Continuous Multi-eEchelon Inventory Optimization

Abstract

Global supply chains are becoming increasingly complex systems that drive significant investments in inventory throughout the network. Our sponsor for this project uses a multi-echelon inventory optimization (MEIO) model to manage safety stock inventory across its network. The MEIO model helps them optimize inventory based on upstream and downstream supply chain performance but it does not guarantee year over year reductions in inventory levels that the company desires. To address this issue, we studied how the company can better utilize MEIO to systematically reduce its inventories over time and created a methodology that can be employed by other companies also. We applied the methodology on two products that are presented as case studies. For the chosen products, we found that variation in supply lead time is the primary reason for high MEIO safety stock values. We further identified the underlying cause of variation and provided recommendations to reduce variation in lead time in each case study. This research creates a framework that companies can use to systematically minimize MEIO safety stocks and presents case studies that apply this framework to minimize variation in supply lead time on two products and their corresponding MEIO safety stocks.