1 sa meat and the global market andré jooste senior manager: market and economic research centre,...
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1
SA Meat and the Global Market
André JoosteSenior Manager: Market and Economic Research Centre, National Agricultural Marketing Council
13 March 2008
2
Structure of presentation
International overview Price trends in SA Consumption trends in SA Pointers Conclusions
3
World cattle producers
200
2,200
4,200
6,200
8,200
10,200
12,200
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014T
ho
usa
nd
Met
ric
ton
nes
USA Brazil China EU India Austrtalia SA
SA ave: 630 000 t
Source: FAPRI, 2004
4
World supply and demand for beef and veal
26 000
26 500
27 000
27 500
28 000
28 500
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
kt c
we
15
15.2
15.4
15.6
15.8
16
16.2
kg/c
apita
Production Consumption Per capita consumption
Source: OECD and FAO secretariats
5
World beef exports
0
500
1000
1500
2000
250019
95
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
Year
Th
ou
san
d to
ns
EU North America Oceanea Mercosur
Source: OECD, 2004
6
Imports projections (beef and veal)
200
400
600
800
1 000
1 200
1 400
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015('0
00 t)
Japan Mexico Russia South Africa South Korea
Source: FAPRI 2006
7
World trade projections (beef)
1 000
2 000
3 000
4 000
5 000
6 000
7 000
8 000
9 000
10 000
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
('000
t)
World trade OECD Developing Least developed countries
Source: OECD and FAO secretariats
8
World beef trade flows, EU-12, 1990
25-5050-100100-150
150-200
200-300
300-400
> 400
Vloei in '000 t cwe
Based on GIRA figures
92
195
116
393
126
134
98
33
Source: Spanghero, 2002
9
World beef trade flows ,EU-15, 1995
117
313
73
597
64
205
172
49 60
25-5050-100100-150
150-200
200-300
300-400
> 400
Vloei in '000 t cwe
Based on GIRA figures
Source: Spanghero, 2002
10
World beef trade flows, EU-15, 2000
29
155
35
317
48
60
112
279
39 25
25-5050-100100-150
150-200
200-300
300-400
> 400
Vloei in '000 t cwe
Based on GIRA figures
Source: Spanghero, 2002
11
World beef trade flows, AU/NZ - 2005
12
World beef trade flows, EU and North America - 2005
13
World beef trade flows, S.Am - 2005
14
World beef trade flows,2005 (GMC)
15
16
Per capita consumption 2006 vs 2016
0
10
20
30
40
50
60
70
Argentina
US
A
Brazil
Australia
Canada
New
Zealand
Mexico
EU
-25
Russia
South
Africa
kg/p
er
2006 2016
Source: FAPRI, 2007
Decline
17
Results - Beef finishingPurchase prices (US$ per 100 kg live weight)
0
100
200
300
400
500
600
700
800
900
AT-2
5FAT
-35
AT-1
20AT
-150
T
DE-2
30DE
-260
DE-2
80DE
-800
DE-5
25T
FR-4
5FR
-70
FR-9
0AFR
-90B
ES-6
30ES
-940
ES-6
790
IT-9
10IT
-288
0T
IE-1
85
UK-3
5UK
-90
UK-9
8
SE-1
40SE
-230
T
PL-1
2PL
-30
CA-9
600
US-7
200
AR-8
00AR
-220
0
BR-1
40BR
-240
BR-3
40BR
-600
CN-3
00CN
-940
AU-2
7K
ZA-7
5K
Calf price Weaner price Backgrounder price
18
Results - Beef finishingShort and medium term profitability (US$ per 100 kg carcass weight)
-400
-300
-200
-100
0
100
200
AT-2
5FAT
-35
AT-1
20AT
-150
T
DE-2
30DE
-260
DE-2
80DE
-800
DE-5
25T
FR-4
5FR
-70
FR-9
0AFR
-90B
ES-6
30ES
-940
ES-6
790
IT-91
0IT-
2880
T
IE-18
5
UK-3
5UK
-90
UK-9
8
SE-1
40SE
-230
T
PL-1
2PL
-30
CA-9
600
US-7
200
AR-8
00AR
-220
0
BR-1
40BR
-240
BR-3
40BR
-600
CN-3
00CN
-940
AU-2
7K
ZA-7
5K
Short-term: Total returns less cash cost
Medium-term: Total returns less cash cost+depreciation
19
Background: Evolution of the industry The major transition periods:
Opportunity driven (1970s) Production driven (1980s) Cost driven (1990s) Consumer driven (2000 -)
Liberalization in 1995Deregulation in 1997
- Beef industry already started in 1992
IS IT GOOD ENOUGH TO BE CONSUMER ORIENTATED??
20
Price trends
Source: AMT
Prices of different meat types
0500
100015002000250030003500
Oct
-03
Jan-
04
Apr
-04
Jul-0
4
Oct
-04
Jan-
05
Apr
-05
Jul-0
5
Oct
-05
Jan-
06
Apr
-06
Jul-0
6
Oct
-06
Jan-
07
Apr
-07
Jul-0
7
Oct
-07
Months
c/kg
Clas A2/A3 lamb Class A2/A3 beefPorkerprice Fresh chicken
21
Price trends – focus on beef
Source: DoA, 2008
0
200
400
600
800
1000
1200
1400
1600
1800
2000
19701971197219731974197519761977197819791980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007
c/kg
0
5
10
15
20
25
30
Kg
per
capi
ta
Real price Nominal price Per capita consumption
22
Weaner and A2/A3 carcass prices
Source: AMT, 2007
500
700
900
1100
1300
1500
1700
1900
2100
2300
Jan-02
Apr-02
Jul-02
Okt-02
Jan-03
Apr-03
Jul-03
Okt-03
Jan-04
Apr-04
Jul-04
Okt-04
Jan-05
Apr-05
Jul-05
Okt-05
Jan-06
Apr-06
Jul-06
Okt-06
Jan-07
Apr-07
Jul-07
Oct-07
c/kg
Weaner A2/A3 carcass
23
Price trends
Source: DoA
0
50
100
150
200
250
300
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
Year
Ind
ex
20
00
=1
00
PPI-Summer grains PPI-Cattle slaughtered
PPI-Sheep slaughtered PPI-Pigs slaughtered
FRPI-Fuel FRPI-Animal health and crop protection
More or less in balance
Increased volatilityPeriod of significant gains and losses
24
Producer share in the retail price of rump
y = -0.0059x + 38.082
25
27
29
31
33
35
37
Sep-99
Dec-99
Mar-00
Jun-00
Sep-00D
ec-00
Mar-01
Jun-01
Sep-01
Dec-01
Mar-02
Jun-02
Sep-02D
ec-02
Mar-03
Jun-03Sep-03
Dec-03
Mar-04
Jun-04
Sep-04D
ec-04
Mar-05
Jun-05Sep-05
Dec-05
Mar-06
Jun-06
Sep-06D
ec-06
Mar-07
Jun-07Sep-07
Dec-07
%
Producer share in retail price Trend
Source: STATSSA & own calculations
25
Producer share in the retail price of sirloin
y = 0.0158x + 12.258
25
27
29
31
33
35
37
39
Sep-99D
ec-99M
ar-00Jun-00Sep-00D
ec-00M
ar-01Jun-01Sep-01D
ec-01M
ar-02Jun-02Sep-02D
ec-02M
ar-03Jun-03Sep-03D
ec-03M
ar-04Jun-04Sep-04D
ec-04M
ar-05Jun-05Sep-05D
ec-05M
ar-06Jun-06Sep-06D
ec-06M
ar-07Jun-07Sep-07D
ec-07
%
Producer share in retail price Trend
Source: STATSSA & own calculations
26
Producer share in the retail price of topside
y = 0.005x + 35.668
35
37
39
41
43
45
47
49
Sep-99D
ec-99M
ar-00Jun-00Sep-00D
ec-00M
ar-01Jun-01
Sep-01D
ec-01M
ar-02Jun-02Sep-02D
ec-02M
ar-03Jun-03Sep-03
Dec-03
Mar-04
Jun-04Sep-04D
ec-04M
ar-05Jun-05Sep-05D
ec-05
Mar-06
Jun-06Sep-06D
ec-06M
ar-07Jun-07Sep-07D
ec-07
%
Producer share in retail price Trend
Source: STATSSA & own calculations
27
Producer share in the retail price of brisket
y = -0.013x + 72.256
45
50
55
60
65
70
Sep-99
Dec-99
Mar-00
Jun-00
Sep-00
Dec-00
Mar-01
Jun-01
Sep-01
Dec-01
Mar-02
Jun-02
Sep-02
Dec-02
Mar-03
Jun-03
Sep-03
Dec-03
Mar-04
Jun-04
Sep-04
Dec-04
Mar-05
Jun-05
Sep-05
Dec-05
Mar-06
Jun-06
Sep-06
Dec-06
Mar-07
Jun-07
Sep-07
Dec-07
%
Producer share in retail price Trend
Source: STATSSA & own calculations
28
Producer share in the retail price of chuck
y = -0.0291x + 89.771
40
45
50
55
60
65
Sep
-99
Dec-9
9
Mar-0
0
Jun
-00
Sep
-00
Dec-0
0
Mar-0
1
Jun
-01
Sep
-01
Dec-0
1
Mar-0
2
Jun
-02
Sep
-02
Dec-0
2
Mar-0
3
Jun
-03
Sep
-03
Dec-0
3
Mar-0
4
Jun
-04
Sep
-04
Dec-0
4
Mar-0
5
Jun
-05
Sep
-05
Dec-0
5
Mar-0
6
Jun
-06
Sep
-06
Dec-0
6
Mar-0
7
Jun
-07
Sep
-07
Dec-0
7%
Producer share in retail price Trend
Source: STATSSA & own calculations
29
Consumption trendsTotal and per capita consumption of beef
300
400
500
600
700
800
9001970/7
1
1972/7
3
1974/7
5
1976/7
7
1978/7
9
1980/8
1
1982/8
3
1984/8
5
1986/8
7
1988/8
9
1990/9
1
1992/9
3
1994/9
5
1996/9
7
1998/9
9
2000/0
1
2002/0
3
2004/0
5
Year
Th
ou
san
d t
on
s
10
12
14
16
18
20
22
24
26
kg
per
cap
ita
Total consumption of beef Per capita consumption of beef
Source: DoA
30
Consumption trends (…continue)
Source: DoA
Total and per capita consumption of white meat
0
200
400
600
800
1,000
1,200
1,4001970/7
1
1972/7
3
1974/7
5
1976/7
7
1978/7
9
1980/8
1
1982/8
3
1984/8
5
1986/8
7
1988/8
9
1990/9
1
1992/9
3
1994/9
5
1996/9
7
1998/9
9
2000/0
1
2002/0
3
2004/0
5
2006/0
7
Year
Th
ou
san
d t
on
s
0246810121416182022242628
kg
per
cap
ita
Total consumption of white meat
Per capita consumption of white meat
31
Consumption trends (…continue)
Source: DoA
Total consumption white meat and red meat
0
200
400
600
800
1,000
1,200
1,4001970/7
1
1972/7
3
1974/7
5
1976/7
7
1978/7
9
1980/8
1
1982/8
3
1984/8
5
1986/8
7
1988/8
9
1990/9
1
1992/9
3
1994/9
5
1996/9
7
1998/9
9
2000/0
1
2002/0
3
2004/0
5
2006/0
7
Year
Th
ou
san
d t
on
s
Total consumption of white meat
Total consumption of red meat
32
Consumption trends (…continue)
Source: DoA
Per capita consumption of white meat and red meat
05
101520253035404550
1970/7
1
1972/7
3
1974/7
5
1976/7
7
1978/7
9
1980/8
1
1982/8
3
1984/8
5
1986/8
7
1988/8
9
1990/9
1
1992/9
3
1994/9
5
1996/9
7
1998/9
9
2000/0
1
2002/0
3
2004/0
5
2006/0
7
Year
Kg
per
cap
ita
Per capita consumption of red meat
Per capita consumption of white meat
33
Short term trends
Beef prices are high and will most probably remain firm Aren’t we lucky??
Consumption on the up, i.e. total and per capita
Alternative scenario: Prices low Consumption on historical
downward trend (prior to 2000)
We know the end result!!
0
200
400
600
800
1000
1200
1400
1600
1800
2000
19701971197219731974197519761977197819791980198119821983198419851986198719881989199019911992199319941995199619971998199920002001200220032004200520062007
c/kg
0
5
10
15
20
25
30
Kg pe
r cap
ita
Real price Nominal price Per capita consumption
34
Let’s look at this from another angle Red meat industry realized that much must be done
to change the image of red meat R&D on consumer behaviour Promotion Competitions
However, a closer look shows: Total per capita red meat consumption more likely to be
23.96kg Beef down to 15.73kg, Pork down to 3.27kg, Sheep down to 3kg.
Turn around in macro-economic conditions (Econ growth) Mainstreaming economic activity of blacks (“black
diamonds”)
35
Composition of food and non-alcoholic beverages
Source: IES 1995, IES 2000, IES 2005/06
36
Time to rethink our orientation??
Although the industry transformed with positive results one can safely postulate that being consumer orientated (in theory) is not sufficient It falls short of international developments in agro-
food chains.
37
Some pointers: Factors determining buying decisions Factors determining beef buying decisions
are changing Economic vs non economic factors This is the trend internationally
38
Desirable characteristics of beef USA(1=extremely desirable; 5 = not at all desirable)
0 0.5 1 1.5 2 2.5 3 3.5
Organic/natural Fat content
ConvienienceRaised in Your region in the US
Environmentally friendly prod
Source assuranceMarbling
Coutnry-of-origin labelingNutritional value
TenderHigh Quality Grade
LeannessPrice
Colour
USDA unspected for safetyFreshness
Sitz, Calkins, Umberger, Feuz -U of Neb., 2004
39
Desirable characteristics of beef Japan
89
81
72
70
59
52
47
46
41
39
Safe
HGP/Che
mica
l free
Delicio
us
Juicy
Reaso
nable
pric
e
Availa
bility
Tende
r
Non fa
tty
Nutrit
ional
0 20 40 60 80 100 120
% of consumers surveyed
Purch
ase
with co
nfide
nce
Source: MLA
40
Importance of product attributes per Cluster - (Free State Province)
0.0
1.0
2.0
3.0
4.0
5.0
6.0
Attributes
Scal
e of
Impo
rtnac
e
Inferior Conumer (low nutrition) (34.8%) n = 282 At Home (Basics) (23.7%) n = 192Balanced Consumer (26.6%) n = 216 Value Added Orientated (12.3%) n = 100High Frequency Consumer (Broad Product Range) (2.6%) n = 21
Source: Botha, F., Taljaard, P., Jooste, A. & Pelser, A. (2007). UFS.
41
Some pointers: Other factors More sophisticated consumers and linking it
with product development E.g. Checkoff program in US – 500 new products
between 03 and 04 In SA probably not even a 100 since 2003 to date
Lack of internationally acceptable traceability system
Problem/impact compounded if one considers guarantees to comply with increasing and more stringent standards set at the retail level, as well as to export.
42
Some pointers: Other factors Is our grading system still appropriate?
Factor Grading Scheme
USDA JMGA MSA
Breed X X Yes
Growth X X Yes
Stimulation X X Yes
Hang X X Yes
Cut X X Yes
Marbling Yes Yes Yes
Ossification Yes X Yes
Meat Colour Yes Yes Yes
Fat Depth Yes Yes Yes
pH X X Yes
pH/temp/pattern X X Yes
Aging X X YesSource: MLA
43
Some pointers: Other factors Transparent, accurate and timely red meat
information system is basically non-existent. The result is far from optimal chain sequencing putting
pressure on chain governance and relationships.
Dualistic nature of beef industry Growing informal market
Policing of regulations and health standards very difficult Puts the whole industry at jeopardy since poor quality
product can now reach the market undetected. Very difficult to manage and control diseases
44
Let me repeat: No/very little information flows Traceability lacking Slackness in the industry to create uniqueness Problems with industry structure
Most notable is the dualistic nature of the industry
This at a time when: Productivity is increasing Improved technology (slaughtering and processing) Continued investment in “uniqueness” Traceability Information systems
45
Therefore:
A value chain orientation (in practical terms) is necessary, e.g. Relationships Info systems
Some companies/chain players are responding, but overall industry response lacking
Challenge for organised structures in red meat industry to respond and maintain momentum
46Source Roduner (2005)
47
Some value chain influencers
48
China – the growing tiger (“the vacuum”)
Has a fifth of the world’s population and GDP gorwth at 9-10%
Food is one of the largest budget items for households 38% for urban households 50% for rural households
The number of rural households in the middle class 7.6 million in 1995 42 million in 2005
This will grow to 199 million in 2015 (McKinsey Quarterly)
49
50
China – the growing tiger
As living standards increase they are curring back on staple foods such as rice and wheat.
Consumption of dairy, fish, wine and processed food on the increase.
Food imports in the region of US$25 billion 4th largest in the world
Do not only buy food, but want safe and sophisticated food.
51
Brazil – the food basket
SECEX, 2005
World AGRI-FOOD CHAINS US$ Million and World Market Share
1st SOYBEAN COMPLEX 10,048 (33%)
1st SUGAR/ETHANOL 3,143 (35%)
2nd POULTRY MEAT 2,595 (35%)
1st BEEF 2,487 (26%)
1st COFFEE 2,058 (30%)
1st TOBACCO 1,38 (27%)
1st ORANGE JUICE 1,4 (83%)
3rd PORK MEAT 774 (12%)
4st CORN & PRODUCTS 638
3rd COTTON 407 (5%)
52
Brazil – the food basket
Source: FAO
NEW AGRICULTURNEW AGRICULTURALAL FRONTIER FRONTIERSS IN BRAZIL IN BRAZIL
Belém
Nova Fronteira na Produção de Grãos
Rio Grande
Porto Alegre
Imbituba
ParanaguáSantos
Vitória
Aratu
Itacoatiara
Santarém
Rosário
BOLÍVIA
ARGENTINA
URUGUAI
Waterways
Ports
Railways
PARAGUAI
Itaqui
New AgriculturalFrontiers
World
%
13.000 850 7%
2.900 550 19%
1.500 55 4%
Brazil
Used
Arable
TOTAL
World’s Distribution of land:
MaceióWORLD BRAZIL
Million of ha Million of ha
53
Brasilië – die voedselmandtjie
54
Brazil – the food basket
Sources: Agrianual, Pensa, MAPA, CONAB, IBGE
* 2003 Crop
HARVEST 2003-04 Potential
PRODUCTS Production Area Yield Production Area Yield
(million t) (million ha) (t/ha) (million t) (million ha) (t/ha)
Soybeans 50,2 21,1 2,4 80,5 23,0 3,5Corn 42,7 12,7 3,4 165,9 23,7 7,0Rice 12,9 3,4 3,8 26,4 6,6 4,0Beans 3,2 4,2 0,8 6,0 4,0 1,5Cotton 3,2 1,0 3,2 5,2 1,5 3,5Wheat 5,9 2,7 2,2 8,0 3,5 2,3others 5,2 1,8 2,9 3,2 2,7 1,2Total Grains 120,1 46,9 2,6 290,1 65,0 4,5Sugarcane * 384,4 4,9 78,4 443,3 4,9 90,0
55
56
Other influencers
Biofuels industry Oil prices Consumer confidence Infrastructure (water, electricity, roads) Exchange rate etc
57
Concluding remarks From a South African and Southern African
perspective this industry vitally important Sustainability (the triple botton line)
Where is the quick wins with long run impacts Proper support services Proper information service Relationship building and cooperation Understand the economics and environment as it
changes
58
59
“It is not the strongest that survives, but the most adaptive”.
Thank you