Reprint: R1401H
Traditional methods of managing supply chain risk require estimations of how likely a disruption is to occur. For fairly common risks—poor supplier performance, forecast errors, transportation breakdowns—the traditional methods work quite well. But it’s a different story for rare, high-impact events such as megadisasters, pandemics, and political upheavals. These risks are hard to quantify using traditional models, and as a result, many companies do not adequately prepare for them, which can have calamitous consequences when catastrophes do strike.
A new model allows managers to quantify the impact of a supply chain disruption on a company’s operational and financial performance, rather than focusing on the cause or likelihood of the disruption. This type of analysis obviates the need to determine the probability of any specific risk’s occurring—a valid approach since the mitigation strategies are equally effective regardless of what caused the disruption.
In this article, the authors describe how companies can use the model to reduce their exposure to all types of supply chain risk.
Traditional methods for managing supply chain risk rely on knowing the likelihood of occurrence and the magnitude of impact for every potential event that could materially disrupt a firm’s operations. For common supply-chain disruptions—poor supplier performance, forecast errors, transportation breakdowns, and so on—those methods work very well, using historical data to quantify the level of risk.
