCTA is total fixed cost for total acres cultivated, TCA is total cultivated acres for crops and TTA is

total cultivated acres.

Fixed cost for fodders, TFCF, for green fodders cultivated by each farm has been calculated as follows:

TFCF = TFCTA (TFA

TTA

)

where TFCTA is total fixed cost for total acres cultivated, TFA is total cultivated acres for green fodders and

TTA is total cultivated acres

234

Total fixed cost for milk production, TFCMk, for the farm has been calculated as follows:

TFCMk = TFCWLA (FL

TL

) + TFCF (FL

TL

)

where TFCWLA is total fixed cost for whole livestock activity, FL is total estimated female livestock and TL

is total livestock owned. TFCF is total fixed cost of green fodder cultivation allocated to milk enterprise.

Total fixed cost for meat production, TFCMt, for the farm has been calculated as follows:

TFCMt = TFCWLA (ML

TL

) + TFCF (ML

TL

)

where TFCWLA is total fixed cost for whole livestock activity, ML is total estimated male livestock and TL is

total livestock owned. TFCF is total fixed cost of green fodder cultivation allocated to meat enterprise.

Milk average variable cost per kilogramme, AVCMk/kg, for milk production has been calculated as follows:

AVCMk/kg =TVCMk

OMk

where TVCMk is total variable of milk production and OMk is milk production.

Milk average fixed cost per kilogram, AFCMk/kg is:

AFCMk/kg =TFCMk

OMk

where TFCMk is total fixed cost of milk production and OMk is milk production.

Milk total cost per kilogramme,TCMk/kg, is:

TCMk/kg = AFCMk/kg + AVCMk/kg

where AFCMk is the average fixed cost of milk production and AVCMk is the average variable cost of milk

production

Profit for milk production, πMk, is calculated as follows:

πMk = TRMk − TCMk

where TRMk is total revenue from milk production, and TCMk is the total cost of milk production.

235

An increase in milk production, Mkkg, is calculated as follows:

↑ Mkkg = (OMk )% ∝𝑐 + OMk

where OMk is actual milk production per farm from primary survey data. The percentage increase, αc is

based on the regression analysis where the value of αc is derived from an increased quantity of

concentrates making MR=MC for MG1, MG2 and MG3 respectively. It is derived from simulated

improved concentrates feeding regime per milking animal.

An increase in total variable cost of milk production, TVCMk, is calculated as follows:

↑ TVCMk = (TCConct ) × 𝛽𝑐 + TVCMk

where TVCMk is actual total variable cost of milk production and TCConct is total of concentrates from

primary survey data. The increase, βc is the actual cost of concentrates times the increase of concentrates

for each of the three milk groups, linked to the %age increase from the regression analysis. The TVCMk for

farms with no concentrates fed has been kept the same as initial.

Increased milk average variable cost per kilogramme, AVCMk/kg, based on %age increase corresponding

to total variable costs for the three production groups and is calculated as follows:

↑ AVCMk/kg = ↑ TVCMk

↑ OMk

where TVCMk is increased total variable cost of milk production, and OMk is increased milk production.

Increased milk total cost per kilogramme, TCMk/kg, after increase is calculated as follows:

↑ TCMk/kg = ↑ AVCMk/kg + AFCMk/kg

where AVCMk/kg is increased average variable cost of milk production and AFCMk/kg is average fixed cost of

milk production that remains unchanged.

Milk marginal cost per kilogram, MCMk/kg ,after increase in productivity is as follows:

MCMk/kg =∆TVCMk

∆OMk

where ΔTVCMk is change in total variable cost of milk production and ΔOMk is change in milk production.

236

Increased gross Income from milk production, GIMkΔ, after increase is calculated as follows:

↑ GIMk∆ =↑ OMk × PMk

where OMk is total milk output after increase and PMk is price per kg of milk

Increased total cost of milk production, (TCMkΔ), after increases is calculated as follows:

TCMk = (TFCMk ) + (↑ TVCMk)

Profit from milk production, πMk, after the increases / changes is calculated as follows:

πMk∆ = TRMk − TCMk

where TRMk is total revenue from milk production after changes and TCMk is total of milk production after

changes.

My original model applied (Malcolm et al., 2005) to this analysis to estimate operating and net profits and

return on assets is as follows:

𝐺𝐼 − 𝑇𝑉𝐶 = 𝑇𝐺𝑀

and

𝑇𝐺𝑀 − 𝑂𝐻 = 𝑂𝑃

where GI is gross income, TVC is total variable costs, OH is total overhead or fixed costs, TGM is total

gross

margin, OP is operating profit. Operating profit is the return on all the capital used in the business, and is

the

reward to all who have contributed the capital used in the business.

𝑂𝑃 − 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑝𝑎𝑖𝑑 𝑡𝑜 𝑐𝑟𝑒𝑑𝑖𝑡𝑜𝑟𝑠 − 𝑙𝑒𝑎𝑠𝑒 𝑐𝑜𝑠𝑡𝑠 = 𝑁𝑒𝑡 𝐹𝑎𝑟𝑚 𝑃𝑟𝑜𝑓𝑖𝑡

Interest is paid out of operating profit to creditors. Operating profit minus interest is the reward to the

farmer’s own capital. This is called net farm income or net profit. Lease payments are also a financing

expense and a reward to the owners of the assets that are being leased.

Profit does not indicate economic efficiency until it is related to the amount of capital used to produce it,

expressed as the percentage return on total capital (operating profit/total capital). This indicates the rate of

237

earning of the total capital relative to the rate of earning of that capital if it were employed in some other

income-producing activity.

𝑅𝑒𝑡𝑢𝑟𝑛 𝑡𝑜 𝑎𝑠𝑠𝑒𝑡𝑠 =𝑂𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑝𝑟𝑜𝑓𝑖𝑡𝑠

𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑡𝑜𝑡𝑎𝑙 𝑐𝑎𝑝𝑖𝑡𝑎𝑙 (𝑊𝐼𝑊𝑂) × 100

For this analysis due to data limitations, to estimate operating and net profits and return on assets,

assumptions have been made on the following basis:

The formula for profit is

𝑃𝑟𝑜𝑓𝑖𝑡(𝜋) = 𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑣𝑒𝑛𝑢𝑒 (𝑇𝑅) − 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑠𝑡 (𝑇𝐶)

From the equation above, Total Cost (TC) is the sum of total variable costs and total fixed costs.

𝑇𝑜𝑡𝑎𝑙 𝑐𝑜𝑠𝑡(𝑇𝐶) = 𝑇𝑜𝑡𝑎𝑙 variable costs (𝑇𝑉𝐶) + 𝑇𝑜𝑡𝑎𝑙 fixed c𝑜𝑠𝑡𝑠 (𝑇𝐹𝐶)

c. Variable costs (also called direct costs, explicit (E) or out of pocket costs) vary with the level of

production. These costs incur in the current period per unit of output, and the manager has control over

them in the short run. Examples include costs of seeds, fertilizers, pesticides, contract labour…

d. Fixed costs (also called overhead and include both implicit (I) & explicit (E) costs) do not vary with

the level of production. These costs are associated with owning a fixed input such as land or labour.

Examples include:

iii. Explicit (E) costs: interest on farm mortgages, property taxes, insurance…

iv. Implicit (I) costs: potential income from employment opportunities foregone and rental rate for

owned assets

Economic profit includes both explicit and implicit costs:

𝐸𝑐𝑜𝑛𝑜𝑚𝑖𝑐 𝑃𝑟𝑜𝑓𝑖𝑡(𝜋𝐸) = 𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑣𝑒𝑛𝑢𝑒 (𝑇𝑅) − Total 𝐶𝑜𝑠𝑡 (𝑇𝐶𝐼+𝐸)

Accounting profit only includes explicit costs:

𝐴𝑐𝑐𝑜𝑢𝑛𝑡𝑖𝑛𝑔 𝑃𝑟𝑜𝑓𝑖𝑡(𝜋𝐴) = 𝑇𝑜𝑡𝑎𝑙 𝑅𝑒𝑣𝑒𝑛𝑢𝑒 (𝑇𝑅) − Total 𝐶𝑜𝑠𝑡 (𝑇𝐶𝐸)

For this analysis:

Operating Profit (OPWF ) for the whole farm is calculated by assuming all farm household labour costs

(variable and fixed) to be explicit (i.e. not opportunity costs).

Operating Profit, OPWF, for the whole farm, has been calculated as follows:

238

OPWF = GMWF − TFCWF

where GMWF is gross margin for the whole farm and TFCWF is total fixed cost for the whole farm which is

labour cost.

TFCWF is the cost of whole farm manual labour allocated to livestock, fodder and crop enterprises, assumed

to be provided by the farmer owner and / or his household. The manual and casual labour costs are excluded

from all enterprise GM estimates. The farmer owner also provides the managerial labour. There is no other

fixed cost.

The managerial labour provided by the farmer is implicit cost. The casual or contractual labour hired by

farmer/farm household is both explicit & implicit as the casual labour is often hired in peak sowing and

harvest

seasons and for taking care of livestock as well. Given the low opportunity cost of farm household labour,

the

implicit labour costs should be zero. However, the analysis assumes that these costs are being paid that is

explicit while calculating operating profits.

Similarly, Net Profit (NPWF) for the whole farm is calculated by applying an annual interest cost on the

value of land and livestock utilized as key farm assets (their opportunity cost).

Net Profit, NPWF, for the whole farm, has been calculated as follows:

NPWF = OPWF − FCWF

where OPWF is operating profit for the whole farm and FCWF is finance cost for the whole farm, which is

estimated at 9% of the value of land and livestock per annum. The percentage on finance costs is based on

the average national savings rate and that used by the government of Punjab in its crop gross margin

estimates for the fiscal year 2008-09 (Government of the Punjab, 2006-13; National Savings Organization,

2000).

Total value of farm assets, VTFA, for the whole farm, that is land and livestock, is assumed to be owned by

the farmer and calculated as follows:

VTFA = VLd + VLs

where VLd is the market value of land, and VLs is the value of livestock. VLs is calculated as follows:

VLS =(OVLs + CVLs)

2

239

where OVLs is opening value of livestock and CVLs is the closing value of livestock.

Return on Assets, RoAWF, for the whole farm has been calculated as follows:

RoAWF = (OPWF

VWFA

) 100

where OPWF is operating profit for the whole farm and VCWFA is the average value of whole farm assets.

240

Chapter 4: Appendix D (Key Assumptions):

Questionnaire used to collect data from the two year longitudinal survey by Australian Centre for

International Agricultural Research (ACIAR) funded project entitled “Improving dairy production in

Pakistan through improved extension services”

Dairy Farmer Record book

Agriculture Sector Linkages Program, Pakistan-Australian Dairy Improvement Project

Basic Information:

Farmer number: Farmer’s name and father’s name

Address: Phone number:

Agriculture Information

Total area cultivated__________________

Land owned __________________ Land leased__________________


Khariff area


Rabi area

Dairy Animal Information

Buffaloes

Number of buffaloes

Number of buffalo heifers

Male calves

Female calves

Bulls (Breeding)

Cows

Number of cows

Number of cow heifers

Male calves

Female calves

Bulls (Breeding)

Total number of animals __________________

Month (Weekly)

Milk Production

Animal identity number Morning (kg) Evening (kg) Total (kg)

Buffalo

Cow

Reproduction information (Weekly)

Animal

identity

number

Dry Pregnant Heat Disease AI Natural Other

Buffalo



241

Cow

Nutrition (Daily)

Details Green Fodders (kg) Straws Concentrates

Type

Quantity

Health (Weekly)

Details Vaccination Deworming Medicine Other

Type

Number of

Animals

Cost

Marketing (Weekly)

Details Quantity Price (Rs) Comments

Milk

Animals

Other

Management (Weekly)

Details Quantity Cost (Rs) Comments

Water

Animals

purchased

Buildings

242

D4.1 MAJOR CROPS grown in the district extracted from the data were wheat (Triticum

spp.), rice (Oryza sativa), cotton (genus Gossypium) and sugarcane (Saccharum

officinarum L.). All other minor crops were summed up as vegetable/horticulture crops.

Average yield for fiscal year 2008-09 varied for wheat, rice, sugarcane and cotton was

taken from Punjab Agriculture Department’s final estimates (Government of the Punjab,

2011d). Yield estimates of vegetable/horticulture category were based on average of

Punjab government’s final summer and winter estimates (Government of the Punjab,

2011d).

Market prices: Market prices for wheat, rice and maize were the average of June 2008

and 2009 prices (Government of the Punjab, 2009). The price of sugarcane was taken as

an average of reported price for the season (Baig & Bashir, 2008; Elahi, 2008). The price

of cotton was an average of 2008-09 monthly prices quoted by APTMA (All Pakistan

Textile Mills Association, 2013). Price estimates for vegetable/horticulture crop category

were based on the average of June 2008 and 2009 market price of potato, tomato and

onion grown as main vegetable crops in Okara (Government of the Punjab, 2009).

Variable cost of production estimates for major crops of wheat, rice, sugarcane, cotton,

maize and averages for horticulture/vegetable crops for the Pakistani fiscal year 2008-09

were adopted from Punjab’s government estimated costs (Government of the Punjab,

2006-13).

D4.2 MAJOR FODDERS were berseem (Trifolium alexandrinum), maize (Zea mays),

lucerne (Medicago sativa), millet (Pennisetum typhoides), sorghum (Sorghum bicolor)

and sugarcane tops (Saccharum officinarum L.) (Top one foot or one sixth of the total

yield) allocated as fodder. Millet, sorghum and maize were taken as fodder crops only.

Smaller land allocation to other fodders grown was categorized as fodder mix.

243

Average yield estimates for all the green fodders was based on averages of Punjab

Agriculture department’s estimates (Government of the Punjab, 2013), and expert opinion

from Pakistan (S. S. Khan, 2012b; Zahid, May 2011).

Price for green fodder(s) per kilogram was taken as the total variable cost of production

for each fodder divided by average yields.

Variable cost of production for fodders was based on expert opinion from Pakistan (S.

S. Khan, 2012b; Zahid, May 2011).

D4.3 LIVESTOCK PRODUCTION (MILK & MEAT): The average milk production

per buffalo and / or cow and the number of milking animals per farm were extracted from

the survey data, and 5% output was added for that going to suckling calves (Farooq, 2012,

2013). The data also distinguished buffalo and cattle and classed them by sex and age.

Female animal were allocated to milk and male to meat enterprise, while one fourth of

milking buffaloes and cows that are culled for meat, were allocated to meat enterprise

(Wynn et al., 2006). Average live weights (S. S. Khan, 2012b; Teufel, 2007) were

assigned to each class of animal to calculate annual meat production. Livestock

reconciliation gave an animal count at the closing of the year that gave a closing asset

value of livestock.

Livestock (milk, meat and per animal) Prices: The farm gate price of milk sold was

recorded by the survey (Wynn, Unpublished). For meat, the average market beef price for

fiscal year 2008-09 in Punjab was used to estimate the production value (Government of

the Punjab, 2011a, 2011e).

Variable cost of production: The three variable costs for rearing livestock were 1) feed

that is green fodders, roughages (mainly rice and wheat straw), concentrates purchased

244

(mainly compound feed, cotton seed cake and wheat bran) 2) health care and 3) breeding

costs.

The total feed cost was calculated by assigning a Rupee value to each kilogram of feed

fed to livestock that was recorded by the primary data along with health and breeding

costs.

D4.4 FIXED OR OVERHEAD COSTS: All the manual labour was taken as fixed cost

for all the farm enterprises. Crop and fodder manual labour estimates62 were excluded

from gross margin estimates and brought in later as fixed costs.

Similarly, livestock labour was based on estimates63 from a study of small dairy holders

in Punjab (Teufel, 2007) and minimum wage rate for fiscal year 2008-2009 was

determined from government of Punjab production costs (Government of the Punjab,

2006-13). Operating profit, for the whole farm was estimated by including whole farm

labour costs for crop, fodder and livestock (milk and meat) enterprises that had earlier

been excluded from GM estimates.

Net farm profit for the whole farm enterprise was estimated by applying an annual

interest cost on the value of land and livestock assets, which were assumed to be the only

major farm fixed assets owned by the farmer(s) and utilized as farmer’s equity for

production activities. The annual interest rate was subtracted from the operating profit.

The land prices per acre were recorded by the data and missing values were estimated

taking averages of village data. For livestock, an assumed market value was assigned to

62 All manual labour costs, that is man hours for the estimation of per acre gross margin budgets, such as labour for bund making,

sowing, canal irrigation and tube well, fertilizer and chemical application, harvesting costs (a range of operations that varied with the crops) were taken as fixed costs i.e. assuming that these functions are being performed by the owner-operator.

63 Teufel Ph.D. thesis page 56 suggests that the annual labour requirements of average and high-yielding adult female buffalo, heifer and calf are assumed to be 412 h (took 438hrs average for adult cows and buffaloes & 219 for bulls as they don’t require milking),

464 h, 412 h and 58 h respectively. Labour charges per day in 2008-09 were 200 Rs/day, which comes to 25Rs/hour. This amount is

then multiplied by the labour requirements per animal per farm to obtain labour costs for livestock.

245

each class of animal in the herd, based on consultation with ACIAR dairy project staff

and expert opinion from Pakistan (S. S. Khan, 2012b; Wynn, 2010; Wynn et al., n.d). The

interest was based on the long term average national savings rate of 9% and that used the

government of Punjab in its crop gross margin estimates for fiscal year 2008-09

(Government of the Punjab, 2006-13; National Savings Organization, 2000).

246

Chapter 5 and 6: Appendix E Questionnaires

E1. Questionnaire for Farmer

(September 2011)

1. Respondent ID & Date of Interview

2. Total no. of animals?

3. No. of milking animals?

4. Agricultural land owned?

5. How much total milk produced today in kg?

6. What milking do you sell? 1. Morning

2. Evening

3. Both

7. How much did you produce in total today? 1. Less than 10 kg

2. Between 11 to 20 kgs



5. Above 40 kgs

8. How many hours does milking take?

1. Less than 2 hours

2. Between 2 to 3 hours



5. More than 5 hours

9. How many traditional milk traders and

companies in this market are you aware of?

10. How much milk did you deliver yourself

and how much was collected at your

doorstep?

1. Self-delivery in kgs

2. Collected at doorstep kgs (if option 2 for all milk

go to Q.15)

3. Both

11. If self-delivery what is the mode of

transport?

1. Cycle

2. Motor Cycle

3. Van

4. Public Transport

5. Others

12. Estimated Cost of Transport in Rs. / km

13. Total approx. distance covered in

kilometres for milk delivery?

14. Total approx. time taken to deliver the

milk?

15. Who do you sell the milk to? 1. Dhodhi

2. Nestle

3. Haleeb

4. Halla

5. Neighbour

6. Hotel

7. Other

8. Self-Consumption

16. Who is your most important buyer(s) of

milk?

Type

1.

2.

3.

Quantity in kgs

247

17. Is there any form of contract to sell milk

between you and your buyer? If yes what

form of contract?

1. Yes

2. No

3. Others

1. Written

Contract

2. Verbal

Contract

18. Are there any specific conditions set for the

contract and so what?

19. Are you satisfied with your buyer(s) and if

not why not?

20. Do your buyers change / leave and if so how

to you find new buyers?

21. Do prices and quantities (supply and

demand) change with change in season?

a. Yes

b. No.

c. Other

22. If yes what is the average price / kg in? Price / kg in Summer

Price / kg in Winter

23. How or on what basis do you determine the

price that you sell for?

a. Total cost

b. Previous season

c. Market Information

d. Price fixed by Dhodhi

e. Price given by Company

f. Other factors

24. For summer and winter seasons, how do

you address the issue of milk shortage or

excess production? i.e. less supply and

more demand for milk and vice versa?

25. Do you sell your milk on credit? 1.Yes

2.No

26. What is the frequency of payments to you? 1. After one week

2. After two weeks

3. After a month

4. Others

27. Do you need any credit to maintain your

cash flows?

1.Yes

2.No

3.Other

28. If yes, who is your lender(s)?

29. What are the terms of borrowing?

30. Do you store your milk before sale? 1. Yes

2. No

31. If yes, how much milk do you store? Approx. kgs. / day

32. Where do you store the milk? Fridge

Freezer

Other(s)

What is the cost of storage i.e. electricity bill

per month?

Generally, what problems do you experience in

storing milk?

33. How does the buyer assess the quality of

milk you sell?

Thickness (density)

Smell

Taste

Visual Appearance

248

Fat %age

All of the Above

Other(s)

34. Do you get information about milk prices,

milk demand and supply?

1. Yes.

2. No.

30. If yes what are your sources of

Information?

1. Radio 2. Newspaper 3.TV 4.Other traders 5.

Relatives and Friends 6. Mobile Phone 7.

Others

31. Do you have any comments to add about

the marketing system?

General Information

32. Village / City

Union Council

District

Province

33. Age 1. Less than 25 years

2. Between 26 to 35 years



5. More than 55years

34. Highest Level of Education completed

1. No education

2. Between 1 and 5 Years


4. Year 11 to 14 Years

5. More than Year 14

35. How many years have you been a farmer? 1. Less than 5 year




5. More than 20 Years

249

E2. Questionnaire for Collectors & Distributor

(September 2011)

MILK MARKETING


2. Level of Transaction /Status

1. Small & Medium Dhodhi (or Milk Collectors)??

2. Pacca Dhodhi or Milk (Collectors & Distributors)

3. How do you sell the milk to? 1. Nestle / Haleeb etc.

2. Halla

3. Hotel

4. Others

4. How many (approx. number) milk

traders in this market?

5. What and how much is your main

investment in milk trade?

6. With a focus on marketing please answer the following questions regarding milk procurement, sales and

volumes:

(Need to note down the terms used for small and large quantities i.e. volumes etc.)

a. Quantity bought in kgs (approx.

/day)?

b. Do you buy same quantity all along

the year?

c. Where do you source your milk from?

(e.g. farmer, kacha dhodhi etc.) and

how many of each category?

1.

2.

3.

d. Who is your most important

supplier(s) and how much do you buy

from that priority source?

Type

1.

2.

3.

Quantity in kgs

e. Time taken to buy milk i.e. hours /

days




7. Do prices and quantities (supply and

demand) change with change in season?

a. Yes

b. No.

c. Other

8. If yes what would be the average price per

kg in? Season

Summer

Winter

Price / kg

9. Do you benefit or loose from seasonal

prices seasonal?

a. Yes

b. No.

c. Other

10. How or on what basis do you determine

the price that

you buy for?

a. Previous season

b. Total cost


d. Price fixed by Pacca Dhodhi

e. Price given by Nestle or other big companies

f. Other factors

11. How or on what basis do you determine

the price that

you sell for?

a. Previous season

b. Total cost


250



f. Other factors

12. How is the profit margin fixed between

you, your supplier and your buyer?

a. No mechanism

b. A %age of final price

c. Based on costs borne by each member of chain

d. Just fixed by Pacca Dhodhi

e. Other factors

13. Is there any form of contract to ensure

supply to you and then between you and

your buyer? If yes what form of contract?

1. Yes

2. No

3. Others

1. Written Contract 2. Verbal Contract

14. Are you satisfied with your seller(s) and

buyer(s) of milk and if not why not?

15. How do you address the issue of milk

shortage i.e. less supply and more demand

for milk? (for farmer more demand and

less supply)

16. Do you sell your milk on credit to your

customers?

1.Yes

2.No

If Yes what percentage of total sales do you sell on credit?

Less than 20%

Between 21 to 40%

Between 41 to 60%

Between 61 to 80%

17. Do you get / need any credit to maintain

your cash flows?

1.Yes

2.No

3.Other

& If yes, who is your lender?

a. Quantity sold in kgs today? 1. Less than 10 kg




5. Above 40 kgs

b. Time taken to sell milk i.e. hours / day

(today)




c. Where do you sell the milk? (e.g. pacca

dhodhi, hotel, khoya maker, consumer?)

and how many of each category? (10

hotels, 2 khoya makers)

1.

2.

3.

d. Who is your most important buyer(s) and

how much does you buy from that priority

source?

Type

1.

2.

3.

Quantity in kgs

Transport and loading / unloading

18. How do you transport your milk to your final / terminal market? What is cost of transportation? How much

do you pay to transport the milk?

Transport Self

Hired

251

Mode of Transport Bicycle

Motor Cycle

Public Transport

Hilux

Mini Truck

Cost of transportation Approx. Total kms / day

Approx. Total kms/ week

Approx. Total kms/ month

Quantity of Milk Transported Per Day

Per Week

Per Month

Have you experienced any problems with

Transport?

1.Yes

2.No

& if yes and If Yes, Please explain

19. Do you have to pay any loading and

unloading additional costs?

1. Yes

2. No

3. Other

20. If yes how much would be the

approximate per milk containers

Approximate Estimate

Storage


2. No

If yes, how much milk do you store? Approx. Per Day

Approx. Per Week

Approx. Per Year

Where do you store the milk? Fridge Freezer

Drum Tank

What is the cost of storage? (Electricity bill

per month?)

Generally, what problems do you experience

in storing milk?

22. Do you have to pay any government

taxes?

1. Yes

2. No

3. Other(s)

If yes what type of taxes?

Quality

23. How do you assess quality of your milk

bought?

Thickness (density)

Smell

Taste

Visual Appearance

Fat %age

All of the Above

Other(s)

24. How does the buyer assess the quality of

milk you sell?

Thickness (density)

Smell

Taste

Visual Appearance

Fat %age

All of the Above

Other(s)

252

25. How do you maintain quality of your milk

bought and sold?

Milk Processing

26. Beside milk do you buy/sell any other

product(s)?

1. Yes

2. No

If Yes than what other products? ---------------------------

27. Do you process / condense milk?

1.Yes

2.No

If yes please tick in which form(s) do you process

your milk and the quantities

-Lassi -Yogurt

-Khoya -Butter

-Desi Ghee -Others-------

Is it more profitable to sell fresh milk or process /

condense milk and sell?

1.Yes

2. No

3. Other

Information

28. How do you get information about prices, milk

demand and supply?

What are your sources of Information? 1. Radio 2. Newspaper 3.TV 4.Other traders 5.

Relatives and Friends 6. Mobile Phone 7. Others

29. Do you belong to any trader to any

organization? (Traders association or any other

informal organization)

1.Yes

2.No

3. Others

30. Do you have any comments to add about the

marketing system?

31. Village / City

Union Council

District

Province

32. Owner of the business

1-Yes

2-No

3- Other






34. Highest Level of Education completed

1. No education





35. How many years have you been involved in this

business?

1. Less than 1 year



253



E3. Questionnaire on Retailer

(September 2011)

MILK MARKETING


2. Level of Transaction /Status

1. Retail Milk Shop

3. How do you sell the milk to? 1. Consumers

2. Company

3. Others

4. How many (approx. number) milk

traders in this market?

5. What is your main investment in milk

trade? and how much?

Price, Volumes and Time

6. With a focus on marketing please answer the following questions regarding milk procurement, sales and

volumes:

(Need to note down the terms used for small and large quantities i.e. volumes etc.)

f. Quantity bought in kilograms? Approx. Per Day

Approx. Per Week

Approx. Per Month

g. Where do you source your milk

from? (e.g. farmer, kacha dhodhi,

pacca dhodhi etc.) and how many

of each category?

Where

1.

2.

3.

How many

1.

2.

3.

h. Who is your most important

supplier(s) and how much do you

buy from that priority source?

Type

1.

2.

3.

Quantity in kgs

i. Time taken to buy milk i.e. hours

/ days




j. Quantity sold in kgs? 1. Less than 10 kg




5. Above 40 kgs

k. Time taken to sell milk i.e. hours

/ days




l. Where do you sell the milk?(e.g.

hotel, khoya maker, halwais,

confectioners, consumer?)

1.

2.

3.

How much

m. Who is your most important

buyer(s) and how much does you

buy from that priority source?

Type

1.

2.

3.

Quantity in kgs

254

7. Do prices and quantities (supply

and demand) change with change

in season?

a. Yes

b. No.

c. Other

8. If yes what would be the average

price per litre in? Season

Summer

Winter

Price / kg

9. Do you benefit or loose from

seasonal prices seasonal?

a. Yes

b. No.

c. Other

10. How or on what basis do you

determine the price that

you buy for?

a. Previous season

b. Total cost




f. Other factors

11. How or on what basis do you

determine the price that you sell

for?

a. Previous season

b. Total cost




f. Other factors

12. How is the profit margin fixed

between you, your supplier and

your buyer?

a. No mechanism

b. A %age of final price

c. Based on costs borne by each member of chain

d. Just fixed by Pacca Dhodhi

e. Other factors

13. Is there any form of contract

between you and your supplier?

If yes what form of contract?

1. Yes

2. No

3. Others

1. Written Contract 2. Verbal Contract

14. Is there any form of contract

between you and your buyers? If

yes what form of contract?

1. Yes

2. No

3. Others

Written Contract 2. Verbal Contract

15. Are you satisfied with your

seller(s) and buyer(s) of milk and

if not why not?

Transport and loading / unloading

16. How do you transport your milk to your final / terminal market? What is cost of transportation? How much

do you pay to transport the milk?

Transport Self

Hired

Mode of Transport Bicycle

Motor Cycle

Public Transport

Hilux

Mini Truck

Cost of transportation Approx. Total kms / day

255

Approx. Total kms/ week

Approx. Total kms/ month

Quantity of Milk Transported Per Day

Per Week

Per Month

Have you experienced any problems

with Transport?

1.Yes

2.No

& if yes and If Yes, Please explain

17. Do you have to pay any loading and

unloading additional costs?

1. Yes

2. No

3. Other

18. If yes how much would be the

approximate per milk containers

Approximate Estimate

Storage


2. No

If yes, how much milk do you store? Approx. Per Day

Approx. Per Week

Approx. Per Year

Where do you store the milk? Fridge Freezer

Drum Tank

What is the cost of storage? (Electricity

bill per month?)

Generally, what problems do you

experience in storing milk?

20. Do you have to pay any government

taxes?

1. Yes

2. No

3. Other(s)

If yes what type of taxes?

Quality

21. How do you assess quality of your

milk bought?

Thickness (density)

Smell

Taste

Visual Appearance

Fat %age

All of the Above

Other(s)

22. How does the buyer assess the

quality of milk you sell?

Thickness (density)

Smell

Taste

Visual Appearance

Fat %age

All of the Above

Other(s)

23. How do you maintain quality of your

milk bought and sold?

Milk Processing

256

24. Beside Milk do you buy/sell any

other product(s)?

1. Yes

2. No

If Yes than what other products? ---------------------------

25. Do you process / condense milk?

1.Yes

2.No

If yes please tick in which form(s) do

you process your milk and much

approximate Quantities

-Lassi -Yogurt

-Khoya -Butter

-Desi Ghee -Others-------

Is it more profitable to sell fresh milk or

process / condense milk and sell?

1.Yes

2. No

3. Other

Information

26. How do you get information about

prices, milk demand and supply?

What are your sources of Information? 1. Radio 2. Newspaper 3.TV 4.Other traders 5. Relatives and

Friends 6. Mobile Phone 7. Others

27. Do you belong to any trader to any

organization? (Traders association

or any other informal organization)

1.Yes

2.No

3. Others

28. Do you have any comments to add

about the marketing system?

29. Village / City

Union Council

District

Province

30. Owner of the business

1-Yes

2-No

3- Other

31. Age

32. Highest Level of Education

completed

1. No education





33. How many years have you been

involved in this business?

1. Less than 1 year





258

E4. Questionnaire for Consumer(s)

(September 2011)

1. Respondent ID

2. Date of Interview

3. How much milk did you buy today?

i.e. quantity bought? Units?

4. Where did you get your milk today i.e.

price / kg

5. How much price / kg(?) did you pay for

the milk today?

6. How did you choose your current source

of milk purchase?

7. What is preferred source of milk? 1. Fresh loose milk from the shop

2. Fresh loose milk delivered at home

3. Packaged Milk

4. Powdered Milk

5. Other

8. Does your consumption change with the

change in seasons?

a. Yes

b. No.

c. Other?

9. If answer to the above question is yes,

how much quantities change on an

average per day?

Averages quantity consumed in kgs in summer:

Averages quantity consumed in kgs in winter :

10. Do prices change with change in season? a. Yes

b. No.

c. Other?

11. If yes what would be the average price in

Rs/kg in?

Price / kg in Summer

Price / kg in Winter

12. Are you satisfied with the quality of milk

you buy?

a. Yes

b. No.

c. Other?

13. How do you assess quality of milk

bought?

Thickness (density)

Smell

Taste

Visual Appearance

259

Fat %age

Cream after boiling

All of the Above

Other(s)

14. What do you perceive to be important in

deciding between different types of milk

sources?

15. Do you buy any other milk based

products? If so how much?

16. Do you have any comments to add about

the milk?

General Information

17. Village / City

Union Council

District

Province

18. Sex 1.Male

2.Female

19. Size of your Household?






21. Highest Level of Education

completed

1. No education





22. Average income per month?

1. Less than Rs. 10,000

2. Between Rs. 10,000 and Rs. 20,000

3. Between Rs. 20,000 and Rs. 30,000

4. Between Rs. 30,000 and Rs. 40,000

5. Above Rs. 40,000

261

Chapter 8 Appendix F: Results: Case Study 1: Kasur-Lahore fresh


The fresh unpackaged rural-urban milk value chain in this study has four tiers including

producers, small dhodhis, a large dhodhi and retailers (Figure 28). The chain originates

from a small village of Kasur district in Punjab province; situated 85km south-west of

metropolitan Lahore city to which the milk is being supplied (Figure 23b). The

geographical area is of particular significance as it used to be the base of Idara-e-Kissan64,

the only milk cooperative in the country, which has recently ceased to operate. The

cooperative was established in the early 1980s and had a membership of 17,000 farmers.

The cooperative collected and marketed pasteurised milk. The milk collection model that

it developed has been adopted by local dhodhis, including those studied.

Figure 28: Kasur-Lahore chain65 model and product physical flows

64 Urdu name which means “an organization of producers”. Cooperative established by the German Federal Enterprise for International

Cooperation (GTZ) 65 Producer household estimates as large dhodhi milk collection 1200L÷20 small dhodhis = 60L÷10 assumed milk producers per small dhodhi = 6L → 1200L ÷ 6 L per Producer = 200 Producers approx.

Producer 1 + 150 to 200 estimated

producer households

Small Dhodhi + 19 small

dhodhis

Retailer1, 2 and 3 specialized

milk shops + 4 other shops that

Large Dhodhi claimed to be his own

1000 estimated consumer households

1 Large Dhodhi

Formal

Processors

Estimated 10 million consumers given a

5% market share

262

F8.1 Introduction of Kasur-Lahore value chain actors, technology and

infrastructure along the chain and spoilage risks

This section introduces the informal Kasur-Lahore value chain actors (Figure 28) studied

from producer to retailer and few important areas in relation to the operation of this chain,

namely:

Geographical location in the chain’s context, age, education, household size, main

source of income, and number of years in the business;

Formal processor(s) in this chain’s context is also introduced from the perspective of

the informal chain actors

Key assets possessed and their estimated market value, labour and time involved in

business operations by each participant (Table 34), and

Risk of spoilage in the absence of inconsistent cool chain infrastructure along the chain

Seven actors are introduced:

1. Milk Producer1 is one of the four milk producers interviewed in rural Kasur.

Producer1 is 32 years old and has no formal schooling. Producer1 lives in a joint

family of 12 members. He has been farming since a very young age, and his farming

is his only source of income. All producers interviewed, are from the same village.

Quotes from another producer (Producer2), who sells to another local small dhodhi

outside this chain, but gave important insights into the working of these informal

chains, will later be used, where appropriate.

Consumer household estimates are based on 2011-12 Household Income Economic Survey (HIES) average per capita fresh milk consumption and average household size. 6.36L per month ÷ 30day = 0.212Lper day × 6.41member per household = 1.4L → 1400 ÷

1.4 = 1000 households approx.

263

2. Small Dhodhi buys milk from Producer1 and is from the same village as the four

producers. He was buying milk from Producer2 as well about six months ago. Small

dhodhi is 45 years old and holds a diploma in civil engineering. He has a family of

five as his immediate household but comes from a big extended family. This family

is quite strong in the village as his brothers hold influential positions in government

service. The small dhodhi had been in the dairy business for the last ten years. Small

Dhodhi’s main business is selling desi ghee66 from a shop in the nearby small city of

Pattoki. Small dhodhi also sells bulk bags of imported powdered milk to the local

dhodhis, which means they also reconstitute milk, a practice commonly associated

with formal processors. He trades in livestock too.

3. Large Dhodhi buys buffalo milk from Small Dhodhi. He is also from the same rural

area of Kasur district. Large Dhodhi is in his late fifties and not educated. His two

sons run the day-to-day business whereas his role is managerial and problem-solving.

They operate from an ice factory as their base in rural Kasur district, which is situated

only a few hundred metres away from the former head office of the old milk

cooperative. Large Dhodhi has been in the milk business for the last 35 years, which

is this family’s only occupation. The milk is supplied to Large Dhodhi by 20 small

dhodhis including the Small Dhodhi mentioned above. These small dhodhis are called

VMCs67, based on old milk cooperative’s collection practice. The collection from

these small dhodhis ranges from 2 to 250 litre68 (L) per day and the quantity supplied

increases in winter, due to lactation cycle of milking animals. Large Dhodhi supplies

milk to seven specialised retail milk shops in Lahore. He claims four of these,

66 Clarified butter 67 Village Milk Collection Centres 68 Not actual litres. The units explained later in Figure 29

264

including Retailer1 and Retailer2, interviewed, to be his own as Large Dhodhi is

vertically integrating at the retail end.

4. Three specialised milk retailers (Retailer1, Retailer2 and Retailer3) in urban

metropolitan Lahore, who buy milk from large dhodhi, were interviewed. Data from

fourteen milk consumers interviewed at these three shops will also be included later,

where appropriate.

5. Specialised Milk Retailer Shop Keeper Retailer1 is the manager of the shop, which

is in a middle-class residential locality of metropolitan Lahore. The shop has been

established by this chain’s large dhodhi and the manager works on a fixed margin of

three Rs per litre. The shop is his only source of livelihood. Retailer1 is 26 years old

and has eight years of formal schooling. He comes from an rural extended family of

five brothers, one sister plus uncles and they all live together in the village. At night,

he and another shop worker, sleep on the rooftop of a nearby market.

6. Retailer2 operates a traditional sweet and milk shop in an impoverished area of

Lahore. This is a family business established 20 years ago by the current manager’s

father. Retailer2 is 35 years old and has a five-member household. “[I have] enough

education to do all the accounts and not be dependent on anyone”, responded R2 when

asked about his formal education.

7. Retailer3 is the proprietor of a relatively larger family owned specialised milk shop

compared to Retailer1 and Retailer2. The shop is in a middle-class residential locality

of Lahore. Retailer3 is 35 years old. He did not want to share formal education. He

comes from a joint family where five brothers and their children live together under

265

one roof in a multi-storey building, approximately 20 metres from the milk shop. The

shop has been operating in its current place since 1990.

8. Formal Processors operate outside but are linked to Kasur-Lahore informal chain as

illustrated in Figure 28. Nestlé is the formal processor that has established its milk

collection centre nearest (10 km away) to the village from which producers and small

dhodhi interviewed belong.

On the option of selling milk to formal processors, Producer1 said, “[formal processors

give] a rupee higher than the dhodhis, but they designate one focal person who collects

milk for their vehicle69 [from this village]...he pays the farmer as per his own will and

not the company price...better if [formal processors’] chiller [installed] in the village”.

This indicates producers are not being offered a better price by the formal processors,

compared to what small dhodhi70 offers.

While Producer2 said, “It would be beneficial to go to the collection centre [of formal

processor] if I had five to seven maunds71 of milk...We don’t have means of transport and

time either”. This statement illustrates the importance of milk pick up at producers’

doorstep by Small Dhodhi, especially given the smaller volumes produced, that saves

them time and transportation costs.

Small Dhodhi was present while Producer2 was being interviewed and he intervened on

the question why the producers are not selling milk to formal processors. Small Dhodhi

explained, “The big milk company talks of LR [lactometer reading] and butter fat, which

is confusing for the small farmer... [They also have] a twelve-day process...company

holds four day’s milk payment and pays for eight days of milk supply to the farmer.

69 Milk collection vehicle 70 There is an even more important aspect of cash advance extended by small dhodhi that will be discussed in section 4 71 A maund at rural level is 40 is kg or L and changes at the urban level. The unit will be discussed section 2. P2 produces 49 kg and sells 43 kg per day to another small dhohdi selling in Pattoki city. This is quite substantial given

266

Nestlé’s nearest collection centre is in [mentioned the name of the place, which was 10km

away] where they have only 20 direct [farmer] milk suppliers whereas rest are the

deceiving72 contractors”.

The Small Dhodhi also sells cow’s milk at Nestlé’s chiller separate from local village

household users. Small Dhodhi admitted that his village milk collection is a side business

in disguise for his main desi ghee73 business. Small Dhodhi said, “[Milk collection] hardly

covers the monthly wage of my labourers74 but I have to show my main business75

customers that I deal with fresh milk”. The reason for this disguise is that he buys ghee

from formal processors (Figure 28) Haleeb & Milac’s plants at 480 Rs/kg and sells it for

Rs 700 to 725 Rs/kg, as consumers prefer the traditional homemade one from fresh milk.

He alters its aroma and colour and deceives the customers saying that it is made from

fresh milk. On the question of quality of this ghee, Small Dhodhi said, “All the fabricated76

milk goes to dairies77 so how can the milk [from which ghee is made] be good? ...[The

milk suppliers to these processors] add whey powder to increase LR78...glucose, urea,

cooking oil...titanium powder79...the ratio is 1milk:3fabricated milk”. This draws attention

to the illicit practices and poor quality of packaged milk supplied by the formal channels.

Large Dhodhi also sells milk to formal processors on demand and in winter when there is

excess supply and less demand at the urban retail shops in Lahore.

Table 32 highlights that collection and distribution using transport is the key function

performed by the Large Dhodhi. The transport and all other equipment used along the

chain are unrefrigerated apart from refrigerators used by retailers for overnight storage.

72 The ones who add various adulterants and deceive the formal processors 73 Clarified butter 74 small dhodhi has hired two labourers referred to in Table 32 75 Shop customers in nearby Pattoki city 76 Adulterated 77 formal processors 78 lactometer reading which is measured with butterfat to access milk quality 79 Some chemical adulterant to change colour

http://www.nestle.com.au/

267

Retailers are the only ones in Kasur-Lahore chain processing milk for sale purposes. The

chain also generates an estimated 407 employment80 opportunities from producers to

retailers. Similarly, producers, Large Dhodhi and retailers put a substantial number of

hours in their business operations. Gyarwee Sharif81 of each Islamic month is the only

holiday in this chain.

80 Average 175 farm household with 2 in each HH taking care of livestock + 20small dhodhis and their 10 daily wage labourers+3large

dhodhi family members and 3 hired labourers+7 retail shop owners & 2 workers on average at each shop 81 Eleventh of each Islamic month celebrated by Muslims in and around Lahore city. This means no milk collection and the farmers

give milk to the needy one. This also means a huge pressure on collectors to collect almost double milk volumes before the Gyarwee

Sharif to meet the demand of Lahore market

268

Table 32: Technology and infrastructure, labour and time along the rural Kasur-urban Lahore milk value chain


Physical

functions

of

transport,

storage

and

processing

No transport and

storage

Processing for

household use

only

No transport required

for the informal Kasur-

Lahore chain as

collection by foot from

the village and milk

picked by large dhodhi

Motorcycle used for

milk delivery at formal

processors’ chiller

Unrefrigerated transport for

collection and delivery

Only storage is during transport as

small volumes of the evening milk

collection frozen into ice blocks at

the ice factory and used the next day

to chill milk for carrying to the

Lahore market

All three shops store milk in refrigerators. Ice in polythene bags is

also regularly used to preserve milk, as there are regular and long

electricity breakdowns

Retailer1 sells fresh milk only whereas Retailer2 & Retailer3

process milk into yoghurt and sell flavoured and chilled milk too.

Retailer2 also sells boiled milk to drink at the shop with local sweets

added called dodh82 jalebi83

Retailer2 sells sweets but purchases Khoya84 separately for making

traditional milk based sweets

Labour 3 i.e. producer

himself and two

younger brothers

to take care of

land and livestock

and hand milking

livestock

2 hired labourers to

collect and check

quality of milk. These

labourers also work at

his farm, manage

livestock and parallel

shop business in the

city

Small dhodhi’s role is

managerial

6 of which 3 family member i.e.

father and two sons and 3 hired

labourers to check milk quality and to

load and unload milk containers /

pots.

Father’s role is managerial &

problem solving

Retailer1: 2 i.e. owner manager who works on a fixed margin of 3

Rs/L and a daily wage labourer

Retailer2: 7 i.e. father and two sons and 4 daily wage labourers who

handle milk and make traditional sweets. The labourers are also

provided food and accommodation

Retailer3: 9 i.e. 5 brothers, two at the shop while 3 brothers are

collecting milk directly from the farmer producers, which makes half

the shop milk sale volume. The shop has also hired five daily wage

labourers to handle and sell milk and milk based products

82 Milk 83 a popular sweet in the Indian Subcontinent made by deep-frying a wheat flour batter in pretzel or circular shapes and then soaked in sugar syrup 84 thickened milk

269


Time

along the

chain (per

day)

6 hours to manage

livestock but, “If

we take proper

care of animals it

takes 10 to 12

hours”, said P1

2 hours only as milk

collection from the

same village

Also take care of small

dhodhi’s land and

livestock

17 hour operation with collection

starting at 6am and return to the rural

base by around 11pm

Retailer1: 17 hours from 5am to 12midnight

Retailer2: 22hours from 4am to 2am

Retailer3: 21.15 hours from 0345am to 1am


270

Minimal cool chain infrastructure along the chain means physical spoilage risks of milk

increase downstream as large dhodhi said, “Yes there are times when the whole collection

gets spoiled”, while Retailer2 responded, “Yes [milk does get spoiled] if we are negligent.

For example, if there is no electricity and we do not use ice to maintain the temperature

of milk”, as there are long and continuous electricity breakdowns in the country.

F8.2 Consumer value, quality determination; grading and quantity measurements

along the Kasur-Lahore chain and gross margins

This section describes:

Milk quality attributes ranked priority wise by all chain actors and their aggregate in

Table 33

Milk quantity units and quality aspects along product’s physical flows, quality sought

by buyer at each step and how is it assessed;

From producer to retailer, rewards associated if any for the seller for better quality,

grading and quantity units for milk purchases and sales; and

Gross margins based on milk flows and volumes associated with quantity units and

quality aspects

The above aspects are described by studying following positions in the chain:

Final Consumers

Producers, Small Dhodhis and Processor

Small Dhodhis, Large Dhodhi and Retailers

Table 33 ranks the importance of six quality attributes sought by various chain actors, in

the absence of product labelling at any tier of the chain. The importance of these attributes

varied for each participant. However, higher fat content associated with buffalo milk

271

followed by taste and aroma are of prime importance in this chain for both final

consumers and chains actors from milk producers to the retailers. The sixth attribute of

lactometer reading (LR) only appeared in conversations with the Small and Large Dhodhi

and is not included in the comparison (Table 33).

272

Table 33: Kasur-Lahore milk quality attribute perspective of various chain actors from farm to final consumer

Attributes Ranking Aggregate of Ranking

Producer1 Producer2 Producer3 Small

Dhodhi

Large

Dhodhi Retailer1 Retailer2 Retailer3

Farmer

to

Retailer

(n=8)

Consumers

(n=14)

Safety and health benefits 1 1 1 5 4 5 5 5 28 52

Visual appearance (colour

and/or cleanliness) 4 4 4 5 1 1 2 4 25 52

Taste (sweetness) 2 2 1 4 1 4 3 2 19 41

Smell (aroma and is it sour) 3 3 3 3 1 3 4 3 23 38

Thickness (higher fat

content) 1 1 2 1 2 2 1 1 11 23

Lactometer Reading NA NA NA 2 3 NA NA NA 5 NA

Note: Ranked on scale of 1 to 5 (where 1 is highest in importance and 5 is lowest)

n=8 for chain actors from farmer to retailers and n=14 for final consumers interviewed at the three retail shops


273

Figure 29 portrays units and various pots used to handle milk and mechanism for quality

assessment along the chain. In brief, Small Dhodhi obtains more volume per local unit(s)

from the producers. At the rural level, the Large Dhodhi collects higher fat content milk,

which is then diluted with ice for the urban retail market to gain volume. Finally, the

retailers sell lesser quantities to the final consumers. The detailed mechanism of how this

occurs in the local context will be studied.

274

Producers Small Dhodhi Large Dhodhi Retailers

Large Dhodhi’s urban Quality standard

Large Dhodhi then lowers the fat for urban retailersto around 4.6 to 4.8% by diluting it with ice

Estimated 1ice : 7 milk

i.e. 6.8 ice : 47.7 milk

Therefore easy for Large Dhodhi to make 46litre Lahori panda or maund

Retailer Quantity

At retail level

Retailer1 & Retailer2 sell

1litre = 950ml i.e. 50 ml less per litre

Large Dhodhi’s 46 litres Lahori panda or maund

=

Retailer’s 48 litres

i.e. 46 ÷ 0.95 = 48

Retailer3 did not disclose how much his units weights but sells in both gadvi and

litres

Small Dhodhi ’s

seer or gadvi

for producer

Small Dhodhi’smeasure used to

convert producer’s seers or gadvi to litres

Producer Quantity

At farm gate

1 seer OR gadvi = 1100 ml

i.e. Small Dhodhi gets 100ml extra per

litre

Producer1’ s 1 gadvi =

Small Dhodhi’s1.1litres

i.e. 1 × 1.1=1.1

Price between Producer & Small

Dhodhi is fixed for a 40 kg maund

Small Dhodhi Quantity

Small Dhodhi gains extra volumes from Producers

For example

40 gadvis becomes 44 litres

i.e. 40×1.1 = 44

So the same maund is 44litres & not 40kg

Large Dhodhi uses 160 litre plastic drums

to collect milk from Small Dhodhi

Lahori 46 litrepanda or 46kg

maund used by Large Dhodhi to transfer milk from his Toyota

Hilux tanker

to retailers’ refrigerators

Litre

for consumer

Gadvi

for consumer

Large Dhodhi’s rural Quality standard

Large Dhodhi has set a 6% fat standard for small dhodhi suppliers with

a reward and penalty system in place

Premium = (litres × actual fat) ÷ 6% base fat standard × base price per litre

Assuming Small Dhodhis 44L milk had 6.5% fat

Premium Paid = 44L × 6.5 ÷ 6% = 47.7 litres i.e. Small Dhodhi gains another 2.7litres

Governance (internal to the chain)

Figure 29: Quantity and quality along the

Kasur-Lahore chain


275

F8.2.1. Final consumers

Value chains are driven by what the final consumer values. In addition to the information

in Table 33, comments by the final consumers interviewed at the three milk retail shops

help us further understand that butterfat or cream is valued most. The only woman85

(Consumer2) interviewed in this research at Retailer1 said, “This milk has a nice aroma,

and I get lots of cream after boiling from which I make butter. Smell and taste both are

very nice. Colour of milk is good as well. I like the tea of this milk.”

Another consumer (C1) at Retailer2 said, “They [i.e. Retailer2] make yoghurt too that can

only be made from better quality milk”. These statements confirm that consumers assess

quality by the cream set on the top or by the tea86, as milk is boiled before use in both

cases. Yogurt made from the same milk is another indicator of quality.

The final milk consumers, irrespective of their socio-economic status and education, have

little understanding of various units used by the retail shops. A consumer (C3)87 when

asked about the units of fresh milk purchased at Retailer1 responded, “[I bought milk in]

litres...not sure [of the difference between kg, litre and gadvi], there should be 1000ml [in

a litre] but not sure what they do as [I have] never weighed it [milk] after buying”.

Another consumer (C5) at Retailer3 replied, “[I bought milk in] gadvi...yes gadvi is more

than 1.25 kg and kg is more than a litre...There is some difference but I am not sure

[what]”. This shows that consumers are unaware of or have little concern for standard

units.

85 As men buy milk from these fresh milk shops due to cultural norms 86 Tea typically made from loose tea leaves, steeped directly in the kettle with milk and water added and boiled for a few minutes 87 A PhD doctor

276

F8.2.2. Producers, small dhodhis, large dhodhi and formal processor

The producers are aware of the variation in units by their dhodhi. There is social

acceptance; however, of these practices as Producer1 said, “...they [small dhodhi] have

their own pot [for buying milk]. They buy in one and sell in another. They buy in gadvi

and sell in litre.” This was verified by small dhodhi who said, “We buy 1100grams88 for

a gadvi bought from producers...we give our own pot to the farmer so that he may not

dilute the milk [with water]”, which illustrates the mistrust between the two parties as

well. A few smarter producers sell milk in their own pots. “We sell milk in kg”, said

Producer2 who sells a larger quantity89 and is assumed to be more cautious of units. The

formal processors buy and sell in standard litres.

The producers generally sell mixed buffalo and cow milk. Producer1 on milk quality said,

“buffalo milk fetches better price”, which is the only understanding of quality by

producers that buffalo milk fetches a higher price compared to cow’s milk. Milk is

collected fresh by almost all small dhodhis at the producer’s doorstep without any quality

check apart from either being present at the time of milking and/or helping farmer hand

milk the dairy animals. This is due to the cultural norms as farmers feel checking of milk

is a disgrace to them, questioning their integrity. Producer1 said, “why would he [dhodhi]

smell [or test anything in our milk] if he milks with his own hands”. Small Dhodhi then

checks milk at his own property, “We daily check fat and also have a lactometer to check

milk quality...the rate is based on fat [percentage]...better price is offered [to the farmer

supplier] for buffalo milk”. Producer2 said, “Dhodhi wants to buy buffalo milk only as

88 Chain participants switched between grams, millilitres and other units 89 P2 sells 43kg to another small dhodhi, who in turn sells milk in nearby Pattoki city. He was selling to our chain’s small dhodhi six

month ago and discontinued because his demand for cash advance was not met, discussed in section 4 Weights might be another

reason of friction.

277

he has to dilute it but we sell mixed milk...if we had all buffalo milk we would get better

price.”

The producers have little understanding of the quality criteria set by the formal processor

as Producer2 said, “The companies buy on fat percent, and we cannot meet that

standard90.” The small dhodhi, however, understands the formal processor’s formula well

and said, “We sell cow milk to Nestlé that buys 3.5 to 4% fat and 27LR milk as 6% fat

[similar to buffalo milk in the informal chain].” He further said, “We sell thicker [higher

fat buffalo] milk to the vehicle [large dhodhi] to get a better rate [price]...we keep cow

and buffalo milk separate”. This separation of cow and buffalo milk for the formal

processor and the informal chain is the only grading that occurs along this chain.

The informal chains are also competing with each other as small dhodhi said, “The local

dhodhi [buying milk from Producer2 and selling in the local market] though dilute milk

half and half and makes good money out of milk sales. We talk of fat and LR, and it is

hard to then compete with a local dhodhi”, as he sell milk to large dhodhi who checks fat

percentage.

Large Dhodhi said, “We buy milk at an average estimated 6% fat”. While buying milk

from the 20 small dhodhi suppliers, he checks milk fat content using Gerber91 method and

dilution by taking lactometer reading (LR). He added, “The main measure of quality and

standard are taste of tongue92, fat & LR”.

90 Formal processor do an organoleptic test i.e. taste, sights, smell and touch. They also do LR and fat. Both have to be adjusted to get

an estimated value (price) of milk supplied. It can be safely assumed that farmers do not understand what it means. Dhodhi does not

do these tests at the farm gate. He also offers cash advance and saves farmers both time and transport; so they do not want to go to the chillers set by formal processors.

91 Milk fat content test to determine the price to be paid. 10 ml of sulphuric acid followed by 11 ml milk and 1 ml of Amyl alcohol added to butyrometer, which is then placed in a hand-operated centrifuge machine and spined for a few minutes to get an estimated

butterfat percentage in milk. 92 As organoleptic was said to be the best method to check adulteration if everything as fails

278

To encourage small dhodhis to supply more buffalo milk, Large Dhodhi has the following

formula93 through which he offers premium for higher fat, and penalises small dhodhis

for fat content less than his 6% standard at rural level:



“We prefer to buy buffalo milk which has all the desired attributes that we need but have

to buy mixed milk”, said Large Dhodhi. This preference is due to higher fat content in

buffalo milk since he has to dilute it with ice, in which case the fat percentage remains

higher despite dilution. Large Dhodhi has to buy mixed cow and buffalo milk, however,

due to farmers having both species. The average fat percentage from his total milk

collection from 20 small dhodhis was 5.7% that day.

Large Dhodhi then dilutes the milk with ice and said, “We determine an average [fat

estimate] at which our milk can reach Lahore market...The Lahore market has a demand

for 4.8% butterfat94, and we have to survive with that twelve point95 difference that is our

profit margin. In this, we have to cover all our expenses96.” Large dhodhi in partnership

with R1 and R2 is making an effort to supply better quality milk to broaden the base of

loyal customers at these shops in particular.

All three retailers have a high level of trust for the Large Dhodhi supplier, and there is no

formal quality check at the retail end. The Large Dhodhi said, “Our buyers do not check

fat. They just make yoghurt to check [milk quality], and some depend on the feedback of

customers”. Both are quality test mechanisms for retailers.

93 To be explained what it means in terms of profits while describing gross margins 94 unwritten rule 95 i.e. 6% - 4.8% = 1.2% and large dhodhi refers to this 1.2% as 12 points 96 i.e. all costs incurred and a margin kept

279

Large dhodhi supplies a litre of milk free of charge in each panda to Retailer 1 and

Retailer2; that is, he only charges for 45 litres for a 46-litre panda. Retailer1 said, “We

buy in kilogrammes and sell in litres...We get a kg of 1000grams and sell in litres which

are 950grams97...Each 46 kg panda will give us 2 litres extra i.e. 48 litres for us”. Thus

R1 and R2 (Figure 29) gain about two98 extra bags or litres per panda while selling milk

in polythene bags to the final consumer.

They also prefer buffalo milk as Retailer1 further said, “We want to have more maja

dhodh99 rather than goga dodh100 which is preferred by the consumers...Our customers are

after thicker cream and better tea [from milk]”. Retailer3 did not disclose how much his

litres weighed but vaguely said, “We sell [milk] in both gadvi... at 60 [Rs/gavdi] and litre

at 55 [Rs/litre]”. It may be assumed that he is exploiting units for his own benefit as well.

Retailer3 does not check the quality of milk bought from the Kasur-Lahore chain’s Large

Dhodhi although he has a specific formula for other dhodhi suppliers. This check is a

common traditional practice in Lahore market called “kaan maar kar” described below by

using an actual scenario from this research.

Retailer3 boils 2400ml of milk, supplied by his dhodhis, at a very high heat in a large pot.

The quality standard is that the milk boiled should give 400 grams of milk solids called

khoya. There is a concession however of 20 grams given to the dhodhi seller. The logic

given for this is that some milk burns while boiling. The standard therefore becomes 380

grams. In this case, the actual khoya obtained after boiling was 330grams that is 50 grams

less than the 380 gram standard.

380grams − 330 grams = 50grams

97 As mentioned by Retailer 1 who switches between grams and millilitres. The reason is that the Lahori maund is both kg and litres (Figure 29) 98 In total, 3 bags or litres extra as an additional litre is provided by large dhodhi free of cost 99 buffalo milk 100 cow milk

280

The 400 grammes standard remains important and relevant, however, as it is used to

determine the price per gramme of khoya. The prevailing average Lahore market milk

price given by retailers to dhohis is 2200Rs per 46 litres Lahori maund, also called panda.

This price is divided by the 400 grammes standard to get the price per gramme of khoya,

which is 5.5 Rs.

2200Rs per 46 litres ÷ 400grams = 5.5 Rs per gram

Now the per gramme 5.5 Rs price is multiplied by the 50 grammes that was less than the

380 grammes standard, which determines the penalty that the dhodhi supplier has to pay

for not meeting the 380 gramme standard.

5.5Rs per gram × 50 grammes less than the 380 standard = 275 Rs

The final price paid to the dhodhi supplier is therefore determined by subtracting the

penalty price from the average market price.

2200Rs per litre 46 litres − 275 Rs penalty = 1925 Rs per 46 litre panda

The price, therefore, comes to 42Rs/litre determined by this complex formula based on

quality assessed by Retailer3.

Table 34 estimates gross margin for each chain actor based on actual average transactions

recorded. The estimates exclude owner operator’s opportunity cost of labour and

disregard interest foregone on the capital invested. For retailers, the milk processed into

yoghurt and other forms have not been estimated to keep the estimation simple. The cost

associated with processing have been excluded accordingly.

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Table 34: Physical and financial flows and capital invested by each actor along the Kasur-Lahore milk value chain


Volumes Total production of 7

gadvi or seer from one

milking cow per day of

which he sells 3 gadvis

based on Small

Dhodhi’s 1.1 litre

collection pot

150 litres of morning

collection only per day

from 6 producers & from

his own animals and those

owned by his extended

family.

Sells 32Lof buffalo milk

only to large dhodhi & rest

to Nestlé where

27gadvi ×1.1=29.5L

→

(29.5×6.5)÷6=32L

i.e. based on extra

volumes procured from

the producers and 6.5% fat

Large Dhodhi collects 1400

litres that includes 45L from

their own animals.

Collects mainly morning

milking (1200L) but there are

“around five maunds”

(200L) from evening milking

as well.

The 1400L total collection

includes 1200L milk and

200kg ice (6milk:1ice)

Retailer1 has the chain’s Large Dhodhi as his single supply

source with 5panda101 (230L) delivered once each afternoon.

He in turn sells 161 L of raw fresh milk to the final consumers

at the shop and do home deliveries of another 69 L.

230 L÷0.95= 242 L as selling 950 ml i.e. a smaller litre to the

final consumer

Retailer2 buys 450 L from Large Dhodhi as his only supplier.

Of this only 90L is sold as loose fresh milk and the rest is used

to produce yogurt or sold as hot and chilled flavoured milk.

He does not do home deliveries.

450 L÷0.95= 474 L as selling 950

Retailer3’s shop outlet sells 30 maunds102 (1380L) of milk

per day, half of which is procured directly from the producers.

Kasur’s informal chain’s Large Dhodhi delivers a small

quantity of one maund (46L) only. Retailer3 also has three

other large dhodhi suppliers and occasionally buys from other

suppliers too.

1,380L÷0.95= 1,453 as assumed to be selling 950 ml too

though did not disclose the actual volumes on his units

282


Price at each step 40 Rs/gadvi 43.75 Rs/litre 47.5 Rs/litre Buying from Large dhodhi

Retailer1: 47 Rs/L

Retailer2: 49 Rs/L

Retailer3: 50 Rs/L

Selling to final consumer

Retailer1: 50 Rs/L

Retailer2: 52 Rs/L

Retailer3: 55 Rs/L

Margins (price cost

for Ps & price for

all else)

-12Rs1 4 Rs / unit 4 Rs / unit Retailer1: -0.5 Rs/unit

Retailer2: 1.5 Rs/unit

Retailer3: 2.5 Rs/unit

Retailer1: 3 Rs/unit



Average variable

cost per unit

52Rs as

1price :1.3cost

38 Rs/litre 43 Rs/litre Retailer1: 48 Rs/unit



Estimated Revenue

/ day (P*Q)

120Rs 1400 Rs

66,500Rs




Estimated variable

costs per day

156Rs 1,220 Rs that includes

1080 Rs paid for

27gadvi milk

51 Rs electricity bill

72 Rs allocating for

hired labourer

17 Rs phone call

60,433 Rs that includes

52,500 Rs for milk

4,200Rs vehicles’ fuel

2800Rs ice blocks

700 Rs hired labour

167 shop rent

67 Rs phone calls

Retailer1: 11,530 Rs that includes

10,810 for milk

175Rs ice blocks

53Rs electricity bill

175Rs polythene bags to package milk

167 Rs hired labour

133 Rs shop rent

17 Rs phone bills


22,050 Rs for milk

175 Rs ice blocks

367 Rs electricity & gas bill

343 Rs polythene bags to package milk

700 Rs hired labour

50Rs shop rent

17 Rs phone bills

283



69,000 Rs for milk

1,000 Rs ice blocks


275 Rs polythene bags to package milk

417 Rs hired labour

150 Rs shop rent

67 Rs phone bills

Gross margins per

day from milk

loses 36Rs


Retailer2: 930 Rs

Retailer3: 8,586 Rs

Capital assets

invested

4.1 million Rs for 3.5

acres of land 14

buffaloes and cows

0.8 million Rs as

cash advances to 6 milk

producers

few collection and

measuring pots

motor cycle to deliver

milk at Nestlé’s chiller

10km away

5.2 million Rs in total of

which

4 million Rs as cash

advances to small dhodhi

suppliers and credit to retail

shops

1 million Rs worth of two

Toyota Hilux vehicles to

collect and deliver milk

0.2 million Rs worth of

milking testing equipment103

each worth Rs 10,000

provided to the 20 small

dhodhi suppliers

Retailer1: NIL as Large Dhodhi invested 0.2 million Rs to

take possession of the shop

two refrigerators

and utensils to sell milk

Retailer2: 0.5 million for

pots to make traditional sweets and yogurt and to boil milk

a refrigerator to store milk

Retailer3: 1 million Rs in

the shop front showcasing

three refrigerators

a number of pots of different sizes to handle, boil and store

milk and to make yogurt

Another 0.2 million Rs as cash advance to a direct farmer

supplier


103 The equipment includes a bytrometer, sulphuric acid & amyl alcohol and a manual centrifuge machine

284

1Producer’s cost price estimates based on author’s detailed farm economic analysis as part of his PhD research (Chapter 4). Assuming that Producer1 produces less than

2,300litres per year based on which his price cost margin is 1price:1.3cost

Note: For Retailer2 & Retailer3 the cost of methane gas used to process milk has been excluded. Similarly, the cost of hired labour for these two retailers, polythene bags used

for packaging milk and shop rent has been halved too to get a better estimat for milk only and not processed in any other form.

285

The average price margin between Large Dhodhi and Retailer1 and Retailer2 is three Rs

per litre, and each retailer sells at a different price. Large Dhodhi and Retailer3 earn the

highest revenues due to the larger volumes they handle. Producer1 is worse off getting

negative returns from his dairy enterprise. Producer 1 though has invested capital only

second to Large Dhodhi. “Farmer does not really save anything from milk; the daily wage

labourers are better than us. [Farmer keeps livestock] just as a symbol of pride in the

village to have so many animals”, said Producer1. This illustrates the low returns from

dairy enterprise and that the animals are more a source of pride rather than an income

generation enterprise.

F8.3 Product seasonality, price determination, pricing power dynamics and

information flows

This section describes the seasonal aspect of milk productions, including price in the

chain, and demand. Pricing mechanism (Figure 30) and price information flows (Figure

31), and associated power dynamics have also been explored. The section examines the

situation in the following sequence:

Final consumer’s response to price change

Retail urban pricing

Price between small dhodhi and large dhodhi

Farm gate Rural pricing

Table 35 summarises the responses of chain actors and consumers on milk supply and

demand. On milk demand, half of the 14 consumers interviewed at the three retail shops

said that their household consumption is highest in summer and decreases in winter.

Retailers supported the consumer’s statement as Retailer1 said, “Yes there is a shortage

of milk in summer and excess supply in winter. Sales are higher in summer.” While

retailer2 said, “not much difference at our shop as in winter there would be less yoghurt

286

but more hot boiled milk [sold]. Only a panda104 or two less in winter though [at our

shop]”. This suggests a change in the form of the product sold too in winter.

On milk supply, the producers pointed out their minimum and maximum cow and buffalo

milk production months with responses summarised in Table 35 showing the opposite

supply and demand trends associated with summer and winter seasons. According to the

responses of producers in this study, the production for both buffalo and cow starts

decreasing in mid-April, whereas summer starts from mid-May when demand for milk

and other dairy products increases.

104 Panda is 46 L at urban retail level called Lahori panda, discussed section 2

287

Table 35: Punjabi105 and Gregorian calendar and buffalo & cow milk production / supply for Kasur Lahore milk value chain

Maximum consumer demand in

peak summer months

Minimum consumer demand in

peak winter months

Chet

(14 Mar-

13 Apr )

Vaisakh

(14 Apr-

14 May)

Jeth

(15

May- 14

June )

Harh

(15

June- 15

July)

Sawan

(16 July-

15 Aug)

Bhadon

(16

Aug-14

Sept )

Assu

(15

Sept- 14

Oct)

Katak

(15 Oct-

13 Nov)

Maghar

(14

Nov- 13

Dec)

Poh

(14 Dec-

12 Jan)

Magh

(13 Jan-

11 Feb)

Phagun

(12 Feb-

13 Mar)

Minimum buffalo and cow milk

supply

Maximum Buffalo & Cow Milk


105 Both Punjabi and Gregorian calendar is used which came up through the field interviews. Chain participants referred to both invariably in their conversations, particularly the producers

288

Figure 30: Pricing mechanism along the Kasur-Lahore chain

Data Source: Author’s Field research

Farm gate price for producerschange with season

i.e.

increasing in summer

and

decreasing in winter

Price between Small Dhodhi & Large Dhodhi

fluctuates (up & down)

regularly with demand and supply.

This price is based on the formal processorprices offered to dhodhi suppliers

Milk Producers Small Dhodhi Large Dhodhi Retailers

Formal Processor(s)

Rural Market Urban Market

Retail price set for the whole year by the government

Price between Large Dhodhi & retailers is fixed for six months to an year &

worked around the price set by the government

& influenced by big market players.

Retailers get around the government price it by altering units and Large Dhodhi by altering quality

i.e. dilution

• Final consumer of informal chains is price sensitive

Governance (internal to the chain & external i.e. industry level)

289

Figure 31: Price information flows along the Kasur-Lahore chain


Producers check

• prevailing rural milk prices

• those offered by other small dhodhis

• communicated by small dhodhi buying milk

Small Dhodhi checks

• Prices paid by formal processors to dhodhis in the rural market


Formal Processor(s)


Retailers are

• Aware of the retail price set by the government

• the prices charged by their competitors in the locality where they operate

• Large operator Retailer3 is also aware for the rural prices as he is also buying directly from rural market too

Information flows (chain and industry level)

Large Dhodhi checks


• Is aware of the annual urban price set per litre by the government

290

F8.3.1. Final consumer’s response to price changes

Final consumers at the retail end, particularly those in the lower socio-economic group,

are price sensitive, yet seek better quality milk. A consumer (C4), who works as a daily

wage labourer interviewed at Retailer2 said: “The shopkeepers should be asked to sell

good milk...I work as a labourer and carry bricks and get 2 Rs per trip [from the ground

floor to multi-storey roof top]. It is really hard to make money but when it comes to

spending it just vanishes106.” While Retailer2 said, “When we increase the price it

becomes an issue for the customers”. This shows consumers are very price conscious.

F8.3.2. Retail Urban Pricing

The retail price in urban markets is fixed on an annual basis by the city district

government. The price is fixed in mid-April to mid-May (Table 35, Figure 31) for the

whole year. For 2012, a price of 57 Rs per litre had been fixed. However, the fixed price

is not strictly followed by the retailers and works as a loose benchmark for prices both

higher and lower. Retailer1 said, “(our) price is even less than current government price.

There is so much variation in Lahore city, and no one is really following the government

fixed price. It starts from 30 Rs and exceeds 70”. While Retailer3 said, “The price in the

Lahore milk market is fixed for a whole year. Generally, the prices are fixed in

Veshaikh.107”

There is no solid basis to determine this benchmark government retail milk price for fresh

milk. The big players, who are dhodhis as well as retailers, influence the government

pricing decision as Retailer3 said, “Retail price for milk and yogurt have been given [by

government to retailers] without any consideration of costs involved... we have [name],

who is the President of Dhodhis108 [in Lahore milk market] and he doesn’t consult anyone

106 Referring to high inflation and very low purchasing power of Rupee

108 Some local organisations with no clear structure and official status

291

else [while fixing the price and negotiating with the government109]”. Retailer3 sets his

own price at the shop and said, “Yes we do check the prevailing prices in our area and

use a price based on our business margins and considering the welfare of our

customers...we communicate it to our dhodhis to set a commonly agreed price...different

shop keepers still sell at different rates [prices]. We have eight to ten shopkeepers in this

area...”. This illustrates that while setting a price he considers the costs and margins, the

price of competitors, the arrangement with dhodhi suppliers and probably the price that

his consumers110 in that particular locality would be able and willing to pay.

The two retailers, Retailer1 & Retailer2, are being given a price by Large Dhodhi.

Retailer2 said, “We do not check price [from elsewhere in the market]...We just take the

price given by them [Large Dhodhi]... there is a binding to sell the same quality and at a

[fixed] margin of 3 Rs / litre”. Large Dhodhi on the price between his retailers said, “The

price fixation in Lahore market is based on the demand and supply principle”. Large

Dhodhi, being the link between rural and urban markets, has to manage these price

fluctuations111 (Figure 30 and Figure 31).

F8.3.3. Price between Small Dhodhi and Large Dhodhi

This price determination between Small Dhodhi and Large Dhodhi is closely linked to

the price offered by formal processors and fluctuates with supply and demand forces.

Processor’s price is a key source of price information for these two actors.

Small Dhodhi said, “Our price changes every two months with Large Dhodhi...as soon as

he demands more milk we ask for a better rate...I am educated, and I check the rate of

[milk] factories112...”

109 As the bigger players bargain on final price with the government representatives 110 Depending on the socio-economic group 111 Possibly by alerting the milk quality that is increasing or decreasing the amount of dilution 112 formal processors

292

Large Dhodhi said, “The price is fixed between the two parties [Small and Large dhodhi]

mutually... the milk factories bring down the rate... [We] used to check [prices] previously

but now we have our own rate”. This shows a fair degree of independence in price fixation

by the Large Dhodhi.

Large Dhodhi keeps buying milk from Small Dhodhis in winter when there is excess

supply and less demand though retailers have the option to reduce procurement based on

final consumer demand. The Large Dhodhi then sells milk he is unable to sell to retailers,

to the formal processors at a lower price.

F8.3.4. Farm Gate Rural Pricing

At the rural farm gate, price fluctuations with summer and winter are linked to the

seasonal nature of milk production. The prevailing farm gate prices are given to producers

by the Small Dhodhis who are also the producers’ key source of price information. The

formal processors lower the price with excess supply associated with lactation and peak

production of cows and buffaloes. Small Dhodhi said, “The price paid to

producers...varies with summer and winter... The summer price goes until October as

when powder plants113 start operating there is an excess supply of milk and price goes

down...the price for farmer goes down...but we keep getting the same price [from Large

Dhodhi] ...”

Small Dhodhi also pointed pricing practice of formal processors and said, “...[formal

processors have a] chor114 rate, which means a contractor supplying bigger volumes would

get [higher price]...[but different price] displayed on rate list for public to view, whereas

they [contractors] get a much higher price”, indicating the price practices of formal

processors.

113 formal processors who produce reconstituted milk using cheap imported powder 114 Hidden price

293

Small Dhodhi further said, “There is plenty of milk ... in winter whereas hardly enough

milk to meet the demand in summer...The processing companies make money out of

winter milk when there is access supply”, again pointing to formal processors using milk

seasonality for their own benefit.

Small Dhodhi informed, “[In summer] dry animal milk fat goes from seven to eleven in

fat content, and this is of great benefit to dhodhi. We though get a loss from factories as

when butterfat rises the LR goes down. For local dhodhi, 10 kg milk of sujjar [fresh

lactation] buffalo and 5 kg milk of tokkar [dry] buffalo are same.”

Producer1 said, “Rate goes down in winter, and they [dhodhi buyers] increase it in

winter...The farmer does not fix the price but dhodhis get together and give the price to

the farmer...price is verified by [Producer1] monitoring prices in [nearby] Pattoki city...”

Producer2 said, “We don’t really have to check prices as [many] small dhodhis come and

make us offers when there is high [market] demand”. Therefore, the producer then comes

to know of the prevailing price.

F8.4 Facilitating functions of financing and payment schedules, relationships and

power dynamics

There is an intricate set of facilitating functions in the chain that enable it to function in

the absence of formal contracts. This section will describe the financing and various

service functions provided in the chain and illustrated in Figure 32. It will examine the

duration and description of relationships, conflict and problem-solving mechanisms,

power dimensions in seller’s role by exploring blocking supply or changing buyer, and a

buyer stopping payment for milk supplied or changing supplier. This examination by

studying interactions between Producers and Small Dhodhi; Small dhodhi and Large

Dhodhi; and Large Dhodhi and Retailers.

294

Figure 32: Financing, relationships and power dynamics along the Kasur-Lahore chain


• Ps takes initial advance from Small Dhodhi to meet monthly household needs & also borrow whenever a need arises

• Retailer1 borrows from Large Dhodhi on need basis

• Cash sales at the shops but some customers buy on credit and pay after a month

• Small Dhodhi takes advance from Large Dhodhi to secure winter sales when access production

Milk Producers Small DhodhiLarge

DhodhiRetailers Consumers

Seller & Buyer relationships (chain level)

Cash Advance

Regulatory of Payments

• Opportunist though some consideration of Small Dhodhi being local

• Price, cash advance and money flows take priority over relationship

• Mistrust as both parties accuse the other of dilution

• Small Dhodhi gets paid by Large Dhodhi every eight day with 4 days payment revolving

• Long term relationship and high level of trust

•Some home deliveries as a service by Retailer1 & Retailer3

•Accounts settled once every month

Nature or Relationship / Trust

Services

• Higher level of trust between Small Dhodhi and Large Dhodhi

•Large Dhodhi provides services such as feed supplements to Small Dhodhi

• Small Dhodhi provides services such as feed supplements to producers on demand

•Retailer1 & Retailer2 pay Large Dhodhi every 2nd

day whereas Retailer3 pays daily

295

F8.4.1. Producer and Small Dhodhi

At his tier of the chain, the Small Dhodhi has to extend initial cash advances to the

producers to procure milk (Figure 32). These advances are used by farmers to meet their

household needs. Some even use the small dhodhi’s money to expand their herds.

Producers also borrow money from small dhodhi, whenever a need arises. The accounts

between the two are settled once each month though the advance is kept by the producer

until the business dealing wholly ends. Small Dhodhi also supplies feed supplements for

livestock if asked by the farmer.

Producer1 shared that Small Dhodhi has advanced him 4500 Rs for procuring milk and

said, “We get payment [from Small Dhodhi] whenever a need arises”. Small Dhodhi said,

“The house grocery and wife’s expenses are all dhodhi’s responsibility...Once the farmer

owns a few animals, he then asks dhodhi to buy him additional animals. Farmer says that

they only feed the animal whereas milk is yours [small dhodhis’]... [For this business]

you always need to have cash in your pocket.” Small Dhodhi further elaborated, “For

example to buy 10 litres of milk [from a farmer] a dhodhi needs to have 50,000 Rs in the

pocket for advance and the same amount in circulation”. This illustrates that small dhodhi

has to meet continuous demands made by producers.

The balance of power is in the producer’s favour. They can hold small dhodhi’s money

as pointed out by Producer2 who said, “at times, in fact, the money of dhodhi is blocked

by the farmer [for a few months] as animals go dry”. Producer2 explained that the

accounts are settled once the animals start milking. Producers can also easily find other

buyers, particularly in extremely hot summer months when milk production goes down

and demand is higher, but all outstanding amounts owed to their previous dhodhi buyer

have to be returned. Producer1 said, “Yes [I can find a new milk buyer easily]...I am even

now being asked by other dhodhis for milk...we will have to clear any outstanding amount

296

owed [to current small dhodhi if a change is made]”. Small Dhodhi said, “the farmer...has

many other buyers particularly in four-five months of hot summer [when production goes

down and demand increases], where he would have many [dhodhi] buyers chasing him

for milk. It is opposite in winter”. This means this balance of power changes with season

though cash advances still give more power to producers.

There is a relational aspect to the dealings between producers and small dhodhis.

Conflicts if any are resolved through the involvement of other villagers as Producer2 said,

“These [dhodhis] are local and from the same baradari115”. Prices are important but a cash

advance is even more important as Producer1 said, “...even if he [Small Dhodhi] gives us

a Rupee less [than the market price], we do consider that he [Small Dhodhi] is our

neighbour, however, if in return he does not care about us, we can choose to sell [milk]

elsewhere. He further explained, “Timely payment is important for us to meet our needs

or else we are compelled to change [dhodhi]...conflict arises if he does not pay us [more

money on demand]”. Small Dhodhi thinks producers are greedy and said, “Sometimes

money is not even needed, and farmer keeps asking just to probe us”, that is producers

explore the possibility of getting more money from Small Dhodhi.

There is friction and mistrust at this tier of the chain as both parties suspect each other of

diluting milk. Producer1 said, “He [Small Dhodhi] may accuse us of dilution [milk with

water]” and because of this the business relationship is usually short. Small Dhodhi said,

“We can capture dilution in milk if any by the farmer and that is why we are not able to

maintain long term relationship with our supplier farmers”. Small Dhodhi described the

relationship with producers as “purely ... business dealings”, and he further said, “Some

buyers are going with us for many years, and others are very seasonal”, which illustrates

115 Kinship as the Pakistani society has a very strong network of kinships at the rural level though it is dominant in all walks of life

(Lieven, 2011).

297

sellers in summer only. On managing business dealings with advance extended Small

Dhodhi said, “If we want to stop buying milk from someone or can guess that he is going

to go to another dhodhi, we just stop making regular payments. An estimate for milk

supplied is done on 1st of the month but [I] then block the payment until the account is

balanced”, which he possibly does in excess milk supply months in winter.

F8.4.2. Small Dhodhi and Large Dhodhi

At this chain tier, Large Dhodhi extends cash advances that can also be understood as

interest-free loans to his Small Dhodhi suppliers. These advances are settled only when

the trade comes to a halt. The small dhodhi is paid every eighth day. Small Dhodhi said,

“We keep our buyer’s [Large Dhodhi] money under us...he pays us every twelfth-day

making payment for eight days [for the milk supplied] keeping four days of payment

revolving”. He further explained, “For example with our milk supplies [to Large Dhodhi]

we keep 300,000 Rs [extended as cash advance by Large Dhodhi] with us as he may kick

us in winter [when there is excess supply] since there is no written contract or litigation

[in court to resolve dispute]...”. This means the advance is security for Small Dhodhi to

ensure his milk will be purchased in winter when there is excess supply.

Large Dhodhi ensures a consistent source of supply through advances. He responded,

“We have invested around 2.5 million Rs as advances to our milk suppliers. This

[account] will close or is settled only when the supply of milk stops... We meet all the

needs of our suppliers ... for example advance money, wanda116 etc. We fulfil all of their

needs such as at marriages or in case of death117”. Thus, Large Dhodhi works as a bank to

meet the need of suppliers.

116 balanced concentrate mixture for animals 117 Marriage and funerals entail huge financial costs

298

Although the balance of power is in favour of Small Dhodhi with the cash advance taken,

both parties can find new business partners. Small Dhodhi said, “We can block the supply

[of milk to Large Dhodhi]... [I] can easily find a new buyer of milk.” Large Dhodhi

responded “[I] can easily find new suppliers [to meet] as much [milk] as required based

on my relationship and love”, which shows that he is well connected.

There is a higher level of trust and longer lasting relationships at this tier as Large Dhodhi

said, “Other people take cheques or stamp paper [as a guarantee for the advance money

extended], but we just extend advance money to our suppliers”. He further said, “We trust

them, and they trust us...We have an old relationship with [name of Small Dhodhi], and

he has been supplying milk for last 4 to 5 years...We treat all our suppliers equally...and

we treat each other with respect...If a conflict arises, I go and talk and the things are sorted

through discussions”. This was seconded by Small Dhodhi who said, “No [conflict with

Large Dhodhi] buyer [as he] is really nice”.

F8.4.3. Large Dhodhi and Retailers

Large Dhodhi also has extended cash advances to some milk retailer buyers. Retailer1

and Retailer2 pay for the milk supplied to them the day following the delivery, and any

outstanding amount is settled at the end of the month. Retailer3 pays for milk the same

day it is delivered.

Large Dhodhi said, “Some retailers keep our money, some have 0.4 million that they owe

us...” Retailer1 said, “If we need money we borrow [from Large Dhodhi]”, which means

some retailers hold Large Dhodhi’s money, only to be settled if the business relationship

concludes.

There is a high level of trust on Large Dhodhi at this tier, and the relationships are quite

long term due to the efficient payment system and better quality milk provided. Retailer2

said, “We are being supplied milk [by Large Dhodhi] for the last 20 years...We always

299

make payment for milk on time, and that is why this relationship has been going well for

so long”. Retailer2 responded, “Relationship is important, but more importantly they

[Large Dhodhi] provide us good quality milk which means satisfied consumer and more

consumption [sales]”.

Retailer2 further said, “No we do not have any conflict as we get the desired quality of

milk...We just trust each other... we just love and take care of each other. If we had a

typical business attitude this relationship will not have lasted this long”. Retailer3 said,

“In my 12 years of experience in milk business I have not seen a person as fair [in business

dealings] as Large Dhodhi118 who does not waiver from his word. I trust him as he supplies

less milk119 [compared to other suppliers] but of good quality”. Retailer3’s father had

known Large Dhodhi and both had long-term relationship.

Both parties are free to part ways but they talk to each other and problems if any are

resolved through discussion as Retailer1 stated, “[I] make them [Large Dhodhi] aware if

there is any complaint by the customers...and they do address our concern”. Retailer2

told, “We never give chance [of conflict] to each other...This is a business so there may

be issues at times...We never argue with each other. The milk is generally sold to final

consumers on a cash basis at the retail shops though some customers buy on credit and

pay monthly.

118 Mentioned name 119 large dhodhi supplies only 1 maund (46L) of the 30 maunds (1380L) sold by R3

300

Chapter 8 Appendix G: Results: Case Study 2: Okara - Lahore fresh,


The informal fresh, unpackaged milk chain outlined in Figure 33 has five tiers before the

product reaches the final consumer. In addition, the formal processing sector operates

parallel and at times integrates with the informal chain. It originates from rural Okara

district 135km south-west of Lahore city, to which the milk is being supplied. The district

in the southern irrigated plains of Punjab lies between the rivers Ravi and Sutlej (Figure

23). It is famous for rearing local Nili-Ravi water buffalo and Sahiwal cattle breeds.

Figure 33: Okara-Lahore chain120 model and product physical flows

120 Producer household estimates as large dhodhi collects 2350L milk ÷ 35small dhodhis = 52L as each of the 3 medium dhodhis have

approx. 10 small dhodhi suppliers & large dhodhi has 15 direct small dhodhi suppliers. Now 52L ÷ 10Ps =5.2L therefore 2350L ÷ 5.2LperP = 452 Ps approx. & Consumer household estimates are based on 2011-12 Household Income Economic Survey (HIES).

Average per capita household size → 6.36L per month÷30day = 0.212Lper day× 6.41 member per household=1.4L → 2350L ÷ 1.4 =

1679 households approx

Producer1 + Producer2

+ approx. 450 milk producers

Small Dhodhi1+Small Dhodhi2

+28 small dhodhis

3 family owned specialized

retail milk shops

including Retailer1 & Retailer2

+ 5 other retailers

1679 consumer households

1 Large Dhodhi

Formal

Processors

1 Medium Dhodhi

+2medium dhodhis

15 small

dhodhis

Mega

Contractors

Estimated 10 million consumers given a

5% market share

301

G8.1 Introduction of value chain actors, product physical flows and spoilage risks

This section introduces informal Okara-Lahore value chain actors (Figure 33) studied

from producers to retailers and in a few important areas in relation to the operation of this

chain, namely:


source of income, and number of years in the business;




business operations by each participant (Table 36), and

Risks of spoilage in the absence of proper cool chain infrastructure

Eight actors are introduced:

1. Milk Producer1 is 50 years old and has no formal education. His household has a

total of 7 members. He has been farming since childhood, which is his only source of

income and knows no other profession. Producer1’s milk buyer Small Dhodhi 1

resides in the nearby Okara city but he and his ancestors are from same village as

producer1. He is 45 years old and has no formal schooling. In addition to milk

collection, he runs a small grocery store in Okara city. Small Dhodhi1 has a household

of six members. He has been collecting milk for the last 8 years. He only buys milk

from the morning milking.

2. Milk Producer2 is 36 years old and holds a M.Sc. in Mathematics. He lives in an

extended eight member family household of which five are his immediate family that

is, his wife and children. Producer2 has been taking care of his family farm since a

very young age. Apart from being a farmer, he is also an elementary school teacher.

302

3. Producer2’s milk buyer Small Dhodhi 2 is from the same rural vicinity as Producer2.

He is 35 years old, single and has eight years of formal schooling. He has been

collecting milk for the past twelve years, and it is his only source of livelihood.

4. Medium Dhodhi buys milk from Small Dhodhi1 and Small Dhodhi2. He is from the

same rural area. He operates from a small shop at a bus stand called “adda121”, which

is a midpoint between rural village roads and is quite near to the main highway.

Medium Dhodhi is 37 years old and holds Master’s degree in Education. He is a not

married and has been in the milk collection business for the last three years. Medium

Dhodhi also operates from another adda at a nearby location and sells milk to a

different chain’s large dhodhi. He is also a school headmaster.

5. Large Dhodhi is from a powerful Gujjar clan that dominates the Lahore milk market.

He is based in a low socioeconomic locality of metropolitan Lahore city. Large

Dhodhi is 36 years old and has ten years of formal schooling. He has been in the milk

collection business for the last sixteen years and recently started a real estate business

in partnership with his cousins. Large Dhodhi then supplies milk to eight retail shops

in Lahore city of which four belong to his close relatives. This chain is integrating

vertically at the retail end, as it is family business owning retail shops. In addition to

his own collection, Large Dhodhi’s truck also collects 3000L milk for extended family

members for which they are charged on a per container basis.

6. Two specialised milk retailers (Retailer1 and Retailer2) who buy milk from large

dhodhi were interviewed in Lahore city. Data from ten consumers interviewed at these

two retail shop will be used in the later sections. Another two relatively large milk

121 Bus stop in Urdu language or the centre of some activity. Central collection point of informal chains in this case.

303

retailers, who were being supplied milk by the same Large Dhodhi, were approached

as part of this research but declined to be interviewed.

7. Specialised Milk Retailer1 owns a Gujjar122 milk shop in a lower middle-class socio-

economic area of Lahore city. Retailer1 is closely related to the Large Dhodhi

supplier. He is 23 years old and has seven years of formal schooling. He is married

and lives in an extended household of 10 members. Retailer1 has been operating this

milk shop for the last five years.

8. Retailer2 also operates a retail milk shop owned by the same Gujjar family as

retailer1 in a lower middle-class socio-economic area of Lahore. He too is a cousin of

Large Dhodhi. Retailer2 is 42 years old, has only four years of formal schooling and

has a household of five.

9. Formal Processors operate outside but are linked to the informal Okara chain as

illustrated in Figure 33. These processors do not have a chiller in producer1’s village

as he said, “There are no companies here only addas. They [formal processors] only

deal with dhodhis and not the farmers. Another team123 buys milk from different

chaks124 on bicycles and pays the 8th day125. Their price is also 1400 Rs/maund”. This

pricing shows no price difference between the two systems at the village level.

Producer2’s village has multinational Nestlé’s village milk collection centre with a chiller

installed. Apart from our chain’s small dhodhi2, he sells milk to Nestlé too and said,

“Company [formal processors] gives a fixed price and does not give any incentive for the

higher fat content...company buys through the same informal contractors at their chillers

who give us the same price as local dhodhis126”. The statement highlights that there is no

122 1st name omitted to protect the identity. Shop named after an elder of the family 123 Engro the 2nd largest processors has buyers doing collection on its behalf 124 Villages 125 In comparison they get cash advance from their small dhodhi buyer in the informal chains 126 Not sure if this is factual but it represent farmer’s understanding

304

incentive for higher fat content offered by the formal processors whereas the dhodhi gives

a relatively better price for higher fat content buffalo milk to the farmers.

Large dhodhi sells any unsold milk and excess winter production to the formal processors

and said, “[winter months when] there is plenty of milk at the back [rural suppliers] and

less demand [in urban Lahore market], and we then sell to companies at a loss...[we sell

to] any company where we find a relatively better rate” (Figure 33).

Table 36 demonstrates that collection and distribution, using transport is the key function

carried out by the dhodhis, though this transport is not refrigerated. The two retailers

perform overnight storage using refrigerators and retailer1 does some processing. The

chain also generates 979 employment127 opportunities. The milk producers, large dhodhi

and retailers work for a substantially large number of hours in their enterprises. The chain

works every day of the week with the only exception being the holiday of Gyarwee128

Sharif each month; a day in Islamic calendar when producers are said to give away their

milk to the needy for free.

127 Average 904 at farms as an estimated 452 farms household with 2workers taking care of livestock + 45small dhodhis + 3medium dhodhi and their 3 record keeper + large dhodhi brothers their 3 loaders and 2 drivers +8 retail shop owners & 2 workers on average

at each shop 128 11th in Urdu language

305

Table 36: Technology and infrastructure, labour and time along the rural Okara-urban Lahore milk value chain

Actors Producer1 &Producer2 Small Dhodhis 1 & 2 Medium Dhodhi Large Dhodhi Retailers 1 & 2

Physical

functions of

transport,

storage and

processing

Producer1 & Producer2:

No transport or storage

Some milk processing for

households usage only

Small Dhodhi1 & Small

Dhodhi2: Both require

transport i.e. motorcycles to

collect and deliver milk

No transport, storage or

processing required

Transport i.e. collection

from rural areas and

delivery to urban shops

using a truck and blue

plastic pots

storage with ice during

transport only

Both shops store milk in

refrigerators. Ice regularly used to

preserve milk, as there are regular

and long electricity breakdowns

Retailer1 processes milk into

yoghurt and lassi

Retailer2 does home deliveries on

motorcycle

Labour Producer1: 3 household

members including women.

Producer1: 1 hired labourer

and 1 household member

Small Dhodhi1

&

Small Dhodhi2:

Sole operators

Operator manager and has

hired one record keeper/

milk tester each at two

collection points

The 2nd collection point

sells milk to another large

dhodhi buyer

3 brothers owner /

manager operators who

take turns

4 hired labourers to

checked milk quality at 4

collections points and for

loading unloading

2 hired drivers, one for

milk collection and

another for delivery

Retailer1: 2 brothers

Retailer2: Father and son

Time along

the chain (per

day)

Producer1: 8 to 10 hours

per day for two people. He

said, “Livestock takes 8 to

10 hours per day for two

people. One person has to be

with the animals for the

whole day.”

Producer1: 12 to 16 hours

per day for hired labourer

and household help

Small Dhodhi1: Eight hours

from 5:00 am to 1:00 pm

Small Dhodhi2: Five hours

from 7:00 am to 12noon

Owner manager and

record keeper’s four hours

from 9:00 am to 1:00 pm

to record volumes

supplied, test fat content

and transfer milk onwards

to the large dodhi’s truck

Eighteen-hour operation

from 6:00 am to

12midnight from

collection to final delivery

& truck’s return to the

rural Okara ice factory

base

Retailer1: Eighteen hours as shop

opens at 6:00 am to 12mid night

Retailer2: Twelve hours i.e.

6am to 12noon

& 6pm to 12 midnight


306

Producers do not face the risk of physical spoilage, but the level of risk varies from small

dhodhi to the retailer. Small Dhodhi1 said, “in summer milk does get spoiled...at times

the whole collection gets wasted...if the truck [Large Dhodhi] is late...my collection

wasted twice this month...we do not add ice as we have to give sample [to test fat

percentage]”. Small Dhodhi does not use ice since Large Dhodhi pays a premium to him

for higher fat content, suggesting small dhodhis are prepared to accept the risk to gain the

higher price.

Large Dhodhi manages risk by collecting milk and carrying it to Lahore in relatively small

128 L and 160 L blue plastic cans129. Large Dhodhi said, “No it [spoilage] is rare, only if

we get late [on our way to the city] or ice [used to dilute milk] is not [of] good [quality]

but not the whole quantity [spoiled], just a matti130”. Retailer2 said, “Yes [milk does get

spoiled] several times...just recently a whole matti was spoiled”, which illustrates that the

spoilage risk increases downstream.

G8.2 Consumer value, quality determination; grading and quantity measurements

along the Okara-Lahore chain and gross margins


Milk quality attributes ranked priority wise by all chain actors and their aggregate in

Table 37

Milk quantity units and quality aspects along product’s physical flows (Figure 34),

quality sought by buyer at each step and how is it assessed;

From producer to retailer, rewards associated if any for the seller for better quality,

grading and quantity units for milk purchases and sales.

129 Not in a tanker where all the milk has to be mixed up

130 Recycled 128 L and 160 L plastic cans (Figure 34) that have previously been used for holding chemicals

307


quality aspects


Final Consumers

Producers, Small Dhodhis, Medium Dhodhis, Large Dhodhi and Retailers

Table 37 ranks and quantifies six quality attributes and their priority ranking by

importance to chain actors from producer to final consumer. The sixth attribute of

lactometer reading (LR) was only mentioned in conversations with the Small, Medium

and Large Dhodhis and is not included in the comparison.

Table 37 helps understand that higher fat content associated with buffalo milk followed

by the sweeter taste of milk are of prime importance in this chain. This section uses more

qualitative data, however, to further understand how higher quality is achieved and the

linked profitability at each tier.

308

Table 37: Okara-Lahore milk quality attribute perspective of various chain actors from farm to final consumer


Producer

1

Small

Dhodhi1

Producer

2

Small

Dhodhi2

Medium

Dhodhi

Large

Dhodhi Retailer1 Retailer2

Farmer

to

Retailer

(n=8)

Consumers

(n=11)

Safety and health benefits 5 5 4 5 5 5 5 5 39 32

Visual appearance (colour

and/or cleanliness) 4 3 3 2 3 4 2 4 25 39

Taste (sweetness) 2 2 1 3 4 2 3 3 20 21

Smell (aroma and is it sour) 3 4 2 4 2 3 4 2 24 33

Thickness (higher fat content) 1 1 5 1 1 1 1 1 12 21

Lactometer Reading (LR) NA NA NA 5 1 1 NA NA 7 NA


n=8 for chain actors from milk producer to retailers and n=11 for final consumers interviewed at the two retail shops. Consumer feedback has been aggregated

Data Source: Author’s primary data collection

309

Figure 34 portrays the units of volume and various pots used to handle milk and the

mechanism for quality assessment along the chain. In brief, more volume is obtained from

producers, the higher fat content milk is standardised to 4.5% fat by diluting with ice, and

finally lesser quantities are sold to the consumers. This mechanism will be discussed in

detail later in the section.

310

Figure 34: Quantity and quality

along the Okara-Lahore chain


Producer Small Dhodhi Large Dhodhi Retailer

Retailer Quantity

At retail

Retailer1 & Retailer2 sell

1litre = 925ml

i.e. 75 ml less per litre

Large Dhodhi’s 46 litres Lahori panda or maund

=

Retailer’s 48 litres

i.e. 46 ÷ 0.925 = 49.7 litres

SD’s seer or gadvi

for producer

Medium Dhodhi /

Large Dhodhi’s

measure used to convert SD’s gadvi to litres

Large Dhodhi uses 128 and 160 litre plastic drums

to collect milk from Small Dhodhi

Gadvi OR litre

for consumer

Medium Dhodhi

Weight

Lahori 46 litrepanda or 46kg

maund for retailers

Large Dhodhi’s urban Quality standard

Large Dhodhi then lowers the fat for retailers from the average of 6% to around 4.5% by diluting it with

ice

1ice : 8 milk

7.2 ice : 50.4 milk

Therefore easy for Large Dhodhi to make 46litre Lahori panda or maund

Large Dhodhi’s rural Quality standard

Large Dhodhi has set a 6% fat standard for Small Dhodhiswith

a reward and penalty system in place

Premium = (litres × actual fat) ÷ 6% fat standard

Assuming Small Dhodhis 46.5L milk had 6.2% fat

Premium Paid = (46.5L × 6.5) ÷ 6% = 50.4 litres i.e. Small Dhodhi gains another 3.5litres

This is only possible as Small Dhodhi given 0.7% extra for fat in summer and 0.5 % in winter

Producer Quantity

At farm gate

1 seer OR gadvi = 1073 ml i.e. Small Dhodhi gets 73ml

extra per litre

Producer1’ s 1 gadvi= Small Dhodhi’s

1.073litres

i.e. 1 × 1.073=1.073

Price between Producer & Small

Dhodhi is fixed however for a 40 kg or

litre maund


With extra quantities from producers

40 gadvis becomes 43 litres

i.e. 40 × 1.073 = 43 approx.

So the same farm gate maund becomes 43litres & not 40kg or litre

Small Dhodhis gains some more volumes at Medium Dhodhi’s central collection point since Large Dhodhi gives him leverage

i.e. buys 0.925

therefore

43 ÷ 0.925 = 46.5 litres

i.e. a gain of 6.5 litres for Small Dhodhi in total

311

G8.2.1. Final Consumers

Value chains are driven by what the final consumer values. In addition to the information

in Table 37, comments by the final consumers interviewed at the two milk retail shops

help us further understand that butterfat or cream closely followed by taste are attributes

most valued by the final consumer. A consumer (C6) at retailer1 said, “taste [is

important]...to my wife quality means more cream after boiling milk” while another

consumer (C4) at the same shop responded, “there should be cream on top of milk, no

matter how many times it is boiled”. The milk is used after boiling, and the amount of

cream set on the top, associated with higher fat content buffalo milk is an indicator of

quality.

The final consumers also have very little understanding of the units used by the retail

shops to sell milk. A consumer (C1) buying milk at retailer1 said, “Not sure [of the unit

of milk purchased]...one gadvi131 equals one kg”. Another consumer (C5) said, “I think

gadvi is more than a kg and probably 1.25 kg”. A consumer (C5) buying milk at retailer2

said, “[I bought milk in] gadvi which is same as kg, only 50 grammes more”. This

illustrates the lack of awareness on the part of the final consumer of quantity units.

G8.2.2. Producers, Small Dhodhis, Medium Dhodhi, Large Dhodhi and Retailers

At the farm gate, there is no precise mechanism for the quality assessment of milk.

“[Small Dhodhi2] doesn’t really check anything in milk [while buying] and takes it with

his eyes closed”, said Producer2 and this is due to rural cultural norms. This statement is

verified by Small Dhodhi1 who held, “We check [milk quality] by hands and eyes and

might taste...we can even tell...how much fat by looking at the milk”, illustrating that

butterfat is important. Small Dhodhi2 said, “I offer a better price for buffalo milk”.

Buffalo milk is associated with better quality and rewarded all along the chain, as the final

131 A local unit between 900 to 1200 grams or ml depending on where and who uses it in the chain.

312

consumer prefers it. The producers however commonly have both species, that is cows

and buffaloes, and sell mixed milk.

There is little clarity and no consistency on the use of measuring units. Producer1 said,

“A gadvi [of milk] is 1kg and one chatank132. They [small dhodhis] take extra milk from

us, saying we cannot meet our weights [while selling]. They take an extra chatank for

free. Dhodhis have their tactics”. Producer2 who is well-educated and understood units

said, “We sell milk [to Small Dhodhi2] in gadvi. Gadvi has 16 chatanks133. The Small

Dhodhi nonetheless gets 17 chatank per gadvi”, which means there is a social acceptance

for this to happen.

Small Dhodhi2 said, “We buy in gadvi and sell in litres”. “We buy from the farmer

chantank more and sell chantank less [to Large Dhodhi]” Small Dhodhi1 further

elaborated, “…in a maund134 we save 4 to 5 kg135 as the quantity has increased”.

Collection pots used to collect milk from producers, and utensils to measure this

collection belong to Medium Dhodhi. The small dhodhis trust these measurements.

Medium Dhodhi clarified the complicated unit conversion, explained as follows:

Small Dhodhi′s gadvi for producer is 1073 ml instead of actual 1000ml

Therefore small dhodhi obtains 73ml of extra milk per gadvi

Large Dhodhi gives leverage to small dhodhi i. e. 1073 ÷ 0.925

= 1160ml. Small Dhodhi has gained 148ml extra milk per gadvi in total

Producers consider the aggregate unit of maund, for which milk price is agreed between

them and small dhodhi, to be 40 L, also referred to as kg, which is contrary to the reality.

This becomes evident by applying the above conversions to a maund.

132 Chatank in a local unit of 62.5 grams. There are 16 chatanks of 62.5 grams each in a kg, which adds up to 1000grams. The chatank however, was referred to be between 50 to 62.5 to 73 grams by various chain actors, depending on their role and position in the chain.

Producer1 incorrectly understands that chatank is 50 grams, which does not add up to 1000grams in a kg. This producer is illiterate

and has little understanding of units 133 Producer2 is educated and knows the correct chatank in a kg 134 40kg or litre at which price is set between Producer & small dhodhi 135 These participants kept switching between various units

313

Small Dhodhi′s maund for producer → 40 × 1073

= 42.92L i. e. , . approx. 3L extra per maund

Large Dhodhi′s leverage is given to small dhodhi → 43 ÷ 0.925

= 46.5L i. e. , approx. 6.5L gain in total

It is not always 6.5L additional milk per maund as Small Dhodhi1 said, “We try to buy

in our own pots but there are sellers [producers] who use their own selling pots, and we

don’t get the extra quantity from them”, demonstrating that not all producers allow small

dhodhis to obtain extra quantities.

Small dhodhis unload their milk collection directly to Large Dhodhi’s plastic cans (Figure

34). Prior to that, however, Medium Dhodhi’s hired munshi136 takes a sample from each

of the twelve small dhodhi supplier’s milk to him to measure the butterfat percentage

using the Gerber137 method. The fat percentage is recorded for making payments later on

to small dhodhis. “On top of that we get an incentive on fat but if a farmer dilutes milk

we bear loss...if fat is 6 or above we save some money”, said Small Dhodhi1, highlighting

the element of distrust pertaining to dilution at the farm gate. It also point to the milk

quality standard at this tier of the chain and the higher preference for buffalo milk. At

Medium Dhodhi’s central collection point Large Dhodhi offers a premium for butterfat

above 6% and penalises small dhodhis with lesser fat, using the following formula:



There is variation in price calculations between summer and winter as explained by

Medium Dhodhi who said, “We give 0.7 extra for fat in summer and 0.5 extra for fat in

winter. For example six [percent] fat is written as 6.7[percent]...the reason for the extra

136 Record keeper and milk tester 137 Milk fat content test to determine the price to be paid. 10 ml of sulphuric acid followed by 11 ml milk and 1 ml of Amyl alcohol

added to butyrometer, which is then placed in a hand-operated centrifuge machine and spined for a few minutes to get an estimated

butterfat percentage in milk.

314

incentive is higher demand in summer, and these incentives bound the suppliers”. This

points out that the milk collection by small dhodhis does not have high enough butterfat

percentage to qualify for Large Dhodhi’s reward, and 6% fat standard is arbitrary138.

Medium Dhodhi explained the milk quality tests done in his purchasing and sale in some

detail stating, “My munshi139...checks [the quality] and the party from Lahore [Large

Dhodhi] then checks it again. Taste tells of foul smell...it tells if there is urea140

present...cooking oil, urea, starch or hair removal cream is commonly added to milk by

small dhodhis to increase fat etc...if milk gets too hot on the way141 we boil it as well to

check if its good...Fat is checked on a daily basis whereas LR [lactometer reading] is

occasionally checked”.

Medium Dhodhi further said, “Starch [test] is done particularly in winter where a

chemical is added that changes the colour of milk and is indicative of the presence of

starch”, most probably to limit buying as there is excess supply in winter and lesser

demand.

In the chain, there is feedback from the final consumer in place too to check quality.

Medium Dhodhi explained, “At times small dhodhis are able to deceive us and our tests

fail. For example, if cooking oil is added to cow’s milk142, we cannot detect it but next

day we may get some feedback after a complaint by consumers [at urban retail milk

shops] who set yoghurt [from the milk]. If this [complaints] continues we can track the

culprit, and it would result in termination of purchase [from that small dhodhi”. This

demonstrates an efficient check and balance mechanism.

138 Medium dhodhi allowed the author to take a picture of his collection data for 12 small dhodhis that day. Author’s co-scientist

studied the milk composition for these chains in both summer and winter, which shows that 6% fat at farm gate does not mean much. 139 Record keeper and milk tester 140 All sort of illicit practices prevalent in the market so the chain actors are quite vigilant 141 As small dhodhi does not add ice due to the fat %age incentive 142 To increase fat and get an incentive for higher fat content buffalo milk given by large dhodhi

315

Large Dhodhi is quite careful, prior to purchase decision, and tests the milk once again.

He said “We first taste then check sample [fat] and finally measure the quantity [of small

dhodhi’s milk].We check fat, LR and temperature”. Large Dhodhi further added, “Both

fat and LR [lactometer reading] are important. Just the fat on its own can be increased by

putting cream143 into water. Fat test tells chicknai144 and LR tells the powder in the milk.

LR and temperature have to go together, if fat is more and LR is less or vice versa that

means the milk is adulterated. If the temperature is higher, LR or gravity will reduce and

vice versa. For example at 20 °C temperature the LR has to be 27, LR will be 26 at 17 °C

and so on i.e. LR will change by one [centigrade] with every three degrees of temperature

change”. These statements show that Large Dhodhi is the real master of this trade and

knows the product quality aspect really well.

The grading of milk along the chain could not be verified because Medium Dhodhi and

Large Dhodhi gave contradictory statements. Medium Dhodhi said, “Some shops offer

better rate [to Large Dhodhi] and so better quality is provided to them [by Large Dhodhi]

whereas others pay less and so lower quality works in that case. Different matti145 are

coloured with different inks to identify them”. Large Dhodhi, however, said, “We can

lower the quality if we want to but I do not want to do so. We sell same quality milk to

all our buyers”.

Large Dhodhi dilutes the milk purchased from small dhodhis at central collection point

with ice, already present in his blue plastic cans (Figure 34)

Ice is required to avoid milk spoilage, particularly in hot summers and to gain volumes

as Large Dhodhi said, “After buying ...for example 110 L of milk and 18 kg of ice for a

143 possibly cheap powdered milk 144 A word for fat in Urdu language 145 128 and 160 litre blue plastic cans (Figure 34) used by large dhodhi to collect and deliver milk

316

128 L matti. We are supplying in summer at around 4.5 [%] fat and 22 to 23 LR”, which

is Large Dhodhi’s standard at retail end of the chain.

Both retailers sell lesser quantities to the final consumer as Retailer2 said, “We buy in

gadvi and sell in litre...We sell 925 ml litre and that is how we make money”. He further

said, “Lahori maund is 46 litres, I don’t know what happens in the rural market”. This is

when he buys milk from Large Dhodhi and before selling lesser quantities. Large Dhodhi,

Retailer1 and Retailer3 later changed their statement saying gadvi is same as litre.

Five retail buyers who are not part of Large Dhodhi’s extended family do check milk

quality “by making khoya146”, said Large Dhodhi. Retailer1 and Retailer2, who are large

dhodhi’s close relatives, are not performing any explicit quality tests for the milk

supplied. Retailer1 said, “Taste and smell are important and tell the quality...if milk stays

on hand it is thicker”. Consumer feedback is important and a quality chains as Retailer2

said, “Customer complaints, if any are conveyed back [to Large Dhodhi] with the request

to improve quality”, which verified the earlier statement of consumer feedback given by

Medium Dhodhi.

Retailers are well aware of the quality sought by the consumer as Retailer1 said,

“[consumers seek] thickness [in milk] while Retailer2 said “[Consumers want] better

quality at cheap price”.

Table 38 shows gross margins (GM) per actor based on the above understating of quantity

and quantity (Figure 33) aspects along the chain using a single day’s transactions. GM

estimates exclude owner operator’s opportunity cost of labour and disregards interest

forgone on the capital invested.

146 A traditional practice in Lahore market where around 2400ml of milk is boiled to get a certain amount of milk solids, based on

which quality is determined

317

Table 38 : Physical and financial flows and capital invested by each actor along the Okara-Lahore milk value chain


Dhodhi

Large Dhodhi Retailers

Volumes Producer1 produces 23

gadvi from his two

buffaloes and two cows.

He sells 10 gadvi morning

mixed cow and buffalo

milk to small dhodhi1 and

another three gadvi

evening milking to another

small dhodhi

Now 10 gadvis based on

small dhodhi1’s 1.073L

collection pot

Producer2 produces a

total 10 gadvi from one

milking buffalo. From this

he sells one gadvi milk to

small dhodhi2 and another

two litres at formal

processor Nestlé’s

collection centre in his

village.

1 kg but still based on

small dhodhi2’s 1.073L

collection pot. Unit does

not mean anything

Based on extra volumes

procured from Producers &

volume leverage and fat

standardisation by large

dhodhi

Small Dhodhi1 collects 80

litres (L) from 13 farmers

supplying from 2 to 10 gadvi

each

where 66.7 gadvi × 1.073 =

71.6 ÷ 0.925 =

(77.4×6.2%fat)÷6 = 80L

Small Dhodhi2’ total milk

collection from eleven

producers is 36 L mixed

buffalo and cow milk

where 31 gadvi × 1.073 =

33.3 ÷ 0.925 = (36×6%fat)÷6

= 36L

Medium Dhodhi

is supplied 570L

milk by ten

other small

dhodhis

including Small

Dhodhi1 &

Small Dhodhi2

Large Dhodhi collects 2,350L

of milk from “three medium

dhodhis supplying 570, 400

and 400 litres each and 15 small

dhodhis 1000litres” in rural

Okara

(6 to 8milk:1ice)

Retailer1 buys ten maund (460L)

from large dhodhi as his only

supplier and sells milk to final

consumers at the shop.

460L÷0.925= 511L as selling 925ml

i.e. a smaller litre or gadvi to the

consumer

Retailer2 buys 256 gadvi of milk

from large dhodhi with that milk sold

to the final shop consumers. He buys

another 60 gadvi of milk from

another supplier at a higher price

with that milk sold through home

deliveries.

256÷0.925= 277L i.e. same as

Retailer1

318


Dhodhi


Average price at

each step

Producer1: 35 Rs / gadvi

Producer2: 35 Rs / kg



40 Rs/L

44.5 Rs / L



Margins

(price cost for

Producers &

price for all else)

Producer1: 11 Rs per

standard litre

Producer2: 6 Rs per

standard litre



2 Rs / L 3.5 Rs / L Retailer1: 4.5 Rs / gadvi

Retailer2: 4.5 Rs / gadvi

Average

variable cost per

unit

Producer1: 1.9price

:1cost

Producer2: 1.4price

:1cost



1 Rs/unit 43 Rs/unit Retailer1: 43 Rs / gadvi


Estimated

Revenue per day

(P×Q)

Producer1: 350 Rs

Producer2: 35 Rs

Small Dhodhi1: 3,040 Rs


1,140 Rs 104,575Rs Retailer1: 23,870 Rs


Estimated

variable cost per

day

Producer1:18.4×10

=184Rs

Producer2: 25×1 =25Rs

Small Dhodhi1: 2635Rs that

includes

2335 Rs for milk procured

300 Rs motor cycle fuel &

maintenance


that includes

1,085 Rs for milk procured

120 Rs motor cycle fuel &

maintenance

613Rs that

includes

415 recorder’s

salary plus 7

litres of milk per

day

33 Rs shop rent

167Rs phone


82,420 Rs for milk procured

10,000 Rs transport fuel and

maintenance

400Rs bus fare for one of the

brothers to reach rural

collection point in the morning

5100ice blocks (7milk:1ice)

2875 for four hired labourers

and two drivers that includes

milk 4 litres milk given to each

of them

700 phone

150Rs miscellaneous for

meals etc.


20,470 for milk procured

100 Rs ice blocks


200Rs polythene bags to package

milk

233Rs shop rent

117 Rs phone bills


70 Rs ice blocks


220Rs polythene bags to package

milk

133 Rs shop rent

319


Dhodhi


33 Rs phone bills

Gross margins

per day from

milk

Producer1: 170 Rs

Producer2: 10 Rs



510 Rs 4,300Rs Retailer1: 3,500Rs

Retailer2: 1,900Rs

Capital assets

Invested

Producer1: 27 million Rs

for

16 acres of agricultural

land and 12 buffaloes and

cattle

Producer2: 12 million Rs

for 10 acres of land and

6 buffaloes only

Small Dhodhi1: 0.5million

Rs as cash advance to

farmers and 50,000 Rs for

motor cycle

Small Dhodhi2: 0.1 million

Rs as cash advance to

farmers.

50,000 Rs for motor cycle

1 million Rs as

interest free

loans to 12 small

dhodhi and for

their milk

collection pots

3 million Rs as credit money in

circulation for milk business

towards retailers

1.4 million Rs worth

of truck

Retailer1: 0.2 million Rs for two

refrigerators,

One each to store milk and yogurt,

utensils and some milk on credit to

consumers buying milk at his shop.

Retailer2: 0.15 million Rs as

security deposit for the shop plus a

refrigerator and few utensils for the

storage and selling of milk

Data Source: Author’s field research 1Based on author’s detailed farm economic analysis as part of his PhD research (Chapter 4, Table 6). It is assumed that Producer1 is producing 3,700 to 10,100L per annum and

while Producer2 produces 2,300 to 3,700L per annum based on which their price cost margin is 1.9price:1cost and 1.4price :1cost respectively

320

The Large Dhodhi and Retailer1 earn the highest margins respectively. The margins

earned by producers from milk enterprise are negligible despite substantial capital

investment in their mixed crop-livestock farms (Table 38). Producer2 on profitability

from dairy as an enterprise said, “...only saving from dairy enterprise is the milk that we

are able to consume [milk] for our household...we do earn some profit from milk and

meat as a joint enterprise. It gives us a lump sum [cash] payment [when an animal is

sold]”, while Producer1 said, “Milk helps with home usage and to cater for guests. The

lump sum payment for milk we get helps us buy diesel or fertilizer or manage monthly

house expenses...If a guest comes we don't have to run to the shop to buy milk. This is

the reason we farmers keep animals”. These statements highlights social and cultural

norms to keep dairy animals.

G8.3 Product seasonality, price determination, pricing power dynamics and

information flows along Okara-Lahore milk chain

This section explores:

Seasonal aspect of milk production, including price in the chain, and demand

Pricing mechanisms and price information flows, and associated power dynamics

The following sequence examined is in the section:


Retail urban pricing

Farm gate rural pricing between large dhodhi, medium dhodhi, small dhodhi and

producers

Table 39 provides a summary of the responses of chain actors and consumers in relation

to milk supply and demand. On milk demand, Retailer1 said, “[in] May, June [and] July

there is more demand and less supply but abundant milk in winter”. On milk supply, both

321

producers said that milk production peaks in winter when there is an abundance of green

fodders. The lactation cycle for the cow is said to be both same and opposite to buffalo,

depending on animal breed.

322

Table 39: Punjabi147 and Gregorian calendar and buffalo & cow milk production / supply along Okara-Lahore milk chain

Maximum Consumer demand in

Peak Summer

Minimum Consumer demand in

Peak Winter

Chet

(14 Mar-

13 Apr)

Vaisakh

(14 Apr-

14 May)

Jeth

(15 May-

14 June )

Harh

(15 June-

15 July)

Sawan

(16 July-

15 Aug)

Bhadon

(16 Aug-

14 Sept )

Assu

(15 Sept-

14 Oct)

Katak (15

Oct-13

Nov)

Maghar

(14 Nov-

13 Dec)

Poh

(14 Dec-

12 Jan)

Magh (13

Jan-11

Feb)

Phagun

(12 Feb-

13 Mar)

Min Buffalo Milk

supply

Max Cow Milk

Max Buffalo Milk

Min Cow

Milk



323

Figure 35: Production and pricing mechanism in Okara - Lahore chain


Farm gate price for producers

changes with season

mainly in

increasing in summer

&

decreasing in winter


fluctuates (up & down )


Medium Dhodhi works on a fixed commission & is not affected by the

price changes

This price is based on the formal processors rural market buying

prices

Milk Producer

Small Dhodhi Large Dhodhi Retailers

Formal Processors


Retail price between Large Dhodhi & retailers is fixed for whole year & worked around the price set by the

government

&

influenced by big market players. This price is a loose benchmark, not strictly followed by most retailers.

• Retailers get around the government price by altering units & Large Dhodhi by altering quality i.e. dilution

• Final consumer of informal chains is price sensitive

Medium Dhodhi

Governance (internal to the chain & external i.e. industry level)

324

Figure 36: Price information flows along the Okara -Lahore chain


Producers check


• the prices offered by other small dhodhis

• communicated by the Small Dhodhi buying milk

Small Dhodhis & Medium Dhodhi check

• Adda rate that is based on prices paid by formal processors to dhodhis in the rural market

Milk ProducersSmall

DhodhiLarge Dhodhi Retailers

Formal Processor(s)


Retailers are



• Large Dhodhi suggests a price to the family retail shops


Large Dhodhi checks

• Prices paid by formal processors to dhodhis in the rural market, which determines adda rate


Medium Dhodhi

325

G8.3.1. Final consumer’s response to price changes

Consumers are aware of price quality trade off. A consumer (C4) at retailer1 said, “Price

matters for good quality but hard...for poor consumers to buy expensive milk, especially

for salaried class”, pointing to the underlying issue of consumers not being able to pay a

higher price. Most consumers questioned have surveyed the market price and quality of

milk elsewhere before making a purchase decision. A consumer (C4) when asked whether

he was getting the desired attributes in terms of quality for the price paid at retailer2 said,

“Some shops are selling same milk for 60 Rs. [I am] not satisfied [with the milk quality

at retailer2]... [but] can get pure milk only if [I do] milking myself”, which is evidence of

compromise made by the consumers.

G8.3.2. Retail Urban Pricing

The retail price in urban markets is fixed on an annual basis by the city district

Government. The price is generally fixed in mid-April to mid-May each year, a time when

milk production starts to decline (Table 39). This year148 a price of 57Rs/litre has been

fixed. Retailer1 said, “Price changes ...after a year...the current price was fixed about two

months ago149...the rate will remain same in winter...this is Punjab government rate...the

price will only change after an year”.

The Large Dhodhi has an impact on the retail sale price of milk in this chain as he has

advised his price per gadvi to Retailer1 and Retailer2 which “is based on market rate” and

has nothing to do with quality said Retailer2. Retailer1 stated, “[Large Dhodhi] gives us

[milk] at Rs 2000/maund150 and we then fix the retail price accordingly [based on our

expenses & margin]...the retail price151 was suggested by Large Dhodhi”.

148 2012 149 April 2012 150 43.5 Rs/L based on a Lahori maund of 46 litres 151 48 Rs / gadvi

326

There is little regard for the price given by the government. “We know the rate in the

market...we do check the price being charged by others in the market and try to keep our

price lower than our competitors...there are around 6 shops on this road and our price is

lowest”, said Retailer1. This demonstrates locality specific price based competition and a

price set lower than the benchmark given by the government.

Large Dhodhi provided further insight on how benchmark retail prices are set in the city.

He stated, “20 to 30 shops in Lahore give a rate led by a key supplier...the magistrate raids

that shop but then others follow and that price is set...The rate initially comes from Kasur

road152 and becomes applicable in the whole market”. This statement describes how

retailers influence the government price. Most of these retailers are large dhodhis as well

supplying milk to formal processors.

G8.3.3. Farm gate rural pricing between Large Dhodhi, Medium Dhodhi, Small

Dhodhis and Producers

The formal processors control farm gate milk prices. “[Rural market] price is determined

on the basis of company153 rate...we have to offer 1 or 2 Rupees higher than that offered

by the company to be able to procure milk [from medium dhodhis & small dhodhis]”,

said Large Dhodhi. This statement highlights the influence that formal processors have

on rural pricing and the competition between the informal and formal channels to procure

milk.

Large Dhodhi’s statement was further consolidated by Medium Dhodhi who explained,

“Different dealers154 have an Adda155 rate and we are bound by it. We can’t pay less than

that price [to small dhodhis]...that is our minimum price...The oldest adda gives the rate”.

Small Dhodhi1 verified what Medium Dhodhi said, “Contractor’s [medium dhodhis]

152 Rural Kasur district adjacent to Lahore and a major supplier of milk to the city 153 formal processor 154 Milk traders like medium dhodhi and large dhodhi 155 Central rural collection points where a number of dhodhis bring their rural collection before it is transported to Lahore

327

commission may vary with the loan extended but the price offered by Lahori [Large

Dhodhi] can’t be different and has to be same at each adda”. This shows that the large

dhodhi is bound to give a minimum price to his small dhodhi suppliers, determined by

the addas.

Medium Dhodhi explained that the add rate is dictated by the formal processors and he

described, “These days Adda “name” is giving the rate...the key price fixation though is

based on factory156 rate...in this area dominated by Adam Cheese, CDL157, Nestlé and

Engro”. These addas are also Medium Dhodhi’s key source of price information as he

said, “[We check price] from different addas...there are 12 addas in this area”.

Medium Dhodhi further said “...in winter...production is high and lesser demand...the

[farm gate] price goes down from December to March and then increases with increase

in demand from April to almost November158 as [its] summer and [therefore] higher

consumption of milk and other dairy products. He further explained, “…the major price

change is with these two seasons and prices are relatively stable otherwise...It [price]

varies with demand increase such as 1 to 2 Rupees will increase in the month of

Ramadan159...political instability, less demand...imports of powdered milk by factories160

will lead to lower prices in the market”.

Small Dhodhi1 said, “The price is fixed with the involvement of tahekadar161”, suggesting

Medium Dhodhi plays a role in price fixation and gets price information, “from other

dhodhis and by visiting other addas”.

156 Formal processors 157 Chaudhry Dairies Limited, one of the big national milk processor 158 Table 39 159 Muslim holy month of fasting 160 Formal processors 161 Medium dhodhi’s sitting at rural central collection points

328

Small Dhodhi2 further explained, “We know the rates from all the addas162 that the truck

[Large Dhodhi] picks milk from...we talk to others [dhodhis] and call [them]”,

highlighting that these addas are the key source of price information for small dhodhis.

On pricing mechanism between small dhodhi and producers, Small Dhodhi1 said, “Lahori

[Large Dhodhi] gives us the rate and we pass the same rate to our farmer...whenever the

rate changes...it is communicated to us”, which means that the price is generally passed

on to the producer. There is an annual fixed price arrangement however, is place between

Producer1 and Small dhodhi1. Producer1 said, “We have mutually fixed a price that will

go on for both summer and winter. We have agreed that it will not change. We have told

the dhodhi [Small Dhodhi1] that milk is yours, whether cheaper or expensive. Here all

the houses are taking cash advance [but we haven’t and therefore able to fix a price]”.

This fixed price is rare.

Commonly the price changes with season as Producer2 said, “The price only changes

twice that is summer and winter”. The producer explores local prevailing prices as

Producer2 said, “We ask other dhodhis, chiller [formal processors village collection

centre] and tubwala163 [adda rate] to know what they are paying the small dhodhi, we do

investigate [price]”.

On price fluctuation Small Dhodhi2 said, “The prices go down from Katak, Maghar &

Poh [mid October to mid-January] when there is very less demand from the buyer”. While

Small Dhodhi1 said, “In sawan [mid July to mid-August] the production increases and

the price goes down ...we keep buying from the farmers as we can’t stop purchasing even

if we get a higher or lower price [from Large Dhodhi]...we will lower the farm gate prices

too. The price of milk keeps fluctuating...its lower in winter and goes higher in

162 Phone calls using mobile which are quite common in Pakistan 163 Medium dhodhi has a huge unrefrigerated steel tank sitting at his shop, which is not used as milk is transferred directly from small

dhodhi to large dhodhi. This steel tank is however called tub and wala means owner i.e. owner of tub

329

summer...whenever the Lahoris [Large Dhodhi] lower the price we request farmers to

give us a discount as well...the [major] rate changes only twice every year...it is the

formula of supply and demand”. This was verified by Producer2 who said “Yes [less

demand and more supply] in winter in the months of November, December...” and small

dhodhis keeps milk buying from producers.

Producer2 further said, “the price of milk in shortage summer months increased...the price

would start going down in August when new lactation starts...the price changes twice for

summer and winter”, highlighting that the major price change at farm gate occurs twice

each year.

G8.4 Facilitating functions of financing and payments, relationships and power

dynamics

There is an intricate set of facilitating functions in the chain that enable it to operate in

the absence of formal contracts. This section will describe the financing and various

services provided in the chain, illustrated in Figure 37. It will examine the duration and

description of relationships, conflict and problem solving mechanisms; power dimensions

in seller’s role by exploring blocking supply or changing buyer and a buyer stopping

payment for milk supplied or changing supplier. This examination proceeds by studying

interactions between producers and small dhodhis; small and Medium Dhodhi; Medium

and Large dhodhi; and Large Dhodhi and retailers.

330

Figure 37: Financing, relationships and power dynamics along the Okara - Lahore chain


• Almost all Ps take cash advance from Small Dhodhis to meet monthly household needs. They also borrow whenever a need arises

• Retailer 1&2 have an arrangement with Large Dhodhi where they don’t need to pay any cash advance to secure milk supply

•Retailer2 does home deliveries at a higher price

• Medium Dhodhiextends interest free loans to most Small Dhodhis enabling them to earn a livelihood and to pay cash advance to producers. This cash advance also makes Small Dhodhi’sfinancial hostages. Medium Dhodhi’scommission is based on the cash advance extended to Small Dhodhis

Milk Producers

Small Dhodhis Large Dhodhi Retailers ConsumersMedium Dhodhi

• Large Dhodhi has not extended cash advance to Medium Dhodhi but to those 15 Small Dhodhi’s from whom he procures milk directly

Cash Advance

Services



• Small Dhodhis also provides services such as feed supplements to Ps

•Accounts settled once every month but the advance generally keeps rolling

•Relationship is based on kinships and time worked together is valued by both parties

• Cash advance & ready cash to meet needs followed by price are important

• Element of mistrust i.e. dilution

• Disputes if any are settled by involvement of locals

•Accounts are settled every eighth day but the Small Dhodhi can borrow more money from Medium Dhodhi if a need arises

• Trust in the sense that both parties are aware of the rules of game

• Price is a contentious issue between Small Dhodhis & Medium Dhodhi

•Smoother relationship and trust as both parties have clear rules of engagement i.e. quality and quantity arrangements

• Both parties are free to part ways as no capital involved but need each other

• Both parties have shared price information source that is rural central collection points (addas) linked to formal processors & market demand and supply

•Accounts are settled every eight day

•Family relationship and both parties need each other too

•Accounts settled on a daily basis and concession given by Large Dhodhi needed

• Cash sales at the shop but some customers buy on credit and pay after a month


331

Five aspects important to the chain actors from producer to final consumer are quantified

in Table 40. Although the priorities varied for each chain member, price closely followed

by trust, on aggregate, are important. Trust is more important from Medium Dhodhi to

the final consumer in maintaining a longer-term business relationship.

332

Table 40: Attributes important to seller farmer and all other buyers of milk in the rural Okara-urban Lahore milk value chain:


Producer1 Small

Dhodhi1 Producer2

Small

Dhodhi2

Medium

Dhodhi

Large

Dhodhi Retailer1 Retailer2

Farmer

to

Retailer

(n=8)

Consumers

(n=11)

Convenience of

selling for farmer

/

buying for all

other chain actors

&

final consumers

5

4 4 5 5 4 1 4 32 24

Price 1 2 1 2 2 1 4 3 16 20

Trust 3 3 3 3 1 2 2 1 18 22

Advance money

for milk 4 1 2 1 3 3 5 2 21 NA

Time worked

together 2 5 5 4 4 5 3 5 33 NA

Note: Ranked on scale of 1 to 5 (where 1 is highest in importance and 5 is lowest) from producer to retailer and 1 to 3 for final consumers for the aggregates of three attributes only

n=8 for chain actors from farmer to retailers and n=11 for final consumers interviewed at the two retail shops


333

G8.4.1. Producer and Small Dhodhi

Producers take cash advances from their small dhodhi buyers. The account between

producer and small dhodhis is settled once every month, and the cash advance keeps

rolling with producer owing small dhodhi. The producer also borrows from small dhodhi

whenever a need arises, and it is then deducted from the milk account. Producer1 said,

“We get payment [i.e. cash from Small Dhodhi1] whenever a need arises, whether he has

the money or not, he has to pay us...we owe him around 15,000 Rupees at the moment...we

get payment for our crops every six months, but money from milk is regular and helps

meet our household needs”.

Producer1 has not borrowed any cash advance, which is unusual and said, “We have

agreed on mix164 [price] with him [Small Dhodhi1]...The [prevailing average] price is

more in the market these days...but this price [between us] will not change in winter as he

is getting milk at a lesser price now”. Buyer Small Dhodhi1 does “give money if a need

arises” and has extended cash advances to other producer suppliers.

Producer1 has been selling milk to Small Dhodhi1 for the last 4 years, and they have a

cordial relationship as Producer1 said, “[Small Dhodhi1] is our neighbour from the same

village but lives in [nearby small Okara] city... [His family] has been our [rural]

neighbours...our forefathers have lived together...no conflicts arise between us as he

[Small Dhodhi1] trusts that we will not add water to the milk. We just milk the animals,

and he comes and picks it. He does, however, keep a check on other [milk] suppliers”,

thus there is a high level of trust in this dealing.

Producer1 further said, “No we do not block the milk [supply] but make a request if the

need for money arises, he [Small Dhodhi1] borrows time...” Small Dhodhi1 also

reciprocated the same views for Producer1 but said that in general for other producers,

164 Cow and buffalo milk

334

“When the farmer asks for cash advance, and I cannot arrange it, the farmer might change

dhodhi. Similarly, if another dhodhi offers a better price even then, the farmer can go to

the new buyer”, which highlights that the producers have an upper hand and are free to

change buyers. These statements also highlight a general mistrust that producer will dilute

the milk.

Producer2 who has been selling milk to Small Dhodhi2 for the last 10 years and is happy

with his buyer saying, “He [Small Dhodhi2] is very cooperative, he supplies us milk if

we don’t have any of ours and recovers it in the next season when our supply

increases165...also his advance will remain with us until the supply starts again...we only

have to clear if we start supplying milk to a different dhodhi”. Producer2 also said, “We

can easily get new buyers on the same [purchase] price...there are many other buyers who

have offered to buy milk from us”. This shows that producers are free to change buyers

and can block dhodhi’s money too.

The conflicts if any are resolved by the involvement of people from the local village as

Producer2 said, “...at times others [local village people] may get involved to sort out

differences”. Small Dhodhi2 said, “[conflicts with farmer sellers] are resolved but many

times we lose our cash advance [extended to secure milk purchase]...it is very difficult to

find new chungan166 suppliers as they demand more advance and higher rate”, which

shows how important ready cash is for the trade to occur.

G8.4.2. Small and Medium Dhodhi

The relationship between small dhodhis and Medium Dhodhi is bound through several

means. Medium Dhodhi has extended interest-free loans to small dhodhis without any

165 small dhodhis money is blocked by the farmers if milking animals go dry 166 A local term use for milk producers / farmers

335

written contract. The Medium Dhodhi however, takes a bank cheque for the amount of

cash advance extended from some small dhodhi recipients as a guarantee. This security

is a risk mitigating approach, particularly applicable to those small dhodhis who are not

from the same rural vicinity or those that he thinks cannot be trusted, probably due to

their bad repute in the market. The Medium Dhodhi’s commission is based on the amount

of advance the small dhodhi has borrowed. That is, if no advance, 39Rs is paid for the

milk sold which is only 1Rs commission on what medium dhodhi pays to small dhodhi.

The commission increases to 3Rs i.e. 37Rs paid to small dhodhi if more is borrowed as

small dhodhi said, “Our role is only that of a commission agent...we are charging a

commission on per litre basis.”

Medium Dhodhi pays small dhodhis every eighth day on a Sunday and said, “If someone

[small dhodhi] needs money in between that period it is paid to him and deducted while

settling the account the eight-day...” On advance cash practice Medium Dhodhi said,

“...advance is good too as we can then have some control on small dhodhi if a person has

not taken any advance he might not show up the next day, and it is worrisome...advance

has some benefits as well167...”

Small Dhodhi1 on cash advance said, “We don’t have much dealing with Lahoris [Large

Dhodhi]...we deal with “name” [Medium Dhodhi] and can ask him for cash advance if

and when needed...his cooperation in terms of cash advance is always there...we can

though have money [extended as cash] deducted for the principal paid [from regular

payment for milk supplied] as well if we want to...the average advance is around

100,000Rs [generally extended at the start of collection arrangement]”.

Small Dhodhi1 and Small Dhodhi2 have been supplying milk to Medium Dhodhi for the

last four and three years respectively. On their relationship Small Dhodhi1 said, “This

167 A mechanism to govern and control the small dhodhis so that they would not go to other buyers

336

[dealing or trade] is all about money and has nothing to do with the relationship”. Medium

Dhodhi however said, “Relationship [with small dhodhis] is based on the amount of

advance extended...apart from business, I do have close relationships with many of them

as I attend their marriages and funerals...they do consider this factor when someone offers

a higher rate [price for their milk]”.

On conflict Small Dhodhi 2 said, “Yes conflicts do arise, but then friends and other

dhodhis get involved in resolving the issues”. While Medium Dhodhi said, “[conflict]

mostly [arises] on the basis of rate [price] as they [small dhodhi] say that they are buying

at a higher price from the farmer...or [ask for] cash advance and we cannot meet their

demand then it leads to conflict...We keep giving them [small dhodhi] their payments [for

milk supplied] as we have extended advance [to small dhodhis] and there is no formal

contract so we then have trouble in getting our advance back, on the contrary, they find

excuses to leave us...” This was confirmed by Small Dhodhi1 who said, “Yes if he does

not pay us [prevailing price] for milk, we can stop the supply and go to another adda168”.

Small Dhodhi2169, however, said, “Yes [we can change buyer] but it is not easy to find

another contractor [medium dhodhi] as the advance [interest-free loan] has to be cleared”,

so the switch is probably dependent on the reputation of small dhodhi.

The power of small dhodhi increases in summer because there is higher demand and

reduced supply, “we can easily find a new buyer and the new buyer would even pay the

money [debt paid as cash advance] I owe to Medium Dhodhi...especially in summer...”

said Small Dhodhi1. This was consolidated by Medium Dhodhi saying, “We find it hard

to get suppliers in summer though it is quite easy in winter”, highlighting the seasonal

nature of power relationships too.

168 Central collection point medium buyer 169 small dhodhi1 was said to be a drunkard, drinking local made alcohol, which is considered a real social evil in the Pakistani society

337

G8.4.3. Medium and Large Dhodhi

Medium Dhodhi and Large Dhodhi have more professional business dealings as both

parties have clear rules of engagement and are better informed than the other chain

participants. Medium Dhodhi has been supplying milk to large dhodhi for the last two

years and gets paid every 2nd day. Medium Dhodhi said, “Our relationship is good as we

maintain supply of good quality milk to [name of Large Dhodhi]”. Large Dhodhi said,

“We do at times have differences, but then we compromise...at times I agree with what

he [Medium Dhodhi] says and at other times he compromises...if things don’t resolve,

both of us are free to go to a different party” This is because Large Dhodhi has not

extended any cash advance to Medium Dhodhi. He though has extended cash advances

to his 15 small dhodhi direct suppliers.

On the nature of power in this relationship, Medium Dhodhi said, “Yes [easy to find a

new buyer in hot summer]” whereas Large Dhodhi said, ‘Yes it is possible [to find new

sellers but] more money [cash advance] has to be paid”. This means Large Dhodhi will

have to invest more as cash advances if he changes supplier and is, therefore, dependent

on Medium Dhodhi who has invested his own capital and deals with small dhodhis, taking

all the pain that comes with these day-to-day transactions.

G8.4.4. Large Dhodhi and Retailers

Large Dhodhi has been supplying milk to Retailer1 and Retailer2 for the last 5 and 3 years

respectively. He is paid on a daily basis by milk retailers for the milk bought. However,

if they could not settle it the same day, it is noted and paid later or at times goes to account

where it will be settled only if the business dealings cease.

338

Large Dhodhi, on relationships with his retailer buyers, said, “... [it is] good as we fix

price for the whole year...we know the practice of kaan170 well”, which illustrates that

Large Dhodhi cannot be deceived since he knows the tricks of the trade quite well.

Large Dhodhi further said, “We have fixed [permanent retail] customers”, so the price is

not an issue of contention and in fact, Large Dhodhi suggests the retail milk price to the

two retailers. On the relationship and conflict, Retailer1 said, “....baradri [kinship] based

[relationship with Large Dhodhi] and we cannot really speak... He is my sandu [brother

in-law]...we never have a conflict”.

A key benefit of this relationship is not having to pay any cash advance to secure milk

supplies as Retailer2 said, “We are relatives...we only get milk based on our relationship

[with Large Dhodhi]. If we buy [milk] from someone else we will have to pay advance

of 200,000 to 300,000Rs...for them [Large Dhodhi & brothers] instead of paying them

we are often indebted to them...we trust each other and don’t have to pay any

advance...they [Large Dhodhi] just charge us on the basis of price purchased [keeping a

margin]...we get along well and just pay on the basis of agreed rate.” This also highlights

that both parties are aware of prevailing Lahore urban market prices and are confident

they have a good arrangement in place. Milk is being supplied without any advance taken

as security, which is otherwise a common practice in Lahore market.

On the balance of power and changing buyers, Large Dhodhi said, “Both parties are free

to go their own way if things don’t work...in summer many [retailers] chase asking for

milk but we try to meet the demand of those whom we had supplied in winter [i.e.

customer loyal in winter]...” On the other hand, Retailer2 on changing supplier said, “You

need to pay advance and it is not easy...I do not have to pay any advance for the milk I

170 A traditional practice in the Lahore market, performed by other retailers, who are not part of the family and boil milk to check

butterfat

339

buy [from Large Dhodhi]... If I had been buying the same quantity of milk from someone

else, I would have paid a big amount [of cash advance to secure supply]. So [the condition

of] not paying advance is very important for me...The reason our price is low is due to the

lesser price we pay to our supplier. He [Large Dhodhi] had his money blocked with

[other] shop keepers [not part of the family] so we thought to have our own shops instead

of selling milk to other shops”. Thus, this is extended family vertically integrating at the

retail end.

The milk is being sold on cash basis to final consumers at both retail shops though there

are a few customers buying on credit and paying after a month.

340

Chapter 8 Appendix H: Results: Case Study 3: Pakpattan - Lahore

fresh, unpackaged milk value chain

The informal value chain outlined in Figure 38 has four tiers before the product reaches

the final consumer. The chain originates from rural Pakpattan district situated 190 km

south-west of urban metropolitan Lahore city to which the milk is supplied. Pakpattan

district is in Sahiwal division, the third tier of government, between the province and

district. Sahiwal city is 45 km from this chain’s central milk collection centre. The milk

is also supplied to a shop in the Sahiwal city. Pakpattan, in old Punjabi, means "Clean

Land", named after a famous Sufi Saint Baba Fareed whose shrine is located there. This

chain has cool chain infrastructure with chillers installed, which is uncommon in the

traditional milk chains, at both the central collection point and the retail shops. In addition,

the formal processing sector operates parallel and at time integrates with the informal

chain.

341

Figure 38: Pakpattan-Lahore chain171 model and product physical flows

H8.1 Introduction of value chain actors, product physical flows and spoilage risks

This section introduces informal Pakpattan-Lahore value chain actors studied from

producer to retailers and few important areas in relation to the operation of this chain,

namely:


source of income, and number of years in the business




business operations by each participant (Table 43)

Risk of spoilage along the chain

171 Producer household estimates as large dhodhi collects 22,000L milk ÷200small dhodhis=110L → 110L ÷ 10Ps =11L therefore 22,000L ÷ 11LperP = 2000 Ps approx. & Consumer household estimates are based on 2011-12 Household Income Economic Survey

(HIES). Average per capita household size → 6.36L per month÷30day = 0.212Lper day× 6.41 member per household=1.4L →

10,000L sold at chain’s retail shops ÷ 1.4 = 7143 households approx.

Producer1 + approx. 2000 milk producers

Small Dhodhi + approx.

249 small dhodhis

Retailer1+3 specialized milk

retail shops owned by Large

Dhodhi +

9 franchise shops

1Large Dhodhi

Formal Processors

Mega

Contractors

Another big

brand milk

retail shop

buyer

Estimated 10 million consumers given

a 5% market share

7143 consumer households

342

Five actors are introduced

1. Milk Producer 1 is 42 years old and has an eight-member household. Producer1 has

ten years of formal schooling. He has been farming for the last fifteen years, and

farming is his only source of income. Four producers, all from the same village were

interviewed. Quotes from another producer (Producer2), who sells to another local

small dhodhi outside this chain, but gave important insights into the working of these

informal chains, will later be used, where appropriate.

2. Small Dhodhi is producer1’s milk buyer and is from the same rural vicinity. Small

dhodhi is 42 years old and lives in an extended family of twelve of which eight are

his immediate family. He has no formal schooling. Small Dhodhi has been collecting

milk for the last eighteen years, which is his key source of income although he is a

farmer as well. He and his two workers collect milk from 100plus producers and

deliver it to the two different collection points set up by the chain’s large dhodhi.

3. Large Dhodhi172 buys milk from Small Dhodhi and has an estimated 250 dhodhi

suppliers. He is the owner of the business and is in his late 40s. His cousin and a

younger brother support him. The younger brother is introduced in the next paragraph.

At the rural end, the business has hired 34 staff to manage the family’s milk collection

business. There are fourteen chillers at different rural points, and each chiller has a

milk tester. The milk is then brought to the main rural collection point, chilled and

transported to Sahiwal and Lahore, using unrefrigerated trucks, three of which are

hired. The milk is chilled again in Lahore.

172 dhodhi is not very appropriate term in this case, given relative sophistication and collection scale of this chain model. Large dhodhi

term will however be used for the sake of consistency. The interview was given by large dhodhi’s milk collection manager, who has

worked with big processors and has extensive experience

343

4. Specialised milk retail shop Retailer1 owner operator is the brother of large dhodhi.

This shop is in the upper middle-class locality of Lahore city. Retailer1 is 40 years

old and has ten years of formal schooling. He manages four of the thirteen retail fresh

milk shops in Lahore. The business has franchised nine other shops.

Another franchise shopkeeper (Retailer 2) was also interviewed, but he provided

limited information. Data from ten milk consumers interviewed at these two retail

shops will also later be used where appropriate.

5. Formal Processor(s) operate outside but are linked to this informal chain as

illustrated in Figure 38. A village adjacent to the village studied from where producers

were interviewed has multinational formal processor Nestlé’s chiller installed.

Producer1 on supply to this chiller said, “only dhodhis sell it [milk] to them [formal

processor]...if we take milk to them we will lose all our day...they offer better rate to them

[dhodhi] but not the farmer...also companies may go on strike but our dhodhi can’t do

that as he has other avenues [to sell milk]”. This statement depicts the importance of time

for producers and the surety of sale offered by small dhodhi who picks milk from their

doorstep. It also illustrates the different prices offered by the formal processors to dhodhis

and the producers.

Producer2 on selling milk to formal processors said, “They offer a better price than dhodhi

but do not offer advance”, thus highlighting that cash advance173 is important for the

producers.

Large Dhodhi said, “[At the rural end there is] surplus in winter174 that has to be disposed

of so [we have to] sell to companies175 [regularly]”. This statement was further clarified

by Retailer1 owner who stated, “Yes we sell milk to the companies, and we do that in

173 To be discussed in detail in the section 4 174 At the overall production increases in winter associated with the lactation cycle of dairy animals 175 Formal processors

344

routine. We reduce our sale to them if more demand at the shop(s)”, which demonstrates

the dependency of Large Dhodhi on formal processors who have a higher demand for

milk in winter when there is excess rural production and less demand at the urban retail

end.

Large Dhodhi further said, “We have agreements with Nestlé, Engro176 and Akbar

Gujjar177 and are also supplying 5000litres to another party178 in Lahore. This is for

security as not much demand in winter...so we have to supply even at a loss [to

processors]”, highlighting the dependency on the formal sector and lesser milk supply at

a lesser price.

Table 41 demonstrates that milk collection and distribution, using transport is the key

function performed by small dhodhi and large dhodhi. The transport is unrefrigerated all

along the chain, but the large dhodhi has installed proper chillers at the rural collection

points as well as chillers and refrigerators at the retailer shops for overnight milk storage.

Both large dhodhi and retailer process milk into various forms for sale purposes. The

chain generates an estimated 3,486 employment179 opportunities. The producers, Small

Dhodhi, Large Dhodhi and Retailer 1 and 2 are also put a substantial number of hours

into their labour intensive business operations.

176 Nestlé is a multination with the largest market share and Engro is assume to be 2nd of 3rd largest formal processor in Pakistan 177 Nestlé’s mega contractor / supplier 178 A retail buyer in Lahore city 179 22,000L÷200small dhodhis i.e. on min side = 110L÷10producers near to P1=11L per farmer therefore simply 22,000L÷11L per

producer= 2000 producer and assumed half the Ps have hired labourers i.e. 1000hired farmer workers + 2000Ps = 3000Ps →Now 200 small dhodhi×0.75hired worker per small dhodhi = 150+200 actual small dhodhis on min side=350small dhodhis; large dhodhi has

hired 34 staff+4family members=38 & each retailer shop has around 7 staff × 14 = 98. The calculation excludes the staff hired by

external parallel chains to which milk is being supplied

345

Table 41: Technology and infrastructure, labour and time along the rural Pakpattan-urban Lahore milk value chain

Producer 1 Small Dhodhi Large Dhodhi Retailer1

Physical functions

of transport,

storage and

processing

No transport or storage

involved as milk collected

fresh at their doorstep.

Some milk processing for

households usage.

Transport and each person

travels between 200 to 250km

on motor cycle to collect and

deliver milk

No storage or processing

involved

Transport that is collection from rural areas

and delivery to urban shops using five trucks

of which three are owned by the business.

Proper chillers installed for storage and milk

collected twice and transported one.

Ice also used when electricity breakdown and

during transport as trucks are not refrigerated

Processing milk into rabri180, kulfi181 at the

central collection point

Milk transported by large dhodhi

part of the business

Apart from the two products

made by large dhodhi, sweet milk

and yogurt is made at the urban

end

Labour Two brothers and one full

time hired labourer

Small Dhodhi himself and 2

hired two workers, one of

whom is his nephew

2 brothers owners and 1 cousin as family plus

sons also help look after the business

36 hired workers from collection manager to

milk quality checker to

4 labourers working and there

were same estimated number of

staff at each shop which make a

total of 52 at 13 shops

Time along the

chain (per day)

Each of the 3 person spends

around 12 hours each day

managing land and livestock

with the later taking more

than three quarters of that

time

3 persons spend 10 hours each

to collect morning and evening

milking

14 hour operation with rural collection starting

at 6:00am and return to the rural base by

around 9pm after delivery to retail shops in

Lahore city

Shops operate 24 hours a day


180 condensed sweet milk with nuts 181 traditional ice cream

346

There is higher spoilage risk borne by Small Dhodhi upstream in the absence of proper

cool arrangements. He said, “Yes [milk] does get spoiled though it is very rare...we do

however boil it and use it to make yoghurt here [at the central collection point of Large

Dhodhi]”, which means there is the alternative usage of milk if it has just started to spoil.

Large Dhodhi bears less risk since he deals in large volumes and ensures the quality of

milk before purchase and transferring. To ensure quality, Large Dhodhi has hired

experienced milk testers. The risk, however, increases downstream at retail end as

Retailer1 said, “Yes [milk does get spoiled] if traffic blockade or in very hot summers. If

[milk] just started to putrefy we boil and use it for [making] yoghurt but if totally spoiled

then [milk is] wasted...We ensure to sell milk which can maintain quality the next day or

two as consumers use it the day after”. The statement illustrates an alternate use of milk

and ensuring supply of relatively longer life milk to the final consumers.

H8.2 Consumer value, quality determination; grading and quantity measurements

along the Pakpattan-Lahore chain and gross margins


Milk quality attributes ranked by priority for all chain actors and their aggregate in

Table 42

Milk quantity units and quality aspects along product’s physical flows (Figure 39);

quality sought by buyer at each step and how is it assessed; rewards associated if any

for the seller for better quality, grading and quantity units for milk purchases and sales;

and


quality aspects


347

Final Consumers

Producers and Small Dhodhis

Small, Medium and Large Dhodhi

Large Dhodhi and Retailers

Table 42 ranks the importance of six quality attributes sought by various chain actors, in

the absence of product labelling, at any tier of the chain. The importance of these

attributes varied for each participant. However, taste followed by aroma were of prime

importance until large dhodhi when the priority changed to higher fat for retailer and

consumers. The sixth attribute of lactometer reading (LR) only appeared in conversations

with the Small and Large Dhodhi and is therefore not included in the comparison.

348

Table 42: Pakpattan-Lahore milk quality attribute perspective of various chain actors from farm to final consumer

Attributes Producer to Retailer Ranking Aggregate of Ranking

Producer 1 Producer 2 Producer 3 Producer 4 Small

Dhodhi

Large

Dhodhi Retailer

Producer to

Retailer

(n=7)

Consumers

(n=10)

Safety and health benefits 1 1 1 5 5 5 5 25 50

Visual appearance (colour) 4 3 3 2 1 3 4 20 40

Taste (sweetness) 2 1 1 1 2 1 2 10 22

Smell (aroma) 3 4 4 3 4 2 3 23 26

Thickness (higher fat content) 1 2 2 4 5 5 1 20 12

Lactometer Reading NA NA NA NA 3 4 NA 7 NA




349

Figure 39: Quantity and quality along the Pakpattan - Lahore chain


Producer Small Dhodhi Large Dhodhi Retailer

Small Dhodhi’s urban Quality standard

Large Dhodhi then lowers the fat for retailers from 5.4% at to around

4.5 to 4.6% by diluting it with ice

1ice : 16 milk

Retailer Quantity

At retail

Retailer1 sells in standard kg

where 1kg = 100grams

Producers sell in

standard kg

Small Dhodhi’smeasure used to convert Small Dhodhi’s kg to

litres

Producer Quantity

At farm gate

1 kg = 1000grams

&

maund is 40 kg

Price between Producer & Small Dhodhi is fixed for

a standard kg maund


Small Dhodhis loses volumes at Small Dhodhi’s central collection point due to

kg litre conversion as milk bought in litres

1 kg = 0.9681L

i.e. 40 kg × 0.9681 = 38.7 L

Small Dhodhi’s rural Quality standard

Large Dhodhi has however a 13% total solids (TS) standard for Small Dhodhis with a reward and

penalty system in place.

Assuming Small Dhodhi had 5.4% fat and 27LR milk he gains and the net volume now becomes 42L

Large Dhodhi has installed 1000, 1800 & 2300 litre proper milk chillers at the 14

rural collection points

5 unrefrigerated trucks

Governance (internal to the chain)

Standard kg for consumers

350

H.8.2.1 Final Consumers

Value chains are driven by what the consumer values. In addition to the information in

Table 42, comments by the final consumers interviewed at the two milk retail shops help

us further understand consumer perspective on quality.

A consumer (C1) at Retailer1 said, “[Quality means] more fat and good aroma”. Another

consumer (C1) at Retailer2 said, “Thickness and taste [are quality indicators]. Smell is

tested while using [milk]”, as milk is boiled before use. These statements demonstrate

that butterfat or cream, taste and aroma are the most valued attributes.

The consumers also have little awareness of the units used. A consumer (C5) at Retailer1

said, “[I bought milk] in litres182...Not sure of the difference [in units183]”. Another

consumer [C4] at retailer2 said “[Not sure of the unit] of purchase...litre and gadvi are the

same. This shop is selling milk in litres, quite similar to kg184”, though it does make a big

difference when dealing with larger volumes.

H8.8.2. Producers and Small Dhodhis

At farm gate, the only quality standard is higher fat content buffalo milk as Producer1

said, “There is a better price for buffalo milk as they [small dhodhis] are after higher

fat...[we] sell mixed milk”. Producers commonly have both buffalo and cow species.

Small Dhodhi through his experience has a good idea of milk quality sold by different

households as he said, “Some farmers dilute milk with water so they are given a lower

price as we do know it ...we do know which households supply pure milk”. Small Dhodhi

also formally tests milk quality at farm gate and said, “[Our185] first criteria to test milk

quality is taste of tongue...we do occasionally check fat and LR [lactometer reading]...if

182 although these shop were selling milk in kg and had even displayed the units on the shop 183 As most retail shops sell in the local unit gadvi apart from litre and kg 184 Acceptable but 1 litre of milk corresponds to 1.033 kg of milk OR 1 kg equals 0.968 litres. It is ok for smaller quantities but adds

up to quite a bit of difference for larger volumes 185 Works as a three member team i.e. himself and his two worker (Table 41)

351

in doubt I do check [milk bought] by taste first and don’t buy if not good”. Small Dhodhi’s

statement was verified by Producer2 who said, “dhodhis have lactometers, and they do

occasionally check milk for gravity”.

This chain does not have any issues on the quantity units at this tier (Figure 39). Producer1

said, “We sell (milk) in kilogramme186...here [in this area] the gadvis [milk pots] have

been measured187...we just fill them, and he [Small Dhodhi] picks it up”. Small Dhodhi’s

statement supported Producer1’s claim as he said, “We never measure [the quantity

supplied by the producer] and just trust whatever farmer says and note it down... I know

the quantity and can tell the difference of even pau188 by holding the pot...we buy in

kilogrammes and sell in litres”. These accounts demonstrate a high level of trust between

these two chain participants. The practice of not measuring milk before buying was also

observed in the field.

H8.2.3. Small and Large Dhodhi and Retailer

There is, however, an inconsistency on milk exchanges between Small Dhodhi and Large

Dhodhi (Figure 39). Small Dhodhi said, “They [Large Dhodhi] have a measure of 40

litres...sometimes there is a loss of 2 to 3 litres, but we never go into that and just buy and

sell”, which means that Small Dhodhi loses volume due to the kg to litre conversion189.

Large Dhodhi further verified this as he said, “We have our own collection measure of 5

litres to measure the collection [of small dhodhis]”. Large Dhodhi further added, “We

have our own collection measure...and can measure the collection, for example, 63 [kg]

collection [by Small Dhodhi] become 58 litres”, due to kg to litre conversion.

The product exchanges hand as standard litres between Large Dhodhi and Retailer1 as

these are two arms of the same business. The milk is sold, however, in kg again at the

186 Although was mentioning litres earlier in the conversation. Quantities commonly are reported in both as volume i.e. litres and

weight i.e. kg 187 Selling in 8, 14 or 15 kg pots 188 Urdu word for 250 grams 189 1 litre of milk corresponds to 1.033 kg of milk OR 1 kg equals 0.968 litres. So 40kg equals 38.72L

352

retail end, which helps the Large Dhodhi cum retailer gain substantial volumes. The retail

shop had clearly displayed that the shop sells milk in kg.

On milk quality assessment Small Dhodhi said, “[Large Dhodhi’s milk tester] takes a

small sample from each batch and tastes it, which is as if the milk has gone to the

laboratory190...they then also check fat and LR...We get paid [by Large Dhodhi] on the

basis of quality”.

Small Dhodhi further informed, “[Price] depends on the quality of milk that is lower

quality and cow milk has a lower price and buffalo milk has higher price” that is more

butterfat191 is rewarded in the chain. Large Dhodhi on quality check said, “...organoleptic

[is the best] test. If more laboratory tests are done there is more adulteration...the suppliers

develop a recipe to deceive.”

Large Dhodhi at the rural collection points has the following specific formula to check

milk quality:

0.22 × Actual Fat + 0.72 + SNF + Actual Fat = (TS per liter × Gross volume) ÷ 13%TS

= Net volume

where TS (Total solids) = Fat + SNF (Solid Not Fat)

and SNF (Solid Not Fat) = LR(lactometer reading) × 0.25

This formula is similar to that which large processors such as Nestlé use that is 13% total

solids (TS) standard. Large Dhodhi’s milk tester further wrote and explained, “Milk is

cleared at 25LR + 5.0fat + 13TS or 27LR + 5.4fat + 14TS”, as both equations give the

same net volume. Quality check at retail end is not relevant to this chain, which is

vertically integrated at the retail end.

190 Referring to the experience and expertise of the milk tester at this central milk collection centre in the chain 191 Associated with buffalo milk

353

On selling quality milk to the final consumer Retailer1 said, “We try to sell at 5.0% fat

but this effort is becoming unsuccessful as Nestlé has now started buying at 13TS...earlier

the 5.3 to 5.4 [%fat] was considered as 6.0 points both by Nestlé and us to avoid dhodhis

making any problem...but now Nestlé is not buying keenly anymore...maybe they have

bought milk from abroad or what we are not sure...they now have set 13 TS that is for 5.0

fat they give 6.0 that is ten extra points192...and so we have to do the same reluctantly”.

Retailer1’s statement highlights an important fact of competition being distorted by

formal processor Nestlé setting a lower total solid (TS) quality standard. What this means

is that previously 14% TS meant lesser net volumes for small dhodhis after using the

formula and an extra incentive was given to small dhodhis. Now the actual net volume

has increased, and the small dhodhis have to be paid more on the actual formula basis,

which makes it hard for the Large Dhodhi and informal chains to procure milk from the

rural market. The import of powdered milk also gives a huge advantage to the formal

processors as the same cannot be used by this chain where consumers are very taste

conscious and want fresh milk.

This change of TS standard is affecting the fat percentage target of Retailer1 at retail end

as he further said, “...now with this 5.4 fat we can sell it at 5.0 but the milk that our vehicle

picks from far away has to be diluted with ice to bring it to the chiller...and to avoid the

taste from being spoiled...the fat reduces around 2 to 4 points193 to bring it to Lahore...we

have no other option but to use ice to save milk from spoilage...our mission is to sell at

5.0 fat but it is not possible to maintain it, but we have displayed it on the shop...and tell

that it might be lower than that...our milk is 4.5 to 4.6% fat”. This shows that Retailer1 is

not able to meet his desired quality standards.

192 1 point for each 0.1% 193 0.2 to 0.4 % so fat becomes 4.8 to 4.6%

354

There is no grading at any stage in the chain as Small Dhodhi said, “No it is all mixed

milk, and it all goes together in the chillers so why do we grade unless they [large dhodhi]

ask us”. This was confirmed by Large Dhodhi who said, “We do not have any sort of

grading such as low or high quality...we generally give same rate [price to sellers] on the

basis of quality”.

The Retailer1 is well aware of what consumers seek and said, “Freshness of our milk is

liked by consumer very much...taste too...generally very unhygienic practices by others

[traditional chains]...if milk is spoiled we replace it for the consumer...our consumer is

satisfied with the price as he is educated”. The statement represents views of the upper-

income group to whom this shop in the chain sells, given its locality. Replacement is

offered as an additional service.

There is consumer feedback in place too as Large Dhodhi said, “Some days when ice is

used then consumers complain and so we cannot really use ice”, which supports that fat

is the most valued attribute. This shop, unlike other retailers in the Lahore urban milk

market, has clearly displayed 5% fat and kg unit as standards for the sale of milk to the

final consumer.

Table 43 estimates gross margins per actor, excluding owner operator’s opportunity cost

of labour and disregarding interest foregone on the capital invested. For large dhodhi and

retailer1, milk processed into yoghurt and other forms have not been included and the

costs associated with processing have been excluded accordingly.

355

Table 43: Physical and financial flows and capital invested by each actor along the Pakpattan-Lahore milk value chain


Volumes

(units as

mentioned

by each

actor)

14 kg

810kg×0.9681=784 litres.

Now using the large dhodhi formula explained

above and assuming that Small Dhodhi’s milk had

5.4% and 27LR, the net volumes based on the 13TS

would rise to 848 litres.

Small Dhodhi is losing 26kg due to kg to litre

conversion. He gains 64L due to the total solid

formula set by the large dhodhi. Small Dhodhi’s net

gain is 38 litres.

22,000 litres total net collection and with

the stated fat of 4.6% at the retail level the

volume becomes 23,387 litres milk i.e.

16milk:1ice

1,577kgs sold. Retailer1 has

gained 50 litres from litre to kg

conversion at the shop as

1577×0.9861=1,527kg

&

1,577-1527=50L

Average

price at

each step

36.25 Rs/kg

41.50 Rs / L

50 Rs / L 57 Rs / kg

Margins

(price cost

for

Producer s

& price for

all else)

11 Rs per standard

kg

6 Rs / unit 6 Rs / unit 8.5 Rs/unit

Average

variable

cost per

unit

1.9price :1cost

38 Rs/litre 43 Rs/litre Retailer1: 48 Rs/unit

Estimated

revenue per

day (P×Q)

508 Rs

34,000 Rs

1,134,235 Rs 89,889 Rs

356


Estimated

variable

cost per

day

18.4×14 =257.6Rs


28,363 for the milk procured

1800 Rs motorcycle fuel

150 Rs motorcycle maintenance

400 Rs hired labour

17Rs phone calls

1,1066,328 Rs that includes


56,429 for transport & fuel

1000 maintenance

49,000 ice blocks

1,167 electricity bill

2,466 maize straw used as fuel

9,600 for thirty four hired workers

1,167 shop rent

5000phone bill



1,000 transport

1,000 spoilage

7,000 ice blocks

1,500 electricity bill

2,333 gas bill

2,000 for polythene bags

2,800 hire labour

1533 shop rent

Gross

margins

per day

from milk

250.4 Rs 194

2,762 Rs

67,907 Rs -3,322 Rs

Capital

assets

invested

12 million Rs for

11 acres of

agricultural land

and 24 buffaloes

and cattle owned

by two brothers

2.5 million Rs as cash advance to 100 plus producer

suppliers,

milk collection pots

and 100,000 Rs for 3 motorcycles for himself and

two hired workers

Estimated 100m195 Rs plus as proper

chillers installed at rural collection points

and at urban retail shops, two trucks

&

credit money in circulation for procuring

milk from small dhodhis

1.7 million Rs per retail shop that

included milk chiller installed

worth 0.7 million with 1800 litres

capacity

Data Source: Author’s field research 1Based on author’s detailed farm economic analysis as part of his PhD research (Chapter 4, Table 6) and assuming Producer 1 produces 3,700 to 10,100kgs per annum based on

which the price cost margin is 1.9price:1cost

194 195 Authors’ estimate based on the milk volumes purchased and sold, compared to other chains studied

357

The highest gross margins earned by the Large Dhodhi are due to the large volumes

handled, but these are negligible in comparison to the capital tied up in the business. The

retail arm of the business, Retailer1, is making a loss, however. The margins earned by

Producer 1 from milk his enterprise are negligible despite substantial capital investment

in the mixed crop-livestock farm. Producer1 on the profitability of dairy enterprise said

“...Never estimated our cost of production...If we do that, and it will make us

worried...there is too much care of animals and less return...No other work opportunity in

this area i.e. factory etc. [so have to work on the farm]”. Similarly, Producer2 said, “...we

have never estimated the costs...once buffaloes start lactating in winter it [milk

production] becomes profitable”. These statements highlight that farmers are ignorant of

their costs. There are few work opportunities in the market hence low opportunity cost of

labour. Dairy enterprise profitability is seasonal.

H.8.3 Product seasonality, price determination, pricing power dynamics and

information flows

This section explores the seasonality aspect of milk production, including pricing in the

chain, and demand. Pricing mechanism (Figure 40) and price information flows (Figure

41), and associated power dynamics have also been explored. The section examines the

situation in the following sequence:


Retail Urban pricing

Farm Gate Rural pricing between Large Dhodhi, Small Dhodhi and producers and the

role of processors

Table 44 summarises the responses of chain actors and consumers on milk supply and

demand. On milk demand, six of the ten consumers interviewed at the two retail shops

said that their household consumption decreases in winter. The consumer’s statement was

358

supported by Retailer1 who said that there is excess supply in winter, which is sold to the

formal processors.

On supply, the producers, Small and Large Dhodhi informed that the milk production for

both buffaloes and cows starts decreasing in mid-April when demand for milk and other

dairy products starts to increase. Some producers, however, had cows producing more

milk in summer and less in winter. This production cycle of cow helps, meet some of the

increased summer demand.

359

Table 44: Punjabi196 and Gregorian calendar and buffalo & cow milk production / supply for Pakpattan Lahore chain

Maximum consumer demand in

peak summer months

Minimum consumer demand in

peak winter months

Chet

(14 Mar-

13 Apr )

Vaisakh

(14 Apr-

14 May)

Jeth

(15 May-

14 June )

Harh

(15 June-

15 July)

Sawan

(16 July-

15 Aug)

Bhadon

(16 Aug-

14 Sept )

Assu

(15 Sept-

14 Oct)

Katak

(15 Oct-

13 Nov)

Maghar

(14 Nov-

13 Dec)

Poh

(14 Dec-

12 Jan)

Magh

(13 Jan-

11 Feb)

Phagun

(12 Feb-

13 Mar)

Min buffalo milk supply

Min cow milk supply

Max buffalo milk supply

Max cow milk supply



360

Figure 40: Production and pricing mechanism in Pakpattan - Lahore chain


Farm gate price for Producerchanges with season

mainly in

increasing in summer with decrease in production /supply

&

decreasing in winter with increase in production /supply


fluctuates (up & down )


This price is based on the formal processors rural market buying prices

Milk Producer

Small Dhodhi Large Dhodhi Retailers

Formal Processors


Retail price is fixed for whole year & worked around the price set by the government

&

This chain strictly follows the price set by the government.

•Final consumer is price sensitive but relatively educated and willing to pay more for better quality

361

Figure 41: Price information flows along the Pakpattan - Lahore chain


Producers check


• those offered by other small dhodhis

• communicated by Small Dhodhibuying milk

Small Dhodhi checks



Formal Processor(s)


Retailers are




Large Dhodhi checks



362

H8.3.1. Final consumer’s response to price change

Consumers at both retail shops were not very price sensitive. The retailers were selling at

the price set by the government that is 57Rs per litre, whereas most retailers were selling

at a lower price than that benchmark. A consumer (C2) at retailer2 said, “Price of milk is

ok as there is generally very high inflation”. The relatively higher price was also linked

to satisfaction as another consumer (C4) said, “This milk is better than anywhere else in

the city”, suggesting that consumers in this part of the city were seeking quality and were

prepared to pay a higher price to gain that quality.

H8.3.2. Retail Urban Pricing

The price in urban Lahore market is fixed by the city district government for the whole

year. Retailer1 said, “the current government rate is fine, but those selling at lower prices

are a problem for us...we fix the same price as given by the government which is

ok...DCO197 should organise a meeting with all the stakeholders and set market-wide

standards”, highlighting the retailer's belief in the need to set uniform quality standards

that are associated with the price.

H8.3.3. Farm Gate Rural pricing between large dhodhi, small dhodhi and

producers and the role of formal processors

The large formal processors control and influence farm gate prices. Large Dhodhi

described, “The rate can change any time in summer by 50paisa198 to 1Rupee...the prices

go down from November to April199...the prices are linked to the import of powdered milk

by big milk factories as it is cheaper to them...the market slows with the import of

powder...we give a price slightly higher than the company [processor]”. The statement

197 District Coordination Officer, a representative and head of the city district government and committee that sets milk price per annum 198 Similar as cents in a dollar 199 Peak production season due the lactation cycle of dairy animals and higher availability of green fodders

363

highlights that market is distorted by the import of powdered milk and that there is

competition between formal and informal channels and the latter has to pay a higher price

to procure milk.

The procurement price is further verified by Producer2’s statement, who said, “We seek

information from others [producers] supplying to Nestlé...we are getting higher rate than

others”, which illustrates that the traditional chains are offering a better price and

producers also use the formal processor price both as a benchmark and source of price

information.

On price information source Large Dhodhi said, “[we verify the prices] with other big

players200 in the market”, that is the large formal processors.

Small Dhodhi informed that the price between him and Large Dhodhi is fixed, “By

exploring the competitors in the area...The price depends on the quality of milk

supplied...the price keeps varying and may change weekly or monthly and is linked to the

companies201 increasing or decreasing the milk prices”, which further validates the

information provided by Large Dhodhi.

Small Dhodhi said that price between him and the producer supplier is fixed, “In April

and May...[the rate] is linked to sale price [given by large dhodhi]...generally price

increases in summer and decreases in winter...when we get the rate [i.e. better price] it is

passed on backwards to them [producers]”. On price information, the Small Dhodhi said,

“We keenly monitor prevailing prices in the area”, which means he keeps a check on rural

market prices linked to those offered by the formal processors.

Producer 1 on price change said, “[Price changes] every six months and in between as

well202... [prices] mainly [change in] summer and winter”. On price information, he said,

200 Formal processors

202 Which means the price changes are passed on to the producers

364

“We keep checking the rate from neighbours and dhodhis then negotiate [with small

dhodhi]...lesser rates offered if the advance is taken and cow milk has lesser rate...”

highlighting the significance of buffalo milk and cash advance203.

Producer 1 on supply consistency said, “No there is always a demand except when there

is a strike”. This was verified by Producer 2 who said there is, “never a time when there

is...no demand [by Small Dhodhi]”. Small Dhodhi, however, referred to the time of excess

supply saying, “There was more supply and no demand, and we bore losses.” These

statements demonstrate that the informal chains are consistent buyers of milk irrespective

of seasonal variations in demand and supply. The price fluctuation risk is borne by the

dhodhis rather than the farmers.

H8.4 Facilitating functions of financing and payments, relationships and power

dynamics

There is an intricate set of facilitating functions in the chain that enable it to function in

the absence of formal contracts. This section describes the financing and various services

provided in the chain and illustrated in Figure 42. It will examine the duration and

description of relationships, conflict and problem-solving mechanisms; power

dimensions in seller’s role by exploring blocking supply or changing buyer and a buyer

stopping payment for milk supplied or changing supplier. This examination proceeds by

studying interactions between Producer 1& 2 and Small Dhodhi; Small and Large

Dhodhi; and Large Dhodhi and Retailer1.

203 Cash advance to be discussed in section 4

365

Figure 42: Financing, relationships and power dynamics along the Pakpattan-Lahore chain


• Almost all Producers take cash advance from Small Dhodhis to meet monthly

household needs. They also borrow whenever a need arises

• Accounts settled once every month but the advance generally keeps rolling

• Small Dhodhis also provides services such as feed supplements to Producers

• Relationship and time worked together is valued by both parties

• Cash advance & ready cash to meet needs are important

• Small Dhodhi trusts most of his suppliers and knows the households that dilute milk

• Disputes if any are settled by involvement of locals. Small Dhodhi is the one generally at loss as often loses his cash advance paid

•Retailer shops owned by Large Dhodhi as family

business

• Cash sales at the shop

Milk Producer Small Dhodhis Large Dhodhi Retailers Consumers

• Large Dhodhi has not extended cash advance to Small Dhodhis from whom

he procures milk directly

• Accounts are settled every eighth day

• Smoother relationship and trust as both parties have clear rules of

engagement i.e. quality and quantity arrangements

• Both parties are free to part ways as no capital involved but need each other

• Both parties have shared price information source that is rural central

collection points (addas) linked to formal processors & market demand

and supply


Cash Advance

Services



366

Five aspects important to the chain actors from producer to final consumer are quantified

in Table 45. Although the priorities varied for each chain member, overall, price and trust

are important. Trust is more important from transactions between Small and Large

Dhodhi and between Retailer and final consumers.

367

Table 45: Attributes important to seller farmer and all other buyers of milk in the rural Pakpattan-urban Lahore milk value chain:


Producer

1

Producer

2

Producer

3

Producer

4

Small

Dhodhi

Large

Dhodhi

Retailer1 Farmer

to

Retailer

(n=7)

Consumers

(n=10)

Convenience of selling for farmer /

buying for all other chain actors

and final consumers

5 4 2 5 3 2 1 22 22

Price 1 2 4 3 2 3 4 19 12

Trust 3 3 1 2 1 1 2 13 20

Advance money for milk 2 1 5 1 1 5 5 20 NA

Time worked together 4 5 3 4 4 4 3 27 NA

Note: Ranked on scale of 1 to 5 from farmer to retailer & 1 to 3 for final consumers for three attributes only (where 1 is highest in importance and 5 is lowest)



368

H8.4.1. Producer and Small Dhodhi

The relationship between the producers and Small Dhodhi is seen in the various services

provided by the Small Dhodhi. In particular, the Small Dhodhi provides financial services

to the milk producers as outlined in this section. Producers take cash advances from their

Small Dhodhi buyer. The account for milk procured is settled once every month, and the

initial cash advance keeps revolving with producer owing the dhodhi. Producer1 said,

“Yes [only] verbal commitment...He [Small Dhodhi] brings whatever we need...khal204,

choker205...whenever we need money we get it...not only for the milk supplied but

whatever amount we need...with the time when we keep borrowing more and supply less

milk we owe more [money] than we supply, and it becomes advance...currently we owe

him around 70,000 Rupees...at time it balances out, but this money keeps increasing or

decreasing”, illustrating that dhodhi is providing a form of financial service for the

producers. Small dhodhi also provides additional services such as animal feed

supplements.

Further information on the financial services is provided by Producer2 who said, “We get

money in advance [from Small Dhodhi] whereas Nestlé pays every eighth day...it is

convenient that milk is picked from our doorstep, and we get advance too...we generally

owe him 20 to 25,000Rs advance each month that keeps revolving”. This statement

demonstrates that the Small Dhodhi’s payment mechanism, incorporating other services,

suits producers better compared to the formal processors, who do not offer an advance

and make a delayed payment for milk supplied by the farmers.

In relation to the contractual arrangement with the milk producer suppliers, Small Dhodhi

said, “It is all verbal [arrangement]...we just keep a record [of milk supplied]...have not

204 cotton seed cake 205 wheat bran

369

taken any cheque [as guarantee]...only a few houses keep their record otherwise they trust

us... [I] supply them khal206 wanda207 but also advance when they need. We meet all their

needs even if we go through trouble ourselves”, highlighting the reason this tier of the

chain works smoothly.

Producer1 on relationships said “[I have been selling milk to Small Dhodhi for] more than

ten years... he is a good man, friend and neighbour... [We do not have] a business

relationship... [Conflict] never arose so far [among us]” showing the good terms between

the two. Small Dhodhi further clarified, “I have most of my suppliers [producers] going

on with me since when I started in 1994208... [I have a] very good relationship with all my

suppliers...they are like family to me...they trust me... [Farmers] are from the same area,

and they are like brothers and sisters to me. I love my suppliers...I never argue with them”,

which illustrates Small Dhodhi’s positive attitude towards his producer suppliers.

On handling conflicts with farmers, Small Dhodhi said, “Yes [conflicts do arise] on

payment as there are some who are dishonest, who keep borrowing and when we don’t

meet their demands they stop milk [supply]...we do involve the community to resolve it

as we can’t fight...and if no solution we just leave it even though we have to lose money”.

This indicates that since the Small Dhodhi has extended a cash advance, he occasionally

loses his money. He also believes that he is the one who has to compromise.

In order to further explore the nature of power in these dealings Producer1 said, “Yes

[we] can stop [milk supply] but don’t do it as he has never given us a chance [of

conflict]...other dhodhis do come to us [to buy milk] but we say to them as we are going

fine with the current arrangement...in summer we can easily get new buyers as milk is

less”, illustrating producers’ leverage as a seller increases even further in summer. Small

206 cotton seed cake 207 balanced concentrate feed for animals OR concentrate ration 208 18 years as the data was collected in 2012

370

dhodhi on the same topic said, “No we can’t stop payment as farmers owe money to us

and whenever we stop buying we lose the money extended as advance...We can get new

[suppliers] if we try at the same price”, which shows that the producers hold more power

in this chain due to the cash advance taken.

Producer2 who supplies milk to a different dhodhi said, “[we have] business relationship

only [with Small Dhodhi], he pays us for the milk supplied...Yes we do have differences

with dhodhi on rate, we then threaten him that we will stop the supply of milk and then

mutually agree to a price...yes [can stop milk supply]...very easily can find new dhodhis

as many i.e. around 10 to 15 [small dhodhis]...”, highlighting fierce competition among

local dhodhis and the informal milk channels.

H8.4.2. Small and Large Dhodhi and Retailer1

In terms of the payment schedule for supplier, Large Dhodhi said, “we make payment for

milk [to suppliers] ... either fourth or eighth day”, verified by Small Dhodhi who said,

“payment [for milk supplied] is made every Wednesday...we have no contract, and we

work on the basis of trust”. The contractual arrangement was further clarified by Large

Dhodhi who described, “We do have a contract with those [small dhodhis], who take the

advance and a [bank] cheque is taken as security [guarantee], but it is more trust based.”

Large Dhodhi further elaborated, “Those with whom we do not want to go permanent are

offered a better price as there is excess supply [of milk] in winter and so these suppliers

are offered a higher rate in summer, but we do not need milk from them in winter.”

Large Dhodhi had a more streamlined money transfer system and said, “[We] get online

payment from Lahore [retail end] whenever need to make payments [to suppliers]. This

is important given the serious law and order situation in the country and the risk of theft

and dacoits.

371

Small Dhodhi has been supplying milk to large dhodhi for the last three years and said,

“he [large dhodhi] respects us and we also never upset him...it works both ways...he treats

us as his brother... [we] never had an argument...even if a small issue arises he [large

dhodhi] tries to please us and agrees to whatever we ask...we can easily get another

buyer”, but it seems that the two parties respect and value their relationship.

Large Dhodhis’ manager said, “We have both commercial and personal relationships,

but the owner [of the milk business] has more personal relationships...mainly trust...90%

of our suppliers keep going with us...our main focus is on quality and so we refuse milk

which is not up to the mark and suppliers understand it...we explain that the poor quality

milk can spoil our whole lot...we do keep buying milk if it is up to the standard and have

to pay for it...it is hard to find milk in summer”, highlighting the need to carry on the

long-term relationship, which is based on clearly defined quality of milk. As the chain

was vertically integrated downstream, the payment schedule was not an issue with

retailer1.

372

Chapter 8 Appendix I: Largest formal processor in the dairy industry

On milk price fixation at the farm gate and 13% total solid standard the senior

collection manager of Nestlé stated, “We review farm gate milk prices paid on weekly

basis. The price is based on estimated domestic milk supply, competitors’ demand

international price of powder milk. The average farm gate or contractor price range this

year will vary from a minimum of Rs 37.5 to a maximum of Rs 50…Nestlé is completing

an exercise to evaluate the cost of milk production for 650 farmers from a range of farm

categories, small to large (100 cows/buffalo +)...”

He further said, “Nestlé has also changed its collection formula from 14 TS [total solids]

to 13 TS this year as this is aligned to the actual TS of the milk we receive which averages

around 13.4%TS. The farmer perception of his payment showing a reduction from the

defined price was the main reason for the change, which has been well received by

producers. Farmers now see themselves as being paid the actual quoted price plus a small

premium for the TS they supply, rather than being penalised for not making a target that

they could not achieve with cows’ milk”.

He informed, “Forty-five percent of our total collection comes through milk contractors

who collect from other agents and direct from mainly small farmers. Of the total

collection target, the village milk collection centres (VMCs) at the grassroots level

contribute about 17% of milk supplied”.

On milk shortages, peaks, and competitive market environment the manager stated,

“Nestlé’s milk collection drops substantially in summer with a peak/trough ratio of 3:1

which presents problems for manufacturing. Imported milk powder is blended with fresh

milk as a part of the manufacturing process, and this ensures that we meet the demand i.e.

373

reconstituted milk is used to produce milk based products including UHT milk. In winter

peak or flush there is much more supply then we can handle...”

On milk quality testing, he said, “At VMC: Organoleptic test, Fat, SNF and TS

percentage tests are done to check the quality. More tests are done at sub-centres and main

centres”.

On the loans extension, policy manager said, “Nestlé also extends twelve-week interest-

free loan to the farmers as ‘milk advance payments’. At any time, this is capped at around

130 million as advances to farmer suppliers. A maximum of Rs 10 million to a single

borrower has been extended which is finance to meet short-term seasonal needs with no

strings attached. Repayment, however, is by deduction from milk payments in uniform

instalments over 12 weeks.

A Nestlé employee at one of the VMCs, called “Centre Agent” or Milk Supplier Agent”

informed that these loans are only extended to large farmers only called commercial direct

farmers to whom advisory services are also provided. The loan is only considered after a

6-month history of milk supply to Nestlé, which is recovered without interest.

Nestlé maintains accounts on a weekly basis for all farmers. Small farmers are paid cash

after each week, through the Milk Supply agent, whereas the large farmers are paid by

direct bank deposit to the farmer’s account.

374

Chapter 8: Appendix J Questionnaires

Introduction to the research for each interviewee:

I am a PhD student. My colleague, from the on-going dairy project, accompanies me. I

am doing research on traditional milk value chains in Pakistan. This interview with you

is to understand milk production in a mixed farming system and the associated marketing

practices. The aim is to explore what happens from milk being sold at the farm gate to it

reaching the final consumer.

I will ask questions on milk production, storage, processing and associated costs. I will

also explore how people interact and business is done to make this marketing chains work

effectively.

The results from the survey will guide in analyzing and understanding the traditional milk

value chains. Based on this we will be able to identify the opportunities and constraints

to the development of the dairy industry and how more effective strategies can be

developed to supply milk from the farm to the consumer, in the best interest of all the

members of this milk chain.

Please note that your participation in this research is voluntary and there are no penalties

for not participating. The information you provide is confidential available only staff

involved in this research project. All data will be stored securely and reports will not

identify you in any way. The survey will take approximately half an hour depending upon

your answers. Is this time convenient to you or should we sit together some other time

which suits you?

375

J1. Milk Producer

a) Code for Interviewee

b) Date of interview

c) Place of interview

d) Time of interview _________ AM

_________ PM

I. Name, address and contact details of the

respondent

Mobile No:

II. Age

III. Gender

Male Female

IV. How many years have you been doing

farming?

V. Highest Level of Education completed?

VI. How many member in your family and

does anyone help you in the farming?

VII. Can you please share your average /

month household income?

up to Rs 11,500

Rs 11,501 to Rs 15,500

Rs 15,501 to Rs 20,000

Rs 20,001 to Rs35,000

Above Rs 35,000

376

1. As we are studying milk

value chains, what is your

primary role in this chain?

Milk producer

Small milk collector

Other and if so what?

2. Is farming your main

business?

Yes

No

Other

3. To whom did you sell

your milk today?

Self for home consumption

Small milk collector & distributor

Medium milk collector & distributor

Large milk collector & distributor

Retail or shop keeper

Farmer Neighbour / Final Consumer

Processing Company Collection point

4. How much milk did you

sell today & at what

price?

Buffalo milk

_________ in the morning

_________ in the evening

at _______Rs/ _______

Cow milk

_________ in the

morning

_________ in the evening

at _______Rs/ _______

OR mixed cow and buffalo

___________ at morning

___________ evening

at _______Rs/ _______

4.1 How much did you keep for home

consumption today?

Buffalo milk

_________ in the

morning

__________ in the

evening

Cow milk

_________ in the

morning

__________ in the

evening

4.2 Do you sell milk in kg i.e. 1000 grams

or litres i.e. 1000ml?

Not Sure Litre Kg Gadvi NA

4.3 If selling in kg or gadvi, can you

please tell me how many grams does it

have?

377

4.4 Can you please tell me how many kg

in a maund?

5. How many buyers of milk do you have?

6. Apart from milk supply, do you get

any other services to your sellers?

Such as loans, bag of fertilizer etc.

7. Is there any wastage of milk in

summer at your farm and if so how

much on average wastage on a hot

summer day?

Yes

No

Other

8. Are there months when you have

enough milk and there is no demand

by your buyer?

9. I assume buffalo and cow milk production changes with the season. Can you please guide me in

which month is the milk maximum and minimum?

Unaware Buffalo

Milk

Min

14 Mar-

13 Apr

14 Apr-

14 May

15 May-

14 June

15 June-

15 July

16 July-

15 Aug

16 Aug-

14 Sept

15 Sept-

14 Oct

15 Oct-

13 Nov

14 Nov-

13 Dec

14 Dec-

12 Jan

13 Jan-

11 Feb

12 Feb-

13 Mar

Chet

Vaisakh

Jeth

Harh

Sawan

Bhadon

Assu

Katak

Maghar

Poh

Magh

Phagun

Approx

Quantiti

es

Buffalo

Milk

Max

14 Mar-

13 Apr

14 Apr-

14 May

15 May-

14 June

15 June-

15 July

16 July-

15 Aug

16 Aug-

14 Sept

15 Sept-

14 Oct

15 Oct-

13 Nov

14 Nov-

13 Dec

14 Dec-

12 Jan

13 Jan-

11 Feb

12 Feb-

13 Mar

Chet

Vaisakh

Jeth

Harh

Sawan

Bhadon

Assu

Katak

Maghar

Poh

Magh

Phagun

Approx

Quantiti

es

Unaware Cow

Milk

Min

14 Mar-

13 Apr

14 Apr-

14 May

15 May-

14 June

15 June-

15 July

16 July-

15 Aug

16 Aug-

14 Sept

15 Sept-

14 Oct

15 Oct-

13 Nov

14 Nov-

13 Dec

14 Dec-

12 Jan

13 Jan-

11 Feb

12 Feb-

13 Mar

Chet

Vaisakh

Jeth

Harh

Sawan

Bhadon

Assu

Katak

Maghar

Poh

Magh

Phagun

Approx

Quantiti

es

Cow

Milk

Max

14 Mar-

13 Apr

14 Apr-

14 May

15 May-

14 June

15 June-

15 July

16 July-

15 Aug

16 Aug-

14 Sept

15 Sept-

14 Oct

15 Oct-

13 Nov

14 Nov-

13 Dec

14 Dec-

12 Jan

13 Jan-

11 Feb

12 Feb-

13 Mar

Chet

Vaisakh

Jeth

Harh

Sawan

Bhadon

Assu

Katak

Maghar

Poh

Magh

Phagun

Approx

Quantiti

es

378

10. When, how often and how much

does the price of milk change for you

as a milk producer and seller?

11. Do these prices only change in

summer and winter?

12. How long have you been supplying

milk to the same buyer(s)?

13. How would you describe your

relationship with your milk supplier

(s)?

14. Do you have any form of contract

with ________ milk buyer?

Yes

No

15. If not how does this system of trade

work?

16. The aspects below describe some criterion of your milk business as a buyer.

Can you please score and rank these aspects as a milk buyer?

Attributes Not Important Somewhat

important

Very Important Ranking

Convenience of

selling

Price

Advance money for

milk

Trust

Time worked

together

17. When do you get paid for your milk

sold i.e. after a month, after every

two week or advance payments?

18. How do you fix the price of milk you

sell with your with ___________

buyer?

(explore information flows i.e. type,

direction, timing, completeness,

accuracy, distortion)

19. Do you / how do you verify this price

to be prevailing price in the market?

20. Do you at times have conflict with

buyer and if so how do you resolve

these issues?

379

21. Can you block the milk supply if you

are not happy with the collector?

22. Do you think you can easily get other

milk buyers in summer and at the

price you are being paid?

23. What is the quality of milk to you

from a milk producer and seller’s

perspective?

24. Can you please score and priority wise rank these attributes for me from a milk producer’s

perspective? Attributes Not Important Somewhat important Very Important Ranking

Safety and health benefits

Visual appearance

(colour? Or cleanliness)

Taste (sweetness?)

Smell

Thickness (higher fat

content)

Lactometer Reading

25. Are you paid a higher price for better

quality of milk?

Yes

No


26. Do sort your milk in different grades

of quality?

Yes

No

27. If yes, how do you then use the

graded milk?

TIME and MAJOR ASSETS OR INVESTMENT

28. Time taken to milk each animal and

the total number of milk animals

(milking is done twice a day)?

________minutes / animal

________ milking animals

29. How much time does it take each

day to take care of land and

livestock?

380

30. How many milking buffaloes and

cows do you have?

(I will try to ascertain the whole

information given in the next three

columns depending on time and

situation but even number of milking

animals will be enough)

Head

Estimated

Market

Price/head

Milking Buffalo (Sujjar) Dry Buffalo (Tokhar) Buffalo Heifer (Choti/Gudapan)

(Ghaban or pregnant)

Buffalo Heifer (Choti) (Not

pregnant)

Buffalo Steer (Sun) Female Buffalo calve (Katti) Male Buffalo calve (Katta) Buffalo Bull (Sanda)

Head

Estimated

Market

Price/head

Milking Cow (Sujjar) Dry Cow (Tokhar) Heifer (Wehri/Gudapan)

(Ghaban or pregnant)

Heifer (Wehri/Gudapan) (Not

pregnant)

Steer (Wehra) Female cattle calve (Wachi) Male cattle calve (Wacha) Bull (Dand or Bael)

31. How much land do you cultivate

including leased and owned?

No land

Land leased:______________Acres at

_____________Rs/Acre/Annum

Land owned: _____________Acres at ____________

Rs/Acre market value

LABOUR

32. Do you have to hire labour for producing

milk or is it all done by the family?

Yes

No

33. If hired, how many, what functions do

they perform, wage rate and number of

hours worked each day?

Hired No. ________

Functions performed ________

Wage rate ________

Hours worked / day ______

34. If family labour, how many, functions

performed and hours worked each day?

Family No. ________


381

Wage rate? ________


TRANSPORT

35. Do you have to deliver the milk to the

collector?

Yes

No Go to storage

36. If yes what mode of transport do you use?

37. If the transport hired or owned?

Hired

Owned

38. If transport hired what is the approximate

rent / day?

If owned Purchase value of vehicle

Estimated km / day

Cost of fuel / day

Petrol price / litre

Estimated maintenance

cost / month

STORAGE

39. Do you need to store or chill the milk for

selling?

Yes

No Go to processing

40. If yes how much milk did you store and /

or chill today?

41. How did you store the milk today?

Ice blocks

Ice factory

Freezer

42. What is the cost of chilling or storage/day

approximately?

Ice blocks Rs_______/_______/day

Freezer electricity bill Rs_______/_______/month

PROCESSING

41.1Do you process milk in any other form? Yes

No

41.2 What products do you make from milk?

What are the estimated quantities and

prices?

NIL

Yogurt

Lassi

Cream

Quantity in Approx. price /

unit if sold

382

Butter

Desi Ghee

Khoya

QUALITATIVE DATA:

43. What attributes does your milk buyer

look for?

44. Do you know what your cost of

production of milk is?

45. Is milk production profitable?

Yes

No

Other

46. If not then why do you keep dairy

animals?

47. Does processing company pay a better

price?

Yes

No

Other

48. If yes then why don’t you sell milk to the

processing company?

I. Are there any specific comments that you

want to make that may help milk

marketing system work better for you as

milk producer, your collector and final

milk consumer?

383

J2. Milk Trader (Collector and Distributor)

NAME&ADDRESS&MOBILE No.:

a) Code for interviewee



d) Time of interview

________AM

________PM

I.Name, address and contact details of the

respondent

Mobile No:

II.Age

III.Gender Male Female

IV.How many years have you been involved

in this business?

V.Highest Level of Education completed?

VI.How many member in your family and

does anyone else in the family help you in the

business?

VII.Can you please share your average /


up to Rs 11,500

Rs 11,501 to Rs 15,500

Rs 15,501 to Rs 20,000

Rs 20,001 to Rs35,000

Above Rs 35,000

1. As we are studying milk value chains, what is your

primary role in this chain?

Milk Producer

Milk collector & distributor

Milk retailer

2. Is milk collection and sale your main business? Yes

No

Other

3. Where did you get your milk supply today?

Own milking

animals Quantit

ies

Prices

Collect

directly from

farmer

Buy from

supplier(s)

384

4.How much milk did you buy today and at what price? Buffalo milk

_________ at

_______Rs/

_______ in the

morning

_________ at

_______Rs/

_______ in the

evening

Cow milk

_________ at

_______Rs/

_______ in the

morning

_________ at

_______Rs/

_______ in the

evening


___________ at _________Rs/

________ morning only

___________ at _________Rs/

________ evening

5.How many suppliers of milk do you have?

6. Apart from milk collection, do you provide any other

services to your sellers? Such as loans, bag of fertilizer etc.

7.Is there any wastage of milk in summer from collection to

delivery if so how much average wastage on a hot

summer day?

Yes

No

Other

8.Are there months when you have enough milk collection

and there is no demand by your buyer?

9.I assume there is higher milk production in winter and less in summer. If so your milk collection also

changes. Please tell me in which month is your collection minimum and maximum?

Unaware Buffalo

Milk

Min

14 Mar-

13 Apr

14 Apr-

14 May

15 May-

14 June

15 June-

15 July

16 July-

15 Aug

16 Aug-

14 Sept

15 Sept-

14 Oct

15 Oct-

13 Nov

14 Nov-

13 Dec

14 Dec-

12 Jan

13 Jan-

11 Feb

12 Feb-

13 Mar

Chet

Vaisakh

Jeth

Harh

Sawan

Bhadon

Assu

Katak

Maghar

Poh

Magh

Phagun

Approx

Quantiti

es

Buffalo

Milk

Max

14 Mar-

13 Apr

14 Apr-

14 May

15 May-

14 June

15 June-

15 July

16 July-

15 Aug

16 Aug-

14 Sept

15 Sept-

14 Oct

15 Oct-

13 Nov

14 Nov-

13 Dec

14 Dec-

12 Jan

13 Jan-

11 Feb

12 Feb-

13 Mar

Chet

Vaisakh

Jeth

Harh

Sawan

Bhadon

Assu

Katak

Maghar

Poh

Magh

Phagun

Approx

Quantiti

es

Unaware Cow

Milk

Min

14 Mar-

13 Apr

14 Apr-

14 May

15 May-

14 June

15 June-

15 July

16 July-

15 Aug

16 Aug-

14 Sept

15 Sept-

14 Oct

15 Oct-

13 Nov

14 Nov-

13 Dec

14 Dec-

12 Jan

13 Jan-

11 Feb

12 Feb-

13 Mar

Chet

Vaisakh

Jeth

Harh

Sawan

Bhadon

Assu

Katak

Maghar

Poh

Magh

Phagun

Approx

Quantiti

es

Cow

Milk

Max

14 Mar-

13 Apr

14 Apr-

14 May

15 May-

14 June

15 June-

15 July

16 July-

15 Aug

16 Aug-

14 Sept

15 Sept-

14 Oct

15 Oct-

13 Nov

14 Nov-

13 Dec

14 Dec-

12 Jan

13 Jan-

11 Feb

12 Feb-

13 Mar

Chet

Vaisakh

Jeth

Harh

Sawan

Bhadon

Assu

Katak

Maghar

Poh

Magh

Phagun

Approx

Quantiti

es

385

10.When, how often and how much do you change the price of milk

for you supplier(s)?

11.Does your prices offered/ given to farmer(s) change with change

is season i.e. summer and winter?

12.How long have you been buying milk from the same supplier(s)?

13.How would you describe your relationship with your milk

supplier (s)?

14.Do you have any form of contract with ________ milk buyer?

Yes

No

15.If not how does this trade work?

16.The aspects below describe some criterion of your milk business as a seller.



important


Convenience of

selling

Price

Advance money for

milk

Trust

Time worked

together

17.When do you make payment for milk bought i.e. after a month,

after every two week or advance payments?

18.How do you fix the price of milk with your ________milk

supplier?

(explore information flows i.e. type, direction, timing,

completeness, accuracy, distortion)

19.Do you / how do you verify this price to be prevailing price in the

market?

20.Do you at times have conflict with supplier and if so how do you

resolve these issues?

21.Can you block the payment to your milk supplier if you are not

happy with the supplier?

386

22.Do you think you can easily get other milk suppliers in summer

and at the price you are paying?

23.How do you assess the quality of milk you collect?

24.Can you please score and priority wise rank these attributes for me from a milk collector’s

perspective?


important Very Important Ranking

Safety and health

benefits

Visual appearance

(colour? Or

cleanliness)

Taste (sweetness?)

Smell

Thickness or fat

check

Lactometer Reading

25.When buying, do you offer a higher price for higher quality

product?

Yes

No


26.Do you sort your milk in different grades of quality for your

buyers?

Yes

No

27.If yes, how do you then use the graded milk?


28.Do you have to collect the milk you sell? Yes

No go to labour

29.How long did it take to collect the milk today?

Morning

Evening

30.How long did it take to sell the milk today?

Morning

Evening

31.What is your major investment in your business?

LABOUR

387

32.Do you have to hire labour for your business or is it just family

business?

Yes

No Go to storage

33.If hired, how many, what functions do they perform, wage rate

and number of hours worked each day?

Hired No. ________

Functions performed

________

Wage rate ________


34.If family labour, how many, functions performed and hours

worked each day?

Family No. ________

Functions performed

________

Wage rate? ________


TRANSPORT

35.Do you have to use transport for you milk collection operation? Yes

No If no go to storage

36.What type of transport do you use to collect and sell your milk?

37.Is the transport hired or owned?

Hired

Owned

38.If transport hired what is the approximate rent / day?

If owned Purchase value of vehicle

Estimated km travelled /

day

Cost of fuel / day


Estimated repair and

maintenance cost / month

STORAGE

39.Do you need to store or chill the milk collected at any stage i.e.

from collection to delivery?

Yes

No If no go to processing

40.If yes, how much milk did you store and/or chill the milk today?

41.How did you store the milk today?

Ice blocks

Ice factory

Freezer

42.What is the cost of chilling or storage/day approximately?

Ice blocks

Rs__________/_________/day

Ice factory

Rs__________/_________/day

388

Freezer electricity bill

Rs_______/_______/month

PROCESSING:

i. What do you do with milk over

supply?

ii. Do you process milk in any other

form?

Yes

No Go to packaging

iii. Is de-creaming done at any stage?

iv. What products do you make from

milk? What are the estimated

quantities and prices?

NIL

Yogurt

Lassi

Cream

Butter

Desi Ghee

Khoya

Quantity in kg Price / kg

SHOP RENT

42.1 Do you have to own a shop to

runs your business?

Yes

No if no go to other costs

42.2 If yes, do you own or rent

this shop?

Own

Rent

42.3 If rented how much is the

rent per month?

42.4If owned what is the

estimated market value of the

property?

OTHER COSTS

42.4 What are the any other

costs associated with buying

and selling milk?

41.5 Do you have to make

phone calls to get in touch with

your suppliers of milk and to

find new suppliers?

41.6 Is there any government

tax and if yes how does it work?

Yes

No


41.7 Do you need to borrow

money for any aspect of your

business?

Yes

No

41.8 If yes, from where do you

borrow and on what terms?

389

41.9 Who do you sell milk to?

Self for home

consumption

Quantities Prices

Farmer

Small milk collector

& distributor

Medium milk

collector & distributor

Large milk collector

& distributor

Company


Consumer

QUALITATIVE DATA:

GOVERNANCE / INFORMATION FLOWS/RULES:

RESPONDENT AND HIS BUYER

43.What attributes does your milk

buyer look for?

44.How long have you been

supplying milk to _________?

45.How would you describe your

relationship with your milk buyer

(s)?

46.Do you at times have conflict with

buyer and if so how do you resolve

these issues?

47.Can you block the supply if you

are not happy with the buyer?

48.Do you think you can easily get

other milk buyers at the price you

are paid?

49.How do you fix the price of milk

with your milk buyer(s)?

(explore information flows i.e.

type, direction, timing,

completeness, accuracy,

distortion)

50.How do you verify this price to be

prevailing price in the market?

51.When do you get paid for the milk

you sell i.e. every day, after two,

after a month or advance

payments?

390

52.How often does the milk price

change which your milk buyer and

what do you then do with the

farmer supplier of milk?

53.Do you have any form of contract

with ________ milk supplier?

Yes

No

54.If not how does this trade work?

55.Please help me understand the

difference between litre, kg and

gadvi?

56.In what units do you buy and sell

milk?

57.Please help me understand the

difference in maunds in your

collection and final market?

I. Are there any specific

comments that you want to

make that may help milk

marketing system work better

for your supplier, yourself and

the final milk consumer?

391

J3. Milk Retailer

NAME&ADDRESS&MOBILE No.:

a) Code for interviewee



d) Time of interview

________AM

________PM

I.Name, address and contact details of the

respondent

Mobile No:

II. Age

III. Gender Male Female

IV.How many years have you been involved

in this business?


VI.How many member in your family and

does anyone else in the family help you in

the business?

VII.Can you please share your average /


up to Rs 11,500

Rs 11,501 to Rs 15,500

Rs 15,501 to Rs 20,000

Rs 20,001 to Rs35,000

Above Rs 35,000

1. As we are studying milk value

chains, what is your primary

role in this chain?

Milk retailer

Milk collector as well

Milk supplier to houses and tea stalls

2. Is milk sales at this shop your

main business your main

business?

Yes

No

Other

3. Where did you get your milk

supply today?

Own milking animals Quantities

Prices

Collect directly from

farmer

Buy from supplier(s)

392

4. How much milk did you buy

today and at what price?

Buffalo milk

_________ at

_______Rs/ _______ in

the morning

_________ at

_______Rs/ _______ in

the evening

Cow milk

_________ at _______Rs/

_______ in the morning

_________ at _______Rs/

_______ in the evening


___________ at _________Rs/ ________ morning only

___________ at _________Rs/ ________ evening

5. How many suppliers of milk

do you have?

6. Apart from milk sale at the shop,

do you provide any other services

to your sellers? Such as loans, bag

of fertilizer etc.

7. Is there any wastage of milk in

summer from collection to

delivery if so how much

average wastage on a hot

summer day?

Yes

No

Other

8. Are there months when you

have enough milk collection

and there is no demand by

your buyer?

9. I assume there is higher milk

production in winter and less

in summer. If so your milk

sales also changes. Please tell

me in which month is your

sales minimum and

maximum?

Unaware

Buffalo

______________

minimum month

______________

maximum month

Unaware

Cow

______________ minimum month

______________ maximum month

10. When, how often and how

much do you change the price

of milk for you suppliers?

393

11. Does your prices offered/

given to supplier(s) change

with change is season i.e.

summer and winter?

12. How long have you been

buying milk from the same -

__________supplier(s)?

13. How would you describe your

relationship with your

_________milk supplier (s)?

14. Do you have any form of

contract with _________ milk

supplier?

Yes

No

15. If not how does this trade

work?

16. The aspects below describe some criterion of your milk business as a buyer.



important


Convenience of selling

Price

Advance money for milk

Trust

Time worked together

17. When do you make payment

for milk bought i.e. after a

month, after every two week

or advance payments?

18. How do you fix the price of

milk with your ________milk

supplier?



completeness, accuracy,

distortion)

19. Do you / how do you verify

this price to be prevailing

price in the market?

20. Do you at times have conflict

with supplier and if so how do

you resolve these issues?

394

21. Can you block the payment to

your milk supplier if you are

not happy with the supplier?

22. Do you think you can easily

get other milk suppliers in

summer and at the price you

are paying?

23. How do you assess the quality

of milk supplied to you?

24. Can you please score and priority wise rank these attributes for me from a milk collector’s

perspective?


important


Safety and health benefits

Visual appearance (colour? Or cleanliness)

Taste (sweetness?)

Smell

Thickness or fat check

Lactometer Reading

Knan marna

25. When buying, do you offer a

higher price for higher quality

product?

Yes

No


26. Do you sort your milk in

different grades of quality for

your buyers?

Yes

No

27. If yes, how do you then use

the graded milk?


28. Do you have to collect the

milk you sell?

Yes

No go to labour

29. How long did it take to collect

the milk today?

Morning

Evening

30. How long did it take to sell the

milk today?

Morning

Evening

395

31. What is your major

investment in your business?

LABOUR

32. Do you have to hire labour for

your business or is it just family

business?

Yes

No Go to storage

33. If hired, how many, what

functions do they perform,

wage rate and number of hours

worked each day?

Hired No. ________


Wage rate ________


34. If family labour, how many,

functions performed and hours

worked each day?

Family No. ________


Wage rate? ________


TRANSPORT

35. Do you have to use transport for

you milk collection and sale

operation?

Yes

No If no go to storage

36. What type of transport do you

use to collect and sell your milk?

37. Is the transport hired or owned?

Hired

Owned

38. If transport hired what is the

approximate rent / day?

If

owned

Purchase value of vehicle

Estimated km travelled / day

Cost of fuel / day


Estimated repair and

maintenance cost / month

STORAGE

39. Do you need to store or chill the

milk collected at any stage i.e. from

collection to delivery?

Yes

No If no go to processing

40. If yes, how much milk did you store

and/or chill the milk today?

396

41. How did you store the milk today?

Ice blocks

Ice factory

Freezer

42. What is the cost of chilling or

storage/day approximately?

Ice blocks Rs__________/_________/day

Ice factory Rs__________/_________/day

Freezer electricity bill Rs_______/_______/month

PROCESSING:

v. What do you do with milk over

supply?

vi. Do you process milk in any other

form?

Yes

No Go to packaging

vii. Is de-creaming done at any stage?

viii. What products do you make from

milk? What are the estimated

quantities and prices?

NIL

Yogurt

Lassi

Cream

Butter

Desi Ghee

Khoya

Quantity in kg Price / kg

PACKAGING:

ix. I assume you sell milk, yogurt etc in

polythene bags?

Yes

No

x. How much polythene bags do you

use per day?

polythene bag kg

xi. What is the approximate cost of

polythene bags per day?

______________Rs/ kg / day

SHOP RENT

42.1 Do you have to own a

shop to runs your

business?

Yes

No if no go to other costs

42.2 If yes, do you own or

rent this shop?

Own

Rent

397

42.3 If rented how much is

the rent per month?

42.4If owned what is the

estimated market value of

the property?

OTHER COSTS

42.4 What are the any

other costs associated with

buying and selling milk?

41.5 Do you have to make

phone calls to get in touch

with your suppliers of milk

and to find new suppliers?

41.6 Is there any

government tax and if yes

how does it work?

Yes

No


41.7 Do you need to

borrow money for any

aspect of your business?

Yes

No

41.8 If yes, from where do

you borrow and on what

terms?

41.9 Who do you sell milk

to?

Self for home consumption Quantities

Prices

Small milk collector &

distributor

Medium milk collector &

distributor

Large milk collector &

distributor

Company


Consumer

QUALITATIVE DATA:

GOVERNANCE / INFORMATION FLOWS/RULES:

RESPONDENT AND HIS BUYER

43. What attributes does your milk

buyer look for? OR How is the

quality of milk assessed by your

shop customers?

44.

45.

46. Do you at times have conflict with

customers and if so how do you

resolve these issues?

47.

398

48. Are customers happy with your

price and quality of milk?

49. How do you fix the price of milk

for customers at the shop?



completeness, accuracy, distortion)

50. How do you verify this price to be

prevailing price in the market?

51. When do you get paid for the milk

you sell i.e. every day, after two,

after a month or advance

payments?

52. How often do the milk prices

change in your milk market?

53.

54.

55. Please help me understand the

difference between litre, kg and

gadvi?

56. In what units do you buy and sell

milk?

57. Please help me understand the

difference in maunds in your

collection and final market?

I. Are there any specific comments

that you want to make that may

help milk marketing system work

better for your supplier, yourself

and the final milk consumer?

399

J4. Milk Consumer

a) Code for Interviewee



d) Time of interview ________________ AM

_________________ PM

CONSUMER PREFERNCE:

1. What is your preferred source of getting / buying milk and can I please ask the reason for this

preference?

2. Can you please score and rank these milk sources for me?


important


This shop

Home delivery by milk man

Packaged milk from grocery shop

3. Any specific reason for this preference?

4. How many years have you been buying milk from the same shop /seller?

5. (16) Can you please score and rank these aspects for me as a milk consumer?


important


Convenience of buying

Trust and loyalty with seller

Price

6. What is your preferred form of milk and can I please ask the reason for this preference?

7. Can you please score and rank these forms of milk for me? Attributes Not Important Somewhat

important


Fresh milk

Packaged milk

Powdered milk

400

CONSUMER VALUE:

8. If I ask what is milk quality to you how would you answer that?

9. (24) Can you please score and rank these attributes for me from a milk consumer’s perspective?


important


Safety and health

benefits

Visual appearance

(colour? Or

cleanliness)

Taste (sweetness?)

Smell

Thickness (higher

fat content?)

10. Do you think you are getting these desired attributes of milk in terms of quality and for the price

you are paying?

11. Can you tell difference between buffalo

and cow milk?

Yes

No

Somewhat

12. If yes, what milk would you prefer to

buy and can I please ask the reason for

this preference?

Buffalo milk

Cow milk

No preference

BUYING BEHAVIOUR

13. How much milk, fresh or in any other form

did you buy today both in the morning and

evening?

____________________ Morning

____________________ Evening

14. What was the unit of fresh milk purchased?

Not Sure Litre Kg Gadvi NA

15. Can I tell the difference between litre, kg and

gadvi?

Not Sure

16. What price did you pay for milk today?

Rs/

17. Who generally buys the milk in your

household?

18. How is milk consumed in your household i.e.

for tea, drinking milk by parents and kids etc?

401

19. What other milk based products did you buy

today?

NIL

Quantity

bought

Price/unit

Yogurt

Lassi

Cream

Butter

Desi Ghee

Khoya

Cheese

Margarine

Ice cream

Other and if

so what?

20. Does your milk consumption change in

summer and winter?

Yes

No

21. If yes how much maximum and minimum in

summer and winter?

______________/ day in summer

______________/ day in winter

402

DEMOGRAPHICS:

I.Are there any specific comments that you

want to make that may help milk marketing

system work better for this milk supply from

producer, collector(s) through to this shop

and you as final milk consumer?

II. Where do you live?

III. Age

IV. Gender

Male Female


VI. How many member in your family and does

anyone help you in the farming?

VII. Can you please share your average / month

household income?

up to Rs 11,500

Rs 11,501 to Rs 15,500

Rs 15,501 to Rs 20,000

Rs 20,001 to Rs35,000

Above Rs 35,000

milk value chain analysis: industry competitiveness and

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