Retail Business Intelligence Accelerator (RBIA)

August 2009

Business Intelligence (BI) and the retail market

Business Intelligence/Data Warehouse (BI/DW) is moving from being seen as a support system to a “mission critical” application in Retail. Retailers are looking beyond reporting capabilities to applications that synthesize information from a wide variety of systems and analyze performance — of sales, margin, supplier delivery times, promotions effectiveness —allowing them to react more effectively to business insights. AMR research shows that the most strategic software investment between 2008 and 2010 is BI/Performance management (figure 1).

Key retail BI trends:•Retailerscontinuetomovefromstatic/periodicreporting

to dynamic understanding of business- predictive analytics and actionable insights

•Customersegmentation,marketbasketanalysisandanalytical dashboards will continue to gain popularity among top subject choices as BI focus for retailers (Please see Appendix A figure 5).

Figure 1: Most strategic software investment in 2008 and 2010

•Ascustomer-centricretailingbecomesakeydifferentiator for many retailers, BI will help break-out customer data from the silos of marketing to also include merchandising and stores operations.

•BIuserbaseisgoingbeyondthetraditionalseniorexecutives and analysts to operational managers, workers and even to external business partners (Please see Appendix A figure 6).

However, BI adoption barriers and challenges still remain

Top adoption barriers:•Highcostofthesolutionandimplementation•LackoftopmanagementcommitmenttoBIinitiatives•LackofITresourcesorbandwidthforimplementingBI

solutions

Top BI challenges:•Lackofcompletecustomerdata(45%ofrespondents)•Datanotcleanenoughforanalysis(43%ofrespondents)•Lackofcentralizeddataanddataintegrationchallenges(41%ofrespondents)

8

10

11

13

13

16

9

7

19

10

9

15

SCM

Manufacturing ops.

BI/Performance mgmt.

Gov, Risk mgmt., and compliance

ERP

Customer management

2010 2008

Figure: 1.0 Most strategic software investment in 2008 and 2010

Source: AMR Research, 2008

20%

Retail Business Intelligence Accelerator

Helping retailers get on the fast track to quick thinkingDynamic changes in purchasing trends are challenging the retail industry not only to satisfy customers but also to remain profitable. In today’s retail environment, gauging consumer demand and responding to it effectively requires companies to change their approach to information management and business intelligence. Deloitte’s Retail Business Intelligence Accelerator (RBIA) is an end-to-end offering designed to quickly equip retailers with the insight needed to enhance customer satisfaction and improve competitive positioning.

The data dilemma: Out-of-date and out-of-touchMany retail companies are finding that their current-state information environments are not sufficient to produce the rapid insight needed to keep pace with their customers and to make informed business decisions.

For instance, traditional processes and technologies, such as static reports based on lagging metrics, do little to support the “anything, anytime, and anywhere” model that is now expected by consumers. Typical information repositories from which historical reports are drawn are not time-sensitive enough to capture business opportunities. Furthermore, business leaders often struggle with reconciling “many versions of the truth” because the repositories contain information collected from disparate, non-integrated systems. This frequently leads to a morass of spreadsheets, disputes among the business units over the correctness of the data, and perhaps most alarming, poor decision-making and failure to satisfy customers.

Disparate, aging legacy systems and historical data repositories create other concerns too: •Retailersmustknowtheircustomers.Leadingretailers

segment their customers based on demographics, buying patterns, and profitability in order to indentify opportunities, yet many legacy systems are unable to provide these types of analytical capabilities.

•Aretailer’ssuccessdependsuponeffectiveleadership,a supportive culture, efficient processes, and successful executionofbusinessstrategy.Companiesneedtobe

able to measure the effectiveness of their initiatives across these areas in order to manage performance. This requires meaningful KPIs and dynamic access to enterprise data, which is often not possible with older non-integrated operating systems.

•Alongwithreportingandintelligencecomeissuespertaining to security and protection of the business’s intellectual property. Thought must be given to how, where, and to whom information and insights are delivered. With large amounts of data being disseminated, enterprise-wide security standards and practices must be established and enforced to prevent lossorunauthorizeddistributionofinformation.Legacysystems often do not feature robust security capabilities like many of today’s leading enterprise applications do.

•Dataqualityisavitalsuccessfactorindataacquisitionand profiling; however, aging, disparate operating systems and historical data repositories create issues when it comes to cleansing, aligning, calibrating, relating, and integrating with syndicated data. Often, atomic attributes and time dimensions are missing, making it nearly impossible to integrate with new sources of information. Poor data quality and lost data can cost the company money in terms of lower productivity, faulty business decisions, and an inability to achieve results from Business Intelligence (BI) technology investments.

•Amore-subtle,butstillsignificant,concerninvolveschanges to historical business rules within operating systems. Many companies are unable to track the adjustments that have been made to attributes and relations over time because there have been too many rule changes without audit trails. Old historical stores of operational data may even be missing due to lack of data retention and synchronization across operating systems or because of new products or upgrades.

•Manyretailersoperatewithalargenumberofhistoricaldata stores, which naturally raises issues concerning ballooning hardware and software requirements. The cost of disk storage is also a concern as the amount of data increases. In turn, this growing complexity frequently correlates with poor system-performance and slower user response times.

Asusedinthisdocument,“Deloitte”meansDeloitteConsultingLLP,asubsidiaryofDeloitteLLP.Pleaseseewww.deloitte.com/us/aboutforadetaileddescriptionofthelegalstructureofDeloitteLLPanditssubsidiaries.

•Gobeyondthebasicsofdirectmarketingtocorrelatecustomer data with product assortment, space planning, and channel preference for a more-personalized customer experience.

•Minecustomerdatatounearthhiddenbuyingandusagepatterns across channels.

•Establishenterprise-levelperformancemetricsandKPIsto support the company’s strategic objectives.

•Providereal-timeinformationvisibilityacrosstheenterprise, including insight into demand patterns within and across channels.

•Supplyusersthroughouttheorganizationwithself-service access to actionable information and insights.

Figure3:Deloitte’sRetailBusinessIntelligenceAccelerator

Distinctive components of RBIARBIA is built upon a framework of value-based methodologies and tools, including Deloitte’s Retail EnterpriseValueMapandEnterpriseInformationMethodology. These tools help retailers to examine their end-to-end information challenges — spanning business processes, data, people (change management), and the adoptionandintegrationofnewtechnologies.Evenmore,they assist companies in their efforts to determine the shortest path forward for leveraging their information assets to generate shareholder value.

The RBIA offering

Leading Retail KPI & Metrics repository and Retail Business

Analytics

BI Strategy & Roadmap

Implementation and

deliveryBI/DW/OBIEE

training

BI/DWtechnical

infrastructure

Datagovernance

Master data management

ChangemanagementDeloitte’s Retail Business Intelligence Accelerator offers a

means to address this broad range of challenges. RBIA is an end-to-end business intelligence and data warehouse (BI/DW) offering composed of consulting services, delivery support, and preconfigured prototypes. The RBIA offering, which is appropriate for retailers within any sector, is supported by Oracle’s Retail Data Model (ORDM), which is based on the retail standard reference data model as established by the Association for Retail Technology Standards(ARTS).ORDMofferstheflexibilityandtemplatesto include key performance indicators (KPIs), business intelligence reports, and dashboards along with advanced analytics and data-mining reports (figure 2).

The RBIA offering incorporates the industry knowledge, experience, and business insights of Deloitte practitioners and is supported by Oracle’s leading technology platform. By leveraging this combination, it provides a customizable BI/DW solution that supports a company’s ability to analyze customer trends while reducing the cost and time required for implementation.

More specifically, the RBIA offering assists retailers in their efforts to: •Collectandconsolidatecustomerdatafromacrossthe

enterprise to create a single view of the customer. •Recognizecustomerinteractionsacrossvarioustouch

points and channels to better understand shopping behavior.

Figure 2: Oracle Data Model — “Out-of-Box”

Subject areas Example – AnalyticOracle Retail Data Model includes

Store operations Traffic patterns, comparative store performance, what sells vs. what doesn’t

Point of sale POS flow, shopper conversion, transaction value, time of day, entry method, time series, trend

Loss prevention “Sweetheart” deals, outliers for return/discount

• Data Model with 650+ tables and 10,500+ attributes• Industry specific 1,200+ Measures & KPI• Pre-built 15+ OLAP cubes• Pre-built 12+ Mining Models• Complete Intra ETL database packages shrinkage, employee-basket analysis, trend

Merchandising Item-basket, product ‘stars’ & ‘dogs’, frequent item mix, GMROS, cluster item traits, trend

Inventory Sales anomalies — out-of-stock, zero selling, forecast and score, time series, supplier scorecard

W kf M AUS AVS UPT i i

• Complete Intra ETL database packages• Well-defined interfaces• Sample reports & Dashboard using OBIEE• Sample IBM 4690 POS Adapter

Workforce management Measures — AUS, AVS, UPT, prescriptivedeployment, SPIFF and Split, Plan vs. actual

Order management Channel volume, web commerce and interactions, fulfillment performance, customer order analysis

Customer Segment — formation, migration, analysis, price elasticity, RFMP, churn model, trendB y, , ,

Category management Assortment/product mix, clustering, Plan-o-gram, customer purchase vs. syndicated data, trend

Promotion Causal factor, lift, halo impact, predictive response model, predictive cross-sell

DB

Retail Enterprise Value MapTheRetailEnterpriseValueMap(EVM)isapractical,one-page management framework, designed from a client’s point of view that shows the relationship between shareholder value and business operations. It helps the professionals and clients organize, discuss, and prioritize improvement opportunities that deliver maximum value in terms of revenue growth, operating margin, asset efficiency, and market expectations of future growth.

Overall,EVMfocusesontherightthingsandservesasa graphic reminder of what should be done and why. In Figure4,themapcanbeusedinmanyways:focusingframe work, program planning, selling, and leading discussions.Figure4:EVMinRelationtoORDMavailableKPI’s

The above tools are further supported by the work of Deloitte’sOracleTechnologyNetworkandSolutionNetwork(SNET)organizations.Theseorganizationsprovide pre-configured, intranet-based environments for demonstration and learning purposes. ThroughSNET,prospectivecustomerscanexperiencedemonstrations of ORDM. At present, one environment presents out-of-the-box reports and another features custom reports and is used primarily by Deloitte practitioners to build additional reporting capabilities. Additional environments that demonstrate how ORDM can integrate with other reporting applications are currently in progress.

Branding &Marketing

Products &Services Assortment Mix

CustomerRelationshipManagement

Order to Delivery

Management

SalesTransaction

(Cross-Sell,Up-Sell, Customer

Orders)

Rationalize &/orrefocus product or service assortment

Improvemerchandise or serviceassortment to meet customer demand

Alignassortment with high value customersegments

Align breadth of product &serviceofferings to customerneeds

Change focus to high-value/high-potentialcustomers

Focus on relationshipswith high potential lifetime valuecustomers

Increaseemphasis on customerrelationshipdevelopment

Segmentcustomers by potential lifetime value

Increase focus on likely cross-sell/up-sellcustomers

Increase focus on most profitableproducts &services

Increase focus on expansion of customerrelationships

Reducefulfillment order to delivery cycle time

Prioritize back order allocation

Focus on high value/highpotentialcustomers

Focus on high value orders

Sales Volume

Increase focus on product innovation &product &serviceleadership

Target new segments within currentgeographies

Targetpromotions to new customer segments

Improve Merchandising Effectiveness

Improve Customer Relationships

RevenueGrowth

% contributionvalues of Sales Category

% ofcustomerretention by category

FrequencyScore Detail

CorrectEstimatedDelivery Date Calculation

No Match

CustomerShoppingfrequency

Back order amount detail by period

Customer by City , State

No Match

Sales value byDemography

Sales profit amount detail by customer

Number of Vouchersissued by customer

Customeranalysis and shoppingbehaviour

No Match

No Match

No Match

Inventoryanalysis and stock and hand

Inventoryanalysis and Stockmovement

The Deloitte differenceDeloitte has been successfully implementing global Oracle solutionssince1992.AsanOracleCertifiedAdvantagePartner(CAP),thehighestlevelofpartnership,Deloitte’sOracle practice has grown worldwide, developing deep industry and functional knowledge, including extensive experience in the retail sector.

Based on this experience, Deloitte recognizes that there is more to resolving retailers’ data dilemma than implementing new reporting technology. In order for retailers to obtain sound business intelligence, they need to develop an information strategy that treats data as an asset. This strategy should include plans for a scalable technical architecture and address synchronization of current and future operational systems. There is also a need to develop standards for data governance, which should be jointly formulated by IT and management.

Deloitte member firms have capabilities in business consulting; IT advisory; governance, risk and compliance; performance management; tax; finance; HR; and change management — as well as systems implementation. This makes Deloitte one of the few professional services providers that can assist retailers with the full gamut of business intelligence issues, spanning the collection and management of customer data to the creation of an enterprise-wide information strategy.For more informationData is not just a byproduct of transactions; it is an indispensable asset. And like any asset, it must be valued across the enterprise and managed for maximum return on investment. To find out more about the RBIA offering and how it can help you in your efforts to extract more value fromthedatainyouroperatingsystems,pleaseContact:

Moris ChemtovDirector,DeloitteConsultingLLP+14048624673mchemtov@deloitte.com

AppendixIntheareaofCustomer,ODWRcantrackcustomersegmentation, be it formation or migration across segments. ODWR basket analysis analyzes both frequent shoppers and anonymous customers leveraging data mining clustering algorithms.

Figure5:Out-of-BoxSampleminingreportsaroundtopsubjects

Copyright©2010DeloitteDevelopmentLLC.Allrightsreserved.MemberofDeloitteToucheTohmatsuLimited

ORDM also comes with 10 major business areas that could provide multiple BI capabilities within the business area. For instance, customer subject area provides customer segmentation and customer basket analysis (Product Mix) capabilities. It also provides the capability of data mining, such as loyalty analysis and customer category mix. Figure6:ORDMOut-of-BoxSamplereport