Quantifying supply chain disruption: a recovery time equivalent value at risk approach

Abstract

The global pandemic COVID-19 has disrupted supply chains in many industries all over the world. If not well contained and managed at an early stage, such unprecedented disruptions may lead to even more serious consequences in the era of supply chain reglobalization. The attendant challenge for research and practice is on how to readily measure and quantify the disruption risk. To address the plethora of concerns, this article presents a recovery time equivalent (RTE) disruption risk measurement model using Value at Risk (VaR). We consider a disruption recovery model comprising abrupt, normal, fast, and slow modes. To demonstrate the practical relevance of our study, we establish a case study with a multinational corporation from the IT sector. Decision makers and supply chain managers can use the model to conduct ‘what-if' analyses on their supply chain vulnerabilities and risks for a more proactive business continuity planning and contingency management.

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