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Success Stories in Building a GlobalData StrategyDonna BurbankManaging Director, Global Data Strategy Ltd.Enterprise DATAVERSITY, November 4th, 2015
Donna Burbankconsulting company that specializes inthe alignment of business drivers withdata-centric technology. In past roles,she has served in key brand strategy andproduct management roles at CATechnologies and EmbarcaderoTechnologies for several of the leadingdata management products in themarket.She has worked with dozens of Fortune500 companies worldwide in theAmericas, Europe, Asia, and Africa andspeaks regularly at industryconferences. She has co-authored twobooks: Data Modeling for theBusiness and Data Modeling MadeSimple with CA ERwin Data Modeler r8.She can be reached atdonna.burbank@globaldatastrategy.comDonna is based in Boulder, Colorado,USA.As an active contributor to the datamanagement community, she is a longtime DAMA International member and isthe President of the DAMA RockyMountain chapter. She was also on thereview committee for the ObjectManagement Group’s InformationManagement Metamodel (IMM) and amember of the OMG’s FinalizationTaskforce for the Business ProcessShe is currently the Managing Director at Modeling Notation (BPMN).Global Data Strategy, Ltd., aninternational information managementFollow on Twitter @donnaburbankDonna is a recognized industry expert ininformation management with over 20years of experience in datamanagement, metadata management,and enterprise architecture. Herbackground is multi-faceted acrossconsulting, product development,product management, brand strategy,marketing, and business leadership.Global Data Strategy, Ltd. 20152
AgendaWhat we’ll cover today Aligning with Business Motivations & Drivers Components of a Global Data Strategy Case Studies International Telcom companyInternational Pharmaceutical companyConsumer Energy companyProfessional Development & Certification organizationGlobal Data Strategy, Ltd. 20153
Aligning with BusinessMotivation & DriversWhy are we doing this, anyway?4
How can we Transform the Business through Data? Optimization: Becoming a Data-Driven Company Making the Business More Efficient Better Marketing Campaigns Higher quality customer data, 360 view of customer, competitive info, etc. Better Products Data-Driven product development, Customer usage monitoring, etc. Better Customer Support Linking customer data with support logs, network outages, etc. Transformative: Becoming a Data Company Changing the Business Model via Data – data becomes the product Monetization of Information: examples across multiple industries including: Telcom: location information, usage & search data, etc. Retail: Click-stream data, purchasing patterns Social Media: social & family connections, purchasing trends &recommendations, etc. Energy: Sensor data, consumer usage patterns, smart metering, etc.Global Data Strategy, Ltd. 20155
The Motivation ModelCommon Set of Goals & Guidelines There is benefit in formally documenting the motivations for the project. Commonly-agreed upon guidelines for project tasks & deliverables Reminder of “why we’re doing this” - Neutral arbitrator for disagreements Components of the Motivation Model include: Corporate Mission: describes the aims, values and overall plan of an organization. e.g. To be provide the most comprehensive, customer-driven online shopping experience in the market Corporate Vision: describes the desired future state e.g. To transform the way consumers purchase goods through social-media-driven connections. External Drivers: What market forces are driving this initiative? e.g. Cultural shift to online retail Internal Drivers: What internal pressures or initiatives are key for this project? e.g. Disparate systems require need for an integrated view of customer Project Goals: high level statement of what the plan will achieve. e.g. To improve customer satisfaction with over 90% satisfaction rating in 2 years. Project Objectives: outcome of projects improving capabilities, process, assets, etc. e.g. To link consumer purchase history with social media activity.Global Data Strategy, Ltd. 20156
Sample Business Motivation ModelArtful Art SuppliesCorporate MissionArtfulArtCorporate VisionTo provide a full service online retail experience To be the respected source of art products worldwide,creating an online community of art enthusiasts.for art supplies and craft products.External DriversDigital Self-ServiceOnline Community &Social MediaInternal Drivers Corporate-level Mission & VisionMay already be created or mayneed to create as part of project.Project-level, Data-Centric DriversExternal Drivers are what you’refacing in the industryInternal Drivers reflect internalcorporate initiatives.IncreasingRegulation PressuresTargeted Marketing360 View ofCustomerRevenue Growth Customer Demandfor Instant ProvisionBrand ReputationCommunity BuildingCost Reduction CGoals & ObjectivesAccountability Create a Data GovernanceFramework Define clear roles &responsibilitiesC for bothbusiness & IT staff Publish a corporateinformation policy Document data standards Train all staff in dataaccountabilityQuality Define measures & KPIs forkey data items Report & monitor on dataquality improvementsC Develop repeatableprocesses for data qualityimprovement Implement data qualitychecks as BAU businessactivitiesGlobal Data Strategy, Ltd. 2015Culture Ensure that all rolesunderstand theircontribution to data quality Promote business benefitsC qualityof better data Engage in innovative waysto leverage data forstrategic advantage Create data-centriccommunities of interest Project-level, Data-Centric Goals& ObjectivesClear direction for the projectUse marketing-style headingswhere possible7
From Cruise Ship to Life RaftWith a common motivation, disparate skills, personalities and roles become anasset, not an annoyanceGlobal Data Strategy, Ltd. 2015
Roles & Culture DBAs, Data Managers and Executives are different creaturesData ManagersDBAs AnalyticalStructuredCautiousDoesn’t like to talkProject & Task focused“Just let me code!”Global Data Strategy, Ltd. 2015 AnalyticalStructuredPassionateLikes to Talk“Big Picture” focused“Let me tell you about my data model!”Business Executive Results-Oriented“Big Picture” focusedLittle Time“How is this going to help me?”“I don’t care about your data.”“I don’t have time.”
Components of a GlobalData StrategyWhere do we start?10
DAMA DMBOK FrameworkIndustry Best-Practices & Guidelines The DAMA Data Management Body of Knowledge(DMBOK) is a helpful guideline to follow for industrybest practices Modeled after other BOK documents: PMBOK (Project Management Body of Knowledge) SWEBOK (Software Engineering Body of Knowledge) BABOK (Business Analysis Body of Knowledge) Outlines core data management functions: Data Architecture ManagementData DevelopmentDatabase Operations ManagementData Security ManagementReference & Master Data ManagementData Warehouse & Business Intelligence ManagementDocument & Content ManagementMeta data ManagementData Quality Management Data Governance is the central “hub” which controlsthe various functionsGlobal Data Strategy, Ltd. TMETA T SECURITYMANAGEMENTDATAWAREHOUSE& BUSINESSINTELLIGENCEMANAGEMENTREFERENCE &MASTER DATAMANAGEMENT
Building an Enterprise Data StrategyA Successful Data Strategy links Business Goals with Technology Solutions“Top-Down” alignment withbusiness prioritiesManaging the people, process,policies & culture around dataLeveraging & managing data forstrategic advantageCoordinating & integratingdisparate data sources“Bottom-Up” management &inventory of data sourcesGlobal Data Strategy, Ltd. 201512
Case StudiesWhat’s worked in thereal world?13
The Importance of “Right-Sizing” your Data StrategyThe Right Data Strategy Depends on a Number of Factors The following case studies illustrate examples from a variety of organizations From a large international telcom To a small professional development organization There are many common elements required by any organization Alignment with business motivation & drivers Core data management fundamentals (data quality, metadata, etc.) While some elements are unique based on size & scale of organization Global inventory needed for large international firm Geographic considerations: legal, cultural, technological, etc. Smaller organizations often need to be more tactical in their approachGlobal Data Strategy, Ltd. 201514
International Telcom CompanyBusiness Transformation to “Becoming a Data Company” An international telcom company was looking to leverage data as a corporate asset. Data is seen as their most strategic asset and corporate focus Telecommunications is a secondary goal – becoming a commodity Opportunities in Leveraging Big Data New Product & Service Development Data is Anonymized & sent to digital arm for new product and development Data-driven prototyping – using analytics to see what products are working best and used most Customer Value Management Marketing with Opt-in, e.g. ads for bolt-on roaming when enter a new country—before they use a competitorplatform Sentiment Analysis (via call logs & social media) Operational Performance & Maintenance Network Optimization Integrating call failure information and location information with survey data Monetization Resell anonymized data to Retail, City Planners, etc. Footfall with integrated geospatial location dataGlobal Data Strategy, Ltd. 2015
The Motivation Model Motivations from bothBusiness & IT Business focused ongaining value from data IT focused on costsavings & reuse Common Goals &Objectives Use Case Patterns Clear definition of BigData (& what it’s not) Common Service Catalog Reusable Technology &ArchitectureGlobal Data Strategy, Ltd. 2015
Categorization of Big Data Use Cases Extended interviews were conducted with stakeholders worldwide Demand patterns were categorized into the following groups:Customer ValueManagementOperational AnalyticsProducts and ServicesInnovationData MonetizationCustomer ExperienceOptimisationNetwork AnalyticsKPI Reporting – DeviceAnalyticsNetwork Usage PatternsCustomer InsightStorage MonitoringTroubleshootingFootfall AnalyticsConsumer MarketingData Centre MonitoringSentiment Analysis(Social Media)Family IdentificationGlobal Data Strategy, Ltd. 2015Product & Service UsagePatterns
Use Case Model The Use Case Model Categorizes existing demandworldwide Provides a “heat map” of usagepatterns Particularly important for large,geographically distributed teams& departments. Privacy & Legal issues alsodiffered by country.Global Data Strategy, Ltd. 2015
Establishing Project Governance: Big Data Usage “Checklist” A questionnaire was provided to: Provide education & guidance onproper use cases for Big Data (in thiscase Hadoop) Establish governance criteria forapproving use cases for the platform A subset of this questionnaire is shownhere. Etc.Global Data Strategy, Ltd. 2015
New Operating Model:Interactions Between New & Existing RolesExisting RolesNew RolesAlignmentPrivacyAnalystData ArchitectNetworkAdministratorETL DeveloperGlobal Data Strategy, Ltd. 2015Data ScientistHadoopAdministrator
Roles & ResponsibilitiesRolesHadoopAdministratorNetwork ArchitectHadoop DeveloperData ScientistETL DeveloperResponsibilities Deploy, configure, monitor & tune Hadoop clusterAdd and remove nodesCapacity monitoringConfigure & manage schedulingManage memory, CPU, OS, & storage Hadoop infrastructureLinuxJava or related programming skills Architects network requirements for the Hadoop service (latency,capacity, availability, etc.) Networking architectureNetworking engineering Implements Hadoop components within the frameworkWrites MapReduce code for analysis, data movement scripts, etc. Hadoop framework & components (e.g. MapReduce, Pig, Hive, etc.)LinuxJava or related programming skills Builds statistical modelsUnderstands business requirementsDiscovers new patterns & insights from data Statistical analysisProgrammatic knowledge in MapReduce codingBusiness knowledge of data Understands sources and targets for data, and requirements fortransformation & movementChooses fit-for purpose ETL solution based on BI stack and/orHadoop stackCreates ETL scripts/code within the Hadoop ecosystem and/or BIecosystem Knowledge of source and target data systemsHadoop ETL components e.g. MapReduce, Flume, Sqoop, Hive, Pig,etc.SQL and relational technologiesBI ETL components, e.g. Ab Initio, ODI Knowledge of source data systemsSQL and relational technologiesBusiness knowledge of data Privacy regulations within the organizationGovernmental privacy regulations Data ArchitectSkills Organizes, aggregates, and structures the data to ensure it can beusefully queried in appropriate timeframes by all users. Understands and communicates privacy policies around data bothgovernmental & within the companyApproves data sharing policiesPrivacy Analyst Global Data Strategy, Ltd. 2015
The ResultsNew Insights from Integrated Big Data & Traditional Sources Results of this Data Strategy included: New insights & increased value from data as a corporate assetBetter alignment between BI and Infrastructure teamsImproved education & governance for Big Data use casesClearer understanding of value propositions for Big Data and BINewInsightsGlobal Data Strategy, Ltd. 2015
Data Strategy – International TelcoCovering most areas of the Strategic Framework w/ Focus on Big Data, BI, & Analytics“Top-Down” alignment withbusiness priorities driven by BigData Use CasesGovernance & policies around fitfor use technology. Roles definedfor current & future staffing.Analytics & BI were a key driverfor the initiative.Asset inventories & “heat maps”were crucial for integration.Management of disparate datasources was key.Global Data Strategy, Ltd. 201523
International Pharmaceutical CompanyBusiness Alignment and IT Strategy An international Pharmaceutical company was looking to make better use of its data tostreamline its Clinical Development, Commercial Processes, and R&D. Business alignment was a key first step Created “blueprints” of how the business runs—then how data maps to that”Data models, process models, & mappingsIdentified opportunities for business efficienciesGreater understanding how data was used by and critical to key business activities Streamlining IT Services was a core parallel activity Solution Planning & Definition Defining “who we are & what we do” , aka “Marketing” Best Practices & Architecture New best practices around MDM, data modeling, etc. Governance Models & architecture required for each new projectGlobal Data Strategy, Ltd. 201524
Business-Driven “Blueprinting” Detailed “blueprints” (aka models) outlined several views of the organization.Business ViewKeyBold Purple text – PTS accountabilityGreen – Not sure if in PTSLight Blue – Key interfacesCommit to TargetPTS DiscoveryDeveloping target knowledgeExploratory disease basedresearchCreate/identify chemicallibrariesInformaticsCommit to CandidateStart of Chemistry toCandidate SelectionHigh throughput screeningHuman geneticsCreation of pharmacological &animal modelsGenomicsDisease geneticsInformation from clinicalgeneticsFunctional analysisVaccines/biological targetsCreate physical form biological or chemicalextraction/synthesis ofactive substance atlaboratory scale (mg ofmaterial)Q1. Does PTS include biopharm ? No, butBiomarkers for predictivePTS doesdo work for them. Need tomedicineclarify BP interfaces on wave.Q2. Don’t IP acquisition & partnershipactivities occur across many phases?N1. Both DD & PTS contribute to theCandidate Selection document.Q3. When are patents filed?BP: Target for Biopharmdevelopment acceptedResearchMake the medicineCommit toProduct DevelopmentFirst Time in Human to Proofof Concept (Phase I & IIa)Basic enzyme/ receptorpotency and selectivityBP: Target validation, Initiatebiomarker and immunoassaydevelopmentIn vitro/In vivometabolism,pharmacological andpharmacokineticscreening of potentiallyactive compoundsSalt/polymorph definition &scale upComplete campaign for 28day toxicology studies &FTIH clinical studiesDevelop analytical methodsfor API and release batchesLead tractabilityBP: Humanise MAb/DabgenerationAnalytical characterisation of drug substance (ActivePharmaceutical Ingredient; API)Small scale synthesis of API (grams) for dose-rangingtoxicology studiesDevelop route to provide dose ranging & 28 day toxicologysuppliesDefine predictive medicine agent characteristicsDevelop formulation for FTIHand prepare clinical suppliesDevelopment of analyticalmethodology for stabilitytesting of dosage formsSynthesis of radiolabelledcompounds forpharmacokinetic studiesSelection of technologyplatforms for biomarkers inpredictive medicineBP: Cell line and processdevelopment,Acute toxicityinitiate– singleproductionof materialsadministrationto two fortoxicologyand early clinical trialanimalspeciesAPI and Drug ProductDesign Targets finalisedDrug Product Definition forCommercial Supply & pivotalClinical Trials, incl.formulation, process andpackaging materialsPreparation of API for midphase toxicology andclinical studies.API final synthetic routeand crystallisationselectedPreparation of API for longterm oncology studies andPhase III supplies using finalroute (or biosynthetic route)Preparation of drugproduct clinical suppliesSite of manufacture forpivotal clinical, regulatorystability and commercialproduct selectedStability testing of API anddrug productIntellectual Propertyevaluation and applicationBiomarkers assaydevelopmentBP: Finalise & transfermanufacturing process,compatibility andcomparability studies;manufacture materials forlong term toxicity studiesBP: 1st Molecular Design to evaluate DevelopabilityPRECLINICAL DEVELOPMENT Dose range findingSafetyTest the medicineOpportunity mappingMedicalDefine Target Product ProfilePerform clinical trialsInitial profile identificationOpportunities to changemedical practice throughuse ofpharmacogenetics andapplied diagnosticsIntegration of researchinvestment with long-termcommercial goalsRegulatoryRegister the medicinePreliminary metabolismAssay developmentPreliminarygenotoxicityScreening toxicityHigh throughput screeninggenotoxicityin vivo toxicologyselection studiesInvestigativetoxicogenomicsDefinition of clinical options forprogression to proof of concepttoxicology Formal repeatdose toxicity studies(medium duration) in twospeciesPharmacokinetics:absorption, distribution,metabolism & elimination(ADME)Evaluation of surrogates forearly clinical trialsEvaluation of potentialbiomarkers for use in predictivemedicineOutline Clinical DevelopmentPlanLong-term toxicity studiesBP: Tissue cross reactivity,Presentationof datarepeatdose toxstudies,safetydevelopment,review prior toPK/PDassayclinical evaluationstudiesIdentify current and future unmet needs: patients, prescribers, payors,regulatorsSelect (genetic)biomarker fordevelopment inpredictive medicineVOLUNTEERSTUDIES PHASE I(20 volunteers)Safety and tolerability inhealthy volunteers- highest tolerable dose- smallest effective dose- mode of action- dose/effect relationship- duration of effect- side effects- QTc drug interaction studyPharmacokinetics in manPreparation ofdossiers/ summarydocuments of allrelevant data andclinical trials protocolfor application tolicensing authority toconduct clinical trials(CTX/IND)VALUE PROPOSITIONIn-licensingProduction of pivotal ClinicalTrials drug product,including placeboManufacturing processscale-up strategy defined,incl. waste treatment &recycling measuresChange and Late-stage RiskManagement commencedChronictoxicity – repeatBP: Manufacturingcampaignadministration(long term)for Phase III materialsusingfinal process in final site.ContinuinganimalConfirm supplychainpharmacology studiesFile ( Approval,Reimbursement & Launch)Life CycleManagementContinuingresearch intothe diseaseProduct & Process understandingCommencement of validation of definedmanufacturing processes for API anddrug product at sites of manufactureNDA/MAA batch stability confirmed forAPI and drug product in final packagingManufacture of drug product forongoing clinical suppliesDevelopment, validation and finalisationof QC methodology and specifications(control strategy)First controlled trials in patientsto establish proof of concept indication of efficacy & clinicalbenefitConfirmation of safetybioavailability & bioequivalenceof different formulationsDevelopment of clinical geneticsdatabasesEvaluation of biomarkers forpharmacogenetics and applieddiagnosticsEvaluation of surrogatesOrdering, scheduling andproduction of the API andthe final drug product, incl.packaging and productliteratureTransfer to maturesupplyQuality control for releaseof commercial API anddrug productProduct & processperformanceverified, includingQC methodologyand specifications(control strategy)Validation for launch ofproduct & manufactureprocess validation batchesInitial design development for newmanufacturing plant initiated (if required)Design and preparation of packagingmaterialsLine extensionopportunitiesPHASE IVPHASE IIIBInternational large-scale multi-centretrials with different patient populations todemonstrate proof of safety and efficacy- initiate health outcomes studiesExpand disease and product knowledge- Use of predictive medicine agents inprognosis and diagnosis- Validation of surrogate markers andpharmacogenetic testsEstablishment of the therapeuticprofile/product labelling claims:- indications- dosage and routes of administration- contra-indications- side effects- precautionary measuresPaediatric development plans(or waivers)Evaluation of potential productdifferentiatorsRegulatory approvalEnd of Phase II /for biomarkers,Scientific Advisorysurrogates etcmeetings- Regulator adviseDraft summary ofon Phase III plansproduct characteristics& labellingExternal Clinical trialsreporting registerCTX/CTA variations /IND amendmentsOngoing Changeand RiskManagementDistribution ofproductsOncogenicity studiesReproductivetoxicology studies- peri-postnatalCLINICAL TRIALS PHASE III(1000 volunteers)CLINICAL TRIALSPHASE II(50 volunteers)BP: Early clinical studiesmay be in patients ratherthan volunteersDevelopment of broadRegulatory strategiesPROFILE OPTIMISATION8-10 year horizonIndication assessment and prioritisationDefine target product profile and fit with disease area strategyPricing and reimbursement environment analysis and trendsFuture competitive landscapeIdentify drivers of treatment decisionsAssess future treatment trends, pivotal trials, guideline changesPrepare early economic model and burden of diseaseExternal Expert identificationGlobal forecast and scenarios with value driversCommit toFile and LaunchPhase IIIReproductive toxicologystudies- fertility & embryo foetalDetailed safetypharmacology studies(CVS, CNS and othermajor systems)Genotoxicity studiesMedical development strategy- differentiation- evidence basedCommercialMarket the medicineSupport the productCommit toPhase IIIProof of Concept to Committo Phase III (Phase IIb)PTS CommercialDevelopment of diagnostics for personalised medicinesDESIGN FOR MANUFACTUREConfirm molecule is developableTechnicalIdentifying, defining andvaluing disease areas5 - 15 year horizonPotential for predictivemedicine in disease diagnosisMake range of leadcompounds screen againsttargetsPreliminary safetypharmacology andpharmacokineticsPre-formulation studies to determine formulationconstraints and possibilitiesDiscover the moleculeDiseaseOpportunityAssessmentApproval forFirst Time in HumanCandidate selection toFirst Time in HumanPTS DevelopmentPatent strategydevelopmentValidation of hits by rescreeningCreate robust (screen) assaysIntellectual Property acquisitionand Partnership activitiesMapping Data to ProcessSlide 7Product Discovery, Development, Reimbursement, Marketing and SupplyStart of ChemistryTarget toStart of ChemistryTarget identificationPTS DiscoveryData ViewProcess ViewDemonstration oftherapeutic advantage,e.g. vs. competitorsHealthcare Outcomes- Quality of Life- pharmacoeconomicsDevelop communicationspublication strategy (e.g.congresses & workshops)Knowledge transfer tooperating companiesUtilization ofpharmacogeneticsPhase IV commitmentsTrials in support ofMarketingNew line extensionsPharmacovigilence &post-marketingSurveillanceInitiate long-termsafety/health outcomesstudiesAnswering questions onsubmissionsNew Line Extensionapprovals- new formulations- new indicationsPreparation for Advisory- label changesmeetingsREGISTRATION WITH GOVERNMENTLICENSING AUTHORITIESDocumentation of all relevant datafor submission for registration(MAA/NDA)- expert opinion on clinical trialsresults- expert opinion on toxicological& pharmacological data- expert opinion on analytical,pharmaceutical & chemical dataLAUNCH OPTIMISATIONAdvance predictivemedicineNew IndicationsFurther comparative trialswith competitor productsSummary of productcharacteristics/labellingAnnual safetyreporting toRegulatorsLicense renewalprocessesRisk managementassessmentPharmacogenetics andapplied diagnosticsNew marketsPossibleconversion toOTCGenericsRETURN MAXIMISATION3-8 year horizon1-3 year horizon1-10 year horizonDraft scientific advantage and differentiation strategyDraft and evaluate core claims, message elementsDevelop market access value propositionSet pricing and reimbursement targetsCommission primary market research to support decision-making and insight generationRefine asset profile and label requirementsEngage regions to gain input to payor, prescriber, patient perspectives across regionsPrepare detailed forecasts and assumptions with regionsDefine strategic options for clinical development and gain senior management agreement for progressionDevelop Scientific Communications, publications, PR strategiesBegin External Expert advisory boardsDraft Health Outcomes plan and begin trialsObtain and register generic nameDefine market shaping strategyAgree countries, sequence to file and launchRegions and local operating companies take lead- Regional message development, including communications plansDetailed launch planning and promotional strategy developmentCampaign development and testingSales force and resourcing decisionsLocal pricing and reimbursement negotiationsHealth outcomes data definedForm local operating company launch teamsSet distribution strategyRegister trade namesCongresses and External Experts plans implementedLaunch plan executionLocal operating companies sales and marketingimplementationMonitor performanceReview and revise promotional campaignsPR & issues managementIndication assessment and prioritisationLine extensionsEnhance labelSupport Intellectual propertyKey:API: Active Pharmaceutical Ingredient(Version 4, Aug-06)BP:Biopharmaceuticals (i.e. indicating where Biopharm activities (or their timing) differs from small molecule developmentVersion 8: Oct08 Motivation Model Business Capability Models Solution Planning High-Level Process Models Detailed Process ModelsGlobal Data Strategy, Ltd. 2015 Conceptual Data ModelsBusiness GlossaryLogical Data ModelsPhysical Data Models Process to Data Mapping Process to System & Data Mapping
Solution Planning & “Marketing” A Solution Planning effort was undertaken to: Clearly define services provided by IT Architecture Communicate and “Market” these services to the wider organization Integrated into a clearly-defined Project Governance Model1Clearly Define & Promote Services3Global Data Strategy, Ltd. 20152Map Services to SpecificCapabilities & OfferingsIntegrate into Project GovernanceArchitecture a stage gate for every project26
Roles & Culture Business Acceptance: Clinical Scientistshad data models on their office walls “Blueprints” describing their clinicaldevelopmentGlobal Data Strategy, Ltd. 2015 Architecture team had clear direction “Who we are and what we do” clearlyarticulated to the business Best Practices for data management madeprocesses more efficient Governance driving architecture as a “musthave” for each new initiative.27
Data Strategy – International Pharmaceutical CompanyStrong focus on Business Alignment, Architecture & Governance“Top-Down” alignment withbusiness priorities via data &process modelingGovernance driven by solutionplanning & architecture at theproject levelData Architecture & Modelingplayed a key roleMetadata captured via datamodels & glossaries.Relational databases were mainfocus of this effort.Global Data Strategy, Ltd. 201528
Consumer Energy CompanyBusiness Transformation via Data For the consumer energy sector Big Data and Smart Meters are transforming the ways ofdoing business and interacting with customers. Moving away from traditional data use cases of metering & billing. Smart meters allow customers to be in control of their energy usage. Control over energy usage with connected systems Custom Energy Reports & Usage Smart Billing based on usage times As energy usage declines, data is becoming the true business asset for this energy company. Monetization of non-personal data is a future consideration. While the Big Data Opportunity is crucial, equally important are the traditional data sources New Data Quality Tools in place for operational and DW data Data Governance Program analyzing data in relation to business processes & roles Business-critical data elements identified and definitions createdGlobal Data Strategy, Ltd. 2015
Data-Driven Business EvolutionData is a key component for new business opportunitiesTraditional Business Model Usage-based billingIssue-driven customer serviceMore Efficient Business Model DatabasesMore efficient billingFaster customer servicerespons
and enterprise architecture. Her background is multi-faceted across consulting, product development, product management, brand strategy, marketing, and business leadership. She is currently the Managing Director at Global Data Strategy, Ltd., an international info
