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This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/09600039610113182. When citing the article, please cite: Denis R. Towill, (1996), “Industrial dynamics modelling of supply chains”, International Journal of Physical Distribution & Logistics Management, Vol. 26 Iss: 2, pp. 23 - 4.

This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/13598549610799040. When citing the article, please cite: Denis R. Towill, (1996), “Time compression and supply chain management - a guided tour”, Supply Chain Management: An International Journal, Vol. 1 Iss: 1, pp. 15 - 27.

Our total cycle time (TCT) compression strategy encompasses the whole system in the supply chain from consumer demand to customer satisfaction. TCT has two major components that are essential to meeting customer demand: information flow and material flow. Both are necessities and together make up the total supply chain lead‐time; the information activates the material pipeline. Therefore to optimise a time compression strategy TCT must include both the information and material flows. We show in the paper that a very effective way of achieving TCT is via access to EPoS data by all “players” in the supply chain. The tremendous benefits exhibited by TCT compression within the supply chain can be described as “squaring the dynamic response circle”. Not only are the stock dynamic responses improved via time compression, but the capacity dynamics are also radically improved. Therefore TCT compression avoids the dilemma frequently faced by companies when implementing change of having to trade off customer service level against capacity utilisation. Our results are verified using a simulation model of a common real‐world supply chain.

The purpose of this paper is to reflect upon the impact of the original work and provide an updated model to reflect the changing environment for supply chains. In 2000, a migratory model for supply chain evolution was proposed.

The authors start by analysing the content of the papers that have cited the original Christopher and Towill (2000) paper. The development of an updated migratory model is informed by the findings from this, and then demonstrated through a case study of the book supply chain.

Despite being the major contribution, the majority of citing papers actually use other parts of the original work, and some potential reasons for this are proposed. An extra stage is added to the migratory model, reflecting a customer centric strategy.

Given that the migratory model appears under-researched, the authors identify this as an opportunity for future research and suggest that methods less common in supply chain management are used.

The updated migratory model can be used by supply chain managers to develop appropriate supply chain strategies for their organisations, while emphasising that many of the underlying tools to enable this reflect traditional industrial engineering approaches.

The updated migratory model represents a new contribution to understanding the evolution of supply chains.

Shows how the lean and agile paradigms may be selected according to marketplace requirements. These are distinctly different, since in the first case the market winner is cost, whereas in the second case the market winner is availability. Agile supply chains are required to be market sensitive and hence nimble. This means that the definition of waste is different from that appropriate to lean supply. The proper location of decoupling points for material flow and information flow enable a hybrid supply chain to be engineered. This encourages lean (efficient) supply upstream and agile (effective) supply downstream, thus bringing together the best of both paradigms. The paper concludes by proposing a cyclic migratory model which describes the PC supply chain attributes during its evolution from traditional to its present customised “leagile” operation.

To minimise business risk of incurring increased marketability and acquisition costs due to volatile demand exacerbated by the bullwhip phenomenon.

Based on the vision of the seamless supply chain and the active support of the decision support system exploiting the automatic pipeline inventory and order based production control system (APIOBPCS) algorithm. The approach has been tested on simulated real‐world value stream data.

Demonstrates that it is possible to reduce risk via a combination of the APIOBPCS algorithm plus optimal location of the material flow de‐coupling point separating lean and agile pipelines.

The methodology only substantially reduces risk generated within the supplier echelon. External bullwhip must be reduced via other routes to streamline flow.

Provides businesses with a composite methodology for matching their ordering systems to enable risk minimisation within their span of control.

The Bullwhip On‐costs Johari Window is a unique tool for mapping supply chain ordering policy risks.

From the arguably poor platforms described by the Egan, Latham, and Royal Academy of Engineering reports on the construction sector, there is now evidence that the supply chain revolution experienced over the last decade in the electronics products and automotive sectors is impacting on housebuilding in the UK. This case study describes how a first‐tier supplier has applied “best practice” to design and implement a BPR programme. In total span the resulting change covers a baseline of traditional operations to the present status of agile response. Essentially the BPR programme has been conceived around the need for streamlined material flow through internal processes and both supplier and customer interfaces. The paper highlights the BPR stages necessary for enabling change, which is audited in terms of assessment of improved material flow. Finally, the “bottom‐line” impact of the BPR programme is documented, and demonstrates that substantial benefits have accrued.

The purpose of this paper is to assess the appropriateness of using the 12 previously published material flow simplicity rules (SRs) to shape the successful design and implementation of improvements in a casting company product delivery process (PDP).

The business process improvement (BPI) project described in this case study was actively supported by the UK knowledge transfer partnership initiative. Hence, the outcome in terms of gain in the key performance indicators has been subjected to close and independent scrutiny. The dynamics of process change observed (and displayed on the factory floor) can thereby be exploited as signatures showing actual rates of improvement. It is then straightforward to highlight the qualitative impact of SR relevance to the likely outcomes.

The 12 SRs were originally posited based on published research (particularly by Jay Forrester and Jack Burbidge) and many others. This case study independently tests their detailed application in one specific environment.

None emerged during this case study. Other investigations may subsequently lead to prioritisation of the rules.

On this evidence the 12 material flow SRs are directly relevant and highly effective in the planning and execution of industrial PDP improvement programmes. They provide structure and build confidence during execution of this important task.

The paper has originality and values primarily due to new proven application of a recent published technique for BPI auditing.

In this paper, we show that reducing supply chain uncertainty increases responsiveness and thereby benefits bottom line performance as assessed via total cycle time reduction. We term this effect as the uncertainty reduction principle. To enable uncertainty reduction we use the uncertainty circle to focus on the sources to be eliminated. We also show that these sources of uncertainty can react and magnify in a flywheel effect caused by poor supply chain management. A supply chain audit methodology is described for identifying and codifying uncertainty. The proposition advanced herein is that smooth material flow leads to and statistically correlates with uncertainty reduction. Examples are given of good real‐world supply chain practices thus identified and subsequently improved. Transferability of the uncertainty reduction principle is assured by establishing readily assimilated “best practice” guidelines via the study of “exemplar” operating characteristics.

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.