If the nature of your business is manufacturing, chances are one of your biggest concerns is supply chain disruption. While there are plenty of traditional ways to manage ordinary risks, when dealing with high-impact occurrences like viral epidemics or devastating storms--when the risks are often difficult to quantify and prepare for--a different method can help.
A model developed recently by MIT Sloan Professor David Simchi-Levi and his colleagues William Schmidt and Yehua Wei offers an alternative solution that concentrates on quantifying supply chain risk by using a breakthrough Risk Exposure Index (REI). In essence, says Simchi-Levi, the model "focuses on the impact of potential failures at points along the supply chain (such as the shuttering of a supplier’s factory or a flood at a distribution center), rather than the cause of the disruption."
It's a mathematical depiction of the supply chain that can be computerized and updated by employing a common math technique, called linear optimization, to determine the best response to a disruption. Simchi-Levi says that a key component of the model is "time to recovery (TTR), or the time it takes for a particular node (e.g., a distribution center, supplier facility, or transportation hub) to be restored after a disruption." The model removes one node at a time and determines the supply chain response that would minimize the performance impact of the disruption at that node--allowing the company to identify the nodes that need the most attention.