Supporting Material is available for this work. For more information, follow the link from
the Table of Contents to "Accessing Supporting Material".
Table of Contents
Time will tell:
The impact of product life cycle demand and supply lead times
on customer order information sharing in supply chains
Henk Akkermans Kim van Oorschot
Eindhoven University of Technology Minase BV
Technology Management P.O. Box 278, 5000 AG
P.O. Box 513, 5600 MB Tilburg, The Netherlands.
Eindhoven, The Netherlands Tel. +31-13-544 3468
Tel. +31-40-247 2230 Fax. +31-13-544 6864
Fax. +31-40-246 4596 E-Mail: kim@minase.nl
E-Mail: h.a.akkermans@tm.tue.nl
Keywords: Supply chain management (SCM), supply chain collaboration, collaborative
planning & forecasting (CPFR), system dynamics (SD) simulation, high-tech electronics,
semiconductors.
Abstract
Sharing of customer order information with suppliers is often cited as adequate way of
improving performance in decentralised supply chains, but its effectiveness remains
problematic in practice as well as in theory. In industry practice, enthusiastic success
stories conflict with accounts of scepticism and failure. In academic theory, there is a
great deal of recent interest in this topic, but the benefits of information sharing that are
found appear to be relatively limited and located mainly with the supplier, not the buyer.
This paper investigates if this mixed picture is perhaps due to a number of implicit
assumptions in both business and academia. Perhaps customer order information sharing
is highly beneficial in some settings, and not at all in others. If that is the case, then what
are the factors that will tell if information sharing is worthwhile?
We introduce a generic system dynamics simulation model of a supplier-buyer supply
chain to investigate what happens if these characteristics are changed. One of the key
balancing loops in the model defines the relationship between delivery delays and lost
(future) sales: when customer orders rise, inventories drop and delivery delays increase,
resulting in a decline of future customer orders, which in turn decreases the order backlog
and improves delivery delays. Because of this loop, we are able to measure whether
customer order information sharing results in improving sales results and/or inventory
levels for both the supplier and the buyer in the chain.
The demand pattern we simulate is that of a Product Life Cycle, describing the
gradually introduction and phase-out of a new product during the modeled time interval,
according to a logistic function.
For this demand pattern we simulate the effect of customer order information sharing
in different scenarios based on a) the production lead-time of both the supplier
(short/long) and the buyer (short/long), and b) the production response time of both the
supplier (short/long) and the buyer (short/long).
Back to the
