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Retailing in the 21st Century
Computer Models Help Decision Making, Bottom Line
Two decades ago, the tools available to retailers for choosing assortments, managing their inventories and setting prices were, comparatively speaking, in the Dark Ages.
“It used to be that retail chains primarily bought merchandise, allocated it to stores, and tracked only their sales revenue,” said Stephen Smith, Professor of Operations and MIS at the Leavey School of Business. “As a result, they couldn’t estimate lost sales or predict consumer response to new pricing and supply chain strategies, thereby leaving a lot of money on the table.”
Since retailing is an extremely competitive arena, retailers have found themselves under intense pressure to find ways to maintain profitability and contain costs. The IT revolution in the past 15 to 20 years has allowed them to develop comprehensive data bases.
“Retailing has become a data-rich environment,” said Narendra Agrawal, Associate Professor and Chair of the Department of OMIS. “Now that we have the ability to capture relevant data at the right level of detail, we can develop sophisticated analytical methodologies to address key challenges faced in the retail supply chain. Coupled with the inherent complexity of its environment, retailing has become an intellectually fruitful area for academic research.
“Imagine, for example, a chain of a thousand stores, where each store carries an average of 30,000 items, many of which change over the course of a year. It is impossible to manually determine sourcing, inventory and pricing decisions for each store-item combination for each week of the year, but statistical models and software can help make those decisions.”
Agrawal and Smith, both of whom are affiliated with the Retail Management Institute at Leavey, have been working together on research in retail supply chain management since 1992. In addition to publishing about 20 papers on retail operations between them, they are co-editors of a book, Retail Supply Chain Management: Quantitative Models and Empirical Studies, which will be published in late 2008.
Targeted towards researchers and practitioners, the book presents the state-of-the-art research in retail supply chain management. It includes chapters on empirical studies of retail practices, methods for assortment planning (which items to stock and display), joint pricing and inventory management, and managing inventory for multi-location retailers. Much of the research in the field utilizes sophisticated statistical and optimization models that help retail executives make decisions on inventory and merchandise assortment that were previously made by buyers acting on intuition and experience.
In one of the chapters, Smith has tackled the problem of clearance pricing in retail chains, developing a statistical model that takes into account the impact of reduced merchandise assortment and seasonal changes on sales rates. The value of working with this sort of model can be significant. Smith reported in his chapter that a software vendor found that department store revenues increased roughly 4% as a result of using these clearance-pricing methods. Since the department store sector of retailing has yearly revenues of over $500 Billion, this would amount to $20 billion a year in additional revenue, if similar gains could be achieved across the industry.
In another paper that Agrawal and Smith are working on currently, they tackle the challenge of managing procurement and inventory allocations decisions across large retail chains for short-life-cycle, fashion merchandise. Given the high level of forecast uncertainty associated with such products, they argue that supply chain flexibility is the only way to meet customer demand cost effectively.
However, retailers don’t have to rely solely on the external flexibility of their vendors. They can also exercise internal flexibility by updating their forecasts using real time store sales data and reallocating their inventory based on the new forecasts. In this paper, they develop analytical methodologies to incorporate both external and internal flexibility, and compare the potential values of different types of flexibility.
“The most exciting thing about working on retail research at SCU is that we get to work on real problems faced by real companies,” Agrawal said. “Work on such cutting-edge challenges has allowed us to develop new insights about key decision problems in retailing and offered us opportunities to apply our results in retail operations.”
Added Smith, “At the same time, we also get to contribute to basic research which applies beyond the retail sector.”
CUTTING EDGE RETAILING: The research done by Narendra Agrawal and Stephen Smith helps retail businesses make decisions such as what to stock and how much to mark down on a sale.