Information flow in automotive supply chains – identifying and learning to overcome barriers to change
| Published date | 01 October 2003 |
| Pages | 491-502 |
| Date | 01 October 2003 |
| DOI | https://doi.org/10.1108/02635570310489197 |
| Author | Paul Childerhouse,Ramzi Hermiz,Rachel Mason‐Jones,Andrew Popp,Denis R. Towill |
| Subject Matter | Economics,Information & knowledge management,Management science & operations |
Information flow in automotive supply chains ±
identifying and learning to overcome barriers to
change
Paul Childerhouse
Management Systems, WMS, Waikato University, Waikato, New Zealand
Ramzi Hermiz
Federal Mogul Corporation, South Field, Michigan, USA
Rachel Mason-Jones
Federal Mogul Corporation, South Field, Michigan, USA
Andrew Popp
Royal Holloway College, University of London, Egham, UK
Denis R. Towill
Cardiff Business School, Cardiff University, Cardiff, UK
Introduction
In a cognate paper (Childerhouse et al., 2002)
we outlined the pressures surrounding
automotive first-tier suppliers. This was
discussed in terms of the three ``top pains''
facing a typical major ``player''. These pains
were the ``performance pain'', ``lack of
strategic thinking pain'', and ``lack of
information pain''. In particular we saw that
in real-world supply chains information is
withheld, masked, distorted, or just plain
missing. But not only does lack of
information lead to panic and chaotic
behaviour within supply chains, it also leads
to unnecessary costs. Bullwhip is one typical
phenomenon observed under these
circumstances. Excess costs due to bullwhip
have been estimated by Metters (1997) as
between 5-10 per cent (when due to batching
effects, etc.) and 15-20 per cent (when due to
special promotions, etc.). As these estimates
are for excess factory costs alone (many other
supply chain costs being additional thereto),
there are clearly substantial benefits likely to
accrue from effective supply chain
re-engineering. It is our industrial
experience that information flow is a key
enabler in successful BPR programmes
(Towill, 1997a). Within the supply chain
context there is considerable theoretical
evidence to support this viewpoint, including
Lee et al. (2000) and Mason-Jones and Towill
(1997).
For example, as part of our extensive
research into supply chain design, a systems
dynamics simulation was exploited to provide
benchmarks for performance improvements
consequent on adopting particular strategies.
This was initially based on what has become
known as the Jay Forrester model (Forrester,
1961) but has since been replicated on other
supply chain systems (Mason-Jones et al.,
1997). This latter work has confirmed that the
priorities so identified are applicable to a
range of models. A number of generic
strategies soon emerged from the Forrester
model (Wikner et al., 1991), which have found
application in a number of real-world supply
chains. For example, in Towill and McCullen
(1999) these generic strategies are correlated
with individual actions executed with a
specific agile manufacturing BPR programme
applied to a global mechanical precision
products supply chain. Typical
improvements recorded include bullwhip
reduction by 50 per cent, stock-turns at least
doubled, and product availability on demand
greatly increased.
Figure 1 shows typical simulation results
in which performance improvements are
predicted for a particular set of BPR
strategies. Manifestly the results are for a
specified supply chain structure and
operation scenario. Nevertheless the results
have proved suitable for ranking competitive
strategies and thus pin-pointing areas for
leveraging performance boosts. A good
example is described by Towill and McCullen
(1999), in which a number of these
improvement strategies have been included
within a successful agile manufacturing BPR
programme. The cost index used herein is the
factory production on-costs via the formula
derived by Stalk and Hout (1990). The
original design used as datum is the
traditional, sequential information flow
supply chain leading to extensive bullwhip
and with behaviour typified by the law of
industrial dynamics (Burbidge, 1984).
In the terminology adopted in Figure 1 to
describe the improvement options available,
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[ 491 ]
Industrial Management &
Data Systems
103/7 [2003] 491-502
#MCB UP Limited
[ISSN 0263-5577]
[DOI 10.1108/02635570310489197]
Keywords
Automotive industry,
Supply chain management,
Business process re-engineering,
Change management,
Information management
Abstract
Improving competitive advantage
to the first-tier echelon of
automotive supply chains is
enabled via the requirement for
transparent information flows in
both the order-generating and
order fulfilment channels.
However, four generic areas are
identified which are barriers to
improving performance. These are
cultural (is it in our interests?);
organisational (does the supply
chain have the right structure?);
technological (what common
format and standards are
required?); and financial (who
pays the bill?). How these barriers
may be overcome to the benefit of
all ``players'' in the chain is
discussed, plus benchmarking of
current best practice. Exemplar
supply chains are identified as
noteworthy for the emergence of
supply chain ``product
champions''. These have the
vision, authority, and drive to
implement new systems and set in
place mechanisms to minimise
regression to old working
practices.
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