Increasing Supply Chain Robustness through Process Flexibility and Inventory

We study a hybrid strategy that uses both process flexibility and finished goods inventory for supply chain risk mitigation. The interplay between process flexibility and inventory is modeled as a two-stage robust optimization problem. In the first stage, the firm allocates inventory before disruption happens; in the second stage, after a disruption happens, the firm determines production quantities at each plant to minimize demand loss. Our robust optimization model can be solved efficiently using constraint generation, and under some stylized assumptions, can be solved in closed form. For a canonical family of flexibility designs known as the K-chains, our analysis shows that the optimal inventory decision critically depends on the degree of supply chain flexibility, and the widely studied 2-chain design may not be sufficient to mitigate supply risk. Moreover, the optimal inventory allocations vary significantly under different degrees of flexibility. These observations are verified through a numerical case study of an automobile supply chain