Enterprise Data World Webinars: Master Data Management: Ensuring Value is Delivered
 

Enterprise Data World Webinars: Master Data Management: Ensuring Value is Delivered

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Now that your organization has decided to move forward with Master Data Management (MDM), how do you make sure that you get the most value from your investment? In this webinar, we will cover the ...

Now that your organization has decided to move forward with Master Data Management (MDM), how do you make sure that you get the most value from your investment? In this webinar, we will cover the critical success factors of MDM that ensure your master data is used across the enterprise to drive business value. We cover:
· The key processes involved in mastering data
· Data Governance’s role in mastering data
· Leveraging data stewards to make your MDM program efficient
· How to extend MDM from one domain to multiple domains
· Ensuring MDM aligns to business goals and priorities

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Enterprise Data World Webinars: Master Data Management: Ensuring Value is Delivered Enterprise Data World Webinars: Master Data Management: Ensuring Value is Delivered Presentation Transcript

  • Proprietary & Confidential The First Step in EIM Master Data Management Ensuring Value is Delivered
  • pg 2Proprietary and Confidential Agenda • Why is MDM important? • Why is MDM challenging? • How do we ensure it’s successful?
  • pg 3Proprietary and Confidential [ WHY IS MDM IMPORTANT? ]
  • pg 4Proprietary and Confidential Business and IT Drivers  Reduce operational costs  Increase sales force effectiveness  Improve sales and profits  Strengthen customer relationships “A manufacturer can expect to save from $800,000 to $1.2 million for every $1 billion in sales by achieving data sync.” “Businesses that use a formal, enterprise-wide strategy for Global Data Synchronization will realize 30% lower IT costs in integration and data reconciliation at the departmental level through the rationalization of traditionally separate and distinct IT projects.” Analysts Agree… MDM is Important for Addressing Key Business Requirements
  • pg 5Proprietary and Confidential MDM is the Foundation to EIM Vision MDM provides foundational capabilities to achieve broader information management vision Process Automation Architectural Improvements Flexible Data Architecture IT Transformation and Adaptability PAST PRESENT FUTURE Transaction Management Data Warehousing Master Data Management Integrated Information Management and Delivery Process automation and management of transactions with application specific data within isolated business applications including ERP, CRM, SCM, eCommerce and other systems over the past decade Data extraction and normalization for operational as well as management reporting and functional analytics. Data integrity and lack of standards have constrained the maturity of data analytics in the past. MDM and PIM comprises a set of processes, governance, policies, and tools that consistently define and manage the master data or foundational data that supports core business process and is required for accurate data analytics and decision-making EIM and adaptive architecture to deliver business capabilities and flexibility to future changes Big Data Management Integration and management of big data and its relationship across the enterprise through people, processes and technology. Find insights in new types of data, makes an organization more agile, and answer questions that were previously considered beyond reach
  • pg 6Proprietary and Confidential Challenges of MDM Success According to a recent TDWI survey, many of the MDM challenges are organizational and collaborative issues—not technical ones. Half of users surveyed (56%) realize that MDM can be hamstrung without data governance.
  • pg 7Proprietary and Confidential [ LEVERAGE GOVERNANCE ]
  • pg 8Proprietary and Confidential Data Governance Definition Data Governance is the organizing framework for establishing strategy, objectives and policy for effectively managing corporate data. It consists of the organization, processes, policies, standards and technologies required to manage and ensure the availability, usability, integrity, consistency, auditability and security of data. Communication & Metrics Data Strategy Data Policies, Processes & standards Data Modeling & Standards A Data Governance Program consists of the inter-workings of strategy, standards, policies, measurements and communication.
  • pg 9Proprietary and Confidential Governance provides business context Master Data Management MDM Strategy Technology Infrastructure MDM Organization Components Data Architecture & Security Data Mastering Data Quality Data Sharing Measurements & Monitoring Metadata Management GOVERNANCE ORGANIZATIONAL ALIGNMENT
  • pg 10Proprietary and Confidential Governance Decisions for MDM Category Decision Entity Types • What type of data will be managed in the MDM Hub • What are the agreed upon definitions of each type • What is the required cardinality between the entity types • What constitutes a unique instance of an entity Key Data Elements • Purpose, definition and usage of each data element Hierarchies and Relationships • Purpose, definition and usage of each hierarchy / relationship structure Audit Trails and History • How long do we have to keep track of changes Data Contributors • What type of data do they supply • Why is this needed • At what frequency should they supply it • What should be taken for Initial load versus ongoing
  • pg 11Proprietary and Confidential Governance Decisions for MDM (cont.) Category Decision Data Quality Targets • How good does the data have to be • Root cause analysis Data Consumers • Who needs the data and for what purpose • What do they need and at what frequency Survivorship • What should happen when… Lookups • Which attributes are lookup attributes • What are the allowable list of values per attribute • How different are the values across the applications and how do we deal with inconsistencies Types of Users and Security • What types of users have to be catered for • Can they create, update, delete, search • Can they merge, unmerge Delete • How should deletes be managed Privacy and Regulatory • Privacy and regulatory issues Recommendations Meeting – Master Data Management (MDM) Assessment 071411
  • pg 12Proprietary and Confidential [ MDM POLICIES & PROCESSES ]
  • pg 13Proprietary and Confidential Creating Policies Charter Principles Policies Processes Procedures
  • pg 14Proprietary and Confidential MDM Policies • Security, Privacy, Access, Visibility • Party – Rules supporting: — Party relationships — Hierarchies — Data lifecycle - CRUD — Data classification — Data integrity • Product – Rules supporting: — Product relationships — Product definition — Product components (Items) and their relationship to Product
  • pg 15Proprietary and Confidential Standard MDM Processes • Exception Handling • Duplicate Handling • Consensus Delete • Company / Customer On-boarding • Company Merger • Hierarchy Management • Match / Merge • Data Quality
  • pg 16Proprietary and Confidential Issue Management Process Decision Meeting Data Governance Working Group Chair Data Governance Working Group Coordinator Impacted Business Lead/Data Steward Identifying Business/IT Formalize recommendation Identify options/ evaluate implications Issue identified by Business/IT Identify issue type and severity Stewards consults other Stewards regarding issue (weekly stewards meeting) Identify options/ evaluate implications (impact assessment) Issue and supporting documentation brought to Coordinator Issue and impact logged in issues log Chair reviews issues log Issue is evaluated in monthly meeting Update all documentation Review issue and impact assessment Update issue and impact assessment, if necessary Formalize recommendation Voting membership votes Coordinator closes issue Publish communication Issue and impact assessment brought to Business Lead/Data Steward Communicate analysis and recommendations back to DQS
  • pg 17Proprietary and Confidential [ ENSURE ALIGNMENT ]
  • pg 18Proprietary and Confidential Alignment Process • Why is this important? • Why should we care? Value • Who cares? • Why should they care? Stakeholders • How does the value benefit the stakeholders? Linkage
  • pg 19Proprietary and Confidential pg 19Proprietary & Confidential Example: Stakeholder Map
  • pg 20Proprietary and Confidential MDM Program pg 20Proprietary & Confidential Sales/Marketing Improve Segmentation Understand Risk Optimize Relationships for Revenue IT Improved Productivity Proactively support business Contain Costs Single View of Customer Improved Data Quality Common Service Platform Example: Articulate Linkage The Single Repository of Customer data will improve my understanding of customers by providing me a trusted source of timely, accurate and pertinent data from which to execute analytics, segmentation and risk assessment. The common service platform for data access and sharing will increase IT productivity by providing a more unified integration infrastructure. This will enable IT to better support the business in a timely manner because there will be repeatable processes and less rework.
  • pg 21Proprietary and Confidential [ MEASUREABLE SUCCESS CRITERIA ]
  • pg 22Proprietary and Confidential Metrics and Measurement • Metrics and Measurement  The right metrics help maintain alignment  Metrics define the requirements for the information you need to answer the questions  Measurement is the data reviewed, tracked and reported on an on-going basis • Key Performance Indicator (KPI)  A Key Performance Indicator (KPI) is a quantifiable metric that the MDM Program has chosen that will give an indication of MDM program performance.  A KPI can be used as a driver for improvement and reflects the critical success factors for the MDM Program • A metric is not necessarily a KPI
  • pg 23Proprietary and Confidential Example: Metrics and KPI’s Measurement Target Frequency Increased confidence in the quality of information Reduce time spent in data reconciliation activities Number of requests coming into the DG Group Data owner assigned for each entity type Length of time from account opening to availability online Number of target systems using master data Reduce time spent on creating a common customer list after an acquisition Improved ability to find the right data quickly and easily Data quality becomes a part of performance objectives across LOB’s Presence/Usage of a unique identifier Survey – yes 50% Increasing 100% 24 hours 10 20% reduction from previous Survey – yes Increasing 100% Every 6 months Monthly Monthly Quarterly Monthly Quarterly After every acquisition Quarterly Quarterly Quarterly
  • pg 24Proprietary and Confidential Impact Determines Success Issues • Report Quality and Accuracy • Low Productivity • Regulatory Compliance / Audit Response Goals • Improve data’s usability • Improve efficiency and productivity • Reduce compliance / audit cost Metrics/KPI’ s • Data Quality • Data remediation time • Effort to comply • Use of identifiers Impact • Improve client relationships • Address new markets • Reduce/avoid fines • Improve analysis & decision making
  • pg 25Proprietary and Confidential [ EXTENDING MDM ]
  • pg 26Proprietary and Confidential Extending MDM to the Enterprise • Create a Roadmap:  Steps to implement and operationalize a MDM program in a phased approach given known IT and Business initiatives  Presentation / high level work plan detailing the phased implementation steps necessary, resource requirements and potential costs involved to deliver the intended future state
  • pg 27Proprietary and Confidential Roadmap Overview 6 Months 12 Months 18 Months 24 Months Data Quality Client & Prospect Contact & Partner Extend DQ Product & Account Goals: • Establish DG program • Business Case Approval • Establish DQ Foundation • Profiling • Reporting • Scorecards • Define Client, Prospect & other Entity types and attributes Goals: • Establish the MDM Foundation • Matching • Profiling • Reporting • Single Source for Client & Prospect • Single Source for Credit Lines Goals: • Single Source for Contact & Partner • DQ at point of entry • Enable reporting and analysis groups • Enable Address synchronization across operational systems Goals: • Measure, Refine & Monitor • Single Source for Product and Account • 360 degree view of client • Improve monitoring of master data across operational systems Operationalize Data Governance DG Management and Maintenance 27
  • pg 28Proprietary and Confidential Keys to Success Successful MDM Implementation Technology Process People Failed MDM Implementation! Technology Process People
  • Proprietary & Confidential The First Step in EIM Contact Info www.firstsanfranciscopartners.com Kelle O’Neal kelle@firstsanfranciscopartners.com 415-425-9661 @1stsanfrancisco