University of California at Berkeley
We are developing tools and approaches to help Bayer understand the relationship between cost, risk, and service level in its supply chain. We will model the supply chain, and develop algorithms that enable us to efficiently create a three dimensional graph of cost of optimal inventory position vs. supply chain node downtime vs. customer service level, so that mangers can understand the implications of effective inventory positioning decisions on cost and risk mitigation, and make more informed decisions. Note that this project is related too, and will leverage tools developed in, similar projects.
This project has two core components:
1) Development of novel tools based on retrospective optimization that can be used to optimize parameters in Bayers supply chain. These tools will utilize the same technology developed for a similar project with Genentech, so that the resources of both firms can be leveraged.
2) Application of these tools to answer specific questions regarding inventory positioning accounting for both day to day variation in demand, and risk mitigation in the case of various types of supply chain disruption.