Complexity and performance measurement for retail supply chains

Abstract

Purpose The purpose of this paper is to present how complexity on retail supply chains should be recognized and its relationship with the performance. Different supply chain structures and planning horizons have been analyzed to support practitioners taking action on the short, mid and long terms. Confronted complexity in the supply chain has been categorized as system, perceived and value adding. This would also help practitioners to understand the sources of the complexity and if the complexity is useful for the system or not. Design/methodology/approach Three different retail supply chain scenarios – each concentrating on different planning horizons – have been simulated on system dynamics software STELLA. Using the new classification scheme for complexity and suggested performance metrics, a multi-perspective analysis has been performed on the STELLA output. Findings The results and the methodology can be easily applicable in practice to support decision-making process and to answer “what-if” type scenario analysis on systems design and configuration. Using the selected complexity metrics, complexity of the system considering time factor – static and dynamic – and different information levels – system, perceived and value adding – has been evaluated. Used complexity metrics indicate the problematic areas in the systems to be distinguished. Originality/value This paper uses system dynamics modeling in retail supply chains to derive insight about dynamic behavior and to represent the complex interactions and a new classification scheme for system complexity.