Modelling the tradeoff between postponement capacity and forecast accuracy

Abstract

The ability to offer rapid delivery of a wide variety of customised products requires companies to maintain high levels of product inventories to quickly respond to customer demands. One alternative for reducing final product inventories while providing the required customer service level is delayed product differentiation, known as postponement. This strategy, however, can result in significant costs of increasing capacity at the postponement stage. Another alternative is to improve forecast accuracy, resulting in costs associated with more sophisticated forecasting methodologies. In this study we model the costs associated with each alternative and the resulting reductions in inventory levels, while maintaining a constant service level. We illustrate the interaction between these variables using a numerical example motivated by our work with a local manufacturer of non-durable household goods. Our findings show that large cost differences can exist between the two strategies, and that these costs play a significant role in determining the best strategy. Also, the value of the product (through holding cost) sets a limit on the benefit that can be realised by either strategy. These results have important managerial implications that should be considered when making the postponement decision.