An information‐theoretic methodology for measuring the operational complexity of supplier‐customer systems

Abstract

In a dynamic environment such as the supply chain, even basic supplier‐customer systems with structurally simple information and material flow formations have a tendency to exhibit operational complexity. The operational complexity of supplier‐customer systems is primarily characterised by the uncertainty of the system. As the operational complexity of a system increases there is an associated increase in the amount of information required to monitor and manage that system. Based on this understanding, a novel information‐theoretic entropy‐based methodology for measuring and analysing the operational complexity of supplier‐customer systems has been developed. This paper makes contributions in the theoretical, conceptual and practical developments of the methodology. The methodology can quantitatively detect and prioritise operational complexity hotspots. At the interface, the framework can identify and quantify the transfer of operational complexity. Within the internal manufacturing system, the framework provides a comparative operational complexity measure across sub‐systems such as flows and products. This entropy‐based methodology provides a tool for identifying and measuring four classes of operational complexity transfer corresponding to the extent to which organisations generate, absorb, export and import operational complexity.