Application of Analytics to Achieve Supply Chain Resilience

Abstract

The goal of achieving resilience has become a top priority as companies respond to the current supply chain crisis and develop strategies to manage future disruptions. This paper will discuss supply chain strategies that are required to promote multiple objectives that include agility, resilience, sustainment and ESG. We review recent empirical research that analyzes the global supply chain strategies that companies have implemented to support resilience. This will include discussion of obstacles for implementing such strategies and an empirically based classification that defines strategy archetypes, based on the linkage of such strategies to operational features. We then consider how emerging analytics tools can support the required analysis in order to balance tradeoffs and risks. The paper concludes with a illustration of how such analytics tools, based on the application of machine learning to big data, can support a data driven exploration of policy alternatives in the context of possible, future scenarios.