A Bayesian Framework for Supply Chain Risk Management Using Business Process Standards

Changhe Yuan, Feng Cheng, Henry Dao, Markus Ettl, Grace Lin, Karthik Sourirajan

Abstract

Supply-chain risk management (SCRM) has gained significant attention in recent years. While much of the existing literature focuses on proactive aspects of SCRM such as risk identification, assessment, and mitigation, little work has been done regarding enabling quick actions after risk events. The challenge lies in the lack of a SCRM framework that would support the categorization and integration of complex risk factors, heterogeneous information, and hierarchies of business processes and their interrelationships. In this paper, we describe a framework and methodologyy and a software tool for supply-chain risk analysis that uses Bayesian graphical models to identify, quantify, mitigate, and respond to the risks affecting a company's global supply chain. The proposed methodology uses a two-dimensional network categorization of information about risk factors and business processes. It allows managers to effectively specify the risk environment by mapping all risk variables to business processes. The framework is designed to automatically learn the underlying risk models in a well-structured fashion using historical supply chain data to obtain qualitative and quantitative interdependencies among risk variables. The resulting risk models allow analysts to identify high risk areas in a supply chain business process, diagnose risk factors contributing to observations regarding abnormal events, and analyze the sensitivity of supply-chain performance measures to various risk factors. The models provide guidance for identifying risk mitigation strategies and for responding to disruptive events. We illustrate the methodology using a comprehensive case study based on global logistics process performance data.

Bibtex

@BOOKCHAPTER{Yuan11Bayesian,
author = {Changhe Yuan and Feng Cheng and Henry Dao and Markus Ettl and Grace Lin and Karthik Sourirajan},
title = {A Bayesian Framework for Supply Chain Risk Management Using Business Process Standards},
booktitle = {Handbook of Integrated Risk Management in Global Supply Chains},
year = {In print},
volume = {},
issue = {},
pages = {}
}