Multi-factor Modeling as an Enabler of Supply Chain Risk Management

Supply chains of large-scale, technologically complex products rely on a vast network of suppliers. While supply chain efficiency has improved with the expansion of globalization, supply chain resiliency appears to have worsened. Some would argue, in light of the effects of a global pandemic and war in Eastern Europe, that supply chains have become increasingly fragile.

Suppliers to the US Department of Defense (DoD), the focus of the author’s research and professional work, decreased from 71,655 to 46,180 in the ten years to 2020. The DoD is investing heavily in assessing the resiliency of its supply chains and strengthening its industrial base.
Supply Chain Management, and its focus on efficiency, has long been the subject of academic research and corporate investment. Since 2000, academic research has expanded to address Supply Chain Risk Management (SCRM) and its focus on resiliency. In this paper, the author explores the potential application of multi-factor models in identifying and assessing risk factors that impact supply chain resiliency. Specifically, the author addresses the question of identifying which factors best predict supplier vulnerability and using publicly available data to populate models that assess individual supplier risk exposure. Accurate risk assessment models would enable users to devote limited resources to in-depth analysis of the most vulnerable companies and implementing preemptive mitigations.
This paper provides a brief review of the extant literature, in which the author finds a lack of peer-reviewed research in the DoD supply chain risk management, but encouragingly, finds increasing research and the application of theory into SCRM for the commercial sector. The author briefly reviews risk management theory and its application in the supply chain domain. The author draws on established risk management standards to define a taxonomy that will ensure consistency throughout the research and discussion. This paper provides an overview of multi-factor modeling common in the finance domain, including its origins and basic theoretical underpinnings. The author argues for the application of multi-factor models in assessing companies for risk exposure rather than predicting future financial returns. This novel approach could increase accuracy and efficiency in assessing the thousands of companies that supply large-scale complex products.
This article concludes with a description of the author’s efforts to develop a data analytics tool to illuminate and assess supply chain risks in large-scale weapon systems procured by the US Department of Defense. This project is one of many being conducted by the DoD and illustrates the emphasis on developing innovative approaches to predict supplier vulnerability in times of increasing supply chain fragility.

Authors: Will Cook


Cite as: Cook, W. (2023). Multi-factor modeling as an enabler of supply chain risk management. Muma Business Review 7(10). 121-132.