That includes 10,000 seasonal workers for its distribution centers and 3,000 to help stores cater to cross-channel shoppers.
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And then there’s the case of J.C. Penney Co. Inc., which improved its margins by 290 basis points during last year’s holiday selling season, largely from smarter pricing. J.C. Penney worked with ProfitLogic last year to develop the web-based software. “J.C. Penney was one of the few retailers hitting and exceeding sales targets, especially among general merchandise retailers,” Boone says. “A lot of that performance was due to pricing optimization.”
Penney declines to directly comment, but it said in a statement on its fourth-quarter results that gross margins increased due to improved inventory management and better merchandise assortments. “2003 is definitely a breakthrough year,” says Garrett Sinclair, vice president of strategic initiatives for Spotlight Solutions, vendor of web-based pricing optimization software used by retailers such as Saks Inc. and Shopko Stores Inc. “We’re seeing many more retailers taking it seriously.”
Penney, Northern Group and others are realizing that they can tie their pricing and markdown decisions more directly to consumer demand. “Pricing optimization gets retailers closer to real-time demand parameters,” says Kent Allen, analyst with Aberdeen Group. “The suggested retail price doesn’t mean anything anymore. It’s being replaced by value pricing, because retailers are getting better insight into real-time demand parameters.”
With the flexibility that a web-based system provides, retailers can respond more precisely to demand, retailers say. For instance, pricing managers may analyze such information as which products are selling unusually well in which regional markets, before deciding whether to accept an optimization system’s recommended prices. “Prior to this system, we took markdowns across our whole chain,” says Steve Schwartz, senior vice president of planning and allocation for Casual Male Retail Group Inc., which implemented a ProfitLogic web-based price optimization system last June. “For example, on July 4, we would mark down swimwear across the whole country. Now we can do it by groups of stores. We may mark down swimwear on July 4 in the northern part of the country, but in the central areas not until Aug. 1 and in the south not until after Labor Day.”
Automated systems also force retailers to be more realistic about their pricing. “Retailers are a pretty optimistic group and tend to mark down too late,” Schwartz says. “In the past, we would mark down products really late in the selling season, or after the season when customer traffic is less, and take a deeper hit with margins. Now we take a far smaller hit.” The system, which was up within two months, will pay for itself within the first year, Schwartz says.
Unlike Northern Group, which licenses ProfitLogic’s software to run on its own web server, Casual Male went with a hosted web application to free up its corporate infrastructure, Schwartz says. For hosted applications, ProfitLogic charges $500,000 to $1 million, depending on the retailer’s volume. For licensed software to run on a customer’s web server, ProfitLogic charges about $1 million for every $1 billion in annual revenue and a one-time implementation fee that’s about half the licensing fee.
Until recently, before web-based pricing optimization software from vendors like ProfitLogic, Spotlight Solutions Inc., KhiMetrics Inc., DemandTec Inc. and Marketswitch Corp., in-depth insight into pricing strategies was practically impossible, especially for larger retailers, because it requires review of too many data points among what may be thousands of SKUs and hundreds or thousands of stores. The data include historical prices for each SKU, the length of time it took products to sell at particular prices, the impact on the timing of sell-throughs on other inventory and related inventory and supply chain costs, and the re-compilation of data for each store.
Using data recorded in spreadsheets, retailers have attempted to come up with pricing strategies based on their hunches of which price would move a particular product within a planned timeframe. “Few retailers have any formal process around this,” von Hirschberg says. “Some literally work with paper reports one or two inches thick on sales performance of each style of product, and the average rate of sales for the past few weeks. They sit there with a highlighter and a pen, make some arbitrary decisions on how much and when to mark down, then give those figures to a clerk to enter into their price management system. But the analysis is really all manual, and the decision process is not informed by mathematical analysis.”
Price optimization software changes all that by pulling data from multiple sources, such as POS systems and inventory records. Those multiple points of input also mean that price optimization systems work best in a web environment, because it allows faster access to the various information managers need to make decisions about which prices to post. “If you’re web-enabled, you see patterns faster, react faster and plan better,” says Deborah Vollmer Dahlke, a board member of the Professional Pricing Society trade association and president of pricing consultants DVD Associates.
After gathering the data, the software applies algorithms to come up with price recommendations and makes them easily accessible through a web browser. The browser-based user interface lets managers customize the way they view price optimization reports, such as by setting parameters on how quickly a retailer wants to sell out of particular SKUs to get the corresponding pricing recommendations.
A retail manager who accepts a recommended price inputs it directly into the price management system, instantly updating pricing throughout the chain. As price optimization systems become commonly integrated with back-end software systems, as analysts expect, approved price recommendations will flow automatically into enterprise software systems.