| Traditionally, the retail industry has lagged behind other | | | | place retail outlets, how many of each size or color of |
| industries in adopting new technologies, and this holds | | | | an item to put in each store, and when and how much |
| true in its acceptance of BI technology. Some | | | | to discount. The effects of these decisions can save |
| industries, such as financial services, have become | | | | or generate millions of dollars for retailers. |
| very sophisticated in using BI software for financial | | | | The Strength of the Market for BI in Retail Today |
| reporting and consolidation, customer intelligence, | | | | The market is very strong and getting stronger. While it |
| regulatory compliance, and risk management. However, | | | | is difficult to find a comprehensive suite of |
| retailers are quickly catching up and beginning to | | | | retail-specific BI offerings that spans the spectrum |
| recognize the many areas of BI that can be applied | | | | from competitive intelligence to merchandise planning |
| specifically to their businesses. | | | | and optimization (product, price, promotion, and |
| The competitive game is changing for retail. As the | | | | placement) based on customer insight, to knowing how |
| industry continues to consolidate, retailers have begun | | | | to maximize the ROI on the next marketing campaign, |
| to realize that using technology to better understand | | | | to understanding where to build the next store, to |
| customer buying behavior, to drive sales and | | | | reducing supply chain costs. Retailers are telling us |
| profitability, and to reduce operational costs is a | | | | over and over that they are seeking a single, stable, |
| necessity for long-term survival. | | | | reliable, and proven provider of superior BI solutions. |
| Retailers are now paying significant attention to BI | | | | They are implementing projects that span multiple |
| software, specifically in the areas of merchandise | | | | years and will deliver value for years to come. |
| intelligence (including merchandise planning, assortment, | | | | The Retailers that are Realizing the Most Benefits |
| size, space, price, promotion, and markdown | | | | from BI |
| optimization), customer intelligence (including marketing | | | | We find that the retailers that are realizing the most |
| automation, marketing optimization, and market basket | | | | significant returns on their investments are those that |
| analysis), operational intelligence (including IT portfolio | | | | take a purposeful, pragmatic approach to establishing |
| management, labor optimization, and real estate site | | | | an intelligence platform upon which to base all other BI |
| selection), and competitive intelligence. There are many | | | | solutions. A single, reliable demand forecast, for |
| factors that have led retailers to adopt BI software: | | | | instance, can also be used in merchandising, marketing, |
| increased competition, the need to squeeze more | | | | logistics, store operations, call center staffing, etc., for |
| profitability out of less space, prevalent credit card | | | | operational benefit. BI that remains segmented by |
| usage, the Internet's role as an alternative sales | | | | functional area can provide some value, but retailers |
| channel, the popularity of loyalty cards, and soon, RFID | | | | can realize a much larger return by building the |
| (radio frequency identification). These milestones have | | | | foundation upon which the rest of the house will stand. |
| created a wealth of data that retailers are now | | | | This is true of both top-tier and midmarket retailers, |
| beginning to appreciate and use. | | | | regardless of segment. |
| Within individual companies, we view the history of BI in | | | | Specific Areas in Which Retailers can Benefit Most |
| retail through a method that we devised to describe | | | | Include: |
| the status of any company's evolution toward | | | | Merchandising -- This is clearly the most important |
| becoming an intelligent enterprise. We believe that | | | | area of a retailer's business and an area where |
| organizations pass through five fundamental stages as | | | | retailers are beginning to exploit the full value of BI. |
| they advance in their use of BI as a competitive | | | | Analysis of past performance, combined with plans |
| differentiator: | | | | and forecasts of future customer behavior, leads to |
| Operate -- At this most basic level are the companies | | | | more accurate initial allocations of merchandise across |
| rife with information mavericks: the guys in basement | | | | channels and stores. Assortment and size optimization |
| offices hammering away on desktop spreadsheets. If | | | | that are based on customer demand patterns ensure |
| they go, the knowledge goes with them. There are no | | | | that the correct assortments, size, and case-pack |
| processes, and each request becomes an ad hoc | | | | distributions get sent to the correct stores. Daily price, |
| data rebuild, resulting in multiple versions of the truth, | | | | promotion, and markdown optimization ensures that |
| with the likelihood of a different answer to any one | | | | items are priced for optimal profitability, both preseason |
| question every time it is asked. | | | | and in season. Space automation and optimization |
| Consolidate -- At this stage, a company has pulled | | | | ensure that departmental sales and profit per square |
| together its data at the departmental level. Here, a | | | | foot are maximized, and products are given the |
| question gets the same answer every time, at least | | | | correct inventory and space on the shelf or on the |
| within the department. However, departmental interests | | | | rack. Optimized fulfillment ensures that products are |
| and interdepartmental competition can skew the | | | | allocated or replenished based on demand. Accurate |
| integrity of the output and result in multiple versions of | | | | analysis also results in a more efficient use of |
| the truth. | | | | manpower in picking, packing, and shipping the first |
| Integrate -- At this point in the evolution, a company | | | | wave of product, while minimizing additional, costly |
| has adopted enterprise-wide data and bases its | | | | payroll expenses to facilitate transfers between |
| decisions on this more complete information. This | | | | stores, vendor returns, changing signage and labels for |
| company is beginning to have a true awareness of | | | | markdowns, and otherwise correcting mistakes. |
| additional opportunities for the use of BI to improve | | | | Marketing -- By understanding customers better -- |
| processes and profits. | | | | whether by profiling, segmenting, gauging propensity to |
| Optimize -- At this stage, the company's knowledge | | | | respond, or using market basket analysis -- retailers |
| workers are very focused on incremental process | | | | can create better-defined targeted campaigns, |
| improvements and refining the value-creation process. | | | | reducing expenses (printing, paper, postage) while |
| Everyone understands and uses analysis, trending, | | | | increasing response rates, revenues, and gross |
| pattern analysis, and predictive results to increase | | | | margins. Also, as retailers gain a better understanding |
| efficiency and effectiveness. The extended value | | | | of their customers' buying behavior, this analysis can |
| chain becomes increasingly critical to the organization, | | | | then be used to create more effective merchandising |
| including the customers, suppliers, and partners who | | | | plans for the next season. |
| constitute intercompany communities. | | | | Operations -- Understanding and predicting changes in |
| Innovate -- This level represents a major, quantum | | | | demand -- by hour, by day, by location, by promotion, |
| break with the past. It exploits the understanding of the | | | | by price change -- means that the store floors, the |
| value-creation process acquired in the optimize stage | | | | catalog call centers, and the fleet crews delivering |
| and replicates that efficiency with new products in | | | | replenishment orders from the DC to the store are all |
| new markets. Companies operating at this level | | | | appropriately staffed. This understanding also leads to |
| understand what they do well and apply this expertise | | | | optimal productivity since store-level human capital |
| to new areas of opportunity, thus multiplying the | | | | costs can be scheduled better and managed more |
| number of revenue streams flowing into the enterprise. | | | | efficiently. |
| Armed with information and business process | | | | The Integrated Solution |
| knowledge, organizations approaching the innovate | | | | It is important to note that a good BI solution will be |
| level will introduce truly innovative products and | | | | able to integrate with any other system or platform. |
| services that reflect their unique understanding of the | | | | That said different BI solutions need to interface with |
| market, their internal strengths and weaknesses, and | | | | different operational systems for different purposes. |
| an unfailing flow of ideas from continuously engaged | | | | A solution seeking to use customer behavioral data to |
| employees. | | | | make better merchandising or marketing decisions |
| We are finding that most large retailers have reached | | | | needs to interface with sales transaction systems, |
| or are approaching the integrate stage, with many | | | | loyalty systems, in-house credit systems, coupon |
| making great strides toward the optimize and innovate | | | | redemption systems, catalog and Internet customer |
| levels. There is an enormous opportunity for the | | | | data systems, and so forth. A system that |
| evolution to continue -- within every retail organization. | | | | recommends optimized price changes should interface |
| The Presence of BI in the Retail IT Infrastructure | | | | with the price management system, the item master, |
| In the typical retail IT infrastructure, there are two | | | | the system that generates labels, etc. |
| fundamental categories of systems: transactional | | | | There must be a closed-loop interface between the |
| operational systems, such as POS and purchase order | | | | operational systems that retailers rely upon to conduct |
| management systems; and analytic/BI systems. | | | | day-to-day business and the BI systems that help |
| Operational and transactional systems such as | | | | them conduct that business more efficiently and |
| merchandise management, ERP (enterprise resource | | | | profitably. |
| planning), and POS, are very good at what they do -- | | | | The Future of BI in Retail |
| organizing huge amounts of operational data and | | | | BI will be defined by the retailers that have figured out |
| transactions. These systems can tell retailers what has | | | | how to maximize customer satisfaction and profitability |
| happened in their business and what their customers | | | | with the right combination of quality products, friendly |
| have done -- last week, last month, and last year. | | | | and efficient service, unique value, a differentiated |
| It's critical, however, for retailers to understand what will | | | | shopping experience, and a business model that truly |
| happen: what the demand will be for a select | | | | serves its community -- locally and globally. How will |
| assortment of merchandise, what impact an | | | | this be accomplished? It starts with understanding the |
| incremental price change will have on demand, which | | | | customer and then linking that insight into every |
| floor plan will sell more designer shoes, which | | | | decision that is made, from merchandising to marketing |
| customers will respond to a direct mail or catalog offer. | | | | to distribution to store operations to finance, so that |
| Real value comes from systems that go beyond the | | | | retailers can predict how to best serve their |
| limitations of operational software alone, systems that | | | | customers' ever-changing needs and desires. |
| can take operational data and create enterprise | | | | Our vision for the future of retail BI provides for that |
| intelligence and predictive insights. | | | | very scenario, through our intelligence platform and our |
| These BI systems must combine data management | | | | solutions for customer, merchandise, operations, and |
| (consolidating, organizing, and cleansing huge amounts | | | | performance intelligence that are combined in a suite |
| of disparate data from varying systems and | | | | designed to equip retailers to become truly innovative. |
| platforms) with predictive analytics (data mining, | | | | A solution seeking to use customer behavioral data to |
| forecasting, optimization). When they do, retailers can | | | | make better merchandising or marketing decisions |
| make sense of customer, product, supplier, and | | | | needs to interface with sales transaction systems, |
| operational data and draw insights that will help them | | | | loyalty systems, in-house credit systems, coupon |
| run their businesses better and more profitably. | | | | redemption systems, catalog and Internet customer |
| Leading retailers around the globe -- like Wal-Mart, | | | | data systems, and so forth. A system that |
| Foot Locker, Staples, Williams-Sonoma, and and many | | | | recommends optimized price changes should interface |
| others -- have begun using BI and analytics to make | | | | with the price management system, the item master, |
| an array of strategic decisions. These include where to | | | | the system that generates labels, etc. |