Traditionally, the retail industry haslagged behind other industries in adopting new technologies, and thisholds true in its acceptance of BI technology. Some industries, such asfinancial services, have become very sophisticated in using BI softwarefor financial reporting and consolidation, customer intelligence,regulatory compliance, and risk management. However, retailers arequickly catching up and beginning to recognize the many areas of BIthat can be applied specifically to their businesses.

Thecompetitive game is changing for retail. As the industry continues toconsolidate, retailers have begun to realize that using technology tobetter understand customer buying behavior, to drive sales andprofitability, and to reduce operational costs is a necessity forlong-term survival.

Retailers are now paying significantattention to BI software, specifically in the areas of merchandiseintelligence (including merchandise planning, assortment, size, space,price, promotion, and markdown optimization), customer intelligence(including marketing automation, marketing optimization, and marketbasket analysis), operational intelligence (including IT portfoliomanagement, labor optimization, and real estate site selection), andcompetitive intelligence. There are many factors that have ledretailers to adopt BI software: increased competition, the need tosqueeze more profitability out of less space, prevalent credit cardusage, the Internet’s role as an alternative sales channel, thepopularity of loyalty cards, and soon, RFID (radio frequencyidentification). These milestones have created a wealth of data thatretailers are now beginning to appreciate and use.

Withinindividual companies, we view the history of BI in retail through amethod that we devised to describe the status of any company’sevolution toward becoming an intelligent enterprise. We believe thatorganizations pass through five fundamental stages as they advance intheir use of BI as a competitive differentiator:

Operate — Atthis most basic level are the companies rife with informationmavericks: the guys in basement offices hammering away on desktopspreadsheets. If they go, the knowledge goes with them. There are noprocesses, and each request becomes an ad hoc data rebuild, resultingin multiple versions of the truth, with the likelihood of a differentanswer to any one question every time it is asked.
Consolidate –At this stage, a company has pulled together its data at thedepartmental level. Here, a question gets the same answer every time,at least within the department. However, departmental interests andinterdepartmental competition can skew the integrity of the output andresult in multiple versions of the truth.
Integrate — At thispoint in the evolution, a company has adopted enterprise-wide data andbases its decisions on this more complete information. This company isbeginning to have a true awareness of additional opportunities for theuse of BI to improve processes and profits.
Optimize — At thisstage, the company’s knowledge workers are very focused on incrementalprocess improvements and refining the value-creation process. Everyoneunderstands and uses analysis, trending, pattern analysis, andpredictive results to increase efficiency and effectiveness. Theextended value chain becomes increasingly critical to the organization,including the customers, suppliers, and partners who constituteintercompany communities.
Innovate — This level represents amajor, quantum break with the past. It exploits the understanding ofthe value-creation process acquired in the optimize stage andreplicates that efficiency with new products in new markets. Companiesoperating at this level understand what they do well and apply thisexpertise to new areas of opportunity, thus multiplying the number ofrevenue streams flowing into the enterprise. Armed with information andbusiness process knowledge, organizations approaching the innovatelevel will introduce truly innovative products and services thatreflect their unique understanding of the market, their internalstrengths and weaknesses, and an unfailing flow of ideas fromcontinuously engaged employees.
We are finding that most largeretailers have reached or are approaching the integrate stage, withmany making great strides toward the optimize and innovate levels.There is an enormous opportunity for the evolution to continue –within every retail organization.

The Presence of BI in the Retail IT Infrastructure

Inthe typical retail IT infrastructure, there are two fundamentalcategories of systems: transactional/operational systems, such as POSand purchase order management systems; and analytic/BI systems.

Operationaland transactional systems such as merchandise management, ERP(enterprise resource planning), and POS, are very good at what they do– organizing huge amounts of operational data and transactions. Thesesystems can tell retailers what has happened in their business and whattheir customers have done — last week, last month, and last year.

It’scritical, however, for retailers to understand what will happen: whatthe demand will be for a select assortment of merchandise, what impactan incremental price change will have on demand, which floor plan willsell more designer shoes, which customers will respond to a direct mailor catalog offer.

Real value comes from systems that go beyondthe limitations of operational software alone, systems that can takeoperational data and create enterprise intelligence and predictiveinsights.

These BI systems must combine data management(consolidating, organizing, and cleansing huge amounts of disparatedata from varying systems and platforms) with predictive analytics(data mining, forecasting, optimization). When they do, retailers canmake sense of customer, product, supplier, and operational data anddraw insights that will help them run their businesses better and moreprofitably.

Leading retailers around the globe — like Wal-Mart,Foot Locker, Staples, Williams-Sonoma, and Amazon.com and many others– have begun using BI and analytics to make an array of strategicdecisions. These include where to place retail outlets, how many ofeach size or color of an item to put in each store, and when and howmuch to discount. The effects of these decisions can save or generatemillions of dollars for retailers.

The Strength of the Market for BI in Retail Today

Themarket is very strong and getting stronger. While it is difficult tofind a comprehensive suite of retail-specific BI offerings that spansthe spectrum from competitive intelligence to merchandise planning andoptimization (product, price, promotion, and placement) based oncustomer insight, to knowing how to maximize the ROI on the nextmarketing campaign, to understanding where to build the next store, toreducing supply chain costs. Retailers are telling us over and overthat they are seeking a single, stable, reliable, and proven providerof superior BI solutions. They are implementing projects that spanmultiple years and will deliver value for years to come.

The Retailers that are Realizing the Most Benefits from BI

Wefind that the retailers that are realizing the most significant returnson their investments are those that take a purposeful, pragmaticapproach to establishing an intelligence platform upon which to baseall other BI solutions. A single, reliable demand forecast, forinstance, can also be used in merchandising, marketing, logistics,store operations, call center staffing, etc., for operational benefit.BI that remains segmented by functional area can provide some value,but retailers can realize a much larger return by building thefoundation upon which the rest of the house will stand. This is true ofboth top-tier and midmarket retailers, regardless of segment.

Specific Areas in Which Retailers can Benefit Most Include:

Merchandising– This is clearly the most important area of a retailer’s business andan area where retailers are beginning to exploit the full value of BI.Analysis of past performance, combined with plans and forecasts offuture customer behavior, leads to more accurate initial allocations ofmerchandise across channels and stores. Assortment and sizeoptimization that are based on customer demand patterns ensure that thecorrect assortments, size, and case-pack distributions get sent to thecorrect stores. Daily price, promotion, and markdown optimizationensures that items are priced for optimal profitability, both preseasonand in season. Space automation and optimization ensure thatdepartmental sales and profit per square foot are maximized, andproducts are given the correct inventory and space on the shelf or onthe rack. Optimized fulfillment ensures that products are allocated orreplenished based on demand. Accurate analysis also results in a moreefficient use of manpower in picking, packing, and shipping the firstwave of product, while minimizing additional, costly payroll expensesto facilitate transfers between stores, vendor returns, changingsignage and labels for markdowns, and otherwise correcting mistakes.
Marketing– By understanding customers better — whether by profiling,segmenting, gauging propensity to respond, or using market basketanalysis — retailers can create better-defined targeted campaigns,reducing expenses (printing, paper, postage) while increasing responserates, revenues, and gross margins. Also, as retailers gain a betterunderstanding of their customers’ buying behavior, this analysis canthen be used to create more effective merchandising plans for the nextseason.
Operations — Understanding and predicting changes indemand — by hour, by day, by location, by promotion, by price change– means that the store floors, the catalog call centers, and the fleetcrews delivering replenishment orders from the DC to the store are allappropriately staffed. This understanding also leads to optimalproductivity since store-level human capital costs can be scheduledbetter and managed more efficiently.
The Integrated Solution

Itis important to note that a good BI solution will be able to integratewith any other system or platform. That said different BI solutionsneed to interface with different operational systems for differentpurposes.

A solution seeking to use customer behavioral datato make better merchandising or marketing decisions needs to interfacewith sales transaction systems, loyalty systems, in-house creditsystems, coupon redemption systems, catalog and Internet customer datasystems, and so forth. A system that recommends optimized price changesshould interface with the price management system, the item master, thesystem that generates labels, etc.

There must be a closed-loopinterface between the operational systems that retailers rely upon toconduct day-to-day business and the BI systems that help them conductthat business more efficiently and profitably.

The Future of BI in Retail

BIwill be defined by the retailers that have figured out how to maximizecustomer satisfaction and profitability with the right combination ofquality products, friendly and efficient service, unique value, adifferentiated shopping experience, and a business model that trulyserves its community — locally and globally. How will this beaccomplished? It starts with understanding the customer and thenlinking that insight into every decision that is made, frommerchandising to marketing to distribution to store operations tofinance, so that retailers can predict how to best serve theircustomers’ ever-changing needs and desires.

Our vision for thefuture of retail BI provides for that very scenario, through ourintelligence platform and our solutions for customer, merchandise,operations, and performance intelligence that are combined in a suitedesigned to equip retailers to become truly innovative.

Asolution seeking to use customer behavioral data to make bettermerchandising or marketing decisions needs to interface with salestransaction systems, loyalty systems, in-house credit systems, couponredemption systems, catalog and Internet customer data systems, and soforth. A system that recommends optimized price changes shouldinterface with the price management system, the item master, the systemthat generates labels, etc.
About the Author

Mitchell Dubin is Director of Microsoft Solutions for OnX Enterprise Solutions

Tags: BI, loyalty, Loyalty.ie, retail

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