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MDM - The Key to Successful Customer Experience Managment

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Slide deck from a webinar presented by Earley Information Science on "MDM - The Key to Successful Customer Experience Management." Featured speaker is EIS Director of Delivery Services, Tim Barnes.

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MDM - The Key to Successful Customer Experience Managment

  1. 1. Copyright © 2015 Earley Information Science1 MDM - The Key to Successful Customer Experience Management Copyright © 2015 Earley Information Science Tim Barnes Dave Zwicker Earley Information Science Foundations for Successful Digital Transformation Click to view a recording of this webinar
  2. 2. Copyright © 2015 Earley Information Science2 Today’s Agenda • Welcome & Housekeeping – Session duration & questions – Session recording & materials – Take the survey! • Introduction – Dave Zwicker, CMO (@davezwicker) Earley Information Science • MDM – The Key to Successful Customer Experience Management – Tim Barnes, Director, Professional Services, Earley Information Science • https://www.linkedin.com/in/timothybarnes • Questions & Answers
  3. 3. Copyright © 2015 Earley Information Science3 Requirements for a trusted 360-degree view of the customer to enhance the customer experience (CX) are forcing information leaders to initiate or expand master data management (MDM) programs at an increasingly rapid pace. [Gartner] MDM and the Customer Experience…
  4. 4. Copyright © 2015 Earley Information Science4 Customer Experience – Why Companies Care Better customer insights lead to better business outcomes: • Sustained growth in customer acquisition • Increases in revenue per customer • Decreases customer acquisition cost • Reductions in customer churn • Enhancements to product offerings Research findings from Gartner: • 89% of companies will compete based on customer experience by 2016 • 65% have the equivalent of a chief customer officer (office of the CCO) • 18% of marketing budgets in 2014 were spent on customer experience • Customer experience is the top innovation project for 2015
  5. 5. Copyright © 2015 Earley Information Science5 Personalized promotions Seamless multi- channel transactions Streamlined customer service BUSINESS OUTCOMES Product & service innovation BUSINESS OUTCOMES Increased customer value Optimized pricing, availability & delivery Contextualized cross-sell/upsell Higher Conversions Improved loyalty & retention Reduced acquisition cost Personal data Big Data sources DATA SOURCES DATA SOURCES Market data Product data (PIM) Purchase history Customer data (CRM) Operational data (ERP) Clickstream data Service history Data warehouse 360° View of the Customer Experience Customer Lifecycle by Forrester VOC & loyalty programs Online support Social Networks Site search & navigation Mobile commerce Email Promotions TOUCHPOINTS Internet search Advertising Online/in-store merchandising Warranty & registration Call center agents
  6. 6. Copyright © 2015 Earley Information Science6 By 2020, 75% of those organizations that neglect MDM and EIM while creating a 360-degree view of their customers to support the CX will adversely affect CX metrics via the use of inaccurate data during customer interactions. [Gartner] MDM and the Customer Experience…
  7. 7. Copyright © 2015 Earley Information Science7 Copyright © 2015 Earley Information Science Overcoming the Challenges
  8. 8. Copyright © 2015 Earley Information Science8 Tim Barnes • Over 25 years experience in consulting, corporate IT and corporate Finance. • Consulted for Fortune 500 clients in the areas of strategy, working capital management and MDM. • Managed several large, complex MDM implementations Director, Professional Services Earley Information Science SPECIALTIES • Master Data Management • Business Intelligence • Customer Data Integration • Working Capital Management INDUSTRIES • Insurance • Business Services • Telecommunications • Travel
  9. 9. Copyright © 2015 Earley Information Science9 • Overcoming the Process Challenges – Business alignment & process enablement – Dataflow and workflow for master data MDM Challenges: Two Sides of the Same Coin Process Data • Overcoming the Data Challenges – Data integration – Data quality – Data governance
  10. 10. Copyright © 2015 Earley Information Science10 The Data Integration Challenge Order Management ERP CRM Sales Automation eCommerce Data Data Data Data Data Customer Location Contract Customer Interactions Contacts Account Customer Personas Product Product Contact Info Customer Orders Product Location Customer Prospect Contacts
  11. 11. Copyright © 2015 Earley Information Science11 The Data Quality Challenge Data compiled by Talend
  12. 12. Copyright © 2015 Earley Information Science12 The Data Governance Challenge • Set up your governance framework • Start small and build up capabilities • MDM areas of focus – Data Architecture – Data Quality Management – Match/Merge Data Stewardship
  13. 13. Copyright © 2015 Earley Information Science13 Bridging the divide between IT practitioners and business stakeholders The Business Process Challenge IT cares about: • Data quality (de-duping) • Standardizing/centralizing data • Data governance and compliance • Data integration/synchronization • Meeting operational SLAs Business cares about: • Revenue value of a customer • Campaign response rates • Cross-channel customer experiences • Customer support success • Customer loyalty and retention
  14. 14. Copyright © 2015 Earley Information Science14 • Identify producers, consumers and owners • Map the data workflow to identify transformations and process gaps • Determine how the data is used The Data Flow and Workflow Challenge Business Intelligence Operational Integration Master Data Read/Write Application Read/Write Application Read/Write Application Read-Only Application Read-Only Application Read-Only Application MDM Administration MDM Governance
  15. 15. Copyright © 2015 Earley Information Science15 Copyright © 2015 Earley Information Science Implementing MDM - A Systematic Approach
  16. 16. Copyright © 2015 Earley Information Science16 • Do you need an Operational or Analytical Customer Hub? Or both? • Have you identified the producers, consumers and owners of the data and how the users will access it? • Have you identified the data sources? • Have you determined which data sources should be mastered? • Have you identified the Hierarchies, Relationships and Groupings that need to be captured? • Have you created an implementation plan that will bring business benefit quickly? • Do you have a framework for the data governance that’s required to maintain a customer hub? Have you answered these questions?
  17. 17. Copyright © 2015 Earley Information Science17 Total Organizational Project Governance Program objective & success criteria Business case and charter Assess current state Identify data stakeholders (Producers, Consumers and Owners) Develop implementation plan Understand current maturity state of data quality Define future state and roadmap Build use cases Software selection Identify source systems MDM functional requirements Identify data elements Identify match criteria Perform data assessment Determine data cleansing and standardization rules Identify hierarchies, relationships and groupings BI functional requirements Identify consuming systems Identify and prioritize customer 360 components Reporting & analytical requirements Logical data model Analysis & Design High level design Detailed design Data source extract ETL MDM hub configuration Publish & integration Physical data model Development and unit testing Match tuning Testing Integration System (QA) Performance Knowledge transfer System support Prioritized rollout Staggered implementation Release management and deployment Assess Define Requirements Design & Build Deploy Program Manager Information Architect and Business Analyst Development Architects & Team (ETL, MDM, Integration, BI) Test Lead and Testers Roles Phases Business Stakeholders Provide strategic direction Provide functional requirements Assist w/ match tuning Perform user acceptance testing
  18. 18. Copyright © 2015 Earley Information Science18 Staged Implementation Design & Build – Stage 1 MDM Source Systems • Order Mgmt • ERP BI 360 Components • Demographic • Financial Deploy Integration Operational Systems • eCommerce • ERP Assess Define Requirements Business Objective Operational Hub Analytical Hub Source System Prioritization Good data quality High utilization Clear ownership Easily integrated Most trusted BI Prioritization Biggest business benefit Low complexity High utilization Design & Build – Stage 2 MDM Source Systems • CRM • Sales Automation BI 360 Components • Product Usage • VOTC Deploy Integration Operational Systems • CRM • Sales Automation MDM Source Systems • eCommerce BI 360 Components • Third Party • Predictive Integration Operational Systems • Order Mgmt Design & Build – Stage 3 Deploy The determination of the business objective and prioritization of source systems will provide guidance for a staged implementation to realize business value early and often
  19. 19. Copyright © 2015 Earley Information Science19 Copyright © 2015 Earley Information Science Summary of MDM Best Practices
  20. 20. Copyright © 2015 Earley Information Science20 Summary of MDM Best Practices • Establish the business value that an MDM initiative will enable • Keep the focus on the data and how the quality impacts match and merge processes • Create a ‘data governance’ track concurrent to the MDM road map • Focus on the day-to-day business scenarios, not the exceptions • Keep the MDM data lightweight • Keep data transformations simple • Don’t underestimate the time and resources needed for the match tuning process • Emphasize finalizing and creating the customer logical data model • Understand the source system(s)
  21. 21. Copyright © 2015 Earley Information Science21 Copyright © 2015 Earley Information Science Customer Examples
  22. 22. Copyright © 2015 Earley Information Science22 Large Insurance Company | MDM Implementation insurance Business Challenge • Policy centric legacy systems resulted in customer information across policies. • Customer information unreliable – no mechanism to identify customer’s across policies. • Underwriting was manually creating a 360 degree view of the customer Solution • Match and merge customer information from three legacy source systems to create customer master records. • Create households as well as party-to-party relationships. • Build a custom user interface to expose data from the customer hub and integrate the master data to the legacy policy administration systems. • Integrate the customer master data with marketing and actuarial data Outcome • Underwriters able to reduce underwriting time drastically with the ability to view a customer, their policies, their household and relationships to other customers. • Marketing has a clear view of the customer and is better able to segment customers
  23. 23. Copyright © 2015 Earley Information Science23 Large B2B Service Company | Customer 360 Implementation B2B Business Challenge • Five million small, mid and large customer records with duplication due to acquisitions and the legacy system setup of one customer per service sold. • Multiple invoices were sent and Accounts Receivable phone calls made to the same customer • Customers viewed the company as separate business units selling different products. • Multiple business units were selling to the same customer in different locations. Solution • Implement a customer hub by implementing MDM software and matching and merging customer data • Add third party data sources to the customer hub (D&B and InfoUSA) to obtain the corporate hierarchy of the client. • Build data marts for revenue, survey, billing, product and prospects • Layer a BI tool on top of the data marts to provide a 360 degree view of the customer Outcome • A new tool was rolled out to sales, service, marketing and executives to provide a 360 degree view of the customer • Sales was able to visualize where in the customer’s hierarchy they were selling enabling upsell opportunities • Enabled predictive analytics for next most likely purchase by preparing better quality data • Provided sales executives with a “cheat sheet” of a customer prior to a meeting
  24. 24. Copyright © 2015 Earley Information Science24 Large B2B and B2C Car Rental | Customer 360 Implementation B2C/B2BCarRental Business Challenge • 50 million B2B and B2C customers, with multiple brands sharing customers • No method to link customer data across brands creating duplicate customer data. • No way to market across brands or personalize their experience online Solution • Integrate customer data from the legacy customer system, Salesforce.com and the data warehouse creating a customer hub. • Provide a mechanism for the website to consume the customer data using web services. • Build a user interface for customer service and executives. • Enable online marketing. Outcome • Marketing was able to personalize the customer’s online experience by offering targeted ads based on their purchases across brands. • Internal users were able to quickly and easily view details of a customer’s buying habits. • Customer segments were created based on the customer’s buying patterns
  25. 25. Copyright © 2015 Earley Information Science25 Copyright © 2015 Earley Information Science Your Question and Answers
  26. 26. Copyright © 2015 Earley Information Science26 Earley Information Science helps organizations establish a strong information architecture and content management foundation Realize your digital transformation vision with EIS. Earley Information Science (EIS) Information Architects for the Digital Age Founded – 1994 Headquarters – Boston, MA www.earley.com For more info contact: Dave.Zwicker@earley.com

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