Nathan Charles Craig

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Doctoral Student

Nathan Craig is a doctoral candidate in Technology and Operations Management. He holds a BS in Industrial and Systems Engineering and an MS in Operations Research from the Ohio State University. His prior experience includes projects for Honda of America, Digital Automation Associates, American Electric Power, Intel, and Nationwide Children's Hospital.

    Publications

    Working Papers

    1. Improving Store Liquidation

      This paper introduces methods for increasing the efficiency of retail store liquidation, which we define as the time-constrained divestment of retail outlets through an in-store sale of inventory. The retail industry depends extensively on liquidation, not only as a means for investors to recover capital from failed ventures, but also to allow managers of going concerns to divest stores in efforts to enhance performance and to change strategy. The operations literature has examined product liquidation, but retail store liquidation differs significantly. This paper augments the literature by introducing techniques for improving operating decisions during retail store liquidations and by demonstrating the performance of these methods in the field.

      Keywords: Business Exit or Shutdown; Financial Condition; Operations;

      Citation:

      Craig, Nathan, and Ananth Raman. "Improving Store Liquidation." Working Paper, September 2013. (Under revision.)
    2. The Impact of Supplier Reliability on Retailer Demand

      To set inventory service levels, firms must understand how changes in service level affect customer demand. While the effects of service level changes have been studied empirically at the level of the end consumer, relatively little is known about the interaction between a retailer and a supplier. Using data from a manufacturer of branded apparel, we show increases in service level to be associated with statistically significant increases in retailer orders (i.e., demand, not just sales). Controlling for other factors that might affect demand, we find a 1 percent increase in historical service level to be associated with a 12 percent increase in demand from retailers, where historical service level is the type 1 service level performance of the apparel manufacturer over the prior year. Further, we find that retailers that order frequently exhibit a more substantial reaction to changes in service level, an outcome that is consistent with retailers learning about and reacting to changes in supplier service level. Our study not only provides the first empirical evidence of the impact of changes in service level on demand from retailers but also illustrates a method for estimating this relationship in practice.

      Keywords: Customer Satisfaction; Forecasting and Prediction; Learning; Consumer Behavior; Service Delivery; Performance Expectations; Apparel and Accessories Industry; Service Industry;

      Citation:

      Craig, Nathan, Nicole DeHoratius, and Ananth Raman. "The Impact of Supplier Reliability on Retailer Demand." Working Paper, September 2013. (Under revision.)
    3. Inventory Management with Purchase Order Errors and Rework

      Citation:

      Craig, Nathan, Nicole DeHoratius, Yan Jiang, and Diego Klabjan. "Inventory Management with Purchase Order Errors and Rework." Working Paper, August 2013. (Under review.)

    Cases and Teaching Materials

    1. Inventory-Based Lending Industry Note

      Inventory-based lending is a form of asset-based lending used by retailers and wholesalers. This note describes the development and the current state of the inventory-based lending industry.

      Keywords: Banks and Banking; Financing and Loans; Banking Industry;

      Citation:

      Foley, C. Fritz, Ananth Raman, and Nathan C. Craig. "Inventory-Based Lending Industry Note." Harvard Business School Background Note 612-057, January 2012. (Revised May 2013.)

      Research Summary

    1. Overview

      The overarching goal of my research is to produce works that are influential and informative to both academics and practitioners in the field of operations management. To accomplish this, I collaborate with industry partners who provide knowledge about their field, data from their operations, and opportunities to test new ideas and methods. This focus dates back to my graduate work in operations research at Ohio State University, where I worked with managers and analysts at American Electric Power to formulate and solve a mixed-integer program for selecting virtual contracts to hedge operational risk when selling electricity on a power market. During the course of my doctoral studies, I developed a focus on the retail industry and, in particular, on increasing the efficiency of retail store liquidation, which is the time-constrained divestment of a set of retail stores. My collaborators and I define increased efficiency as generating more funds from a given set of inventory, stores, and sale days. Retail store liquidation, which is a novel problem not treated by extant literature on retailing seasonal and perishable goods, is vital to the retail industry: it allows going concerns to improve their performance through the divestment of weak stores, and it frees capital for the promotion of new concepts and firms in retailing. To investigate retail store liquidation, I collaborated with managers at Gordon Brothers Group, the largest retail asset disposition firm in the world, over the past two years. Going concerns use retail chain liquidations for a number of reasons, including freeing capital to implement strategic changes and removing poorly performing stores or chains from their portfolios. For example, this year, Best Buy is closing 50 big-box stores to fund a change of strategy: the retailer now plans to introduce small-format stores geared toward selling mobile devices. Home Depot liquidated its flagging chain of EXPO stores in 2009. More efficient liquidation increases the power of this tool for managers. Bankruptcy and liquidation are common in retailing---Capital IQ records 2,013 retailer bankruptcy announcements over the decade beginning in 2000---and struggling and failed retailers liquidate billions of dollars of inventory each year. The total pre-bankruptcy petition assets, recorded by Capital IQ, of just four major retailers that were liquidated since January 2000 is roughly $10B: Montgomery Ward ($3.4B), Circuit City ($3.4B), Linens `n Things ($1.7B), and Heilig-Meyers ($1.5B). Regardless of whether a firm is liquidated, retail chain liquidation is a key determinant of the outcome of the bankruptcy process because it acts as the debtholders' backstop. Efficient liquidation increases the amount of capital available to stakeholders---including employees, suppliers, and investors---and thus affects not only bankrupt firms but also, e.g., retail finance through \emph{ex ante} contracts. Moreover, efficient liquidation frees capital to be used for innovation in the retail sector and elsewhere. My job market paper, "Applying Management Science to Retail Store Liquidation," (with Ananth Raman) introduces the retail store liquidation problem to the operations management literature. This problem, which we formulate as a dynamic program, differs structurally from those explicated by prior authors through the introduction of store variable operating costs that may be large relative to store revenues. Managers executing a retail store liquidation need not only to set prices and inventory levels but also to consider the timing of store closings. In this paper, we also provide methods for improving the decisions made during a retail store liquidation. These techniques, which include a relaxation of the dynamic program and a demand forecasting model, were developed and tested during the liquidation of over $2B of inventory. Further, we discuss insights and results gleaned from applying the methods during recent major retail store liquidations, including sales conducted by Borders, Filene's Basement, and Home Depot. We argue that our techniques significantly improve the outcome of retail store liquidations, increasing revenues by as much as 5 to 10% while decreasing costs by a similar amount. I believe that research on retail store liquidation has only just begun. There are a number of important questions that follow directly from our first paper. For example, what are the drivers of a retail store's demand during a liquidation? How should a retail asset disposition firm decide between liquidating inventory in a retailer's stores or via the internet? When is it worthwhile to price at the item level rather than at the category level, which is the current practice? In addition, the context of retail store liquidation serves as an ideal laboratory for testing fundamental questions in seasonal and perishable goods retailing. Significant variance in inventory levels will allow us to study the billboard and scarcity effects while rapid markdown cadences abet the examination of strategic customer behavior. I am also currently pursuing research on the intersection between retail store liquidation and retail finance. Along with C. Fritz Foley and Ananth Raman, I am exploring the interaction between retail inventory liquidation value, asset-based lending, and inventory management practices using a unique database containing detailed information about the outcomes of over 100 liquidations in the United States and Europe. These liquidations involve 70 retailers and $8B of inventory. Relatively little is known about the relationship between inventory investment decisions and liquidation values despite the prominence of liquidation value in theory (e.g., the optimal policies prescribed in inventory models often depend on salvage value, which may be construed as liquidation value in many situations, and the textbook theory of capital structure holds that firms select an optimal amount of debt by weighing the tax benefits of debt against the costs of financial distress, which are a function of asset liquidation value). Inventory-based lending, or collateralized lending on retail inventories, is a relatively new form of finance that provides hundreds of billions of dollars of capital to retailers including Whole Foods, Barnes and Noble, and Dick's Sporting Goods. By treating inventory as loan security, inventory-based lending makes the link between inventory management decisions and liquidation values even more explicit. As these works demonstrate, the aim of my research is to augment the academic literature while developing critical insights and useful methods for practitioners. In the long term, I will continue to be guided by this principle as I study other questions and problems related to retail store liquidation, inventory finance, and retail operations management.

        Area of Study

        • Technology and Operations Management