The First Step in EIMMaximizing the Value of MDM   with Data Governance               Kelle O’Neal             Managing Pa...
Keys to Success                                                          People                                        Pro...
Some Warning Signs      Limited business                  Not recognizing the        involvement:                    impor...
Why We’re Here                                 Purpose:                   Drive awareness of how MDM and Data             ...
Agenda     •  FSFP’s Perspective on MDM     •  Data Governance Framework     •  Building the Organization     •  MDM decis...
[   FSFP’S PERSPECTIVE   ]Proprietary and Confidential                                pg 6
Enterprise Information                                                           Management Framework                     ...
Enterprise Data Management                                    Enterprise Data Management                               Ens...
What is Master Data Management?GartnerMaster Data Management (MDM) is a discipline in which the business and the ITorganiz...
Master Data Management Services                                                   FrameworkProprietary and Confidential   ...
MDM Value Proposition                    Business Value                    Technology Enablement•  Improve reporting and d...
Challenges of MDM Success According to a recent TDWI survey, many of the MDM challenges are organizational and            ...
What else is needed?                                         Must Have “Tools”…                                        •  ...
[       DATA GOVERNANCE FRAMEWORK   ]Proprietary and Confidential                        pg 14
Data Governance Definition  Data Governance is the organizing                                                        Commu...
Data Governance FrameworkProprietary and Confidential                          pg 16
Why is Data Governance                                                             Important?     •  Increasing customer d...
Data Governance & MDM Work                                                             Together  Governance               ...
[        BUILDING THE ORGANIZATION   ]Proprietary and Confidential                             pg 19
Operating ModelWikipedia: An Operating Model describes the necessary level of business processintegration and data standar...
Operating Model Design Principles              Principle                                          Description         Desi...
Sample: DG Operating Model                                                Data Governance Steering Committee              ...
Keys to a Successful DG                                                Organization     •  Governance team must contain me...
[       MDM DECISIONS MADE BY DATA                               GOVERNANCE ]Proprietary and Confidential                 ...
Building support for MDM     •  Tie the project to a larger business initiative     •  Link the value of MDM to specific c...
MDM Decisions Made by DG  Category                     Decision  Entity Types                 •    What   type of data wil...
MDM Decisions Made by DG (cont.)                 Category                                           Decision              ...
Customer Data Governance                                                       Stewardship Activities                     ...
[   ENSURING SUCCESS   ]Proprietary and Confidential                              pg 29
Seven Reasons Why MDM Needs                                                              Data Governance                  ...
Success Measures                             # of DG decisions backed up by the Steering Committee (SC)                  ...
The First Step in EIM          Contact Infowww.firstsanfranciscopartners.com            Kelle O’Nealkelle@firstsanfrancisc...
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EDWWS: Maximizing the Value of MDM with Data Governance

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EDWWS: Maximizing the Value of MDM with Data Governance

  1. 1. The First Step in EIMMaximizing the Value of MDM with Data Governance Kelle O’Neal Managing Partner First San Francisco Partners Inc. @1stsanfrancisco Proprietary & Confidential
  2. 2. Keys to Success People Process People Process Technology Technology Successful MDM Failed MDM Implementation Implementation!Proprietary and Confidential pg 2
  3. 3. Some Warning Signs Limited business Not recognizing the involvement: importance of Data We know what the No clear understanding of Stewardship: business wants to do, we what data is needed to We can deal with the support the business can involve them later in concept of Data Stewards testing… objectives: at a later date… Bring all the data just in case… Not enough thought given to metrics and measurement:How will we know when we Inability to reach a clearhave achieved our objective? decision: How do you know when Definitions, Input Sources, you’re heading for trouble? Survivorship, KDE’s, lookup values, exception management Value not understood: processes, data quality targets, I’m not sure that this new piece etc. of technology will actually help me in any way… Proprietary and Confidential pg 3
  4. 4. Why We’re Here Purpose: Drive awareness of how MDM and Data Governance interact to provide business value Outcome An understanding of:   MDM and Data Governance working together   Data Governance decisions for MDM planning & implementation   How to create successProprietary and Confidential pg 4
  5. 5. Agenda •  FSFP’s Perspective on MDM •  Data Governance Framework •  Building the Organization •  MDM decisions made by Data Governance •  Ensuring SuccessProprietary and Confidential pg 5
  6. 6. [ FSFP’S PERSPECTIVE ]Proprietary and Confidential pg 6
  7. 7. Enterprise Information Management Framework Enterprise Information Management GOVERNANCE Information Strategy Business Intelligence Information Asset and Performance Data Management Management Management Content Delivery Content Management Architecture and Technology Enablement ORGANIZATIONAL ALIGNMENT Provides a holistic view of information in order to manage data as a corporate assetProprietary and Confidential pg 7
  8. 8. Enterprise Data Management Enterprise Data Management Ensure data is available, accurate, complete and secure Traditional Reference Master Data Metadata Big Data & Big Data Data Management Management Management Governance Management Data Quality Data Privacy/ Data Architecture Management Retention/Archiving Security Develop and execute architectures, policies and procedures to manage the full data lifecycleProprietary and Confidential pg 8
  9. 9. What is Master Data Management?GartnerMaster Data Management (MDM) is a discipline in which the business and the ITorganization work together to ensure the uniformity, accuracy, semantic persistence,stewardship and accountability of the enterprise’s official, shared master data.Organizations apply MDM to eliminate endless, time-consuming debates about “whosedata is right,” which can lead to poor decision making and business performance.WikipediaMaster data management (MDM) comprises a set of processes and tools that consistentlydefines and manages the non-transactional data entities of an organization (which mayinclude reference data). MDM has the objective of providing processes for collecting,aggregating, matching, consolidating, quality-assuring, persisting and distributing suchdata throughout an organization to ensure consistency and control in the ongoingmaintenance and application use of this information. Proprietary and Confidential pg 9
  10. 10. Master Data Management Services FrameworkProprietary and Confidential pg 10
  11. 11. MDM Value Proposition Business Value Technology Enablement•  Improve reporting and decision making •  Easily integrate data across siloed IT•  Better regulatory reporting compliance solutions•  Maximize revenue with integrated •  Ensure the quality of data being solutions across business units delivered enhances the value of data•  Reduce costs through operational integration investments efficiency gains •  Provides a single integrated•  Easily share trusted data across various architecture and solution business functions and channels •  Support for service oriented•  Drive costs of bad data out of the architecture (SOA) ensures data quality system capabilities can easily be consumed as•  Rapidly respond to new business services and provides a flexible, opportunities scalable environment for data to move across the enterprise•  Provide “plug and play” capabilities to •  Easily assimilate new data elements consolidate and easily extend IT into enterprise processes architecture Proprietary and Confidential pg 11
  12. 12. 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.Proprietary and Confidential pg 12
  13. 13. What else is needed? Must Have “Tools”… •  Documented and enforced governance An MDM initiative is an policies and processes important component of a Data Governance Strategy •  Clear accountability, ownership and escalation mechanisms •  Continuous measurement and monitoring of data quality & adoption Technology alone will not solve the problem •  Executive support to create a culture of accountability around the quality of the data…it’s everyone’s concern •  Solid alignment between business & IT You can’t “do” MDM •  Understanding of data before diving without Data Governance into an MDM “Project”Proprietary & ConfidentialProprietary and Confidential pg pg 13 13
  14. 14. [ DATA GOVERNANCE FRAMEWORK ]Proprietary and Confidential pg 14
  15. 15. Data Governance Definition Data Governance is the organizing Communication framework for establishing strategy, objectives and policy for effectively managing corporate data. Metrics Data and KPIs Strategy It consists of the organization, processes, policies, standards and technologies required to manage and ensure the availability, usability, Data Policies, Processes & integrity, consistency, auditability and standards security of data. A Data Governance Program consists of the inter-workings of strategy, standards, policies, measurements and communication. Proprietary and Confidential pg 15
  16. 16. Data Governance FrameworkProprietary and Confidential pg 16
  17. 17. Why is Data Governance Important? •  Increasing customer demands and new regulations •  Streamlines and unifies the approach to managing data •  Ensures the right people are involved in determining standards, usage and integration of data across projects, subject areas and lines of business •  Balances silo-ed short-term project delivery focus •  Traditional projects don’t give enough focus to data management •  Systems are becoming more challenging to manage •  Data quality issues are persistent Data is a valuable Corporate AssetProprietary and Confidential pg 17
  18. 18. Data Governance & MDM Work Together Governance MDMStandardized Methods Discovery and Profilingand Data Definitions Provide Guidance CleansingRoles and Duplicate DetectionResponsibilities Create & Enforce Policies Data Maintenance andDecision Rights Management Track Progress Measurement andArbiters and Escalation Monitoring Provide Feedback Data SharingStatistics / Analysis /Monitoring Workflow Proprietary and Confidential pg 18
  19. 19. [ BUILDING THE ORGANIZATION ]Proprietary and Confidential pg 19
  20. 20. Operating ModelWikipedia: An Operating Model describes the necessary level of business processintegration and data standardization in the business and among trading partnersand guides the underlying Business and Technical Architecture to effectively andefficiently realize its Business Model. The process of Operating Model design is alsopart of business strategy. •  Outlines how Data Governance will operate •  Forms basis for the Data Governance organizational structure – but isn’t an org chart •  Ensures proper oversight, escalation and decision making •  Ensures the right people are involved in determining standards, usage and integration of data across projects, subject areas and lines of business •  Creates the infrastructure for accountability and ownershipProprietary and Confidential pg 20
  21. 21. Operating Model Design Principles Principle Description DesignBe clear on purpose Build governance to guide and oversee the strategic and enterprise mission PrinciplesEnterprise thinking Provide consistency and coordination for cross functional initiatives. Maintain an enterprise perspective on dataBe flexible If you make it too difficult, and people will circumvent it. Make it customizable (within guidelines), and people will get a sense of ownershipSimplicity and usability are the Adopt a simple governance model people can use. A complicated andkeys to acceptance inefficient governance structure will result in the business circumventing the processBe deliberate on participation Select sponsors and participants. Do not apply governance bureaucracyand process solely to build consensus or to satisfy momentary political interestEnterprise wide alignment and Maintain alignment with both enterprise and local business needs. Guidegoal congruence prioritization and alignment of initiatives to enterprise goalsEstablish policies with proper Clearly define and publicize policies, processes and standards. Ensuremandate and ensure compliance compliance through tracking and auditCommunicate, Communicate, Frequent, directed communication will provide a mechanism for gaugingCommunicate! when to “course correct”, manage stakeholder and effectiveness of the program Proprietary and Confidential pg 21 21
  22. 22. Sample: DG Operating Model Data Governance Steering Committee CFO International Global Compliance Relationship Marketing IT Services Management Data Governance Leads: Business (Full Time) and IT (Support) Program ManagerData Governance Working Group Data Governance Analysts Data Stewards Lead Information Management supports: •  Represents cross-functional data analysis and •  Represents data stewardship within each of •  Data Quality lead data governance principles for the workstreams the workstreams (Data Mgmt, Mgr Acct & •  Metadata Lead (Information, Mgr Acct & Results, Reference Results, Reference Data, Acctg & Settlement) •  Data Custodian Lead data, Acctg & Settlement) •  When MDM is completed, becomes the go to person for data related questions Security –Risk Lead Information (ISSC) Architecture Lead Existing Technology Workstreams and Delivery Teams Data Quality Team Information MDM Reference Data Delivery Team Delivery Team Delivery Team Common Services Proprietary and Confidential pg 22
  23. 23. Keys to a Successful DG Organization •  Governance team must contain members from multiple lines of business •  Team members must represent both business and IT •  Team needs to meet on a regular basis •  Agreed upon fundamentals that serve as the Guiding Principles •  Clear lines of communication •  Ensure the operating model fits the culture of the companyProprietary and Confidential pg 23
  24. 24. [ MDM DECISIONS MADE BY DATA GOVERNANCE ]Proprietary and Confidential pg 24
  25. 25. Building support for MDM •  Tie the project to a larger business initiative •  Link the value of MDM to specific corporate and organizational initiatives •  Utilize metrics to make MDM real •  Leverage the approval process •  Articulate the value to individuals in their terms, per their interests and priorities •  Identify an Executive Mentor who can help you sell up •  Work with those individuals who have the power to approve and/or can influence the approvers •  Publish updates and incremental successesProprietary & ConfidentialProprietary and Confidential pg 25 pg 25
  26. 26. MDM Decisions Made by DG 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 •  Purpose, definition and usage of each hierarchy / Relationships 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 ongoingProprietary and Confidential pg 26
  27. 27. MDM Decisions Made by DG (cont.) Category Decision Recommendations Meeting – Master Data Management (MDM) Assessment 071411 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 issuesProprietary and Confidential pg 27
  28. 28. Customer Data Governance Stewardship Activities Data Stewardship Business Request Change Request Hierarchy Management Match/Merge Data Quality Customer SearchProprietary and Confidential pg 28
  29. 29. [ ENSURING SUCCESS ]Proprietary and Confidential pg 29
  30. 30. Seven Reasons Why MDM Needs Data Governance • MDM needs DG’s collaborative environment 1 • MDM needs DG’s stewardship capabilities 2 • MDM needs DG’s change management process 3 • MDM needs DG’s mandate 4 • MDM needs DG as it grows into enterprise scope 5 • MDM needs DG’s guidance as it matures into new generations 6 • MDM needs DG to support its priorities 7Source TDWI - Seven Reasons Why MDM Needs DG Proprietary and Confidential pg 30
  31. 31. Success Measures   # of DG decisions backed up by the Steering Committee (SC)   # of approved projects from DG People   # of issues escalated to SC and resolved   # of data owners and data managers identified   DG adoption rate by enterprise personnel   # of data consolidated processes   # of approved and implemented standards, policies, and processes to effectively manage core business data   # of consistent data definitions (consistency on how core business data is defined and used Process across enterprise, independently of a specific initiative or context)   Existence of and adherence to a business request escalation process to manage disputes regarding data   Integration into the project lifecycle process to ensure DG oversight of key enterprise initiatives   # of consolidated data sources consolidated   Records/data aged past target   # of data targets using mastered data   MDM Hub availability   Presence and usage of a unique identifier(s)   # of hours spent investigating, cleaningTechnology   # of address exceptions master data   Data integrity across systems   % of matched records   # of new records loadedProprietary and Confidential pg 31
  32. 32. The First Step in EIM Contact Infowww.firstsanfranciscopartners.com Kelle O’Nealkelle@firstsanfranciscopartners.com 415-425-9661 @1stsanfrancisco Proprietary & Confidential

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