System Dynamics Simulation of a Supply Chain Intelligence Model

Abstract

Supply chains today are, primarily, measured by Key Performance Indicators (KPIs) such as order-fulfillment, availability to the consumer (percent in-stock) and cost reduction, as well as financial KPIs such as return on investment (ROI), return on brand equity and inventory. These KPIs measure the performance of supply chain as a whole. A supply chain is a network of nodes. The performances of individual nodes are measured with KPIs such as production rate, shipment rate, inventory and the like. These metrics may indicate the performance but may not indicate the cause of such performance. For example, a node whose production rate is below the desired level may be because of poor supply of inputs of production by its supplier node.Thus mere identification of KPIs and their evaluation will not enable to identify the root cause of a problem in a supply chain. Therefore, we need a business intelligence framework that will satisfy the objectives, namely, identification of outcome of each node of the supply chain and its cause. The existing Supply Chain Intelligence (SCI) frameworks aims at identifying metrics that reflect the performance of individual nodes and the total supply chain, but fail to identify the cause of such outcomes. It implies that the linkages or association between the KPIs of individual nodes are required to be identified and defined. In this paper, contingency and systems approach has been used to identify the dimensions of the firm, its internal environment, the complement and the external environment. A system dynamics based approach has been used to identify the causality and resulting behavior of the supply chain. The paper proposes a SCI framework and a System dynamics Model that help in identifying the reasons for supply chin performance and lead to the actions required to be taken for improvement in performance of the supply chain.