Sales and operations planning in systems with order configuration uncertainty
This paper addresses the problem of aligning demand and supply in configure-to-order systems. Using stochastic programming methods, this study demonstrates the value of accounting for the uncertainty associated with how orders are configured. We also demonstrate the value of component supply flexibility in the presence of order configuration uncertainty. We present two stochastic models: an explosion problem model and an implosion problem model. These models are positioned sequentially within a popular business process called sales and operations planning. Both models are formulated as two-stage stochastic programs with recourse and are solved using the sample average approximation method. Computational analyses were performed using data obtained from IBM System and Technology Group. The problem sets used in our analysis are created from actual industry data and our results show that significant improvements in revenue and serviceability can be achieved by appropriately accounting for the uncertainty associated with order configurations.
sales and operations planning configure-to-order stochastic programming