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Create a 'Customer 360' with Master Data Management for Financial Services


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Create a 'Customer 360' with Master Data Management for Financial Services

  1. 1. Create a „Customer 360‟ with MDM in Financial Services February 26, 2013
  2. 2. About PerficientPerficient is a leading information technology consulting firm serving clientsthroughout North America.We help clients implement business-driven technology solutions that integratebusiness processes, improve worker productivity, increase customer loyalty and createa more agile enterprise to better respond to new business opportunities.
  3. 3. What We Bring to Our ClientsIndustry-leading solution & Collaborative Approachtechnology expertise • Work with our clients, adapting to • ~2000 experienced colleagues their cultures • Dedicated solution practices • Education and mentoring services • Partnerships and certifications in premier technologies Superior Service and Value • Local client service teamsDisciplined project execution • Flexible resource and fee • Highly experienced project managers arrangements • Perficient’s Enable™ methodology • Delivery track record based on best practices Commitment and QualityInnovative approaches and IP Assurance • Perficient’s user-centered design • Track record of 2000 engagements approach with 800+ clients • Application migration methodology • ~85% of clients bring us back • Quick Start Rulebook™ for Enterprise • Strong client references Integration
  4. 4. Our Solutions ExpertiseBusiness Solutions Technology Solutions• Business Intelligence • Business Integration/SOA• Business Process Management • Cloud Services• Customer Experience and CRM • Commerce• Enterprise Performance Management • Content Management• Enterprise Resource Planning • Custom Application Development• Experience Design (XD) • Education• Management Consulting • Information Management • Mobile Platforms • Platform Integration • Portal & Social
  5. 5. Financial Services Expertise 5
  6. 6. Our SpeakersMike Panzarella, Director, Financial Services PracticeWith 20 years of experience with Big Four consulting andcommercial banking, Mike has expertise in BI/DW platformarchitectures for Fortune 100 financial service firms with a focus onsocial media and mobile convergence. Mike also has extensiveexperience in designing and implementing Big Data solutions forFortune 100 companies.Ben Leeson, Data Governance ArchitectBen has over 10 years of Governance and IT leadership experiencewith Fortune 50 Financial Services companies. Ben’s areas of focusare in Data Governance, Data Stewardship, Data Quality, DataSourcing and Data Strategy. He has experience driving enterpriselevel data management programs that span each line of businessand corporate banking functions.
  7. 7. What We Will Cover 2013About Us Defining MDM Tr e n d sChallenges Data Governance Leverage ITU n l o c k i n g B u s i n en v e Vamu e t s I ss st l en Q & A
  8. 8. MDM Overview
  9. 9. What is Master Data Management? Master Data Management (MDM) comprises of a set ofprocesses, governance, policies, standar ds and tools that consistently defines and manages the master data of an organization.
  10. 10. What is Master Data Management?• Disciplines, technologies, and processes that accommodate, control and manage master data across the organization• A means to manage and deliver a unified view of an organization’s data SOURCE SYSTEMS MASTER DATA ENTERPRISE MANAGEMENT APPLICATIONS CRM Name: B. Jones INFORMATION Address: 35 West 15th Street Sales Address: Toledo, OH 12345 First: Bill Last: Jones ERP Name: William Jones Address: 35 West 15th Street Address: 35 West 15th St. Customer City: Toledo Address: Toledo, OH 12345 Support State/Zip: OH / 12345 Legacy Gender: M Name: Billie Jones Address: 36 West 15th St. Age: 30 Claims Address: Toledo, OH 12345 DOB: 1/1/81 Master Data Management Needs Governance to Succeed 10
  11. 11. MDM Business DriversStrategic Initiative•Consolidate data from silos/integrate new systems quickly•Meet demands of new business channels•Grow with the business•Identify key relationships and hierarchiesRevenue•Identify cross-sell, up-sell opportunities•Customize product offerings and bundles•Introduce new products quickly•Identify high-value customers•Improve customer retentionCost•Automate manual business processes•Reduce data errors•Eliminate excess mailings•Identify credit risk•Support system consolidation initiativesCompliance•Automate manual business processes•Reduce data errors•Eliminate excess mailings•Identify risk (credit)•Support system consolidation initiatives 11
  12. 12. I n d u s t r y Tr e n d s
  13. 13. Trend: Gartner‟s Nexus of ForcesThe Nexus of Forces (mobility, social networks, information and cloud services) is acceleratingthe pace and granularity of interconnected markets at a faster rate than ever. Banks Employees and Customers Social Corporate Networks Data Email, IM Retail and Banking End Transactions Customers ApplicationsRetail Stores Source: Gartner (Jan. 2013) 13
  14. 14. Trend: Embracing SocialWhat is “Social MDM”? • Increased social awareness in banking • Need for social collaboration • Evolution of CRM system and use of sensor data • New systems of engagement = more data silos • Data quality is increasingly important • Pending regulatory standards (FFIEC) • Golden Record vs. Golden Profile
  15. 15. Trend: Digital Disruption• Investment in mobile innovations• Create a seamless customer cross-channel experience• Validating data Geolocation data• Data quality known issue• Manage privacy issues• Compliance “GoBank” mobile account from Green Dot 15
  16. 16. Trend: The Big Data Ecosystem• Better processing and management of Big Data• Enhanced metadata and social analytic preprocessing 16
  17. 17. Trend: MDM in the Cloud• Proliferation of cloud based solutions • New entrants into marketplace • Value-added services and solutions for “social listening” • Commoditization of data• Data is data is data• Cost of pulling data in• Regulatory compliance standards 17
  18. 18. Trend: Creating a „Customer 360‟ View
  19. 19. MDM Challenges• Sponsorship at the enterprise level• Data hoarding & mistrust of data centralization• Addition of business process alignment• Continued customer data integration• Introduction of external/new data sources• SOA and SLO compliance• Scalability of architecture
  20. 20. Data Governance 20
  21. 21. MDM Questions to Ask • What is the Data Strategy?Strategy • How does it support the business strategy? • How is data utilized in the fulfillment of business processes? • Does poor data quality impact the company functions? Quality • Is data cleansing simply assumed as part of doing business? • How can data better serve the business? (i.e. Analytics, Operations) Value • Does the company have the skills to fulfill the data strategy?Resources • Who is pushing funding for the data solution(s)?Funding • What is the current and future architecture of the company? Arch. 21
  22. 22. What is Enterprise Data? Types of Enterprise Data Entity Data Master Data is a subset (Something exists)Transactional Data Analytical Data(Something happened) (data for enabling future action) 22
  23. 23. What is Enterprise Data? Another View Govern the Data Contribute Data Data Master Enable Deliver DataProviders Quality Data Sharing Consumers Update Enrich 23
  24. 24. Audiences for MDM MDM, especially the customer domain, requires business input.It’s important to know your audience when implementing a MDM solution. The terms may change but the concepts are similar. Business Perspective: Technology Perspective: data flow, data supply data lineage, metadata, system chain, data producer, data of record, source system, and supplier, and business process integration Data Environment Master Data Data Consumers Management Support Ops Sales 24
  25. 25. Impacts of Changes to Data Data Data profiling & data Originator cleansing – now a hop Q (Upstream) or more removed from the source: telephone game Data Provider BTransformations to fit the schema of the newsystem: e.g. changing the Data format of date Consumer H (Downstream)Data lineage management enables systems to account for the downstreamimpacts of a change to the data.The change can appear to be relatively benign like cleaning up data, to the moreintentional like changing the context of a business element.If Data Provider B changes the format of a data element the downstream systemsneed to be aware of the change and adjust their code to account for it. Data Provider Bis responsible for communicating to their Data Consumers the changes. 25
  26. 26. Data Governance Focus Areas Identify Associated Business Processes Develop the Analyst Community: Who are they? What are their Requirements?People & Process Share ideas, best practices, common resources, communication channels Standardize the Common Business Language: Project Delivery Process: Business glossary, information domains, conceptual data Gather data requirements early in the models process Stand up a Governance Structure: Executive Support and SME Participation Create & maintain routines, policies, standards, review processes (exceptions), and communications Define Data Governance Roles and Responsibilities: Data management executive, data stewards, data custodians, information architects, analysts, SAs, and more Establish Master Data and Data Provisioning Management: Determine authoritative data sources are and the process for attaining data from themTechnology Data Metadata Data Quality Integration/Movement Management Management Technical & Data Quality Operational Standards & Metadata Measures Data management tools are unified and the platform is maximized 26
  27. 27. Data Governance Primary Roles To weave sustainable data governance into the fabric of the company, executive level participation must occur in the administrative component Data Governance Administrator Data Steward Data Custodian (Formal Oversight) (Business Requirements) (Technical Requirements)Direction Business Strategy Data IntegrationScope Business Terms Objective Data QualityPrioritization Data Standards Data ModelingGovernance Structure Business Rules Metadata ManagementOrganizational Alignment Business Process Data LineagePolicy Definition Subjective Data Quality Work Flow ManagementIssue Resolution Data Analytics Data SecurityRoles and Responsibilities Identify OpportunitiesAuthority and Accountability Identify RiskFundingEducationCommunicationEnable Data Management Manage the Data 27
  28. 28. Unlocking Business Value
  29. 29. Enterprise Risk ManagementAlignment of Risk Model: • Reputational • Operational • Regulatory & Compliance
  30. 30. Solution Architecture Mobile Web CRM Business Applications ESB Data Warehouse/Data Mart ETL/ELT LegacySocial Files EDW Systems
  31. 31. The “Golden Social Profile”Social Profiles Customer Service/LOB MDM Hub Targeted MarketingBank Source Systems 31
  32. 32. Questions? 32
  33. 33. Come See Us at Bank Innovation! 33
  34. 34. Connect with PerficientSUBSCRIBE TO PERFICIENT BLOGS FinancialServicesFOLLOW PERFICIENT ON TWITTERPerficient_FSBECOME A FAN OF PERFICIENT ON FACEBOOKw w w. F aceb o o k. co m/ Perfi ci en tD O W N L O AD P E R F I C I E N T W H I T E PAP E R Sw w w. Perfi ci en t. co m/ W hi tePap ers