These days, it seems that both traditional bricks-and-mortar retailers and online "e-tailers" are drowning in a sea of customer information -- knocked by wave after wave of data from online transactions, point-of-service scanners, membership programs, and even sensor chips on shopping carts. The question is, with all this sophisticated technology on hand, why have department store markdowns over the last 20 years grown from 8% to a whopping 33% of sales? Why do lost sales today often exceed 10% of revenue? And why is it that customers are still going away dissatisfied because what they want isn't in stock?
In an article entitled "Rocket Science Retailing Is Almost Here -- Are You Ready?" in the July-August 2000 issue of the Harvard Business Review, Wharton operations professor Marshall Fisher and two coauthors take a hard look at why retailers today may be, as one of their study participants put it, "awash in data but starved for information," and what they can do about it.
Fisher is blunt about the problem: "The big challenge for retailers is achieving what they call the four 'rights' -- the right product in the right place at the right time and at the right price -- and they really are failing miserably." He estimates the costs associated with mismatches between supply and demand, for example, as "about 10% of revenue, in an industry where profit is about 2% to 3%."
Today's large retailers, Fisher notes, have powerful information systems that can store customer data in giant warehouses. Some companies keep data for a few weeks, others for a number of years. In both cases, however, many businesses don't know how to use the information they collect and often don't make it available to their merchants.
Fisher and his coauthors -- professor Ananth Raman of the Harvard Business School and Anna Sheen McClelland, a former research associate at Wharton -- conducted a multiyear study in which they worked with 32 leading retailers, including Borders, Bulgari, Nine West, Staples, and Tiffany & Co., to find out how they use information technology to understand their customers. The researchers deliberately chose retailers of innovative, short-life-cycle products such as fashion apparel, shoes, toys, books, music and consumer electronics, speculating that the unpredictable demand for these products would make them the hardest cases. They surveyed and visited each retailer, working with some of them to improve their capabilities.
While most of the retailers in the study wanted very much to make better use of sales data, they possessed little expertise and few tools to do it. Another factor is also at work here, says Fisher: Some retailers have such long supply chains that even if they discover a particular item has strong early sales, they can't restock it within the season. "If you look at apparel, it's the story of chasing low cost through Asia, resulting in long lead times. Then their lead times are so long that they can't react to sales data, so why bother to try? It's a vicious cycle."
But Fisher asserts that turning customer data into action is eminently doable and very effective. In addition to his professorship at Wharton, Fisher is the founder of 4R Systems, a provider of software and consulting for supply chain management of short-life-cycle products. His company helps retailers determine the economically ideal amount of inventory at each point in the supply chain and life cycle of an item.
Fisher presents his "rocket science retailing" concept as a road map for retailers on getting the most mileage possible out of consumer transaction data. His inspiration for the rocket science concept comes from the movement of the same name that swept Wall Street in the late '70s, when the arrival of information technology revolutionized the investment world. Using examples from companies that have done well using data and those that haven't, Fisher explains how rocket science retailing requires improving capabilities in three basic areas:
In turn, these three capabilities must rest on a foundation of:
As Fisher and his coauthors note, "Retailers can't continue to suffer growing markdown losses yet disappoint a significant portion of their customers who can't find what they want. They can't continue to ignore billions of bytes of unused sales history that could help solve these problems.
"Every decade sees a retailer who innovates so powerfully that it rewrites the rules for other retailers and for all companies in the retail supply chain," they conclude. "In the 1980s it was Wal-Mart. In the 1990s, it was Amazon.com. We believe the next retail innovator will be the one that best combines access to consumer transaction data with the ability to turn that information into action."
All materials copyright © 2000 Wharton School of the University of Pennsylvania