Abstract
Demand uncertainty, rapid changes in the business environment, and high pace of technology innovation are the main causes of supply chain risk for manufacturing companies. Thus, selecting the optimal plants to mitigate the supply chain disruption caused by demand uncertainty is a common problem for many multinational manufacturing companies. In this study, a conceptual risk management plan is proposed to integrate risk identification and risk assessment. Then, a framework of the risk management action plan is developed and a detailed procedure of how to implement the risk management action plan is proposed. Two multi-attribute decision analysis tools, namely, analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS), are utilized to identify the risk factors and to determine the optimal plant for order fulfillment. Finally, strategic directions, actions, and necessary conditions that help advance effective mitigation practices are suggested. The developed approach is implemented in a multinational manufacturing company. The results of this study show that the proposed methodology helps supply chain planners understand the manner of evaluating the risk criteria for each manufacturing site and the problems that should be solved for risk management. By using appropriate tools and strategies for risk management, supply chain planners can turn demand uncertainty into value-added results for the corporation.