Optimal soft-order revisions under demand and supply uncertainty and upstream information

Demand patterns for products with short life cycles or seasonal demand do not follow a discernible pattern for individual sales events and seasons due to uncertainty associated with effectiveness of product promotions, willingness of major retailers to carry product and their support, competition, and other unforeseen marketplace events/factors. These atypical demand patterns can be volatile and unsuitable for traditional demand forecasting. In such cases, buyers utilize market signals to regularly update demand forecasts. Under these settings, sharing early “soft-order” (i.e., order forecast) with the supplier reduces buyer's risk of supply shortages. In this study, we propose an optimal order revision policy for a buyer facing atypical demand and supply uncertainty for a single selling season based on a stochastic dynamic program. We demonstrate the value of soft-orders as well as supplier's inventory position information for the buyer. We make several key contributions: (i) We introduce a decision model for buyer to optimally revise soft-orders under supply uncertainty with or without supplier's inventory position information under a deposit scheme; (ii) We characterize the relationship between the optimal soft-order and final firm-order under demand forecasts and revisions, demonstrating that optimal orders may be aggressive, conservative, or match the demand forecast; (iii) We identify settings under which inventory position information of the supplier is beneficial to the buyer; (iv) We offer a mechanism for identifying the minimum unit deposit cost that will lead to truthful soft-orders from the buyer. A detailed analysis explores the structure of the optimal ordering policies as well as the effect of cost parameters and sources of uncertainty on buyer performance.