Modeling Disruption Risk in Supply Chain Risk Management

Disruptions have often been ignored in supply chain models due to their infrequency; however, there is evidence that disruptions are among the most significant threats to supply chains. This paper presents analytical methods to model and quantify disruption risks. The methods consist of breaking disruption risks down into four components: impact, occurrence, detectability and recovery. Analytical frameworks to quantify each individual component is provided. Methods to combine the individual components of risk are discussed and illustrated with numerical examples. DOI: 10.4018/joris.2012070102 16 International Journal of Operations Research and Information Systems, 3(3), 15-39, July-September 2012 Copyright © 2012, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Closed form expressions of the expected value and variance parameters of the combined risk function are derived. The Quantile Estimation Section provides several theoretical results for combining multiple risk functions under mild assumptions under a priori knowledge of the number of occurrences. Closed form expressions obtained in this section involve integration of complicated functions which was carried out using numerical techniques. The next section discusses the detectability aspect of the disruptive events. Detectability is modeled using the Mean Fist Passage Time concept of Markov chains. The section A Conceptual Model for Risk Recovery introduces our propostion for including disruption recovery time in risk analysis. The section that follows combines all the risk quantification models proposed in the paper and presents a comprehensive example for risk management. Conclusions Section summarizes the major contributions.