Optimal Production and the Value of Information in Supply Chain with Uncertain Information

Abstract

We present a model for determining the value of information sharing (forecast accuracy) when planning production in a supply chain environment. We examine the interaction of forecast errors, shortage vs. holding costs, and the cost of delaying production in a two-stage supply chain of a single product facing uncertain demand. We report computational results showing how to find the value of improved forecast accuracy. Our model can be used to analyze the cost of strategic changes, such as reducing the cost of backorders or lowering the cost of delaying production. We then develop regression analyses generalizing our results. Our model has convinced Nu-kote International to make a significant investment for improving its forecast accuracy. This investment has resulted in improved service levels and reduced inventory.