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Retail Data Warehousing—The-State-of-the-Art

Originally published April 19, 2005

As an early adopter of data warehousing technologies in the 1990s, the retail industry has gained over a decade of practical experience with now-mission-critical data warehousing systems. From the first (and rudimentary) store-item-day historical sales reporting databases created over 10 years ago, retailers have dramatically expanded the use of analytical systems to support the business and drive vital operational decisions.

Retail business intelligence systems were once the domain of a few power users in merchandising groups who were willing to suffer through primitive user interfaces in order to gain a competitive edge in decision-making. Today, the retail data warehouse helps every merchant—as well as store managers, logistics staff, category managers and executives—to make better decisions and improve the performance of the enterprise. Today’s retailer has a wealth of technology to help them address age-old problems in running a retail business, including:

  • Store site selection;
  • Understanding customer buying behaviors and preferences;
  • Product assortment;
  • Inventory management and logistics;
  • Product pricing, including clearances and promotions; and
  • Vendor management.

In addition, the adoption of electronic data interchange (EDI) and the Internet has allowed retailers to share up-to-date information with their vendors and store managers, bringing them further into the fold and empowering them to drive incremental improvements within the product and store mix, and these technologies have even introduced an additional sales channel. Any retail enterprise not leveraging data warehousing technology to address these issues is at a competitive disadvantage. In short, the retail data warehouse has become nearly as vital to the health of a retail business as a reliable point-of-sale system.

Let us briefly examine each of the business challenges listed above and discuss the approaches that best-in-class retailers are bringing to bear to address them:

Store Site SelectionArmed with demographics databases, traffic pattern data from localities and third parties and specialized analytical tools from established vendors, retailers can today predict with a high degree of accuracy the benefits of locating new stores in specific locations. Coupled with information on sales performance of comparable (demographically) stores from the chain, a retailer can more efficiently model the projected performance of a new store opening, including the necessary marketing spend for the launch, foot traffic growth pattern and key promotional activity to optimize their results.

Understanding CustomersThrough loyalty programs, transaction/basket analysis and demographic data, retailers are more capable than ever in understanding income levels, buying habits, regional preferences and other factors that can help them design better promotions, product assortments and store layouts. The improvements in database processing power and the continued decline in storage costs are enablers of these approaches.

Product AssortmentGone are the days when a specialty chain might ship the same product assortment to every store. Based on historical sales at the product characteristic level by store, a retailer can optimize the mix of styles, colors and sizes at the individual store level, minimizing both the likelihood of having too little of a particular item (lost sales) and the likelihood of having too much (heavy clearance selling). Rich data models containing SKU characteristics and improved business intelligence suite functionality are key enablers to this process.

Inventory ManagementRetailers are continually improving the efficiency along all steps in their supply chain: ordering, shipping, receiving, distribution center operations and logistics. The result is less capital tied up in inventory at any point in the supply chain and overall increased inventory turns. Enterprise resource planning (ERP) and specialized inventory systems have automated much of this process. These systems also capture the necessary data to provide a centralized view of inventory positions relative to forecasted sales. This enables analysts with the aid of business intelligence technology to make decisions to continually optimize the supply chain.

Product Pricing and PromotionSpecialized tools leverage sales and inventory trend information stored in the retail data warehouse in order to manage highly targeted promotions and clearances. Best-in-class retailers no longer run the same promotion chain-wide. Before a promotion is offered at an individual store, corporate marketing knows the expected impact on overall corporate margins. While a slow-selling item and a high in-stock position might be an obvious consideration for a promotion, the timing and discount amount are not always obvious. The promotional analysis tools on the market are getting better and better at helping retailers make optimal decisions regarding these “when” and “how much” factors.

Vendor ManagementMore and more, retailers are turning to their suppliers and asking them to take some ownership and responsibility for improving the efficiency of the supply chain in return for better terms (or in the case of industry leaders like Wal-Mart, continued business). By sharing sales and inventory levels through extranets, retailers are putting the necessary information in the hands of their vendors so that they can time orders and replenishments more efficiently, minimizing out-of-stocks and responding to pockets of strength or weakness.

All of these challenges and more are being addressed by data warehousing technologies in today’s retail industry. An effective use of these technologies is critical to the success of any retail business—whether the retailer is a traditional store-based marketer or Internet catalog, listed on the New York Stock Exchange or privately held, or sells cars or soap.

As the industry’s usage of business intelligence evolves, there are some obvious areas where new and improving technology will likely come into play:

  • RFID for better inventory data accuracy and logistics cost improvements;
  • ERP system data interchange between retailer and vendor for better supply chain optimization; and
  • Statistical and data mining tools for better forecasting and buying pattern analysis.

In future articles, we will cover all of these business challenges and more, dive into the details of retail data warehousing technology, as well as explore the cutting-edge tools that tomorrow’s retail leaders will use to achieve their competitive edge. I welcome your thoughts, questions, comments and suggestions on improving the relevancy and impact of this Retail Channel.

  • Dan RossDan Ross
    Dan is the Managing Partner of the Retail Practice at Claraview, a strategy and technology consultancy that helps leading companies and government agencies use business intelligence to achieve competitive advantage and operational excellence. Claraview clients realize measurable results: faster time to decision, improved information quality and greater strategic insight. Dan is a frequent contributor to business intelligence literature, writing on topics spanning technical approaches and business impact, and the Claraview Retail Practice serves some of the world's most advanced users of retail data warehouses.

    Editor's note: More retail articles, resources, news and events are available in the BeyeNETWORK's Retail Channel. Be sure to visit today!

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