MODELING UNCERTAIN FORECAST ACCURACY IN SUPPLY CHAINS WITH POSTPONEMENT

Abstract

We examine a situation where a manufacturer operates in a two-mode production environment. The first mode could involve overseas vendors and manufacturing facilities. If additional units are later required, the company must use its second mode—more expensive last-minute domestic vendors and manufacturing sites. We develop a new methodology for analyzing the impact of forecast accuracy on the decision to postpone production. We examine the interaction of forecast accuracy, shortage vs. holding costs, transportation costs and the cost of postponing production in the supply chain of a single product facing uncertain demand. Our model can be used to analyze the cost of important changes, such as increasing forecast accuracy, reducing the cost of backorders, lowering the cost of delaying production, or lowering transportation costs. Our model allows a firm to understand its overall cost structure so that it can accurately evaluate the impact of improved forecast accuracy and lowered costs in the context of postponement.