Supply Chain Disruption Planning with
Bayesian Information Updating
and Extreme
Value Demand Distribution
Selda Taskin, and
Emmett J. Lodree, Jr.
Department of Industrial and Systems Engineering
Supply
chain disruptions caused by extreme events pose a potentially devastating
threat to the firm. Therefore, it is essential that organizations implement
risk assessment and mitigation techniques to prepare for the effects of major disruptions.
Many strategies are readily available to assist organizations in dealing with
operational risks. However, few scientific methods have been developed for
being used to prepare for and respond to catastrophic events that cause major
supply chain disruptions. The scope of the proposed research is an abstraction
of manufacturing facility’s procurement problem with respect to preparing for
demand disruptions caused by the hurricane season. The primary objective of the proposed
research is to introduce a scientific methodology that will enable organizations
to withstand major supply chain disruptions. A unique combined approach of
Bayesian analysis and Extreme Value Theory is used as a solution methodology to
determine the optimum procurement strategy for this manufacturing facility that
manufactures seasonal product and demand for the product is significantly
influenced by the hurricane season. A Real Options framework is also introduced
to evaluate the procurement strategy as an economical decision. It is expected
that this research will (i) introduce a new
scientific framework and methodology to assist organizations in decision-making
related to disaster planning (ii) enable organizations to effectively evaluate
the economic consequences of disruption planning decisions (iii) improve the
profitability of the constituent organization we are working with.