Quantitative metrics to analyze supply chain resilience and associated costs

Abstract

The growth of global supply chains has allowed trading partners to experience synergistic, economic expansion and increase their competitive success. At the same time, reliance on global supply chains exposes its trading partners to unforeseen disruptions. While the economic benefits are tremendous, they are not without risk as global supply chains are by their very nature susceptible to a wide array of disruptions. Methods that mitigate the effect of disruption directly contribute to the competitive success of global supply chain networks. One approach for mitigating the effects of disruption is to increase resilience. Thus, this research focuses on understanding supply chain vulnerability and how to return the supply chain to its desirable performance level after a disruptive event by reconfiguring the supply chain network. This article frames this foundational work in the context of systems theory to add to the body of resilience research by providing a time-dependent definition of supply chain resilience. This article then provides a mathematical model, based on inventory theory that operationalizes that definition. The model is presented in the context of a multi-echelon, post-production support network of a sustainment-dominated system such as those found in the aerospace, defense, utilities, and construction industries. The model demonstrates the post-disruption resilience at each supply chain network node along with the investment necessary to restore the network.