A method for analysing operational complexity in supply chains

Abstract

This paper proposes a method for analysing the operational complexity in supply chains by using an entropic measure based on information theory. The proposed approach estimates the operational complexity at each stage of the supply chain and analyses the changes between stages. In this paper a stage is identified by the exchange of data and/or material. Through analysis the method identifies the stages where the operational complexity is both generated and propagated (exported, imported, generated or absorbed). Central to the method is the identification of a reference point within the supply chain. This is where the operational complexity is at a local minimum along the data transfer stages. Such a point can be thought of as a ‘sink’ for turbulence generated in the supply chain. Where it exists, it has the merit of stabilising the supply chain by attenuating uncertainty. However, the location of the reference point is also a matter of choice. If the preferred location is other than the current one, this is a trigger for management action. The analysis can help decide appropriate remedial action. More generally, the approach can assist logistics management by highlighting problem areas. An industrial application is presented to demonstrate the applicability of the method.

Keywords:

• operational complexity
• entropy
• reference point
• manufacturing systems
• information theory
• supply chain

Acknowledgements

The authors would like to express their sincere thanks to the industrial collaborators for providing the access of the case studies and the financial support for the project. The authors also gratefully acknowledge the support of EPSRC for grants GR/M52458 and GR/M57842. The authors thank the anonymous reviewers for their comments and suggestions for the improvement of the paper.