Contract Risk

Proceedings of the 2005 Winter Simulation Conference M. E. Kuhl, N. M. Steiger, F. B. Armstrong, and J. A. Joines, eds.

RISK MANAGEMENT IN SUPPLY NETWORKS USING MONTE-CARLO SIMULATION Léa A. Deleris Feryal Erhun Department of Management Science and Engineering Stanford University Stanford, CA 94305 U.S.A.

ABSTRACT Trends such as (1) globalization, (2) heavy reliance on transportation and communication infrastructures, and (3) lean manufacturing have led to an increase in the vulnerability of supply networks. Due to a large number of interrelated processes and products, disruptions caused by these vulnerabilities propagate rapidly. Firms, however, can partially control the robustness and resilience of their supply networks through strategic and tactical decisions. Therefore, a decision-support tool that assists managers to evaluate the risk exposure of their supply networks can considerably increase the robustness/resilience of these networks. In this study, we present a Monte Carlo simulation based tool designed to assess uncertainty in supply networks. We describe its application and discuss the possible drawbacks of our approach. 1 INTRODUCTION

Events within the past decades have shown the extent to which companies, and subsequently their supply chains, are vulnerable to adverse events (Deleris, Erhun, and PatéCornell 2004). This observation should be an expected outcome of recent developments in supply networks. For instance, researchers comment on increasing reliance of corporate supply chains on transportation, utilities, and communication infrastructures (NACFAM report 2003 and Cranfield University report 2002). Trends such as globalization and offshoring further increase the complexities and interdependencies in supply chains which are now predominantly characterized by a large number of interrelated processes and products. However, the strategic and tactical decisions of a firm influence the extent to which its supply network is flexible in the

References: Ayvaci, M., L. A. Deleris, and F. Erhun. 2005. Risk Management in Supply Networks. Working Paper, Department of Management Science and Engineering, Stanford University, Stanford, California. Cranfield University Report. 2002. Supply Chain Vulnerability, Executive Report on Behalf of Department for Transport, Local Government and the Regions, Home Office and Department of Trade and Industry. Deleris, L. A., D. Elkins and M. E. Paté-Cornell. 2004. Analyzing Losses from Hazard Exposure: A Conservative Probabilistic Estimate Using Supply Chain Risk Simulation. In Proceedings of the 2004 Winter Simulation Conference, ed. R. G. Ingalls, M. D. Rosetti, J. S. Smith, and B. A. Peters, pp. 323-330. Institute of Electrical and Electronics Engineers, Piscataway, New Jersey. Deleris, L. A., F. Erhun, and M. E. Paté-Cornell. 2004. Quantitative Risk Assessment of Supply Chain Performance. Working Paper, Department of Management Science and Engineering, Stanford University, Stanford, California. Hicks, D. A. 1999. A Four Step Methodology for Using Simulation and Optimization Technologies in Strategic Supply Chain Planning. In Proceedings of the 1999 Winter Simulation Conference, ed., P. A. Farrington, H. B. Nembhard, D. T. Sturrock, and G. W. Evans, 1215-1220. Institute of Electrical and Electronics Engineers, Piscataway, New Jersey. Ingalls, R. G. 1998. The Value of Simulation in Modeling Supply Chains. In Proceedings of the 1998 Winter Simulation Conference, ed. D. J. Medeiros, E. F. Watson, J. S. Carson, and M. S. Manivannan, 1371-1375. Institute of Electrical and Electronics Engineers, Piscataway, New Jersey. Ingalls, R. G. 1999. CSCAT: The Compaq Supply Chain Analysis Tool. In Proceedings of the 1999 Winter Simulation Conference, ed., P. A. Farrington, H. B. Nembhard, D. T. Sturrock, and G. W. Evans, 12011206. Institute of Electrical and Electronics Engineers, Piscataway, New Jersey. NACFAM Report. 2003. Critical Infrastructures and U.S. Manufacturing: Assessing the Vulnerabilities to Disruptions from Terrorism. AUTHOR BIOGRAPHIES LÉA A. DELERIS is a Ph.D. candidate in the Department of Management Science and Engineering at Stanford University. She received her Master of Science degree from the same department. Her research interests lie in probabilistic risk analysis and decision analysis. Her email address is [e-mail]. FERYAL ERHUN is an Assistant Professor in the Department of Management Science and Engineering at Stanford University. She received her Ph.D. in Production and Operations Management from Carnegie Mellon University. Her research interests include the design, analysis, and optimization of supply chains under uncertainty. Her e-mail address is [e-mail] and her web address is www.stanford.edu/~ferhun. 1649