Events

Successful supply chain operations depend on the effective coordination of inventory management strategies and the information required for their implementation. This presentation explores the integration of time-series forecasting with inventory management to assess the value of information sharing in a two-tier supply chain. We analyze how different inventory policies influence supply chain costs under two information-sharing scenarios: (a) full information sharing and (b) no information sharing. We formulate an infinite-dimensional optimization problem where the decision variables are the MA coefficients characterizing a stationary ordering policy. By leveraging the canonical Smirnov-Beurling inner-outer factorization, we derive a fundamental mathematical identity that quantifies the value of information sharing, by viewing an inventory policy as an element of the Hardy space H2. Additionally, we show that an optimal ordering policy inherently incorporates the efficient delay of inventory replenishment in response to market demand. This delay is necessary to gradually release demand information, making the orders more predictable for upstream suppliers. We study how this delay is encoded in an inventory replenishment policy and how to optimally control it to minimize supply chain inventory costs.