Business Intelligence in Retail: Bringing Cohesion to a Fragmented Enterprise

Transcription

1 Business Intelligence in Retail: Bringing Cohesion to a Fragmented Enterprise A Benchmark Report June 2006 AberdeenGroup i

2 Executive Summary I f asked, many retail executives cannot fully quantify the effect one department s actions and activities have on another within their particular enterprises. This unfortunate situation is a consequence of multiple sets of business analytics, all measuring different processes. As a result, retailers are challenged to make good decisions that directly affect their bottom line. Best in Class retailers, however, are already working toward maintaining a laser-like focus on their sales, store margins, and gross performances. This effort is enhanced by harnessing the power of massive customer and transaction data warehouses into a set of manageable performance metrics. These metrics are called retail business intelligence. Key Business Value Findings Business intelligence has top-of-mind retailer awareness. Seventy-six percent of respondents to an Aberdeen survey indicated that they use or have active, budgeted plans to use business intelligence (BI) in some form or another within their organizations. To that end, merchandising and back-office processes were the two categories most heavily invested in by respondents. Best in Class retailers have distinguished themselves as those that fully utilize the benefits BI has to offer. For example, these retailers are fully utilizing BI at the enterprise level, and enhanced data analysis processes are standardized across all banners or store brands. Best in Class retailers also have proven themselves adept at monitoring key KPIs, such as traditional customer performance measurements, within their enterprises. However, Best in Class and Industry Average retailers have largely missed opportunities to make better decisions by viewing data on an ad-hoc basis, rather than at regularly scheduled intervals. Recommendations for Action The first item on the to do list for any retailer using or considering using BI in the enterprise is to establish the value proposition. Take the time to understand the state of data usability within the enterprise, consider the state of inter-departmental communications, and decide how BI would benefit the organization. If BI is implemented correctly, better business decision-making would be an immediate by-product. Retailers that are considered industry Laggards will be best served by building the base for basic business intelligence investment. Fifty percent of Laggard respondents indicated that they do not use business intelligence anywhere within their enterprises. This provides them with a great opportunity to study the potential business benefits of BI across their enterprises. Fortunately, Laggard respondents indicated a strong desire to plan for BI within the near future, including merchandise and back office operations. Retailers at the Industry Average level have made major strides towards adopting enterprise-wide BI practices. For these respondents, close attention to Best in Class practices is a crucial next step. A nearly equal number of Industry Average respondents indicated they use BI within their enterprises (79% vs. 80% for Best in Class). Now, industry norm ii AberdeenGroup

3 retailers must fully utilize their BI infrastructures to move to the next level by focusing on establishing enterprise-wide BI decision-making abilities and determining where within the enterprise BI could be the most beneficial. Best in Class retailers must let customer centricity drive further BI investment. A majority of Best in Class retailers surveyed are actively using BI within their enterprises and reaping the rewards this software produces. As time goes by, however, the Best in Class must avoid stalling as their investment continues. To do this, tying BI-related ROI to quantitative customer centric benefits will provide a strong impetus for further investments in these decision-facilitating technologies. AberdeenGroup iii

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5 Table of Contents Executive Summary... ii Key Business Value Findings...ii Recommendations for Action...ii Chapter One: Issue at Hand... 1 Decision-Making Pressures Come from All Ends of the Retail Supply Chain... 1 Application Vendors and Best in Class Retailers Respond... 2 Chapter Two: Key Business Value Findings... 4 Best in Class More Invested in Business Intelligence... 7 Challenges and Responses... 8 Chapter Three: Implications & Analysis Process and Organization Data and Knowledge Opportunity Missed Technology Usage Consumer Measurements Close but No Cigar Pressures, Actions, Capabilities, Enablers (PACE) Chapter Four: Recommendations for Action Laggard Steps to Success Industry Norm Steps to Success Best in Class Next Steps Author Profile Appendix A: Research Methodology Appendix B: Related Aberdeen Research & Tools About AberdeenGroup AberdeenGroup

6 Figures Figure 1: Customer-Driven Response Times Drive BI and Predictive Analytics... 3 Figure 2: Business Intelligence Proves Wide-Ranging within Retail Enterprises... 4 Figure 3: Back Office, Merchandising Strong Areas of BI Investment... 5 Figure 4: Customer Service Drives BI Utilization... 6 Figure 5: C-Level Executives are Getting Engaged in Business Intelligence... 7 Figure 6: Best in Class Measure Performance at the Enterprise Level Figure 7: Retailers Miss Opportunities to Use Their Data Figure 8: Best in Class Excel in Customer Retention Measurement Efforts Tables Table 1: Business Intelligence: Retailer Challenges and Responses... 8 Table 2: Planning and Replenishment Competitive Framework Table 3: PACE (Pressures, Actions, Capabilities, Enablers) Table 4: PACE Framework Table 5: Relationship between PACE and Competitive Framework Table 6: Competitive Framework AberdeenGroup

7 Chapter One: Issue at Hand Key Takeaways Retailers are being challenged to fully quantify the effect one department s actions and activities have on another s within their enterprises. Customer centricity, powered by increased speed and efficiency, are the top pressures that have fueled increased business intelligence interest within the enterprise. Application vendors are trying to change the way business and predictive analytics are used within the organization, and the Best in Class have responded accordingly. I f asked, many retail executives can not fully quantify the effect one department s actions and activities have on another within their particular enterprise. This unfortunate situation is a consequence of multiple sets of business analytics, all measuring different processes. As the result, retailers are challenged to make good decisions that directly affect their bottom line. Best in Class retailers are already working toward maintaining a laser-like focus on their sales, store margins, and gross performances. This effort is enhanced by harnessing the power of massive customer and transaction data warehouses into a set of manageable performance metrics. These metrics are called retail business intelligence. Decision-Making Pressures Come from All Ends of the Retail Supply Chain The recent Aberdeen research report, The Proactive Merchant: Anticipating Consumer Demand, discussed the importance of achieving optimal results by increasing visibility into sales, inbound merchandise, and new forecast projections. According to the report, retail merchandising organizations that collaborate with other internal departments perform consistently better than their peers. To improve and institutionalize this collaboration, retailers of all types are moving to advanced planning and forecasting technologies and experiencing improved business results. However, tools alone will not generate the new merchandising cultures needed. The proactive merchant, the report argues, is one who embraces both collaboration with other corporate constituents and the tools and techniques available to create the best possible merchandise assortment, price, and promotion strategy. This proactive merchant helps create a responsive, rather than reactive, retailing enterprise. Competitive Framework Key The Aberdeen Competitive Framework defines enterprises as falling into one of the three following levels of practices and performance: Laggards practices that are significantly behind the average of the industry Industry norm practices that represent the average or norm Best in Class practices that are the best currently being employed and significantly superior to the industry norm Another Aberdeen report, The Empowered Store Benchmark Report: Delighting Customers, Motivating Employees, and Pleasing Shareholders also echoes the impor- AberdeenGroup 1

8 tance placed on intelligent decision-making for retailers by identifying inconsistent store performance task execution, loss prevention, and workforce management as key pressures. Impeccable execution cannot be achieved or maintained without regular and frequent review of in-store activities. Best in Class retailers take advantage of closed loop task management systems to assign and confirm execution of store-related tasks, and the larger retailers make use of computer-based, intelligent forecasting for labor requirements. Survey results confirmed that Best in Class retailers leverage their computer networks to provide up-to-the-minute information on product and employee performance, and update their back office information systems. The April 2006 report, The Empowered Point of Service Benchmark Report: The Customer Regains Her Kingdom, highlighted retailers need to become more customerfocused, even as they are pressured to hold the line on payroll costs. Business intelligence is used to alert the home office and store managers to performance anomalies, allowing them to react quickly, before customers are affected. The extended point of service is a new generation of modular applications, driven by real-time business intelligence-generated data and delivered across broadband networks directly into users hands. Speed and Efficiency Drive Business Intelligence Between March and May 2006, AberdeenGroup surveyed more than 150 respondents on their BI strategies. When they were asked to list the top pressures to implement business intelligence and predictive analytics, respondents zeroed in on speed and efficiency in responding to customer demands as the top motivator, as well as the drive to become operationally efficient and manage demand across all channels (Figure 1). Application Vendors and Best in Class Retailers Respond In response to these growing challenges, application vendors are trying to change the way retailers utilize business intelligence within their enterprises. For example, falling hardware prices and increased processing power, coupled with advances in analytic engines, are coming together to raise the profile of a new generation of business intelligence. This new business intelligence is more feature-rich than just dashboards that show red, yellow, or green flags for exception reporting. Predictive analytics is a key component of the new era of business intelligence, helping retailers understand future trends based on past performance and missed opportunities. Theoretically, the Holy Grail of retailing is the prospect of establishing a single view of manageable data across the enterprise. Although the retail industry has a long way to go to hit that goal, the vendor community is moving in the right direction. Best in PACE Key For more detailed description see Appendix A Aberdeen applies a methodology to benchmark research that evaluates the business pressures, actions, capabilities, and enablers (PACE) that indicate corporate behavior in specific business processes. These terms are defined as follows: Pressures external forces that impact an organization s market position, competitiveness, or business operations Actions the strategic approaches an organization takes in response to industry pressures Capabilities the business process competencies required to execute corporate strategy Enablers the key functionality of technology solutions required to support the organization s enabling business practices 2 AberdeenGroup

9 Class retailers, defined as having annual store sales growth of more than 3%, are seeking new and improved solutions to manage this process. More than 67% of these Best in Class retailers have enterprise-wide business intelligence applications budgeted or in place. Figure 1: Customer-Driven Response Times Drive BI and Predictive Analytics Top factors driving Implementation of BI and predictive analytics Need for more rapid response to consumer demand Must become more operationally efficient 69% 67% Need to manage demand across multiple channels 51% Must improve store performance 40% Must stem the tide of price deflation and eroding gross margins 26% 0% 10% 20% 30% 40% 50% 60% 70% 80% Source: AberdeenGroup, June 2006 AberdeenGroup 3

10 Chapter Two: Key Business Value Findings Key Takeaways Investment in business intelligence and predictive analytics remains active, particularly in merchandising and back-office processes. Those retailers that are more likely to utilize and prioritize BI are more likely to realize Best in Class performance across the enterprise. Unwillingness to use information gathered by BI-related technology is a top retailer challenge, and executive mandates for change is a strategic response. M erchandising, the back office, store operations, loss prevention, customer management, and multi-channel selling are just a few of the major departments that, if linked together for better decision-making, would be a true competitive advantage. For example: The most efficient supply chain is irrelevant if the wrong product is brought to the stores. The best run stores will become museums if the consumer rejects the retailers offerings. Initial gross margin on wonderful merchandise may be high, but total delivered profit will be low if merchandising processes drive costs throughout the stores and logistics departments. Turn may look good by department, but empty store shelves may reveal missed opportunities. In short, the highest form of BI and predictive analytics helps the retailer understand the implications of one department s actions and activities on the rest of the enterprise. Figure 2: Business Intelligence Proves Wide-Ranging within Retail Enterprises Source: AberdeenGroup, June AberdeenGroup

11 Investment in Business Intelligence and Predictive Analytics Remains Active Business intelligence has top-of-mind retailer awareness. Seventy six percent of respondents indicated they use BI in some form, whether currently budgeted or planning for adoption. Figure 3 illustrates the BI investment priorities in the various areas of the retail enterprise Merchandising and back-office processes were the two most heavily invested in categories by respondents. BI in Merchandising Traditional merchandising processes are in need of a serious overhaul. In general, merchandise and apparel, and the processes of assortment, space, price, and promotion planning can be infused with predictive analytics to ensure last years results don t become this year s self-fulfilling prophecies. Predictive analytics, driving plans to SKU/store clusters, can help identify missed opportunities; even as the dashboards implicit in BI applications make results available to both merchants and finance managers. In supermarkets and other fast-moving consumer goods retail segments, BI is invaluable for driving basket size, optimizing sales per square foot and reducing out-of-stocks and fresh item spoilage. Figure 3: Back Office, Merchandising Strong Areas of BI Investment Areas of Investment for Business Intelligence Enterprise-wide 21% 21% 14% 32% 11% Customer Management 20% 33% 16% 27% 3% Loss Prevention 20% 16% 9% 23% 32% Store Operations 31% 22% 18% 23% 6% Back Office 34% 25% 16% 18% 7% Merchandising 29% 29% 13% 20% 9% 0% 20% 40% 60% 80% 100% In Place for > 2 years Budgeted No Plans In Place for < 2 years Planned but not budgeted yet Source: AberdeenGroup, June 2006 AberdeenGroup 5

12 BI in the Back Office Retailers spend vast quantities of time and resources creating, updating, and analyzing corporate department budgets. These budgets are meant to be the bible that drives bottom-line results. Exception management of today s detailed capital and expense budgets is a challenge of wending one s way through mountains of data and information. Business intelligence has emerged as a critical method to conserve human resources while ferreting out misuse of financial resources. Best in Class retailers use BI in the back office to catch anomalies before they get out of hand. BI tools give financial managers instant visibility into expense patterns that would be otherwise detrimental to the bottom line. Customer Service, Productivity Drive BI Strategies Improving customer service was the most popular response to the question of retailer strategies for business intelligence (Figure 4). In addition, 57% of respondents indicated that customer management was the most important capability supported by BI. This increased focus on the customer is not surprising, considering the heightened importance of customer centricity within the retail enterprise. Indeed, BI s measurable, quantifiable effect on the retail enterprise may provide just the tipping point necessary for widespread industry adoption. Many recent AberdeenGroup research efforts echo these findings, including strategic actions retailers take to increase multi-channel data integration, and provide more efficient advanced planning and replenishment, and workforce management within retail. (See Appendix B). Figure 4: Customer Service Drives BI Utilization Strategic actions to utilize BI Improve customer service 52% Improve merchandise productivity 48% Improve promotions effectiveness 39% Raise average transaction value 31% Improve lifetime value of customers 31% Improve merchandise assortments 27% Improve our back office productivity Improve our in-store employee productivity 24% 23% 0% 10% 20% 30% 40% 50% 60% Source: AberdeenGroup, June AberdeenGroup

13 Best in Class More Invested in Business Intelligence Participants considered either Industry Average or Best in Class are finding their BI endeavors driven by top management, including C-level executives. These executives are using the data to, in best cases, make enterprise-level decisions, and in most enterprises, department-level. Gathering support for BI projects, and active support of those projects from top management, should be considered a major boon. Both Industry Average and Best in Class performers indicated spreadsheets as the single most popular way to view data from BI solutions. With a high level of engagement from the CEO level (Figure 5), it s curious that dashboards and portals are not more widely used as delivery devices for crucial enterprise- or department-wide analytics, given their more direct way of delivering crucial BI-related metrics. Figure 5: C-Level Executives are Getting Engaged in Business Intelligence Highest Level in Enterprise to Use BI Manager Director VP 6% 11% 10% 9% 11% 26% C-level (CEO, COO, CFO, CMO) 58% 70% 0% 10% 20% 30% 40% 50% 60% 70% 80% Best in Class Average Performers Source: AberdeenGroup, June 2006 Besides from having high levels of support from top management, Best in Class retailers distinguish themselves from other performers in many other ways. For example: Eighty percent of BIC use BI vs. 50% of Laggards. Sixty three percent of BIC see merchandise productivity as very important vs. 47% of Industry Average performers. Thirty two percent of BIC see store operations management as very important vs. 19% of Industry Average performers. Thirty two percent of BIC see cross-enterprise management as very important vs. 13% of Industry Average performers. AberdeenGroup 7

14 Seventy percent of BIC indicate C-level involvement in BI data management, vs. 58% for Industry Average performers and 50% of Laggards. Challenges and Responses Table 1 highlights the top retailer challenges and strategic responses. Considering how widespread the challenge of data cleansing is, it s not surprising to see this as a top retail challenge when it comes to BI. Retailers have been tackling this problem for years, and thus it remains an obstacle to retailers of all sizes and success levels. Equally unsurprising is the concern that retail executives are drowning in data. This phenomenon has also been a long-term obstacle, and proves that while retailers are good at collecting data, their analysis and decision-making skills need work. What is surprising, however, is the importance retailers place on organizations unwilling to use the information generated by the system. Perhaps the explanation to that challenge lies within the responses column, particularly with the need for executive management for change and bringing in outside help to change existing business processes. Table 1: Business Intelligence: Retailer Challenges and Responses Challenges % Selected Responses to Challenges % Selected Our data is not clean enough for analysis 56% Data cleansing projects to improve data quality 56% Data is scattered throughout the organization; not centralized 41% Executive mandates for change 47% We don t have enough customerspecific information to generate valid results 40% Our business processes do not lend themselves to making use of this information 39% We don t have enough time to make use of any more information. We are already drowning in data. 28% The use, integration, and complexity of the algorithms of these business intelligence engines is daunting 24% Our organization is unwilling to use the information generated by the system. 23% Bring in outside help to change business processes 41% Small projects in pilot departments to measure ROI 34% Select process areas that are easier to install with simpler algorithms 32% Select small cross-functional team to implement 29% Create data farms where disparate data can be stored 22% Source: AberdeenGroup, June 2006 To further understand this response, AberdeenGroup went back to the survey respondents, and inquired as to why. One executive responded: the business and IT departments cannot seem to prioritize the utilization of real-time or near real-time customer data. Business intelligence is essentially underused because the analytics and associated 8 AberdeenGroup

15 reports are not tied directly to the user experience. Uptime is easier to produce than true cross-selling. Another retailer, who disagreed with the hypothesis that BI, which includes predictive analytics, improves top- and bottom-line performance within the retail enterprise, commented: Extremely large companies (Safeway, Albertsons, WalMart, etc.) obtain information so massive they cannot interpret it on the micro level of the individual store that [it was] generated [from]. There is no communication between the information center and the store (I believe). The larger the organization, the harder and slower the information flow to the produce clerk and courtesy clerk, where it is needed for direct impact on the customer base. BI works on the macro side assisting in supply chain initiatives and programs. I believe, though, that on the micro side it does not aid the store manager in generating more revenues from specific customers. A third retailer commented Here in Brazil, we have a 'dilemma'. Our management board has no idea how powerful the information is. We have to do everything on an automation/integration [basis], responsible at the IT team [level]....so that is the reason for the confusion. We know how powerful BI is, but they (management board) do not care so much, they think in old fashioned ways... this kind of approach is more common than we think here. AberdeenGroup 9

16 Chapter Three: Implications & Analysis Key Takeaways For Best in Class retailers, BI is utilized at the enterprise level, and process is standardized company-wide, across all banners or store brands. Best in Class and Industry Average retailers have largely missed opportunities to make better decisions by viewing data on an ad-hoc basis. Best in Class retailers have proven themselves adept at monitoring retention within their enterprises as a traditional customer performance measurement. However, these same executives seemed a little unsure of themselves when it comes to measuring acquisition and conversion. A s shown in Table 2, behaviors and activities directly affect performance. Survey respondents each of the three Competitive Framework categories Laggard, Industry Average, or Best in Class exhibited different characteristics in five key categories: process (consistency across the enterprise); organization (corporate focus/philosophy, level of collaboration among stakeholders); knowledge (visibility into and timing of results); technology (scope of automation and productivity tools) and measurement (frequency of measuring performance). In each category, survey results show that firms exhibiting Best in Class behaviors and characteristics also enjoy Best in Class sales improvements: Table 2: Planning and Replenishment Competitive Framework Laggards Industry Average Best in Class Process Process is different for each store Process is consistent across departments Process is standardized company-wide, across all banners or store brands Organization Business intelligence programs, if existent, measure individual or departmental performance Business intelligence programs measure individual or departmental performance Business intelligence measures enterprise performance, enabling multi-departmental decisions to be made Knowledge Sales and receipt data reviewed on an ad hoc basis Business Intelligence data reviewed daily Business Intelligence data reviewed in near real-time Technology Business Intelligence data is driven through a spreadsheet or portal. Business Intelligence data is driven through a spreadsheet. Business Intelligence data is driven either through spreadsheets or a portal. 10 AberdeenGroup

17 Laggards Industry Average Best in Class Measurement Retention and conversion are not measured as a customer service indicator. New product adoption is not measured as a traditional customer buying behavior. Acquisition and retention are measured as customer service indicators. Product preferences/affinity, and promotion participation are tracked as traditional customer buying behaviors. Retention is measured as a customer service indicator. Product preferences/affinity, and promotion participation are tracked as traditional customer buying behaviors. Source: AberdeenGroup, June 2006 Process and Organization Business processes and organizational structures for business intelligence can clearly be associated with overall sales success levels. For the Best in Class, process is centralized enterprise-wide. For the average retailer, process is consistent across all departments. For the Best in Class, process has been organized in such a way as to take advantage of the promises of BI and correlate, to the best of their ability, one department s activities with another s. These observations are further supported by the overwhelming majority of Best in Class respondents (98%) who indicated widespread use of BI across the enterprise (Figure 6). Merchandise planning, distribution, store operations, customer experience, and multichannel selling efforts are all coordinated for increased visibility. Average performers also showed a lot of enterprise-wide performance ability, but slightly less then their Best in Class competitors. Figure 6: Best in Class Measure Performance at the Enterprise Level What is BI Used to Measure within Your Organization? Individual Performance 32% 30% Department Performance Enterprise performance 77% 73% 74% 98% 0% 20% 40% 60% 80% 100% 120% Best in Class Average Performers Source: AberdeenGroup, June 2006 AberdeenGroup 11

18 Data and Knowledge Opportunity Missed Only 15% of Best in Class and 7% of Industry Average retail respondents take the opportunity to review BI-related information in real- or near-real-time (Figure 7). This was a particularly surprising finding, given retailers objective to create a more dynamic and fast-moving supply network capable of interdepartmental data management processing. In terms of KPI measurement within the organization, Best in Class, Industry Average, and Laggard performers were mostly all in agreement that gross margin, comparable store sales by store, merchandise turn, customer retention, and comparable store sales by department were all widely used KPIs. Figure 7: Retailers Miss Opportunities to Use Their Data Time Frame for Measuring BI Data Week 23% 24% Day 43% 44% Real or near-real time 7% 15% 0% 10% 20% 30% 40% 50% Best in Class Average Performers Source: AberdeenGroup, June 2006 Technology Usage There is little doubt that, given the pressures retailers face and the strategies they contemplate, they recognize the need to move past spreadsheets as the tool of choice for business intelligence applications. However, retailers need to make much progress in this area. Thirty-eight percent of Best in Class respondents, compared with only 10% of Industry Average respondents, indicated spreadsheets as the primary delivery vehicle for delivering and analyzing BI data. Consumer Measurements Close but No Cigar The Best in Class have proven themselves adept at monitoring retention within their enterprises as a traditional customer performance measurement (Figure 8). However, executives at these same companies seemed a little unsure of themselves with acquisition and conversion. Measuring repeat is obviously an important part of understanding the customer base, but the need to have a grasp on new customers, and those who purchase different items at different times, must not be discounted. To their credit, Best in Class re- 12 AberdeenGroup

19 tailers showed more consistent attention to tracking customer buying behavior in terms of product preferences/affinity, promotion participation, and, to a lesser extent, new product adoption. Figure 8: Best in Class Excel in Customer Retention Measurement Efforts KPIs used within the organization Conversion 45% 55% Retention 37% 63% Acquisition 47% 53% 0% 10% 20% 30% 40% 50% 60% 70% Yes No Source: AberdeenGroup, June 2006 Pressures, Actions, Capabilities, Enablers (PACE) Aberdeen s research has consistently shown a clear relationship between the pressures companies identify and the actions they take, and their subsequent competitive performance. In other words, retailing excellence is not just an accident, a function of convenient store locations, or the result of a merchant with a hot hand. We encourage all readers to examine the prioritized PACE selections in Table 3. Comparing their own priorities to those of Best in Class retailers can provide valuable insight into performance improvement opportunities. Table 3: PACE (Pressures, Actions, Capabilities, Enablers) Priorities Prioritized Pressures Prioritized Actions Prioritized Capabilities Prioritized Enablers 1 Need for more rapid response to consumer demand Need for more rapid response to consumer demand Improve customer service Business intelligence software to manage customer management 2 Must become more operationally efficient Must become more operationally efficient Improve merchandise productivity Business intelligence software to manage merchandise planning AberdeenGroup 13

20 Priorities Prioritized Pressures Prioritized Actions Prioritized Capabilities Prioritized Enablers 3 Need to manage demand across multiple channels Need to manage demand across multiple channels Improve promotions effectiveness Business intelligence software to manage pricing 4 Must improve store performance 5 Must stem the tide of price deflation and eroding gross margins Must improve store performance Must stem the tide of price deflation and eroding gross margins Improve merchandise assortments Raise average transaction value Business intelligence software to manage store operations management Business intelligence software to manage crossenterprise management and scorecards Source: AberdeenGroup, June AberdeenGroup

21 Chapter Four: Recommendations for Action Key Takeaways Retailers of all sizes must focus on creating the right impetus for adoption and embracing the data generated by BI-related processes. Laggard retailers should build the business case for basic business intelligence investment, move to more frequent BI-related KPI measurements, and make retention, conversion, and acquisition measurements standard operating procedure. Industry Average retailers would be wise to understand what separates them from Best in Class retailers, and refocus on very important BI capabilities. Best in Class retailers would benefit from letting customer-centricity drive further BI investments and extend BI beyond merchandising and back-office operations. B usiness Intelligence, allocation, and replenishment are neither monolithic business processes, nor are they always supported by the same application vendor. Applications once considered advanced may be little more than glorified spreadsheets, and, as we have seen, many retailers don t even move past un-glorified spreadsheets to a commercial application. Different retail segments will find their own holy grails in building better decision-making and inter-departmental communications capabilities, but in all cases, several pertinent recommendations apply: Create the right impetus for adoption. The first item on the to do list for any retailer using or considering using BI is to establish the value proposition. Take the time to understand the state of data usability within your enterprise, consider the state of interdepartmental communications, and decide how BI would benefit the organization. Chances are, if BI is implemented correctly, better business decisionmaking would be an immediate by-product. Move beyond spreadsheets and slow data collection. Many respondents of all sizes and success levels indicated widespread use of spreadsheets to analyze BI data. This result was surprising, given the widespread availability of dashboards and other portals that make data analysis much more accessible. Executive-level support for BI has proven itself strong, but this support may quickly falter if better presentation methods are not employed more rapidly. Embrace the data generated by the system. Twenty-three percent of respondents indicated that their organizations are unwilling to use information generated by business-intelligence-related technology. Whatever the outcome of this technology on the enterprise, it should AberdeenGroup 15

22 at least be given the chance to improve a company s inter-departmental communications as the ROI for BI is evaluated. Whether a company is trying to gradually move from Laggard to Industry Average, or Industry Average to Best in Class, the following actions will help spur the necessary performance improvements: Laggard Steps to Success 1. Build the business case for basic business intelligence investment. Fifty percent of Laggard respondents indicated that they do not use business intelligence anywhere within their enterprises. This presents them with a great opportunity to study the potential business benefits of BI. Fortunately, Laggard respondents indicated a strong desire to plan for BI within the near future, including merchandise and back office operations. 2. Move to more frequent BI-related KPI measurements. Thirty-three percent of Laggard respondents indicated that they measure data only on an ad-hoc basis, compared with only 9% of Best in Class respondents. Measuring data without a formal, repetitive plan prevents good data comparison. Obviously, the more you measure, the better decision you can make. At a minimum, however, the measurements should be regular. 3. Make retention, conversion, and acquisition measurements standard operating procedure. Laggard respondents made it clear that measuring retention, conversion, and acquisition is not a priority. On the contrary, understanding as much as possible about customer behavior can help improve decision-making all throughout the enterprise. Understanding and measuring these metrics should be crucial. Industry Norm Steps to Success 1. Understand what separates Best in Class behavior from all others. In this study, we have shown that the Best in Class have made major strides toward adopting enterprise-wide BI practices. For Industry Average companies, close attention to Best in Class practices is a crucial next step. A near-equal number of Industry Average respondents indicated use of BI within their enterprise compared with the Best in Class (79% and 80%, respectively). Now, Industry Average retailers must fully utilize their BI infrastructures to move to the next level. 2. Refocus on very important BI capabilities. Sixty three percent of Best in Class retailers recognize the importance of merchandise productivity as very important, vs. 47% of average performers. Similar comparisons were found in the categories of store operations and crossenterprise management. Industry Average retailers must make sure these categories, and others like them, are given the full attention they deserve when it comes to BI-related software capabilities. 16 AberdeenGroup

23 Best in Class Next Steps 1. Let customer-centricity drive further BI investments A majority of Best in Class retailers surveyed are actively using BI within their enterprises and reaping the rewards this software produces. As time goes by, however, Best in Class retailers must avoid stalling as their investments continue. To do this, tying BI-related ROI to quantitative customer centric benefits will provide a strong impetus for further investments in decision-facilitating technologies. 2. Extend business intelligence beyond merchandising and back-office operations. Merchandising and back office processes came across as the two most popular uses of BI among all respondents. But for Best in Class retailers, the focus of BI should not be limited to these specific niches of the enterprise. Instead, the entire business should benefit from good interdepartmental communications. Customers will continue to reward retailers that satisfy their expectations, just as they will not hesitate to drive one more block to get a product they can t find at your store. The trick to winning this game and keeping customers loyal is to make smart decisions company-wide. A big part of any promised return to customer centricity is to have the right product on the shelf when the customer wants it. The bar will only get higher. AberdeenGroup 17

24 Author Profile Greg Belkin Research Analyst Retail Research AberdeenGroup, Inc. As a research analyst, Greg Belkin analyzes how Best-in-Class retailers and their trading partners are utilizing effective IT-based processes to satisfy the needs of the consumer. His studies give executive insight into strategies that empower the consumer to receive just enough product at the right location at the right time at the right price, and at the peak of product usefulness. His current research is focused on how automated workforce management and other customer-centric technologies are empowering retail executives to better serve their customers. Greg brings to Aberdeen over six years of international editorial and research experience covering best-practice process and technology within the retail industry. Prior to joining Aberdeen Group, Greg was editor of Retail Systems Alert Group s Supply Chain Alert, a monthly publication focused on effective business-to-business supply chain collaboration. In addition, Greg worked in the U.K. as editor and head of U.K. publications for Retail Systems Alert Europe. Between 2004 and 2005, Greg was Retail Systems Alert Group s research manager. Greg holds an M.B.A. from Suffolk University in Boston, Massachusetts, and is a member of Beta Gamma Sigma, the honor society serving business programs accredited by AACSB International. He also holds a B.A. from The George Washington University in Washington, DC.. 18 AberdeenGroup

25 Appendix A: Research Methodology B etween March and May 2006, AberdeenGroup examined the business intelligence practices, initiatives, procedures, experiences, and intentions of more than 150 retailers. Responding executives completed an online survey that included questions designed to determine the following: Methods of business intelligence-related deployment and management within the organization (Business intelligence is defined as using data to harness the power of massive customer and transaction data warehouses into a set of manageable performance metrics); Current and planned use of various applications defined as advanced by their use of sophisticated mathematical algorithms; and Business challenges and pressures these retailers face that drive adoption of new initiatives. Our intention was to determine whether and how each of the above created competitive advantage for retailers that use them and a disadvantage for those that do not. From there, we identified emerging best practices and provided a framework by which readers could assess their own capabilities and ways to improve effectiveness. Responding enterprises included the following: Job Titles/Functions: The research sample included respondents with the following job titles: Senior management, including CEOs, CFOs, CEOs and CIOs (32%), Vice Presidents (7%); directors (17%), managers (27%) and internal consultants and staff (9%). Functional areas represented included planning, allocation and/or replenishment, merchandising, logistics, finance, information technology, marketing, product development, and others. Retail Segments: The research sample included respondents from across the retail spectrum. Fast-moving consumer goods companies represented 33% of the respondent base, including supermarket, convenience stores, chain drug, and warehouse stores. More than 51% were from general merchandise and apparel, including large and small footprint specialty stores, mass merchandisers, and department stores. The other 19% came from hardware and do it yourself, furniture, and restaurant and hospitality. Geography: Fifty-three percent (53%) of respondents were from North America, including the U.S., Canada, and Mexico. Twenty-three percent (23%) were from Europe, the Middle East and Africa; and 20% were from the Asia/Pacific region. Remaining respondents were from South and Central America and the Caribbean (5%). AberdeenGroup 19

26 Company Size: About 29% of respondents were from large enterprises (annual revenues more than $1 billion); 39% were from mid-size enterprises (between $50 million and $1 billion); and 33% from small businesses ($50 million or less). Solution providers recognized as sponsors of this report were solicited after the fact and had no substantive influence on the direction of Business Intelligence in Retail: Bringing Cohesion to a Fragmented Enterprise. Their sponsorship has made it possible for AberdeenGroup to make these findings available to readers at no charge. Table 4: PACE Framework PACE Key Aberdeen applies a methodology to benchmark research that evaluates the business pressures, actions, capabilities, and enablers (PACE) that indicate corporate behavior in specific business processes. These terms are defined as follows: Pressures external forces that impact an organization s market position, competitiveness, or business operations (e.g., economic, political and regulatory, technology, changing customer preferences, competitive) Actions the strategic approaches that an organization takes in response to industry pressures (e.g., align the corporate business model to leverage industry opportunities, such as product/service strategy, target markets, financial strategy, go-to-market, and sales strategy) Capabilities the business process competencies required to execute corporate strategy (e.g., skilled people, brand, market positioning, viable products/services, ecosystem partners, financing) Enablers the key functionality of technology solutions required to support the organization s enabling business practices (e.g., development platform, applications, network connectivity, user interface, training and support, partner interfaces, data cleansing, and management) Source: AberdeenGroup, June AberdeenGroup

27 Table 5: Relationship between PACE and Competitive Framework PACE and Competitive Framework: How They Interact Aberdeen research indicates that companies that identify the most impactful pressures and take the most transformational and effective actions are most likely to achieve superior performance. The level of competitive performance that a company achieves is strongly determined by the PACE choices that it makes and how well it executes. Source: AberdeenGroup, June 2006 Table 6: Competitive Framework Competitive Framework Key The Aberdeen Competitive Framework defines enterprises as falling into one of the three following levels of retail practices and performance: Laggards Retail practices that are significantly behind the average of the industry, and result in below average performance Industry norm Retail practices that represent the average or norm, and result in average industry performance. Best in Class Retail practices that are the best currently being employed and significantly superior to the industry norm, and result in the top industry performance. Source: AberdeenGroup, June 2006 AberdeenGroup 21

28 Appendix B: Related Aberdeen Research & Tools Related Aberdeen research that forms a companion or reference to this report include: The Proactive Merchant: Anticipating Consumer Demand (December 2004) The Empowered Store Benchmark Report: Delighting Customers, Motivating Employees, and Pleasing Shareholders (September 2004) The Empowered Point of Service Benchmark Report: The Customer Regains Her Kingdom (June 2005) The Business Benefits of Advanced Planning and Replenishment (December 2005) Perspective: Retail Business Intelligence Drives Top and Bottom Line Growth (March, 2006) Customer Intelligence Management Benchmark Report: Converting Data to Profits (December, 2005) Chasing the Holy Grail: A Unified Planning Process for Retailers (February 2005) Information on these and any other Aberdeen publications can be found at 22 AberdeenGroup

29 About AberdeenGroup Our Mission To be the trusted advisor and business value research destination of choice for the Global Business Executive. Our Approach Aberdeen delivers unbiased, primary research that helps enterprises derive tangible business value from technology-enabled solutions. Through continuous benchmarking and analysis of value chain practices, Aberdeen offers a unique mix of research, tools, and services to help Global Business Executives accomplish the following: IMPROVE the financial and competitive position of their business now PRIORITIZE operational improvement areas to drive immediate, tangible value to their business LEVERAGE information technology for tangible business value. Aberdeen also offers selected solution providers fact-based tools and services to empower and equip them to accomplish the following: CREATE DEMAND, by reaching the right level of executives in companies where their solutions can deliver differentiated results ACCELERATE SALES, by accessing executive decision-makers who need a solution and arming the sales team with fact-based differentiation around business impact EXPAND CUSTOMERS, by fortifying their value proposition with independent fact-based research and demonstrating installed base proof points Our History of Integrity Aberdeen was founded in 1988 to conduct fact-based, unbiased research that delivers tangible value to executives trying to advance their businesses with technology-enabled solutions. Aberdeen's integrity has always been and always will be beyond reproach. We provide independent research and analysis of the dynamics underlying specific technologyenabled business strategies, market trends, and technology solutions. While some reports or portions of reports may be underwritten by corporate sponsors, they never influence Aberdeen's research findings. AberdeenGroup 23

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31 AberdeenGroup, Inc. 260 Franklin Street, Suite 1700 Boston, Massachusetts USA Telephone: Fax: AberdeenGroup, Inc. All rights reserved June 2006 Founded in 1988, AberdeenGroup is the technologydriven research destination of choice for the global business executive. AberdeenGroup has over 100,000 research members in over 36 countries around the world that both participate in and direct the most comprehensive technology-driven value chain research in the market. Through its continued fact-based research, benchmarking, and actionable analysis, AberdeenGroup offers global business and technology executives a unique mix of actionable research, KPIs, tools, and services. The information contained in this publication has been obtained from sources Aberdeen believes to be reliable, but is not guaranteed by Aberdeen. Aberdeen publications reflect the analyst s judgment at the time and are subject to change without notice. The trademarks and registered trademarks of the corporations mentioned in this publication are the property of their respective holders.