Project: Key Performance Indicators in the Automotive Supply Chain

Reference:

Last update: 02/09/2003 15:59:27

Objectives

The objectives of the research are to: (i) design key performance indicators appropriate to the needs and capability of the industry, (ii) collect the data necessary to calculate these indicators with a degree of statistical robustness, and (iii) provide the automotive industry with information about its performance that it can use to use to improve the efficiency of its logistics.

This data should: (a) inform policy makers as to the effectiveness of the logistics system in this market sector, (b) allow inter-company comparison using data collected by common methods, (c) give contributors industry wide transparency to encourage those below average to improve by targeting gross inefficiencies, and (d) help those at the top end of the market to identify those areas that still have small inefficiencies.

Description

Since 1998 the EEBPP has been working on developing and establishing KPIs of vehicle utilisation in individual distribution sectors.

Contractor(s)

AEA Technology Environment
Harwell Business Centre, Didcot, Oxfordshire, OX11 0QJ
+44 (0)1235 432201

Heriot-Watt University
Logistics Research Centre, School of Management, Edinburgh, EH14 4AS
+44 (0)131 451 3850

Contract details

Cost to the Department: £50,000.00

Actual start date: 01 April 2001

Actual completion date: 01 May 2002

Publication(s)

Key Performance Indicators of Distribution in the Automotive Industry
Author: Professor Alan McKinnon Duncan Leuchars, School of Management, Heriot-Watt University,
Publication date: 01/05/2002
£0.00
Source: TransportEnergy Best Practice
More information: http://www.transportenergy.org.uk/downloads/AutomotiveKPI.pdf

Summary of results

  1. Several important lessons have been learned from this pilot KPI survey in the automotive
    sector.
    1. The benchmarking of vehicle utilisation and energy intensity in the automotive sector is
    inherently much more difficult than in the food sector because of the diversity of handling
    equipment and large volume of non-unitised product. Most loads comprise relatively low
    density products, making volumetric measurement much more important than weightbased
    measures. As relatively few companies record accurate data on the volume of
    consignments, there is heavy reliance on subjective assessment of cube utilisation. The
    accuracy of the KPI estimates is therefore likely to be significantly lower than in the food
    industry, where unitised load data was much more readily available.
    2. The decision not to collect leg-specific data for trips with four or more legs should be
    seriously reconsidered in any future KPI survey. The absence of this data severely
    constrains the analysis and makes it difficult to compare companies' transport operations
    on a consistent basis. The concession on more complex multi-drop/collection trips was
    made to secure the involvement of several companies. There is a clear trade-off between
    the desire to maximise sample size and the richness of the survey data. If it is decided in
    future KPI surveys to allow companies to submit non-leg-specific trip data, it will be
    advisable to set the maximum number of legs for trips with leg-specific data at a higher
    level. In the present survey it was set at four. The average number of legs on trips with
    more than four legs was only 6.3, however. As shown in Figure 2 (page 17), the
    distribution of trips by number of legs is heavily skewed to the left, with only 7% of trips
    comprising eight or more legs. Had the threshold been set at six legs rather than four,
    77% of the trips surveyed, as opposed to 55%, would have yielded leg-specific data,
    permitting much more detailed analysis and much more effective benchmarking.
    3. It may be necessary to provide companies with more advice on how to organise the
    survey internally. Based on the experience of companies contributing to the pilot survey,
    one could devise an outline procedure that companies might follow. A key element in
    this procedure would be the briefing of the staff actually undertaking the data collection
    4. This pilot survey in the automotive sector was significantly smaller in terms of the
    number of fleets and vehicles than the equivalent survey which launched the KPI
    initiative in the food sector. A full survey in this sector, of comparable size to that
    undertaken in the food industry in 1998, will require stronger backing from trade bodies
    and the firm co-operation of several major car assembly companies and logistics
    providers active in this sector.