Content area
Full text
In this paper, we analyze demand postponement as a strategy to handle potential demand surges. Under demand postponement, a fraction of the demands from the "regular" period are postponed and satisfied during a "postponement" period. This permits capacity to be procured to satisfy the postponed demands. A reimbursement per unit is paid to customers whose demands are postponed. The basic idea is that by preempting stockouts through demand postponement, we can reduce overall stockout costs. We formulate and solve a two-stage capacity planning problem under demand postponement. We propose a power range class of distributions to capture the nature of demand surges. We establish the scalability and conjugate properties of the power range distributions under demand postponement, which leads to a tractable analysis of the problem. We analytically solve the problem of determining the optimal regular and postponement period capacities, and the demand splitting rule to minimize the supplier's expected cost. We show that (a) the value of postponement may be significant depending on cost and demand parameters, (b) a postponement strategy may lead to reduced investment in initial capacity, and (c) it may be optimal to do no demand postponement over a range of demands even after observing a higher demand signal. We then relax several model assumptions and provide results for these extensions. We conclude with managerial insights.
(Demand Postponement; Capacity Planning; Value of Information)
1. Introduction
In this paper, we focus on demand postponement as a tool to manage demand surges, i.e., situations where demand is likely to exceed short-term capacity. Under demand postponement, a fraction of the demands from the "regular" period are postponed and satisfied during a "postponement" period. This permits capacity to be procured to satisfy the postponed demands. A reimbursement per unit is paid to customers whose demands are postponed. The basic idea is that by preempting stockouts or backorders through demand postponement, we may reduce overall expected costs.
The analytical framework of demand postponement can be applied to a variety of practical situations spanning multiple disciplines. We first discuss an example from the utility industry to provide one motivating context. In [sec]1.1, we expand our model to accommodate examples from a number of other industry contexts. During the power crisis in California, innovative management tools such...