Advance Demand Information and Safety Capacity as a Hedge against Demand and Capacity Uncertainty (Extended Abstract)
2003, Manufacturing & Service Operations Management
To control a production-inventory system, a manager has to consider the variability in demand as well as variability in her production process. Both types of variability corrupt system performance and by alleviating either of them, the manager can improve the performance of the system. There has been a recent trend towards investing in better information systems to provide better advance demand information. Also, many firms have focused on having safety capacity (e.g., outsourcing or overtime) that they can rely on as needed to protect themselves against uncertainty in demand and production. In this paper, we first address the tactical decision of how a firm decides on productioninventory safety capacity levels when faced with production and demand uncertainty. We use a multi-period production-inventory model with backordering to fully characterize the structure of optimal policies. We explore the sensitivity of optimal policies and costs to parameters such as demand and production variability, service level, and utilization. We also analytically show that uncertainty in capacity may result in nonintuitive behavior, such as more variable capacity resulting in less inventory. Using derived policy structure, through a computational study, we address the strategic decision of investing in better information or creating sources of safety capacity. Our study shows that reductions in costs are significant, with averages up to 30% for advance demand information, and up to 85% for outsourcing. Furthermore,conditions that make demand information more valuable tend to make safety capacity less valuable and vice versa and we identify when either will be more valuable. We also show that the benefits from both can exceed the sum of the benefits from either safety capacity or better information.
Hu, Xinxin (2003), “Advance Demand Information and Safety Capacity as a Hedge against Demand and Capacity Uncertainty,” Manufacturing & Service Operations Management, Vol. 5, No. 1, pp. 55-58.