Mitigation Strategies Against Supply Disruption Risk: A Case Study at the Ford Motor Company

Ece Sancı, School of Management, University of Bath

Abstract

Supply chains are exposed to different risks, which can be mitigated by various strategies based on the characteristics and needs of companies. In collaboration with Ford, we develop a decision support framework to choose the best mitigation strategy against supply disruption risk, especially for companies operating with a small supplier base and low inventory levels. Our framework is based on a multistage stochastic programming model which incorporates a variety of plausible strategies, including reserving backup capacity from the primary supplier, reserving capacity from a secondary supplier, and holding backup inventory. We reflect disruption risk into the framework through decision makers’ input on the time to recover and the disruption probability. Our results demonstrate that relying on the strategy which is optimal when there is no disruption risk can increase the expected total cost substantially in the presence of disruption risk. However, this increase can be reduced significantly by investing in the mitigation strategy recommended by our framework. Our results also show that this framework removes the burden of estimating the time to recover and the disruption probability precisely since there is often a small loss associated with using another strategy that is optimal in the neighborhood of the estimated values.
Joint work with Mark Daskin, Young-Chae Hong, Steve Roesch, and Don Zhang.

Short Bio

Ece Sanci is a Lecturer (Assistant Professor) in the Information, Decisions & Operations division of the School of Management at the University of Bath. She received her Ph.D. in Industrial and Operations Engineering in 2019 from the University of Michigan. She received her B.S. and M.S. in Industrial Engineering in 2013 and 2015 from the Middle East Technical University in Ankara. Her research focuses on decision making under uncertainty with applications in disaster relief management and supply chain risk management.

Venue

Friday, April 1, 2022, 4.00 pm - Zoom Meeting