Logistics Research CentreHeriot-Watt University

EDINBURGH

Professor Alan McKinnon

Benchmarking of Transport Efficiency in the Food Supply Chain

Cool Chain Association meeting, 28th August 2003

Brief History of the Transport KPI Initiative1996 Discussion of performance measurement requirements

by CSDF’s Logistic Management Committee

1996 Support from Government (Energy Best Practice Programme)

1997 Pilot survey covering temperature-controlled distribution

1998 First full survey covering entire food supply chain

2001 KPI survey in the automotive supply chain

2002 Second full KPI survey in the food supply chain

KPI surveys of non-food retail distribution and the

road leg of air cargo operations

2003 KPI survey of pallet-load networks

Objectives of the KPI Initiative

■ enable companies to benchmark the efficiency

of their road transport operations

■ estimate average levels of efficiency at both

sectoral and sub-sectoral levels

■ assess the potential for improving the efficiency

of delivery operations

Stages in the Benchmarking Process

Company commitmentto participate

Assign appropriate staff

Attend briefingsession

Make internalarrangements:

- select vehicles to survey- staff briefing- operations / IT liaison

Internal calculation of KPIs

COLLECT DATA

Transfer raw datato LRC

Check for dataconsistency

Liaision withcompanies to rectify

anomalies Analysis:- pooling of data- aggregate values- benchmarking

Distribution ofbenchmark data

Preparation ofreports

Structure of the KPI Survey:‘Synchronised audit’ over 48 hour period

3 Exel spreadsheets:

■ Compilation of general data on vehicle fleet

- to permit ‘grossing-up’ of data

■ Audit of trailer activity

- to measure trailer activity over 48 hours

■ Audit of journeys

- to measure utilisation of transport capacity on a leg by leg basis

KPI 2002: Participating Companies■ 3663 ■ ACC Distribution■ Alldays Stores■ Boughey Distribution■ Christian Salvesen■ Exel■ Frigoscandia■ Gist■ GW Padley,■ Holdsworth Food Service■ Jacksons■ Marks and Spencer■ P&O European Transport■ Palmer and Harvey

! Pentons

! Phil HanLey

! Safeway

! Sainsburys

! Somerfield

! TDG

! Tesco

! Vitacress

! Waitrose

! Weetabix

! Whitbread Food Logistics

! Wincanton

! Yearsley Group

Key Performance Indicators

■ Vehicle fill

by weight, numbers & height of pallets

■ Empty running

■ Time Utilisation

■ Fuel consumption

for motive power and refrigeration equipment

■ Deviations from schedule

Survey Statistics1998 2002

No. of fleets 36 53Tractor Units 1,393 1,446Trailers 1,952 3,088Rigid vehicles 182 546Journeys 4,024 6,068Journey legs 11,873 24,443Pallets delivered 206,202 220,657Kilometres travelled 1,161,911 1,454,221

Food Distribution ChannelsProduction

Primary Consolidation Centre

Independent retailoutlet

catering outlet

Multiple retail outlet Local wholesale / cash and carrywarehouse

Regional Distribution Centre(supermarket chain)

Regional Distribution Centre(large wholesaler)

Secondary

Primary

Tertiary

Capacity utilisation by vehicle fleet

Mean 69%

Mean 53%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

vehicle fleetsdeck area utilisation weight utilisationaverage deck area utilisation average weight utilisation

53 fleets

Load height profile

15% of trips: over 1.7m

9% of trips: 0.8 - 1.5m

9% of trips: under 0.8m

meanavailable

height 2.4m

67% of trips had an averageload height of 1.5-1.7m

Variations in Average Empty Running

Mean 19%Mean 19%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

vehicle fleets

% o

f veh

icle

-km

Mean empty running highly sensitive to: - trip structure

- return of handling equipment

Time Utilisation over 48 hours

Sample of 3128 vehicles

idle(empty & stationary)

28%

maintenance/repair 7%

awaiting unloading/loading 4% pre-loaded, awaiting

departure 15%

loading/unloading 16%

on the roaddaily rest 2%

running onthe road 28%

0200400600800

10001200140016001800200022002400260028003000

1:00

3:00

5:00

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9:00

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maintenance / repair running on the road (including rest) loading / unloadingpre-load, awaiting departure awaiting unloading / loading idle (empty & stationary)

num

ber o

f tra

ilers

/ ri

gid

vehi

cles

Time Utilisation Profile over the 48 hours

running on the road

idle

loading/unloading

pre-loaded

awaiting loading/unloading

Maintenance / repair

48 hours

Deliveries to Distribution Centres(Primary Distribution)

0

500

1000

1500

2000

2500P AmbientP ChilledP Frozen

Deliveries to Shops(Secondary Distribution)

0

1000

2000

3000

4000

5000

6000

7000

8000

0:00

1:30

3:00

4:30

6:00

7:30

9:00

10:3

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0:00

1:30

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6:00

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10:3

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0

Hours

S AmbientS ChilledS Frozen

num

ber o

f pa

llets

Delivery Profile over 48 hours

48 hours

Primary distribution

Secondary distribution

frozen

chilled

ambient

Causes of Delays:

sample of 15,252 journey legs

no delay 71%

collection point problem 9%

delivery point problem 25%

traffic congestion 31%

equipment breakdown 2%

cause of delay not known 16%

lack of driver 1%

own company actions 16%

29% of legs re corded an unsche dule d delay

Frequency and Duration of Delays at Collection Points

0

10

20

30

40

50

60

0% 10% 20% 30% 40% 50%

percentage of legs delayed at start

dura

tion

of d

elay

(m

inut

es)

farm/fisheryfactoryprimary consol centreRDCmultiple retail outletother retail outletcateringwholesalercash&carryrecycling centre

Frequency and Duration of Delays at Delivery Points

05

101520253035404550

0% 10% 20% 30% 40% 50% 60% 70%

percentage of legs delayed at end

dura

tion

of d

elay

(m

inut

es)

farm/fisheryfactoryprimary consol. centreRDCmultiple retail outletother retail outletcateringwholesalercash&carryrecycling centre

0

1

2

3

4

5

vehicle fleets

small rigid medium rigid large rigid draw bar city semi-t railer32 tonne semi 38-44 tonne semi average rigid average 32 tonne art ic average 38 tonne artic

kilo

met

res p

er li

tre (

mot

ive

pow

er)

Average Fuel Efficiency by Vehicle Class

small rigid

medium rigid32 tonne artic

38 + tonne artic

km p

er li

tre

Vehicle fleets

0

10

20

30

40

50

60

70

vehicle fleets

P1 P2 S T M

ml o

f fue

l per

pal

let-k

m

Fleet Energy Intensity by Sub-sector

primary (refrigerated)

primary (ambient)

secondary

tertiary

mixed

Relationship between Fuel Efficiencyand Energy Intensity

0

10

20

30

40

50

60

70

80

90

1.522.533.544.5kilometres per litre (motive)

mediumrigidlarge rigid

32 tonneartic38 tonnearticcity articm

l per

pal

let-

km

0 5 10 15 20 25 30 35 40 45 50 55 60 65

Primary distribution (refrigerated)

Secondary distribution to supermarkets

Tertiary distribution to small outlets

Mixed distribution

All fleets

ml per pallet-km

38 tonne artic medium rigid

1 standard deviation above or below the mean ml per pallet-km

Sub-sectoral Benchmarking of Energy Intensity

Potential Savings in Fuel Consumption, Emissions and Cost

If fleets below mean ofperformance achievemean performance

within each subsector

If fleets below mean ofthe ‘top’ third of fleets

achieve their mean withineach subsector

Fuel savings (motive) litres 3,407,811 11,787,934% Fuel savings % 5 19Reduction in CO2 emissions tonnes 9,065 31,356Total fuel cost savings £ 2,593,344 8,970,618Fuel cost savings per vehicle £ 1,115 2,231

Average Fuel Efficiency and Energy Intensity by Vehicle Type

Fuel efficiency(motive)

Averagevolume load

Averagepayload

EnergyIntensity

units km/litre mpg pallets Tonnes ml/pallet-kmMedium rigid 3.87 10.94 5.78 2.25 32.99Large rigid 2.91 8.21 8.69 7.41 31.79City artic 3.14 8.87 11.24 6.57 21.3832 tonne artic 3.35 9.48 14.38 10.37 19.1138 tonne artic 2.79 7.88 17.11 11.83 17.96

Conclusions■ Average deck-area utilisation relatively high■ Level of empty running is highly variable■ Scope for greater consolidation of returning handling units■ Peaking of deliveries at primary and secondary levels during

morning rush hour■ Greater adherence to schedules at collection and delivery

delivery points would yield significant savings■ Pre-loading of refrigerated vehicles well ahead of departure■ Wide variation in fuel efficiency of rigid vehicles■ Energy intensity should be more widely adopted as a

distribution KPI■ Wide variations in energy intensity even at sub-sector level

Full report of the 2002 KPI survey in the food sector:

‘Analysis of Transport Efficiency in the UK Food Supply Chain’

Download from LRC website:http://www.som.hw.ac.uk/logistics