An integrated supply chain risk mitigation tool – model, analysis and insights

This study proposes a two-phase approach to create insights into disruptions, allowing managers to mitigate supply chain risks using an integrated risk-mitigation tool. In the first phase, we formulate the problem as a Markov Decision Process (MDP) that maximizes the expected long-run revenue induced by supply chain risks, given the current state of the risk score. We map four decision states to four specific managerial actions: ‘do nothing,’ ‘track the supplier,’ ‘monitor the supplier,’ and ‘change the supplier.’ If the optimal policy is ‘do nothing’, then the supply chain risk scores are continued to be monitored. For ‘track the supplier’, the firm will track the supplier’s performance internally. For ‘monitor the supplier’, the firm will hire an external contractor to monitor the external supply chain risks. If the optimal policy from phase 1 is to ‘change the supplier,’ we identify the best-performing supplier using an integrated best-worst goal programming (BWGP) method. We demonstrate the integrated method on a global automation technologies company. An MDP-based risk mitigation tool yields a promising approach. Results based on metrics show that the BWGP method can be used in the integrated two-phase approach with MDP as a supply chain risk mitigation tool.