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Building AnAnalyticalRoadmap : A RealLife ExampleDr Ahmed KhamassiChief Data Scientist & PrincipalConsultant1 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
The Issue Environment: 2 OutcomesBig data analytics is probably going tobe remembered as a technological, ifnot, an industrial revolution Paralysis by analysis Many customers do not knowwhere to start? New technologies are rolling off theassembly line daily They keep revisiting the sameissues over and over again New terminologies and approaches What matters seems to changes quitefrequentlyThe delve into technologicalquestions before answering thewhat and why questions. I hear stories from my competitors,am I behind? Do I need this stuff?Many organise several ‘vendor’contests without a clear endinsight How do I know which are the newopportunities these technologiesallow me to win? They lack coherent approachthat leads to faster results They involve either too many ortoo few stakeholders Skills are short Which skills do we need anyway? How do we organise them? How do we ensure we are compliant?Where do I start and howdo I plan for big dataanalytics? 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
Establishing An Analytical CapabilityBusiness Layer Principles: Analytics is a businessoutcome enabler It bridges commercialmanagement and ITexpertise There are four layers tobe brought togethersuccessfullyWhat needs to be optimised, prioritisation, alignment with overall strategy,process changes etc.Analytical LayerHow analytics supports business objectives, how they are achieved, businesscase, partnerships with business Outcomes The Capabilities Layer Avoid delving intotechnological questionsbefore answering thewhat and why questions. A coherent approach thatleads to faster results 3Adopt a methodologythat ensures focus onbusiness prioritiesInvolve all stakeholdersand experts.The expertise required to enable new analytical based processes, skills, scaleetc.Technology LayerTechnologies required to enable data science & analytical capability, currentestate assessment, addressing gaps and establishing, operating models. 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
The Situation The Organisation A Multi-national, multi-brand retail company Some CRM data Some digital data The vision We would like to catch up with competitors Gather and manager data properly Harness the power of analytics to manage customer lifecycle Our baseline is low The issue4 Where do we start? We did several vendor and technology rounds We realise it is not just technology 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
Business Layer: Optimize Not Just Measure KPIExample: Customer Lifecycle ManagementKey Questions: which keyperformance areas tofocus on What needs to beoptimised for each KPI How will businessprocesses change? How will newprocesses be adopted?Key CLM performance areasOptimization Opportunities1Drive existing customerrevenue growth Share of wallet maximisation Basket size increase Cross-sell rate increase2Reduce cost of customeracquisition and retention Attrition rate reduction Lifetime value optimisation3Identify right set of customersto acquire and target channel Response rates by channelmaximisation Customer lifetime value shift totop end4Increase loyalty of customers Increase % of transactions onloyalty card Increase purchase frequency5 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
The Analytical Layer: Horizontal CapabilitiesCustomer ValueAnalyticsTo Meet BusinessObjectives: Translate businessstrategy into big dataanalytics strategy –answer: Which key horizontalcapabilities to build? How to build themovertime? Organisationalchoices? Investments? Business analytics,elasticitymodelling,dynamic pricingetc.Cross sell-upselloptimisation,loyalty ,optimisation utionsProduct StrategyCustomer ServicePreference andfactor onsistentexperience acrosschannel,anticipate andpredict needs 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
The Capabilities Layer: Enable What best can we do?Optimization Prescription of best choice amongsta complex web of optionsPredictive Modeling Modelling targeted to enabledecisionsInformationDescriptive ModelingWhat will happen? Describe historical event Insights in inference and causalityInsights/Limited What-if Multi-dimensional querying Basic scenario analysisOLAP Reporting Drill-thru Drill-AcrossWhat happened?Basic DataStandard Reporting7 Comp Sales Sell-thruRaw Data Product, Sales, Inventory,CustomerDecision SupportDecision Guidance 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL7
Technology Layer: Limiting OptionsTo enable utilisationof analyticalcapabilities: How to provide andmanage the data? How to enable datascience and analyticalexperts? How to democratiseanalytics with endusers? How to reduce time tovalue and integratewith businessapplications?8Data ManagementVisualisation- Data collection & creation- Executive dashboards- Data integration, mashing- Granular drill down- Information management- Real time transactional- Scaling- Train of thought- Physical storage & cloud options- Sharing & collaborationTechnologyRoadmapData Science- From simplest to mostsophisticatedIntegration- From concept to production- In-house vs. service- Enabling business processes anddownstream business applications- Scale, variety & complexity- Collecting feedback- Time to market- Time to marketKnowledge capture- Operating models & governance 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
Establishing An Analytics BusinessLayerTasks91.2.3.4.1. Business PartnershipEstablish business prioritiesCreate support & urgencyCreate partnership structureAlign organisation3.4.2. Analytics Value GenerationUnderstand business problemsTranslate business problems into analyticalproblemsAssess and organise capabilitiesManage quality and business processes1.2.3.4.3. Capability: Data Science ExecutionExplore, transform and generate dataTranslate business knowledge into signalsModel, deploy, monitor, disseminate etc.Provide insights to business1.2.3.4.4. Technology EnablersData ManagementAnalytics – development & deploymentDissemination – self-service analytics & BIEnterprise nersRoadmapCreation1.2.3.1. PrioritisationLOBs willing to investIdentify their prioritiesEstimate business caseAnalyticsBusinessPartners2. Horizontal Capabilities1. Maturity analysis2. Capabilities needed3. Investments & plans4. Business case creationDataScienceManager3. Building Capabilities1. In-house vs. partnershipsplit2. Resourcing & technicalrequirementsIT SponsorsIT Owners 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL1.2.3.4. Platform BuildingArchitectural designTechnology selectionTechnologyimplementation plans
Suggest Organisation StructureBusinessOwnerBusinessOwnerBusinessOwnerIT Sponsor(CIO)AnalyticsBusinessPartnerCapability LeadershipBusinessSponsor(CXO)Analytics LeadershipOperating alyticsBusinessPartnerCustomer Value ManagementSupply Chain AnalyticsPromotion & Demand AnalyticsDataScienceVisualisationData & EIOperating Model, Governance, AssuranceIT Owner10IT Owner 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIALIT Owner
Analytical Roadmap: A project PlanTechnological StageCapability StageTasks: Analytical StageTasks: Translate objectives intoanalytical requirements Create high level solutiondesignBusiness StageTasks: Understand businessstrategies and objectives Business process & maturityassessments Shortlist areas of focus andestimated returnsOutput A shortlist of possibleinitiatives with clearboundaries and objectivesOwners Analytical Business Partners Business Owners11 Determine technical &scientific toolsData readiness analysis Fix technology evolutionDraw horizontal capability roadmapstrategyOutputOutput Estimate investments & Technologicalreturns – Business cases Technology strategy &requirementstimelines Finalise shortlist Skills strategy including Investment business caseservice procurementOutput Final focused shortlist Implementation roadmap Vendor recommendation Data science operating Owners Horizontal capabilitymodelselection IT OwnersOwners Business cases Analytical BusinessPartners Analytical BusinessOwnersPartners Data Science Manager Analytical Business IT ownersPartners Data science manager Business Owners Identify main priorities & painpointsTasks: Draw detailed executionroadmap Build skills & expertisestrategyConduct technologymaturity assessmentCarry out technology gapanalysisWrite technologyrequirementsAgree vendor strategyAgree cloud Strategy 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
Final Outcome: A Comprehensive Plan1. A roadmap for the analytical components basedon business prioritisation and synergies2. A multidimensional sequentialproject plan where each phasedetails new implementations of:a. Platform and technologiesb. Data & governancec. Skills & Capabilitiesd. Business outcomes12 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
Thank YouDr Ahmed KhamassiChief Data Scientist & PrincipalConsultantAhmed.khamassi@wipro.com13 2014 WIPRO LTD WWW.WIPRO.COM CONFIDENTIAL
Data Science Manager 3. Capability: Data Science Execution 1. Explore, transform and generate data 2. Translate business knowledge into signals 3. Model, deploy, monitor, disseminate etc. 4. Provide insights to business 4. Technology Enablers IT Sponsors 1. Data Management 2. Analytics
