Modelling and Optimization of Supply Chain Disruptions due to Catstrophic Events

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Supply chain management calls for the coordination of activities between different companies resulting in an interlinked network of operations with reduced inventories. While this often leads to a more efficient supply chain, it has also resulted in increasing the risk exposure of companies in the supply chain. The increase in complexity and offshoring of products and services has also increased the risk diversity within the supply networks. The fact that supply chain operational models had traditionally emphasized economic efficiency, leading to supply chains operating on minimum inventories and facilities, is likely to delay the recovery from disruptions. In addition, the use of just in time systems had meant that supply chains reduced their suppliers pool and in turn competing supply chains often share the same supplier. Thus a disruption in one supply point can lead to simultaneous disruptions in several supply chains. For example, when the flooding hit Thailand in 2011, its effect on the auto supply chain were felt all over the world. In North America, Honda announced that its production in Canada and the US would be reduced by about 50% and Toyota had to stop all its overtime production and temporarily shut its plants. Such major disruptions are not unique to supply risks from natural disasters, they can also be the result of demand and operational risks. For example the Maple Leaf Foods recall after the listeriosis outbreak resulted in a temporary layoff of 250 workers, $20 million in recall costs and $27 million for settling class-action lawsuits. After such major supply and demand disruptions, even within the once thought of as highly disciplined supply chains, companies have started questioning the way they operate their supply chains and in particular how to incorporate risk effects in their design and operation. They are now rethinking their supply chain network configurations and operations management: Do they pile up inventory, change prices subsequent to a risk event, add expensive production and/or distribution facilities, or reorganize their supply base? Given the uncertainty in the occurrence of these catastrophic events and the complexity of the aftermath decision making, it is important that supply chains develop models for the identification and assessment of risk and appropriate risk handling measures. It is thus the goal of this proposed research to develop supply chain risk management models to: (1) understand supply chain risks by estimating risk probabilities for multiple events that may be dependent and may involve several partners in a supply chain, (2) develop systematic procedures for the identification and assessment of supply and demand risks and how they propagate through the supply chain, and (3) design robust supply networks that are resilient to disruptions and provide a level of immunity against possible risky events. The models would contribute to risk analysis in the area of operations research and management. They are also expected to benefit and contribute to the theory of insurance mathematics and the growing field of data analytics. In addition to training graduate students, it is anticipated that this research will contribute to the competitiveness of Canadian companies by providing them with tools to prepare for and mitigate supply chain risk disruptions. The importance of studying these issues is further highlighted by a recent global procurement study that found that 80% of companies are vulnerable to a major supply disruption. In addition, the financial implication of a failure in a supply chain link can be enormous. Studies have found that a company’s stock price decreases on average by 10.28% on the day that an announcement of a supply chain failure is made.