2008 M&SOM Best Paper Award

It is a pleasure to announce that the 2008 Manufacturing & Service Operations Management Best Paper is “Hedging Inventory Risk Through Market Instruments,” by Vishal Gaur and Sridhar Seshadri (2005). This annual award is given to a paper, published in one of the prior three volumes of M&SOM, deemed by the M&SOM editorial board to be most deserving for its contribution to the theory and practice of operations management. For their accomplishment, Professors Gaur and Seshadri will share $2,000, which was contributed by the Manufacturing and Service Operations Management Society of INFORMS. This paper asks an intriguing question—can a firm use financial hedging strategies to reduce the risk it faces from its inventory investment? The operations management literature is full of papers that offer advice on making optimal inventory decisions, but that literature had not considered how inventory decisions should change when there exists the possibility of creating a financial hedge. Of course, for a hedging strategy to be effective a firm needs to be able to trade a financial asset that is sufficiently correlated with the firm’s inventory risk. Instead of merely assuming the existence of such an asset, Gaur and Seshadri (2005) use actual data to nicely demonstrate that such a financial instrument may indeed exist for some firms: a regression of same-store sales growth among 60 large U.S. general merchandisers with annual returns to the S&P 500 index reveals an R2 = 0 81. This is indeed an eye-opening motivation and a very nice example of data-driven research. With the plausibility of a financial hedge established, the authors begin with a simple single-period inventory problem and an ideal underlying financial asset that is perfectly correlated with demand. A perfect hedge is constructed so that the firm earns the expected value of its inventory investment without any variance in returns, upfront investment, or a need to dynamically revise the hedge over time. Furthermore, the optimal inventory policy remains unaffected by the presence of the hedge. Hence, there is no need to coordinate the firm’s financial strategy with its inventory management. However, the authors next analyze minimum variance hedges under a more realistic situation: an underlying asset that is only partially correlated with demand. In this setting they provide conditions under which a riskaverse decision maker invests in inventory, rather than just the financial asset. Now, the decision maker purchases more inventory with hedging than without, demonstrating the link between the financial and operational strategies. To complete the loop, the authors finish with an application of their results to a numerical example based on sales data for computer game CDs sold at a consumer electronics retailing chain. The strength of this paper is not that it ends a line of research but rather that it starts a vein of research with significant promise. Others will develop more sophisticated hedges, consider more elaborate inventory models and apply these ideas to other operational issues (sourcing strategies, investments in production flexibility, etc.), but the basic idea to combine financial hedging with operational decisions has been established. As such, the paper need not make a contribution by providing new analytical methods. Instead, its contribution comes from combining two sets of well-established tools, just like an artist who brings two familiar media together to create something entirely new and exciting. Finally, the paper’s blend of analytics and data is undeniably powerful: not only will these results influence academics, these