benchmarking of transport efficiency
DESCRIPTION
Transportation LogisticsTRANSCRIPT
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
7:00
9:00
11:0
0
13:0
0
15:0
0
17:0
0
19:0
0
21:0
0
23:0
0
1:00
3:00
5:00
7:00
9:00
11:0
0
13:0
0
15:0
0
17:0
0
19:0
0
21:0
0
23:0
0
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
0
12:0
0
13:3
0
15:0
0
16:3
0
18:0
0
19:3
0
21:0
0
22:3
0
0:00
1:30
3:00
4:30
6:00
7:30
9:00
10:3
0
12:0
0
13:3
0
15:0
0
16:3
0
18:0
0
19:3
0
21:0
0
22:3
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