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EDM Council General Meeting New York City

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  • 1. EDM Council General Meeting New York City February 16, 2006
  • 2. Implementation Best Practices Working Group Status Report on Progress February 16, 2006
  • 3. Alignment of Objectives EDM Council Mission “ Create value to its membership by providing a senior forum to share information on the business strategies and practical realities of implementing effective solutions to manage data across the enterprise.” Implementation Best Practices Working Group Objective Produce research and provide guidance on EDM implementations to reduce the risks and improve the returns associated with enterprise data management initiatives “ What Works and What Doesn’t Work” Deliverables Leverage experience of EDM Council members to produce and publish a series of practical implementation guides to serve as reference tools for Council members. Alignment of Objectives
  • 4. EDM Implementation Lifecycle
    • Inception
    Governance Elaboration Construction Transition Operate Governance is the single most important requirement for EDM success. Effective cross-functional governance and business commitment to the importance of data management is required to achieve organizational alignment and long-term results. Establish project scope and boundaries. Develop business case. Define internal versus external resource considerations. Design phased project plan. Analyze and capture data control/management problems to address. Establish architectural foundation. Identify risk elements. Refine business case and project plan. Develop, integrate and test all components and EDM platform features. Develop implementation plan and manage user migration from existing environment to the EDM platform. Often includes several iterations. Implement the EDM platform and integrate into daily work processes of users. Initiate measurement and documentation of benefits. Develop continuous system and business process improvement activity.
  • 5. 10 Commandments of EDM Implementation
    • Governance: top-down sponsorship, adequate funding and business unit buy-in as unwavering mandate.
    • Clarity of Objectives: well defined end vision, clear and thorough requirements analysis, broad and sustainable end-user engagement, open lines of communication.
    • Business Ownership: business requirements as driver, IT as enabler.
    • Strategic Leader: a strong Chief Data Officer, CDO, to hold the reins and fully empowered to (and accountable for) achieving EDM objectives.
    • Balanced Team: joint business and IT project managers and team members with sufficient staffing and knowledge about data.
    • Holistic Business Case: covering enterprise-wide interests and incorporating
    • data quality, timeliness, linkages, and process improvements
    • Recognize Complexities: understand data and process dependencies associated with linking front, middle and back office requirements across lines of business.
    • Adhere to Core Policies/Procedures: including data model consistency, business rules and data quality stewardship. Business applications adapt to the model, not the other way around.
    • Phased Implementation: iterative, realistic and disciplined approach to defining project milestones. Phased migration with clear and incremental ROI for stakeholders. Don’t promise what you can’t deliver.
    • Testing, Training and Internal Marketing: process change is like a new religion, hard to convert.
  • 6. Key Findings: Governance Considerations What Works What Doesn’t Work
    • Importance of data management as a core building block for doing business
    • Overall project ownership, areas of responsibility and lines of reporting
    • Scope of governance model to establish priorities, manage conflicts, promote consensus and define the rules of engagement
    • Levels of governance (i.e. one for overall EDM project management, one for subject matter decisions)
    • Balance between team empowerment and executive control
    • Relationship to core stakeholders and compatibility with other initiatives
    • How to promote involvement without decision-making paralysis
    • Role of communication as a key for integration success
    • Empowering a CDO as a single point of contact to reconcile internal business unit data conflicts
    • Utilizing strong project managers guiding delivery teams
    • Obtaining representation by front and back office functions as well as by business units and IT
    • Creating practical policies and structures for data ownership and business unit data stewardship
    • Using an “architecture review board” to ensure alignment between strategy and capabilities
    • Charging reference data teams with responsibility for data model consistency, data integrity and resolution of data discrepancies
    • Maintaining strict change management policies into production
    • Creating and implementing detailed service level agreements
    • Viewing EDM implementation as a technology issue rather than as a business problem
    • Failure to get key business unit stakeholder buy-in and participation
    • Having stakeholders feel alienated
    • Taking a line of business or functional silo orientation
    • Underestimating the logistical challenges related to “management by committee”
    • Failure to communicate on where project stands against budget projection
    • Not establishing an organization that is responsible for data quality and cleansing
    Effective governance is the most important component of success
  • 7. Key Findings: Inception Considerations What Works What Doesn’t Work
    • Use of workflow technology to enhance control and promote business process automation
    • Data integrity and data access throughout the transaction chain
    • Identification of stakeholders, requirements methodology process, level of buy-in and extent of involvement
    • Reuse of common data elements and agreeing to the use of standards to shorten development efforts and to provide early deliverables to business units
    • Determination of the level of resources and extent of internal expertise required for EDM implementation
    • Senior management mandate for downstream systems to use central reference databases
    • Top down sponsorship and active involvement by corporate leadership
    • Flexible central reference data teams to work with timescales of user systems migrating to use of central database
    • Clear understanding of EDM as enabler of other applications rather than end solution
    • Balanced business and IT involvement with strong front office representation and backing
    • Operating without a precise statement of criteria for measuring success
    • Scope creep and lack of clearly defined roadmap to achieve end vision
    • Failure to achieve balance between near-term tactical deliverables and long-term benefit
    • Misalignment between IT and business objectives
    • Underestimating the complexity in raising initial financial sponsorship and securing ongoing funding allocations
    • Failure to understand the sustainability of EDM initiative in competition with other internal priorities
    • Underestimating the challenges in scheduling IT work across multiple downstream systems
    • Outsourcing project without a strong framework plan
    Mobilizing business and IT stakeholders is necessary for buy-in and funding
  • 8. Key Findings: Elaboration Considerations What Works What Doesn’t Work
    • Scope, planning milestones, governance structure, implementation timeframes and budget
    • Current state analysis with key stakeholders (CRM, credit risk, compliance, operations, finance, etc.)
    • Integrity of data model and understanding of data dependencies throughout enterprise
    • Impact on data acquisition, cleansing, storage, processing, distribution to downstream systems and access milestones
    • Level of business case rigor including costs and benefits of various phases
    • Boundaries of new and existing architecture including middleware requirements and interface design
    • Phase and interim operation models for implementation
    • Validation of software RFP and defining best practice implementation and operating plans
    • Realistic and disciplined approach to defining project phases
    • Strong incremental ROI for business units
    • Balanced business and IT involvement with strong front-office representation
    • Concise documentation and substantive communication
    • Strong methodology to boost confidence
    • Honesty about commitments
    • Phased migration approach with ongoing support of multiple databases through the transition
    • Separating the program into smaller targeted stand-alone projects
    • An ideal mix of internal, consultant and third party involvement
    • Failure to recognize the importance of ensuring added value for front office applications
    • Misalignment between IT and business objectives and complexity of engineering solutions
    • Allowing one group to be dominant in defining scope and objectives (and allowing other groups to “lay quiet’)
    • Expecting business units to share architecture as well as the costs of IT development
    • Simplifying operational characteristics and resource requirements related to supporting multiple business units
    • Underestimating the difficulty in reconciling multiple legacy systems
    • Lack of staff resources and underestimating the risks of rework from parallel development
    • Failing to fully understand business unit requirements and how users relate to both data and systems
    Must engage the right people to clearly define requirements
  • 9. Key Findings: Construction Considerations What Works What Doesn’t Work
    • Understanding of user requirements (when application is needed, business functionality, ST vs. LT objectives) prioritized against budget
    • Definition of core business rules to be incorporated into validation and data loading process
    • Definition of testing and implementation strategies
    • Appropriate mix of internal and external personnel and process (skills transfer and effective change management)
    • Use of third party vendors in key portions of overall program
    • Reuse of functionality (assume 80% of functionality can be leveraged)
    • Subsequent data population efforts after initial project phase
    • Ability to demonstrate incremental and measurable progress to key stakeholders through iterative releases
    • Line up early adopters and maintain upfront constituencies
    • Normalization of definitions, attributes and field names for applications precision and ease of use
    • Ample test environments, product release version control and strong change management procedures
    • Use of regional teams to address local data feeds and mapping to local standards
    • Offshore resources for testing
    • Identification of specialized data requirements and unique applications requests
    • Separation of GUI development from backend mapping, enrichment and validation
    • Lack of centralized governance
    • Failure to apply regional feeds and hierarchical rules to counter-party processing
    • Limited knowledge transfer of components developed by external parties
    • Failure to adequately design mapping and domain table storage
    • Over engineering the EDM solution in complexity and detail
    • Over engineering the application construction process
    Building and rolling out the platform in phased increments is key
  • 10. Key Findings: Transition Considerations What Works What Doesn’t Work
    • Business continuity planning on a global basis and quality of MIS
    • Knowledgeable personnel to recognize how the output should appear and identify subtle data issues
    • Documentation, user guides, key operating procedures and training
    • Use of governance to prioritize operational users
    • Constant coordination with users and clear methodology to obtain user feedback and incorporate into future releases
    • Strong end user experience and data knowledge for those that interface with clients
    • End-to-end process definition and UAT with key hub regions (site visits, process walk-through, crib sheets, live telephone support, local presence)
    • Vendor SLA definition and management
    • Tight control over change and implementation plans
    • One-by-one migration of downstream systems (phased implementation)
    • Run new data sources in parallel and compare data (switch off old data sources when content is in sync)
    • Web-based user documentation and user support post initial training
    • Final UAT of central tool using original data sources
    • Allowing sponsors to be uninvolved
    • Underestimating the level of regional variance and resistance to new process
    • Minimizing the level of assistance required to help users understand an entirely new process
    • Underestimating the amount of MIS breaks and local IT support required
    • Insufficient guidance and Toolkits for adopters
    • Postponing training to the last minute
    • Failure to market product to users (alienation)
    • Adopting a “hot fix” mentality
    • Underestimating the importance of version control and scope of regression testing required
    Strong processes are needed to sell migration and support end user adoption
  • 11. Key Findings: Operate Considerations What Works What Doesn’t Work
    • Data model integrity and enforcement of data quality issues
    • Metrics that are needed to determine EDM return on investment (i.e. cycle time, new account creation, account data elements, overall data quality, process replication, processing timeframes)
    • Establishment and management of ongoing data ownership and stewardship
    • Coordination of new applications requirements from users and change control
    • Global maintenance and support
    • SLA process for managing vendors (i.e. feed updates, product enhancements, de-bugging)
    • Building procedures to ensure that the operational model is as well constructed as the data model
    • Continuing to roll out enhancements, refine and add business rules and improving validation checking
    • Implementing sign off process on changes and major releases
    • Establishing a governance program for small changes
    • Establishing a workstation for overrides
    • Maintaining error logs and reports
    • Creation of off-shore support team
    • Sponsor/steering committee satisfaction as gauge of success
    • Poor closure process (lessons learned, budget, benefits documentation)
    • Pushing for rapid change causing instability and data errors
    • Sporadic development after the initial phase is implemented
    • Underestimating the data clean up requirements
    • Underestimating the degree of difficulty in establishing a “go live” date across all global operations
    • Over validation of data causing conflicts in data ownership
    • Underestimating the importance of scalability requirements
    • Underestimating the impact of local variation in data and data usage (regional conflicts)
    Clear operational model needed to support new processes and future enhancements
  • 12. Working Group: Next Steps
    • Expand depth of data collection on current menu of implementation issues by issue, domain area, role and function
    • Extension of research process to cover
      • Governance structures, data stewardship approaches and communications alternatives
      • Internal versus external staffing (mix of buy, build, partner and outsource)
      • Vendor selection and management
      • Strategies to introduce and expand EDM solutions
      • Practical transition management
      • Data validation and quality control processes
      • Implementation metrics and benchmarks
    • Development of EDM infrastructure
      • Repository of EDM best practices and mechanism for ongoing contribution
      • Network of experts and online contact lists
      • Web site functionality (message board)