Demand propagation in the extended enterprise: a comparative analysis of product and process design policies

In this paper, we investigate product and process design policies in the extended enterprise by studying the dynamics of supply-chain demand propagation. In particular, we focus on an integrated decision environment where data from multiple enterprises in the supply chain are used to coordinate production and material scheduling decisions in an Advanced Planning and Scheduling (APS) system. In an earlier paper, we explored coordinated production planning in an extended enterprise and its impact on demand propagation using an analytical model that incorporated basic lot-sizing logic under fairly general settings. Here, we expand on these earlier findings using a designed experiment and simulation, and investigate design policies that drive supply-chain performance. Our primary objective is to compare the impact of four design policies – component standardization, design capacity, setup investment, and demand management – on demand propagation across multiple tiers in an integrated supply chain. Among other things, we find that strategies such as level scheduling and relaxed design capacity that have been successfully utilized to improve performance at single plants do not necessarily improve supply-chain performance, as the effects of these strategies are quickly lost in the dynamics of the supply chain.