In today's globalized economy, supply chains strive to be increasingly efficient and effective by adopting strategies such as outsourcing, just-in-time practices, and lean inventory. However, these measures to operate the supply chain more efficiently often lead to increased fragility. As uncertainties become more prevalent and disruptions arise from many sources, supply chain risk management has become imperative. Considering the complexity of today's supply chains and their operations, this paper proposes a systematic framework for supply chain risk management. Within the framework, this paper presents a structured methodology for risk identification and consequence analysis. Following the well-established HAZard and OPerability (HAZOP) analysis method in process safety, supply chain risk identification can be performed by systematically generating deviations in different supply chain parameters, and identifying their possible causes, consequences, safeguards, and mitigating actions. Consequence analysis can be conducted using a dynamic simulation model of the supply chain operations. The application and benefits of the proposed approach are demonstrated using a refinery supply chain case study. © 2008 Elsevier B.V. All rights reserved.