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Institutionalize Your Data: Designing and Implementing a Dynamic Blueprint for Data Governance and Management

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Title: Institutionalize Your Data: Designing and Implementing a Dynamic Blueprint for Data Governance and Management


1
Institutionalize Your DataDesigning and
Implementing a Dynamic Blueprint for Data
Governance and Management
Julianna Sakamoto, Senior Manager,
Informatica jsakamoto_at_informatica.com Tel.
650-385-5010
Provided for DFW DAMA Meeting on July 18th
1130 am to 130pm
2
Welcome
  • Critical Time to Examine Your Data Governance and
    Management Practice
  • Sarbox 3rd year Foreign companies on the US
    exchange mandated to comply
  • Business is NOT as usual Our Webinar attracted
    881 registrants!
  • Even playing field in a flattening world or is
    it?
  • Scope
  • Intentionally kept broad to meet varying degrees
    of interest and experience levels
  • Perhaps follow-on break-up sessions or workgroups
    in the future?
  • Some sections will be for reference or further
    reading only
  • Electronic copies available
  • Follow-ups
  • Julianna Sakamoto, jsakamoto_at_informatica.com,
    cell 415-407-4817
  • Informatica Team

3
Agenda
  • Importance of Dynamic Blueprint to Data
    Governance and Management
  • Heightened Need of Data-Driven Approach
  • Challenges of Linking Data to Corporate Measures
  • Agile Data Governance and Management
  • Expanding the Definition of Data Governance
  • Best Practices for Securing Endorsement and
    Program Initiation
  • Case Study Financial Services
  • Initiative Engagement Start to Finish
  • Establish Practice Development Strategy
  • Design an End State and Conduct Gap Analysis
  • Identify Quick Wins and Design Project Plan
  • Establish Resource Plan and Team Model
  • Measure and Control Goals
  • Transition to Expanded Scope
  • PowerCenter for Automating Data Governance and
    Management Tasks
  • QA and Open Discussions

4
Importance of Dynamic Blueprint to Data
Governance and Management
5
Elevated Expectation and Anxiety Around Data
Governance
Data governance is the new reality Data
governance and compliance is the new reality,
many attendees said, changing the way they work.
The emphasis on governance gives data management
more visibility in the corporate world. Data
quality is taken more seriously, data integration
is a necessity, and security is an imperative,
not a luxury, attendees said. A competitive
global marketplace and laws such as
Sarbanes-Oxley bring the promise of increased
resources -- but the pitfalls of higher stakes.
Source DAMA International Symposium and Wilshire
Meta-data conference, April 2006
6
Sarbanes-Oxley Adverse Reports over Internal
Control Decreased in Year 2
Industry Sector Adverse Reports Adverse Reports Industry Total Industry Total Adverse Adverse
  2004 2005 2004 2005 2004 2005
Automotive 10 8 72 53 14 15
Banking Capital Markets 57 17 484 469 12 4
Energy Utilities 42 20 285 265 15 8
Entertainment Media 44 14 204 161 22 9
HealthCare Government 8 7 93 79 9 9
Industrial Products 78 18 480 349 16 5
InfoComm 28 16 130 97 22 16
Insurance 10 8 136 141 7 6
Investment Management 1 0 14 13 7 0
Pharmaceutical 22 6 223 191 10 3
Real Estate 21 7 197 205 11 3
Retail Consumer 66 18 337 235 20 8
Services 43 23 275 226 16 10
Technology 136 37 703 433 19 8
Grand Total 566 199 3633 2917 16 7
  • Adverse reports on the decline
  • 16 to 7
  • Marked (gt10) improvements
  • Entertainment Media
  • Industrial products
  • Retail Consumer
  • Technology
  • Lowest of adverse report 05
  • Banking Capital Markets
  • Pharmaceutical
  • Real Estate

Source PricewaterhouseCoopers Webcast, May 06
7
Heightened Need for Data-Driven Approach
  • Applying Six Sigma Concept for Certifying Data
  • Bring rigor and measurements in data management
  • Cornerstone for corporate performance management
  • Increased Layering of Frameworks for Auditability
  • Increasing use of ITIL, CobiT, COSO, and ISO
    9000/17799
  • Refining accountability and transparency to drive
    organization-wide participation
  • Attempt to Link IT Investments to Compounding
    benefits Institutionalize Data as Strategic
    Asset
  • Participation in revenue-driving activities
    beyond traditional IT cost reductions and risk
    management
  • Off-shore/onshore IT outsourcing prevalent with
    large companies

8
Continued Challenges in Linking Data to Business
Value
Data Governance Metric
Business Value-Driven
IT Issue?
Business Issue?
Revenues Cost Risk
Regulatory Compliance
Business Performance Goals
Business Rules
Roles and Processes
Stewardship Definition
Certification
Or Both?
Reports
  • Customer Campaign
  • Access Control
  • Fraud Detection
  • Reconcilability
  • Supply Chain Costs
  • Audit Trails
  • Distribution Management
  • Legacy Data
  • On-Demand Availability
  • Regulatory Compliance
  • Accuracy
  • Privacy Risk

9
Dynamic Blueprint Agility as Part of DNA
Compliance-Driven Internal Control Design Detective Vs. Preventive Measures Risk Level Assignment Automated Vs. Manual Controls Safeguarding Of Confidential Data Revenue-Driven Pricing Optimization Cross-sell / Upsell Sales And Distribution Management New Customer Acquisition Collection And Fraud Prevention
Cost-Driven Supply Chain / Inventory Management Efficiency Partner/Supplier Negotiation (merchant/sell-side) Invoice, Billing and Credit Management IT management - tool and human resource use RD and Product Development/Delivery Risk-Driven Enterprise Business Risk Asset /Financial Performance Management Risk Business Continuity/ Disaster Recovery Risk Personnel/Organizational Risk Geopolitical Risk
Dynamic blueprint - value-driven approach to
data governance validated through incremental
project progression tuned to business demand
10
Expanding the Definition of Data Governance
11
Governance Historical Context
Corporate Governance The set of processes,
customs, policies, laws and institutions
affecting the way a corporation is directed,
administered or controlled.
IT Governance The leadership and organizational
structures and processes that ensure that the
organizations IT sustains and extends the
organizations strategies and objectives.
Data Governance The processes, policies,
standards, organization and technologies required
to manage and ensure the availability,
accessibility, quality, consistency, auditability
and security of data in a company or institution.
Business Processes
CRM System
ERP System
Order Mgmt System
Finance System
HR System
12
Expanded Data Governance Framework to Underscore
Importance of Technology
Corporate Governance The set of processes,
customs, policies, laws and institutions
affecting the way a corporation is directed,
administered or controlled.
IT Governance The leadership and
organizational structures and processes that
ensure that the organizations IT sustains and
extends the organizations strategies and
objectives.
Data Governance
Data Accessibility
Data Availability
Data Auditability
Data Consistency
Data Quality
Data Security
Standards
Organization
Policies Processes
Data Integration Infrastructure
13
Financial Services Customer Case StudyEnabling
Enterprise Integration via Metadata Management
  • Key Business Requirements
  • Meet statutory requirements BASEL II, Sarbox,
    etc.
  • Improve reporting and management decision
  • Facilitate future development of analytical
    applications

Go to the Data Governance Tool Readiness
Assessment
  • Approach
  • Provide a consistent and integrated data
    integration mechanism for management and
    reporting
  • Allow impact analysis before project initiation
  • Simplified reporting reconciliation processes
  • Improved management decision processes and
    outcomes
  • Mitigated cost/impact from potential
    non-compliance
  • Improved estimates for change costs
  • Informatica PowerCenter
  • Oracle, SQL Server, Teradata, Sybase, SQL
    servers, DB2, Cognos, Erwin
  • PowerCenter Metadata Manager 2.1
  • Metadata directory, search, lineage and
    where-used reports
  • Inability to automate metadata source handling
  • Inability to retain knowledge even with IT staff
    departures and project completions
  • Lack of clear KPI definitions
  • Uncertainty with project costing

14
Financial Service Customer Case StudyData
Governance Self-Assessment Map
Data Quality Lifecycle Management (Scorecard,
Monitoring, and Remediation) Data
Profiling Data Cleanse and Match
Server Grid Push-Down Optimization Data
Federation Real-Time Partitioning
Data Quality
Data Consistency
Data Availability
Metadata Management Dashboard, Data Lineage,
Impact Assessment and Data Dictionary/Business
Glossary
Data Accessibility
Data Auditability
Unstructured Data Mainframe Legacy
Data Security
Team-based Deployment Encryption
Support Privilege Management Data Classification
15
Best Practices for Securing Endorsement and
Program Initiation
16
Guiding Principles for Program Initiation
  1. Begin with a clear top-down mission statement and
    key performance indicators that will be boosted
    by the program
  2. Make data management as an integral part of the
    corporate governance and oversight process not
    a separate new initiative
  3. Embed the new standards, practices and processes
    into existing functioning framework where
    applicable
  4. Seek to align with stakeholders and business
    owners to dissolve resistance and accelerate
    approval cycles
  5. Drive visible wins through selected subject
    areas or data governance metrics according to
    value and risk levels

17
5 Phases of the Data Governance and Management
Program
  • Dynamic Blueprint approach

Phase 1. Establish Vision, Framework and Metrics
Phase 3. Conduct Readiness Assessment
Phase 4. Secure Program Endorsement
Phase 5. Conduct Initiative Engagement
Phase 2. Institute Policies and Design Principles
  • Policy
  • Integrated planning cycles
  • Foundational architecture
  • Stewardship
  • Usage validation
  • Data standards and quality
  • Audit processes
  • Design Principles
  • Information classification
  • Record retention and disposal
  • Functional areas
  • Metadata management
  • KPI measurement
  • Risk management
  • Training communications
  • Shared services

Step 1 Establish Practice Development
Strategy Step 2 Design End State and Conduct Gap
Analysis Step 3 Identify Quick Wins and Design
Project Plan Step 4 Establish Resource and Team
Model Step 5 Measure and Control Goals Step 6
Transition to Expanded Scope
  • Vision
  • Mission statement
  • People, process and technology
  • Deployment scope
  • Phased delivery strategy
  • Governance metric
  • Availability
  • Accessibility
  • Auditability
  • Consistency
  • Quality
  • Security
  • Value proposition
  • Linking investments to returns
  • Steering committee formation
  • Assessment model
  • Cultural and behavioral
  • Tool usage maturity
  • Control design
  • Preventive vs. detective
  • Automated vs. manual
  • Assessment results
  • End-state goal setting
  • Gap analysis
  • Role-based mapping
  • Stakeholder analysis
  • Communication and training
  • Program Planning
  • Identification of areas most prepared
  • Exec sponsorship
  • Early adopters and supporters feedback
  • Community of practice
  • Business Case
  • LOB initiatives/pain points
  • Dynamic blueprint
  • Regulatory compliance
  • Revenue boost
  • Cost reduction
  • Risk mgt
  • Financial and op. analysis and buy-ins
  • Value/risks defined
  • Proposal/Approval

18
Financial Services Customer Case Study For Data
Governance and Management
19
Financial Services Firm Best PracticesPhase 1
Establish Vision, Framework and Metrics - 1
  • Vision
  • The firm manages information as an integrated
    enterprise asset
  • Organizations must plan their future needs, and
    effectively utilize and manage information to
    support decision making processes
  • Corporate standards and governance must be
    established in conjunction with the IT
    transformation
  • Guiding Principles
  • Data must be managed as an integrated business
    asset
  • Data standards, policies and processes must be
    institutionalized
  • Standards for corporate governance, IT governance
    and data governance are to be re-established
  • Key Success Factors
  • Launched by CFO and supported by finance and LOB
  • Business leadership provides oversight and
    day-to-day support for key subject areas
  • IT governance committee and other leaders guide
    architecture and tool selection process in
    concert with directives from business

20
Financial Services Firm Best Practices Phase 1
Establish Vision, Framework and Metrics - 2
  • People
  • Identification of existing programs
  • Accountability mapped to functional areas and
    processes
  • Key stakeholders apprised of project
    deliverables, milestones and gating factors
  • Process
  • Integrated, planned and coordinated lifecycle
    approach
  • Regular and ad-hoc work activities structured to
    manage in support of business objectives
  • Operating model and rollout defined
  • Technology
  • Implementation of end-to-end financial reporting
    system
  • Enterprise-wide data warehouse
  • Common infrastructures, standards and interfaces
  • Scope
  • Areas for financial planning, budgeting,
    allocations, forecasting, and regulatory
    reporting
  • Phased Delivery Strategy
  • First Year Enterprise-data warehouse
  • Mid- Master data/Data governance certification
  • Latter stage Linking to business KPI
  • Data Governance Metrics
  • Initial focus on Quality
  • Accessibility improved through master data
    approach
  • Auditability and Consistency considered crucial
  • Access control and classification key to Security
  • Availability tuned to reporting cycles

Value Proposition Gain more accurate and
reliable forecasting, and the reporting
architecture to ensure timely response to
business changes Linking Investments to
End-State Goal World-class organization through
business and IT innovation Reinforced value of
data
Steering Committee Formation
Executive Sponsor
Business Partners and Domain SME
Technology / Project Leadership
21
Financial Services Firm Best Practices Phase
2 Institute Policies and Design Principles -1
Data Governance and Management Policies
(Operating Guidelines and Rules)
  • Integrated planning cycle
  • Data management as formalized discipline
  • Planning for acquisition, creation,
    transformation, usage and retention lifecycle
  • Stewardship
  • Accountability for data management to treat data
    as an asset
  • Business definitions and standard guidelines
  • Consistent interpretation of information
  • Data standards and quality
  • Standard descriptions and common libraries
  • Monitoring, reporting and anomaly prevention
  • Accuracy, conformity, completeness, consistency,
    duplicates and integrity as data quality
    solution considerations
  • Audit processes
  • Walkthrough and testing guidelines according to
    control and risk levels
  • Classification of preventive versus detective,
    and manual versus automatic measures
  • Certification workflow
  • Foundational architecture
  • Organizational, solution and IT architectures
    designed to maximize value
  • Enabler to formalized data management and
    governance practice
  • Usage validation
  • Data usage patterns defined and validated
  • Tasks performed by authorized individuals
  • Data in custody managed in compliance with
    privacy security, compliance and other legal
    requirements

22
Financial Services Firm Best Practices Phase 2
Institute Policies and Design Principles - 2
Data Governance and Management Design Principles
(Structures and Methodology)
  • Information classification
  • Information inventory
  • Supporting resources
  • Functional and subject area
  • Domain use/reuse
  • Record retention and disposal
  • Retention period by class
  • Secure disposal according to biz, legal and
    regulatory mandates
  • Record keeping
  • Functional areas
  • Subject area model
  • Boundaries and accountabilities
  • Process integration
  • Common and reusable structure
  • Metadata management
  • Integrated repository
  • Data flow validation
  • Reconciliation across formats, categories, and
    types
  • KPI measurement
  • Target metric and definition
  • Prioritization and categorization framework
  • Review model
  • Alignment to organizational goals
  • Risk management
  • In/out of scope
  • Indicators and impact
  • Likelihood analysis
  • Control designs
  • Preventive / detective -testing
  • Automation
  • Training communications
  • Data treatment cultural assessment
  • Gap analysis
  • Foundational messages
  • Logistic and frequency
  • Shared services
  • Service definition
  • Resource design
  • Model design mix of distributed and
    centralized
  • Business partners
  • Practice development

23
Financial Services Firm Best Practices Phase 3
Conduct Readiness Assessment
  • Assessment results
  • End-state goal setting
  • Unified process, infrastructure and format for
    GL
  • Timeliness and precision for monthly, quarterly
    and annual reporting
  • Full change management capture and traceability
  • Gap analysis
  • Completeness and consistency in documentability
    key risk areas
  • AP handling/legacy retirement
  • Enterprise risk model/reporting integrity
  • Excessive low/no value-added activities
  • Role-based mapping
  • Workflow control and exception handling
  • Stakeholder analysis
  • Impact and risk areas for regular reporting
    cycles and Sarbanes-Oxley walkthrough
  • Communication and training
  • Part of the career development program
  • Assessment model
  • Cultural and behavioral
  • Interviews of selected employees and management
  • Tool usage maturity
  • Quantitative and qualitative
  • Deployed and planned
  • Control design
  • Control selection
  • Evaluation metric for controls
  • Preventive vs. detective
  • Data asset inventory
  • Assign risk class and resulting control type
  • Automated vs. manual
  • Kept open initially
  • Policy-based mitigation for control that cannot
    be automated

24
Financial Services Firm Best Practices Phase 4
Secure Program Endorsement - 1
Progressive Expansion of Focus - Focus 1 High
Priority Segments ? Focus 2 Cost Reduction ?
Focus 3 Enterprise Risk and Revenue Optimization
Compliance-Driven Internal Control Design Detective Vs. Preventive Measures Risk Level Assignment Automated Vs. Manual Controls Safeguarding Of Confidential Data Revenue-Driven Pricing Optimization Cross-sell / Upsell Sales And Distribution Management New Customer Acquisition Collection And Fraud Prevention
Cost-Driven Supply Chain / Inventory Management Efficiency Partner/Supplier Negotiation (Merchant/Sell-side) Invoice, Billing And Credit Management IT Management - Tool And Human Resource Use RD And Product Development/Delivery Risk-Driven Enterprise Business Risk Asset /Financial Performance Management Risk Business Continuity/ Disaster Recovery Risk Personnel/Organizational Risk Geopolitical Risk
25
Financial Services Firm Best Practices Phase 4
Secure Program Endorsement - 2
Focus Area 1 Focus Area 2 Focus Area 3
Compliance Internal Control Design
Detective And Preventive Measure
Risk Level Assignment
Automated Vs. Manual Control
Safeguarding Of Confidential Data
Revenue Pricing
Cross-sell / Upsell
Sales Distribution Management
Cost Supply Chain / Inventory Management Efficiency
Partner/Supplier Negotiation (Merchant/Sell-side)
Invoice, Billing And Credit Management
Risk Enterprise Business Risk
Asset Management / Financial Performance Risk
26
Financial Services Firm Best Practices Phase 4
Secure Program Endorsement - 3
  • Compliance
  • Demonstrate adherence to internal control
    through clear workflows and system design
  • Risk-driven approach to manage audits
  • Control related policy and enforcement practice
    in place

Focus Area 1 Goal Justify High Priority Segments
Steering Committee
Executive Sponsor
Business Partners and Domain SME
  • Revenue
  • Better, more targeted pricing model,
    differential to segments and customer behaviors
  • Developing customer master data to ensure
    completeness for cross-sell and upsell

Technology / Project Leadership
Relevant benefits articulated to each segment
  • Program Planning
  • Identification of areas most prepared
    Selected corporate IT and Finance Dept
  • Exec sponsorship CFO/CIO
  • Early adopters and supporters feedback
    Reflected in the vision, policies and design
    principles
  • Community of practice Practice
    development phase
  • Cost
  • Stop non-value added activities for agents
    related to invoicing, billing and credit
    management
  • Remove unnecessary documentation and codes that
    require maintenance cost
  • Risk
  • OUT OF SCOPE

27
Financial Services Firm Best Practices Phase 4
Secure Program Endorsement - 4
Focus Area 2 Goal Drive Cost Reduction
  • Compliance
  • SUSTAIN FOCUS AREA 1 EFFORT

Steering Committee
Executive Sponsor
Business Partners and Domain SME
  • Revenue
  • SUSTAIN FOCUS AREA 1 EFFORT

Technology / Project Leadership
Relevant benefits articulated to each segment
  • Program Planning
  • Identification of areas most prepared
    Added supply chain and partner management
  • Exec sponsorship Added VP and partner
    execs
  • Early adopters and supporters feedback
    Domain SME integrated
  • Community of practice Reuse existing
    best practice within subject areas
  • Cost
  • Provide metadata-driven supply master to handle
    complex network of supply chain relationships
  • Unify the partner merchant negotiation data
    systems so that agents can us
  • Risk
  • Lay foundation for business partner risk
    management
  • Model data flows and dependencies associated
    with business relationships
  • Assess risk impact and likelihood

28
Financial Services Firm Best Practices Phase 4
Secure Program Endorsement - 5
Focus Area 3 Goal Secure Enterprise Risk and
Revenue Optimization
  • Compliance
  • Increased automation versus manual control for
    cost containment and liability mitigation
  • Align treatment of confidential data with
    security and privacy practice

Steering Committee
Executive Sponsor
Business Partners and Domain SME
  • Revenue
  • Increased oversight for partner management with
    the use of metadata management
  • Add reference data from sales distribution to
    leverage customer and product data optimally used
    for planning

Technology / Project Leadership
  • Program Planning
  • Identification of areas most prepared
    Mobilized corporate IT and selected lines of
    business
  • Exec sponsorship Expanded to include
    major BU
  • Early adopters and supporters feedback
    Formal survey and training in place
  • Community of practice Reestablishing
    best practice

Relevant benefits articulated to each segment
  • Cost
  • SUSTAIN FOCUS AREA 2 EFFORT
  • Risk
  • Launch an integrated risk management tied to
    financial and asset management
  • Initiate automated correlation and verification
    for risk assessment data for future expansion

29
Initiative Engagement Start to Finish and
Expand Scope
30
Resource Model Integrated with Data Governance
and Management Initiative
Integral to all aspects of practice development,
sensible strategy design and execution
  • Enterprise Integration Strategy and Development
    Services
  • Enterprise Architecture
  • Data Integration Services
  • Business Process Improvement
  • Data Warehouse Development
  • Reporting Services
  • IT Security
  • Practice
  • Policy, Standards and Guidelines
  • Corporate Standards
  • Tools
  • Training
  • Implementation Support
  • Operations
  • KPI Measures
  • Reporting

Key Subject Areas / Lines of Business
Extended Partners
Financial Reporting
Audit
Corporate IT
Integration Competency Center (ICC)
Governance Steering Committee
Legal
Compliance
Departmental
Privacy
Risk Management
BU
31
Phase 5 Conduct an Initiative
EngagementOverview of Six Steps
  • Step 1 Establish Practice Development Strategy
  • Step 2 Design End State and Conduct Gap Analysis
  • Step 3 Identify Quick Wins and Design Project
    Plan
  • Step 4 Establish Resource and Team Model
  • Step 5 Measure and Control Goals
  • Step 6 Transition to Expanded Scope

32
Phase 5 Conduct an Initiative EngagementStep 1
Establish Practice Development Strategy -1
Accessibility Auditability Availability Consistenc
y Quality Security
Management Infrastructure
Data Valuation
Data Governance Metric
Existing Practice
Project silos dominate without organization-wide
standards
Information classification and controls designed
Departmental readiness evaluated quality
considered major
Areas for Improvement
People, technology, process misalignment
Valuation incomplete Stakeholders with different
lists and metrics
No enterprise-wide program formalized
Developmental Goals
Integrated, reusable architecture Formalized
stewardship
Unified data asset valuation with common
vocabulary and classes
Institutionalized data governance and management
monitoring and tracking
  • To succeed, data governance and management
    program must include practice development
    strategy and plan in place

33
Phase 5 Conduct an Initiative Engagement Step
1 Establish Practice Development Strategy - 2
  • STEP 1 Checklist
  • Review existing templates and documents to
    pinpoint deficiencies
  • Identify and interview key affinity groups and
    business users
  • Identify key business initiatives that will gain
    benefits when practice is developed
  • Determine what areas of data governance metric
    improvement provide accelerated value to those
    initiatives
  • Fully understand development needs
  • Identification of key subject and functional
    areas
  • Individual or group-level educational
    requirements
  • Design a stewardship development plan
  • Objectives, scope and tasks
  • Identify educational vehicle
  • Create a progressive plan to adapt to changing
    infrastructure
  • Practice development tasks

34
Phase 5 Conduct an Initiative Engagement Step
1 Establish Practice Development Strategy - 3
Enter here based on interviews
  • ltExample Stewardship Plangt - can take different
    forms but important to assess existing roles and
    activities

Data Accountability Standards Developmental Areas
Strategic Stewards Objective Top-down, risk-driven value creation Scope Executive-Level Task Ensure strategic alignment with corporate goals, focus on enterprise-level. Domain area intervention as needed
Operational Stewards Objective Supervision and operational oversight of policies, standards and guideline enforcement Scope Program-Level Task Sustain operational activities and meet guidelines
Domain Stewards Objective Implementation of guidelines Scope Business/Functional Level Task Work performed to the specified requirements
35
Phase 5 Conduct an Initiative EngagementStep 2
Design End State and Conduct Gap Analysis -1
Example Focus Area 1 High Priority Segment
Current State Business Impact End State Solution to Address Gap Investment Reqd
Internal control classification and design in place Used for regular walk-through with auditors. Extensive testing Automating preventive measures End-to-end integration with access security and full dashboard control High
Risk level assigned without being integrated with financial reporting system Bottom-up examination o f ALL types of financial transactions Continuous regular and material event reporting with sufficient evidence Enterprise risk framework integrated with data entry and reporting cycles Medium to High
Missing invoice and inaccurate description of products and services rendered Days sales outstanding impact Low performing cash flow management Complete, accurate invoice management End-to-end order mgt Integrated handling of structured and unstructured data. Data profiling and quality management Low
Limited understanding of customer profiles Inefficiencies in sales promotions Dynamic packaging of prod/services with differential pricing Master data Integrated Metadata and Data Quality Management High
Focus Area 1 Focus Area 1
Compliance Internal control design
Detective and preventive measure
Risk level assignment
Automated vs. Manual control
Safeguarding of confidential data
Revenue Pricing
Cross-sell / upsell
Sales distribution management
Cost Supply chain / inventory management efficiency
Partner/supplier negotiation (merchant/sell-side)
Invoice, billing and credit management
36
Phase 5 Conduct an Initiative EngagementStep
2 Design End State and Conduct Gap Analysis -2
  • STEP 2 Checklist
  • Enumerate pain areas for the focus area
  • Complete gap assessment sheet through walkthrough
    and interviews
  • Examine both tangible and intangible factors
    impacting the results
  • Identify key affinity groups, supporters and
    champions who will support the cause
  • Conclude this step with a proposed master plan
  • Pragmatically select Gap areas can be used as
    an Exemplary case
  • Areas of visible governance issues
  • Combined use of policy and guidelines
  • Characterization of before / after in hours/work
    impact
  • Test / prototype solutions/suggested changes
  • Small areas that can be tested short term
  • Validate stewardship model
  • Identify areas for elimination or retirement
  • Removal of non-value added activities

37
Phase 5 Conduct an Initiative EngagementStep 3
Identify Quick Wins and Design Project Plan - 1
IMPERATIVE - Disciplined Approach to Balancing
Strategic Agenda and Tactical Activities. Choose
Nature and Degrees of Involvement According to
Value Delivery
Initiative Engagement
Program Involvement
Value Nature Degree
Strategic
Operational
Domain
Operational
38
Phase 5 Conduct an Initiative EngagementStep 3
Identify Quick Wins and Design Project Plan - 2
Process for evaluating new initiatives as well as
qualify and stage them in the overall master plan.
  • Internal selling of the data governance and
    management program for Business Value delivered
  • Overview of automated, reusable solutions vs.
    hand-coded alternatives
  • Proof of usability and validity
  • Continued supporting during project lifecycle

Initiative Lifecycle
39
Phase 5 Conduct an Initiative EngagementStep
3 Identify Quick Wins and Design Project Plan - 3
  • STEP 3 Checklist
  • Conduct initial projects either with policy /
    guidelines or ideally with add-on solutions
  • Assess the results within the core team
  • Design a pragmatic project plan for 3-6 month
    cycle with the vision for 2-3 years
  • Conduct small team meetings to refine a plan
  • Seek an approval of a proposed project plan with
    initial results
  • Demonstrate the value through early projects
  • Hours saved, dollars collected, more strategic
    assignments, etc.
  • Shut down non-value added components
  • Get proof points on validity, applicability and
    recommended areas for future implementation
  • Anecdotal stories about paybacks
  • Perception-building through active dialogs
  • Position to extend value through an extended pool
    of resources
  • No major full-headcounts yet! Early adopters and
    champions to grow the extended team

40
Phase 5 Conduct an Initiative EngagementStep 4
Establish Resource and Team Model - 1
For Initiative Engagement, while investment
returns vary by environment, gradual move toward
Shared Services may often yield better results
Integration Competency Center Models
Central Services
Shared Services
Technology Standards
Best Practices
Project Silos
Technology
Processes
Organization
Independent
Independent
Independent
Recommend
Defined
Distributed
Standardized
Defined
Distributed
Shared
Defined
Hybrid
Shared
Defined
Centralized
Benefits
Project Optimization
Leverage knowledge
Consistency
Resource optimization
Control
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Phase 5 Conduct an Initiative EngagementStep 4
Establish Resource and Team Model - 2
Inner working of the data stewardship activities
  • Steering Committee nominate resources to work
    with team lead and assign stewards
  • Data Stewards perform tasks with team leads
  • As needed, stewards work with team members
    directly
  • Analysts, SMEs and Metric Experts (HA, security,
    quality, etc.) work as a team
  • Data Integration provides resources and work with
    IT strategy and architect team

IT Strategy and Architect Team
Steering Committee
Data Stewards
Data Integration Expert (s)/ Resource (s)/ ICC
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Phase 5 Conduct an Initiative EngagementStep 4
Establish Resource and Team Model - 3
  • STEP 4 Checklist
  • Develop task descriptions and qualification
    guidelines
  • Informally interview or ask for referrals to
    identify advocates
  • Look for champions who are both business and
    technology savvy (all areas of IT)
  • Identify skill gaps
  • Seek approval of a proposed resource plan
    including skill development
  • Design a team model and resource plan
  • Emphasis on initiative engagement
  • Previous experience and problem-solving mindset
    plus
  • Alternative approaches to be presented
  • Provide scenario assessment
  • Pros and cons of specific resource model and
    requirements
  • Risks and open issues clarified
  • Get endorsement for a small team
  • Secure baseline to demonstrate focus area value
  • Communication and training plan in place

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Phase 5 Conduct an Initiative EngagementStep 5
Measure and Control Goals
  • STEP 5 Checklist
  • Get updated on businesses about their current
    directions
  • Verify whether the current data governance
    initiatives are generating intended results
  • Clearly document root cause analysis results if
    the results are less than what you expected
  • Make a call whether you proceed with the current
    scope or alter dont make a huge change
    incremental ones only
  • Ensure ongoing communication
  • IT investment defined tangible/intangible
  • Value revenue, cost, compliance and risk
  • Particular components worked/worked less
  • Make small incremental changes tuned to business
    needs
  • Delivery of results and incremental changes
    reflective of ongoing business changes
  • Positive organizational impact highlighted
  • Get support for developmental areas
  • Reinforcement for people, process and technology
  • Communication and training plan in place

44
Phase 5 Conduct an Initiative EngagementStep 6
Transition to Expand Scope - 1
  • STEP 6 Checklist
  • Use the initiative engagement results as a guide
    to approach target BU or functional areas
  • Project prospective results what if you
    expanded scope to the next areas
  • Examine all metrics that are to be affected by
    the expanded scope
  • Revise a project plan with an expanded scope
  • Step up to evaluate and use tools to automate and
    move preventive
  • Perform rigorous assessment on the initiative
    phase
  • Reassessment on architecture, tools, skill sets,
    processes, training, and communication
  • Organization dynamics
  • Get departmental/functional buy-ins to expand
    scope
  • Current major objectives defined
  • Find small ways to make a difference
  • Progressively automate with an expanded scope
  • Incremental value add defined with less risk
  • Preventative, automated measure in place

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Phase 5 Conduct an Initiative EngagementStep 6
Transition to Expand Scope - 2
Key Subject Areas / Lines of Business
Operational Areas
  • Select specific areas of implementation

Financial Reporting
  • Re-alignment
  • Buy-in
  • Resourcing
  • Role augmentation
  • Deployment
  • Training
  • Hand-off

Audit
Legal
Compliance
Privacy
Risk Management
Assess
Assess
Governance Steering Committee
Implement
Implement
Realign
Go Live
Go Live
Realign
Measure
Measure
Program Direction
Integration Competency Center (ICC)
Technology Enablement
Departmental
Extended Partners
Corporate IT
BU
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Lessons Learned
  • Achieve sponsorship and organizational alignment
    with a compelling business case quickly
  • Linking the data governance to a major business
    initiative such as SOX or Basel compliance, or
    merger consolidation becomes a thrust for
    executive buy-in and funding approval
  • Utilize supporting tools and methodologies to
    accelerate approval and implementation cycles
  • Maturity assessment tool and economic value of
    data framework raise the profile of data
    governance and management
  • Progressively increase automation to reduce
    personnel or culturally driven issues, as well as
    to normalize changes
  • Preventive measures help mitigate cost impact and
    risks
  • Ensure communications and training to promote a
    new mindset and vigorous approach toward data
  • Making data asset management as part of the DNA
    keep it simple and robust

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Concluding Remarks
48
PowerCenter 8 - Platform for Automating Data
Governance and Management Tasks
DATA CONSUMERS
INTERNAL
EXTERNAL
DATA SOURCES
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Harnessing the Power of Data through an Automated
Approach
  • Exploiting Data Management Technology for
    Business Performance
  • Take a unified approach to data integration
  • Ensure data standards as the cornerstone of an
    effective data governance and management program
  • Institutionalize your data
  • Applications come and go, but the data largely
    stays the same
  • Data governance and management decisions you make
    today will have profound impact on your business

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