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Real Analytics: Retail Business Intelligence Accelerator

Real Analytics: Retail Business Intelligence Accelerator



Business Intelligence/Data Warehouse (BI/DW) is moving from being seen as a support system to a "mission critical" application in retail.

Business Intelligence/Data Warehouse (BI/DW) is moving from being seen as a support system to a "mission critical" application in retail.



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    Real Analytics: Retail Business Intelligence Accelerator Real Analytics: Retail Business Intelligence Accelerator Document Transcript

    • Retail Business Intelligence Accelerator (RBIA)August 2009
    • Business Intelligence (BI)and the retail market Business Intelligence/Data Warehouse (BI/DW) is moving • As customer-centric retailing becomes a key from being seen as a support system to a “mission critical” differentiator for many retailers, BI will help break-out application in Retail. Retailers are looking beyond reporting customer data from the silos of marketing to also include capabilities to applications that synthesize information merchandising and stores operations. from a wide variety of systems and analyze performance • BI user base is going beyond the traditional senior — of sales, margin, supplier delivery times, promotions executives and analysts to operational managers, effectiveness —allowing them to react more effectively workers and even to external business partners (Please to business insights. AMR research shows that the most see Appendix A figure 6). strategic software investment between 2008 and 2010 is BI/Performance management (figure 1). However, BI adoption barriers and challenges still remain Key retail BI trends: Top adoption barriers: • Retailers continue to move from static/periodic reporting • High cost of the solution and implementation to dynamic understanding of business- predictive • Lack of top management commitment to BI initiatives analytics and actionable insights • Lack of IT resources or bandwidth for implementing BI • Customer segmentation, market basket analysis and solutions analytical dashboards will continue to gain popularity among top subject choices as BI focus for retailers Top BI challenges: (Please see Appendix A figure 5). • Lack of complete customer data (45% of respondents) • Data not clean enough for analysis (43% of respondents) • Lack of centralized data and data integration challenges (41% of respondents) Figure 1: Most strategic software investment in 2008 and 2010 Figure: 1.0 Most strategic software investment in 2008 and 2010 Customer management 15 16 ERP 9 13 Gov, Risk mgmt., and 10 compliance 13 BI/Perf ormance mgmt. 19 11 Manuf acturing ops. 7 10 SCM 9 8 20% 2010 2008 Source: AMR Research, 2008
    • Retail Business IntelligenceAcceleratorHelping retailers get on the fast track to quick thinking able to measure the effectiveness of their initiativesDynamic changes in purchasing trends are challenging across these areas in order to manage performance.the retail industry not only to satisfy customers but also to This requires meaningful KPIs and dynamic access toremain profitable. In today’s retail environment, gauging enterprise data, which is often not possible with olderconsumer demand and responding to it effectively requires non-integrated operating systems.companies to change their approach to information • Along with reporting and intelligence come issues management and business intelligence. Deloitte’s Retail pertaining to security and protection of the business’sBusiness Intelligence Accelerator (RBIA) is an end-to-end intellectual property. Thought must be given tooffering designed to quickly equip retailers with the insight how, where, and to whom information and insightsneeded to enhance customer satisfaction and improve are delivered. With large amounts of data beingcompetitive positioning. disseminated, enterprise-wide security standards and practices must be established and enforced to preventThe data dilemma: Out-of-date and out-of-touch loss or unauthorized distribution of information. Legacy Many retail companies are finding that their current-state systems often do not feature robust security capabilitiesinformation environments are not sufficient to produce the like many of today’s leading enterprise applications do.rapid insight needed to keep pace with their customers • Data quality is a vital success factor in data acquisition and to make informed business decisions. and profiling; however, aging, disparate operating systems and historical data repositories create issuesFor instance, traditional processes and technologies, such when it comes to cleansing, aligning, calibrating,as static reports based on lagging metrics, do little to relating, and integrating with syndicated data. Often,support the “anything, anytime, and anywhere” model atomic attributes and time dimensions are missing,that is now expected by consumers. Typical information making it nearly impossible to integrate with newrepositories from which historical reports are drawn sources of information. Poor data quality and lostare not time-sensitive enough to capture business data can cost the company money in terms of loweropportunities. Furthermore, business leaders often struggle productivity, faulty business decisions, and an inability towith reconciling “many versions of the truth” because the achieve results from Business Intelligence (BI) technologyrepositories contain information collected from disparate, investments.non-integrated systems. This frequently leads to a morass • A more-subtle, but still significant, concern involves of spreadsheets, disputes among the business units over changes to historical business rules within operatingthe correctness of the data, and perhaps most alarming, systems. Many companies are unable to track thepoor decision-making and failure to satisfy customers. adjustments that have been made to attributes and relations over time because there have been too manyDisparate, aging legacy systems and historical data rule changes without audit trails. Old historical storesrepositories create other concerns too: of operational data may even be missing due to lack• Retailers must know their customers. Leading retailers of data retention and synchronization across operating segment their customers based on demographics, systems or because of new products or upgrades. buying patterns, and profitability in order to indentify • Many retailers operate with a large number of historical opportunities, yet many legacy systems are unable to data stores, which naturally raises issues concerning provide these types of analytical capabilities. ballooning hardware and software requirements. The• A retailer’s success depends upon effective leadership, cost of disk storage is also a concern as the amount a supportive culture, efficient processes, and successful of data increases. In turn, this growing complexity execution of business strategy. Companies need to be frequently correlates with poor system-performance and slower user response times.As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of the legal structure of Deloitte LLP and its subsidiaries.
    • The RBIA offering Oracle Retail Data Model includes Subject areas Example – Analytic • Go beyond the basics of direct marketing to correlate • Data Model with 650+ tables and 10,500+ attributes Store operations Traffic patterns, comparative store performance, customer data with product assortment, space planning, • Industry specific 1,200+ Measures & KPI what sells vs. what doesn’t • Pre-built 15+ OLAP cubes Point of sale POS flow, shopper conversion, transaction value, and channel preference for a more-personalized time of day, entry method, time series, trend • Pre-built 12+ Mining Models Loss prevention “Sweetheart” deals, outliers for return/discount customer experience. • Complete Intra ETL database packages • Well-defined interfaces shrinkage, employee-basket analysis, trend • Mine customer data to unearth hidden buying and usage Merchandising Item-basket, product ‘stars’ & ‘dogs’, frequent item • Sample reports & Dashboard using OBIEE mix, GMROS, cluster item traits, trend patterns across channels. • Sample IBM 4690 POS Adapter Inventory Sales anomalies — out-of-stock, zero selling, forecast and score, time series, supplier scorecard • Establish enterprise-level performance metrics and KPIs Workforce management W kf Measures — AUS AVS UPT prescriptive M AUS, AVS, UPT, i i deployment, SPIFF and Split, Plan vs. actual to support the company’s strategic objectives. Order management Channel volume, web commerce and interactions, • Provide real-time information visibility across the fulfillment performance, customer order analysis Customer Segment — formation, migration, analysis, price enterprise, including insight into demand patterns within elasticity, RFMP, churn model, trend y, , , and across channels. DB B Category management Assortment/product mix, clustering, Plan-o-gram, customer purchase vs. syndicated data, trend • Supply users throughout the organization with self- Promotion Causal factor, lift, halo impact, predictive response model, predictive cross-sell service access to actionable information and insights.Figure 2: Oracle Data Model — “Out-of-Box” Change Deloitte’s Retail Business Intelligence Accelerator offers a management Leading Retail means to address this broad range of challenges. RBIA is KPI & Metrics an end-to-end business intelligence and data warehouse repository and (BI/DW) offering composed of consulting services, delivery Master data Retail Business management Analytics support, and preconfigured prototypes. The RBIA offering, which is appropriate for retailers within any sector, is Data BI Strategy & supported by Oracle’s Retail Data Model (ORDM), which governance Roadmap is based on the retail standard reference data model as established by the Association for Retail Technology BI/DW Implementation Standards (ARTS). ORDM offers the flexibility and templates technical and infrastructure BI/DW/ delivery to include key performance indicators (KPIs), business OBIEE intelligence reports, and dashboards along with advanced training analytics and data-mining reports (figure 2). Figure 3: Deloitte’s Retail Business Intelligence Accelerator The RBIA offering incorporates the industry knowledge, experience, and business insights of Deloitte practitioners Distinctive components of RBIA and is supported by Oracle’s leading technology platform. RBIA is built upon a framework of value-based By leveraging this combination, it provides a customizable methodologies and tools, including Deloitte’s Retail BI/DW solution that supports a company’s ability to Enterprise Value Map and Enterprise Information analyze customer trends while reducing the cost and time Methodology. These tools help retailers to examine their required for implementation. end-to-end information challenges — spanning business processes, data, people (change management), and the More specifically, the RBIA offering assists retailers in their adoption and integration of new technologies. Even more, efforts to: they assist companies in their efforts to determine the • Collect and consolidate customer data from across the shortest path forward for leveraging their information enterprise to create a single view of the customer. assets to generate shareholder value. • Recognize customer interactions across various touch points and channels to better understand shopping behavior.
    • Retail Enterprise Value Map The above tools are further supported by the work ofThe Retail Enterprise Value Map (EVM) is a practical, Deloitte’s Oracle Technology Network and Solution one-page management framework, designed from a Network (SNET) organizations. These organizations client’s point of view that shows the relationship between provide pre-configured, intranet-based environments forshareholder value and business operations. It helps the demonstration and learning purposes.professionals and clients organize, discuss, and prioritize Through SNET, prospective customers can experience improvement opportunities that deliver maximum value demonstrations of ORDM. At present, one environmentin terms of revenue growth, operating margin, asset presents out-of-the-box reports and another featuresefficiency, and market expectations of future growth. custom reports and is used primarily by Deloitte practitioners to build additional reporting capabilities.Overall, EVM focuses on the right things and serves as Additional environments that demonstrate how ORDM cana graphic reminder of what should be done and why. In integrate with other reporting applications are currently inFigure 4, the map can be used in many ways: focusing progress.frame work, program planning, selling, and leadingdiscussions.Figure 4: EVM in Relation to ORDM available KPI’s Revenue Growth Sales Volume Improve Customer Improve Merchandising Relationships Effectiveness Sales Transaction Order to Customer (Cross-Sell,Up- Delivery Relationship Branding & Products & Sell, Customer Management Management Marketing Services Assortment Mix Orders) Increase focus Focus on high Frequency Segment on likely cross- value/high customers by Customer by Change focus to Customer Align breadth Rationalize &/or Score Detail sell/up-sell No Match potential potential lifetime City , State high-value/high- analysis and of product & refocus product customers customers value potential shopping service No Match or service No Match customers behaviour offerings to assortment Increase focus Customer Focus on customer Focus on high Shopping needs on most % contribution value orders relationships Sales value Target new Improve profitable values of Sales frequency with high by segments within Sales profit merchandise or Inventory products & Category Reduce potential lifetime Demography current amount detail Increase focus service by customer on product services fulfillment order Correct value geographies innovation & assortment to analysis and to delivery cycle Estimated customers product & meet customer stock and hand Increase focus % of time demand customer Delivery Date Target Number of service No Match on expansion of Calculation Increase promotions to customer retention by Vouchers leadership category emphasis on new customer issued by relationships No Match Align Prioritize back customer segments customer assortment with Inventory order allocation Back order relationship analysis and amount detail development high value customer Stock by period movement segments
    • The Deloitte difference AppendixDeloitte has been successfully implementing global Oracle In the area of Customer, ODWR can track customer solutions since 1992. As an Oracle Certified Advantage segmentation, be it formation or migration acrossPartner (CAP), the highest level of partnership, Deloitte’s segments. ODWR basket analysis analyzes both frequentOracle practice has grown worldwide, developing deep shoppers and anonymous customers leveraging dataindustry and functional knowledge, including extensive mining clustering algorithms.experience in the retail sector. Figure 5: Out-of-Box Sample mining reports around top Based on this experience, Deloitte recognizes that subjectsthere is more to resolving retailers’ data dilemma thanimplementing new reporting technology. In order forretailers to obtain sound business intelligence, they needto develop an information strategy that treats data as anasset. This strategy should include plans for a scalabletechnical architecture and address synchronization ofcurrent and future operational systems. There is also aneed to develop standards for data governance, whichshould be jointly formulated by IT and management.Deloitte member firms have capabilities in businessconsulting; IT advisory; governance, risk and compliance;performance management; tax; finance; HR; and changemanagement — as well as systems implementation.This makes Deloitte one of the few professional servicesproviders that can assist retailers with the full gamut ofbusiness intelligence issues, spanning the collection andmanagement of customer data to the creation of anenterprise-wide information strategy.For more informationData is not just a byproduct of transactions; it is anindispensable asset. And like any asset, it must be valuedacross the enterprise and managed for maximum return oninvestment. To find out more about the RBIA offering andhow it can help you in your efforts to extract more valuefrom the data in your operating systems, please Contact:Moris ChemtovDirector, Deloitte Consulting LLP+1 404 862 4673mchemtov@deloitte.com
    • ORDM also comes with 10 major business areas that couldprovide multiple BI capabilities within the business area.For instance, customer subject area provides customersegmentation and customer basket analysis (Product Mix)capabilities. It also provides the capability of data mining,such as loyalty analysis and customer category mix.Figure 6: ORDM Out-of-Box Sample reportCopyright © 2010 Deloitte Development LLC. All rights reserved.Member of Deloitte Touche Tohmatsu Limited