A methodological framework for the design of efficient resilience in supply networks

Abstract

Disruptions can adversely affect profitability, service level, and even the viability of supply networks (SNs). Natural disasters, the COVID-19 pandemic, and geopolitical tensions heightened disruption risks for SNs. We propose a methodological framework to guide the design of resilient SNs, with a focus on efficient resilience. In fact, despite an increasing economic and social interest in SN resilience and a large variety of qualitative resilience frameworks, there is a lack of model-based frameworks to guide decision makers in the complex task of designing resilient SNs. Differently to the existing literature, that mostly focuses on industry- or disruption-specific approaches, the framework of this paper is general, independent from sectors and causes. It consists of three steps to guide practitioners through model-based stress testing of their SNs: it integrates and organises methods from the literature, from the selection of data to be collected to the validation of the resilient and efficient SN. We illustrate the application of descriptive, predictive, and prescriptive analytics at each phase using real-life case studies data supplemented by literature references. Finally, we present an industrial case study with the step-by-step application of the framework highlighting its strengths and objectives.