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1
Institutionalize Your Data:
Designing and Implementing a Dynamic Blueprint for Data Governance and Management
Julianna Sakamoto, Senior Manager, Informaticajsakamoto@informatica.comTel. 650-385-5010
Provided for DFW DAMA Meeting on July 18th – 11:30 am to 1:30pm
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@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
• Q&A and Open Discussions
4
Importance of Dynamic Blueprint to Data Governance and Management
5
Elevated Expectation and Anxiety Around Data Governance
Source: DAMA International Symposium and Wilshire Meta-data conference, April 2006
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.”
6
Sarbanes-Oxley Adverse Reports over Internal Control Decreased in Year 2
Industry Sector Adverse Reports Industry Total % 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 (>10%) 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
• Audit Trails• Legacy Data
• Access Control• Reconcilability
Business Value-Driven
Revenues Cost Risk
• On-Demand Availability• Accuracy
Reports
Regulatory Compliance
Business Performance Goals
Business Rules
Roles and Processes
Stewardship Definition
Certification
• Supply Chain Costs• Distribution Management
• Customer Campaign• Fraud Detection
• Regulatory Compliance• Privacy Risk
IT Issue?
Business Issue?
Or Both?
9
Dynamic Blueprint – Agility as Part of DNA
Dynamic blueprint - value-driven approach to data governance validated Dynamic blueprint - value-driven approach to data governance validated through incremental project progression tuned to business demandthrough incremental project progression tuned to business demand
Compliance-Driven
1. Internal Control Design
2. Detective Vs. Preventive Measures
3. Risk Level Assignment
4. Automated Vs. Manual Controls
5. Safeguarding Of Confidential Data
Revenue-Driven
1. Pricing Optimization
2. Cross-sell / Upsell
3. Sales And Distribution Management
4. New Customer Acquisition
5. Collection And Fraud Prevention
Cost-Driven
1. Supply Chain / Inventory Management Efficiency
2. Partner/Supplier Negotiation (merchant/sell-side)
3. Invoice, Billing and Credit Management
4. IT management - tool and human resource use
5. R&D and Product Development/Delivery
Risk-Driven
1. Enterprise Business Risk
2. Asset /Financial Performance Management Risk
3. Business Continuity/ Disaster Recovery Risk
4. Personnel/Organizational Risk
5. Geopolitical Risk
Focus 1Focus 2Focus 3
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 organization’s IT sustains and extends the
organization’s 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 ProcessesCRM
System ERP System Order Mgmt System
Finance System HR System
Customer Data
Product Data
Supplier Data
Finance Data
Employee Data
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 organization’s IT sustains and extends the organization’s strategies and objectives.
Data Governance
Data Integration Infrastructure
Standards Organization
Data Accessibility
Data Availability
Data Auditability
Data Consistency
Data Quality
Data Security
Policies & Processes
Enterprise Data Model
Data Definitions & Taxonomies
Master/Reference Data
Technology Standards
Data Access & Delivery
Data Definition Monitoring & Measurement
Data Change Management
Planning & Prioritization
Roles & Responsibilities
Organizational Structure
Org. Change Management
IntegrationCompetencyCenter (ICC)
Approach
Service-OrientedArchitecture– Data Services
Architecture
Data Integration
Platform
Technology
13
Challenge
Financial Services Customer Case StudyEnabling Enterprise Integration via Metadata Management
Solution Results
• 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
• 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
• Simplified reporting & reconciliation processes
• Improved management decision processes and outcomes
• Mitigated cost/impact from potential non-compliance
• Improved estimates for change costs
Key Business Requirements:• Meet statutory requirements – BASEL II, Sarbox, etc.• Improve reporting and management decision• Facilitate future development of analytical applications
Approach:• Provide a consistent and integrated data integration mechanism for management and reporting • Allow impact analysis before project initiation
Go to the Data Governance Tool Go to the Data Governance Tool Readiness AssessmentReadiness Assessment
14
0.0
1.0
2.0
3.0
4.0Data Quality
Data Consistency
Data Auditability
Data Security
Data Accessibility
Data Availability
Financial Service Customer Case StudyData Governance Self-Assessment Map
Data Accessibility
Data Quality
Data Security
Data Consistency
Data Auditability
Metadata ManagementDashboard, Data Lineage, Impact
Assessment and Data Dictionary/Business Glossary
Unstructured DataMainframe
Legacy
Data Quality Lifecycle Management (Scorecard, Monitoring, and
Remediation) Data Profiling
Data Cleanse and Match
Team-based DeploymentEncryption Support
Privilege ManagementData Classification
Data Availability
Server GridPush-Down Optimization
Data FederationReal-Time
Partitioning
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
Dynamic Blueprint approach Internal selling example
Focus for the second half
5 Phases of the Data Governance and Management Program
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
• 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
• 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
•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
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
18
Financial Services Customer Case Study For Data Governance and Management
19
Financial Services Firm Best Practices:Phase 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
Integrated planning cycle
• Data management as formalized discipline• Planning for acquisition, creation, transformation, usage and retention lifecycle
Data Governance and Management Policies (Operating Guidelines and Rules)
Foundational architecture
• Organizational, solution and IT architectures designed to maximize value• Enabler to formalized data management and governance practice
Stewardship• Accountability for data management to treat data as an asset• Business definitions and standard guidelines• Consistent interpretation of information
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
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
22
Financial Services Firm Best Practices: Phase 2: Institute Policies and Design Principles - 2
Information classification
• Information inventory• Supporting resources• Functional and subject area • Domain use/reuse
Data Governance and Management Design Principles (Structures and Methodology)
KPI measurement• Target metric and definition• Prioritization and categorization framework• Review model• Alignment to organizational goals
Record retention and disposal
• Retention period by class• Secure disposal according to biz, legal and regulatory mandates• Record keeping
Risk management• In/out of scope• Indicators and impact• Likelihood analysis• Control designs• Preventive / detective -testing• Automation
Functional areas• Subject area model• Boundaries and accountabilities• Process integration• Common and reusable structure
Training & communications
• Data treatment cultural assessment• Gap analysis• Foundational messages• Logistic and frequency
Metadata management
• Integrated repository• Data flow validation • Reconciliation across formats, categories, and types
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 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
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
24
Financial Services Firm Best Practices: Phase 4: Secure Program Endorsement - 1
Compliance-Driven
1. Internal Control Design
2. Detective Vs. Preventive Measures
3. Risk Level Assignment
4. Automated Vs. Manual Controls
5. Safeguarding Of Confidential Data
Revenue-Driven
1. Pricing Optimization
2. Cross-sell / Upsell
3. Sales And Distribution Management
4. New Customer Acquisition
5. Collection And Fraud Prevention
Cost-Driven
1. Supply Chain / Inventory Management Efficiency
2. Partner/Supplier Negotiation (Merchant/Sell-side)
3. Invoice, Billing And Credit Management
4. IT Management - Tool And Human Resource Use
5. R&D And Product Development/Delivery
Risk-Driven
1. Enterprise Business Risk
2. Asset /Financial Performance Management Risk
3. Business Continuity/ Disaster Recovery Risk
4. Personnel/Organizational Risk
5. Geopolitical Risk
Focus 1Focus 2Focus 3
Progressive Expansion of Focus - Focus 1: High Priority Segments → Focus 2: Cost Reduction → Focus 3: Enterprise Risk and Revenue Optimization
25
Financial Services Firm Best Practices: Phase 4: Secure Program Endorsement - 2
Focus Area 1 Focus Area 2 Focus Area 3
ComplianceInternal Control Design Detective And Preventive Measure Risk Level Assignment Automated Vs. Manual Control Safeguarding Of Confidential Data
RevenuePricing Cross-sell / Upsell Sales Distribution Management
Cost Supply Chain / Inventory Management Efficiency Partner/Supplier Negotiation (Merchant/Sell-side) Invoice, Billing And Credit Management
RiskEnterprise Business Risk
Asset Management / Financial Performance Risk
26
Financial Services Firm Best Practices: Phase 4: Secure Program Endorsement - 3
Revenue- Better, more targeted pricing model, differential to segments and customer behaviors- Developing customer master data to ensure completeness for cross-sell and upsell
Executives – Share holder value, earning and compliance accountability - CEO/CFO - CIO/CTO - BU General Managers and VP
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
Cost- Stop non-value added activities for agents related to invoicing, billing and credit management- Remove unnecessary documentation and codes that require maintenance cost
Focus Area 1 Goal: Justify High Priority
Segments
Finance, Legal and Operations- Financial integrity, liability and productivity measure - Auditors / Analysts - Controllers - Compliance officers - General counsel
Line of Business –Revenue, product and customer - Sales operations - Marketing - Customer analytics
IT Team – Productivity and cost containment - Enterprise architect. - Dir. Of IT - IT Analyst - Data modeling - Data warehouse manager
Risk- OUT OF SCOPE
Steering Committee
Executive Sponsor
Business Partners and Domain SME
Technology / Project Leadership
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
Rel
evan
t b
enef
its
arti
cula
ted
to
eac
h s
egm
ent
27
Financial Services Firm Best Practices: Phase 4: Secure Program Endorsement - 4
Revenue- SUSTAIN FOCUS AREA 1 EFFORT
Executives – Share holder value, earning and compliance accountability - CEO/CFO - CIO/CTO - BU General Managers and VP
Compliance- SUSTAIN FOCUS AREA 1 EFFORT
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
Focus Area 2 Goal: Drive Cost Reduction
Finance, Legal and Operations- Financial integrity and liability and productivity measure - Auditors / Analysts - Controllers - Compliance officers - General counsel
Line of Business –Revenue, product and customer - Sales operations - Marketing - Customer analytics
IT Team – Productivity and cost containment - Enterprise architect. - Dir. Of IT - IT Analyst - Data modeling - Data warehouse manager
Risk- Lay foundation for business partner risk management- Model data flows and dependencies associated with business relationships- Assess risk impact and likelihood
Steering Committee
Executive Sponsor
Business Partners and Domain SME
Technology / Project Leadership
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
Rel
evan
t b
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its
arti
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to
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egm
ent
28
Financial Services Firm Best Practices: Phase 4: Secure Program Endorsement - 5
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
Executives – Share holder value, earning and compliance accountability - CEO/CFO - CIO/CTO - BU General Managers and VP
Compliance- Increased automation versus manual control for cost containment and liability mitigation- Align treatment of confidential data with security and privacy practice
Cost- SUSTAIN FOCUS AREA 2 EFFORT
Focus Area 3 Goal: Secure Enterprise Risk and
Revenue Optimization
Finance, Legal and Operations- Financial integrity and liability and productivity measure - Auditors / Analysts - Controllers - Compliance officers - General counsel
Line of Business –Revenue, product and customer - Sales operations - Marketing - Customer analytics
IT Team – Productivity and cost containment - Enterprise architect. - Dir. Of IT - IT Analyst - Data modeling - Data warehouse manager
Risk- Launch an integrated risk management tied to financial and asset management- Initiate automated correlation and verification for risk assessment data for future expansion
Steering Committee
Executive Sponsor
Business Partners and Domain SME
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
Rel
evan
t b
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its
arti
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to
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29
Initiative Engagement – Start to Finish and Expand Scope
30
Resource Model Integrated with Data Governance and Management Initiative
Dep
art
men
tal
BU
Exte
nd
ed
P
art
ners
Inte
gra
tion
Com
pete
ncy C
en
ter
(IC
C)
Audit
Legal
Compliance
Privacy
Risk Management
Financial Reporting
Corp
ora
te
IT
Key Subject Areas / Lines of Business
Govern
an
ce S
teeri
ng
Com
mit
teePractice
• Policy, Standards and Guidelines
• Corporate Standards
• Tools
• Training
• Implementation Support
• Operations
• KPI Measures
• Reporting
Enterprise Integration Strategy and Development Services
• Enterprise Architecture
• Data Integration Services
• Business Process Improvement
• Data Warehouse Development
• Reporting Services
• IT Security
Integral to all aspects of practice development, sensible strategy design and execution
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
To succeed, data governance and management program must include practice development strategy and plan in place
Existing Practice
Areas for Improvement
Developmental Goals
Management Infrastructure
Project silos dominate without organization-wide
standards
Integrated, reusable
architecture; Formalized stewardship
People, technology,
process misalignment
Data Valuation
Information classification and controls designed
Unified data asset valuation with
common vocabulary and
classes
Valuation incomplete;
Stakeholders with different lists and
metrics
Data Governance Metric
Departmental readiness
evaluated – quality considered major
Institutionalized data governance and management monitoring and
tracking
No enterprise-wide program
formalized
AccessibilityAuditabilityAvailabilityConsistencyQualitySecurity
33
Phase 5: Conduct an Initiative Engagement Step 1: Establish Practice Development Strategy - 2
• 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
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
34
Phase 5: Conduct an Initiative Engagement Step 1: Establish Practice Development Strategy - 3
<Example Stewardship Plan> - 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
Enter here based on interviews
35
Phase 5: Conduct an Initiative EngagementStep 2: Design End State and Conduct Gap Analysis -1
Current State Business Impact
End State Solution to Address Gap
Investment Req’d
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
Example: Focus Area 1 – High Priority Segment
Focus Area 1
ComplianceInternal control design Detective and preventive measure Risk level assignment Automated vs. Manual control
Safeguarding of confidential data
RevenuePricing 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
• 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
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
37
Phase 5: Conduct an Initiative EngagementStep 3: Identify Quick Wins and Design Project Plan - 1
Strategic
Domain
Operational
Initiative Engagement Program Involvement
Value Nature Degree
Strategic
Operational
Domain
IMPERATIVE - Disciplined Approach to Balancing Strategic Agenda and Tactical Activities. Choose Nature and Degrees of Involvement According to Value Delivery
38
Phase 5: Conduct an Initiative EngagementStep 3: Identify Quick Wins and Design Project Plan - 2
• Internal selling of the data governance and management program for ‘Business Value’ delivered‘Business Value’ delivered
• Overview of automated, reusable solutions vs. hand-coded alternatives
• Proof of usability and validity
• Continued supporting during project lifecycle
2. Overview
1. EarlyAdopters
4. Proof
3. Demo5. Project
6. Integrate
7. Control and Monitor
Initiative Engagement
Initiative Lifecycle
Process for evaluating new initiatives as well as qualify and stage them in the overall master plan.
39
Phase 5: Conduct an Initiative EngagementStep 3: Identify Quick Wins and Design Project Plan - 3
• 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
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
40
Independent
Independent
Independent
Recommend
Defined
Distributed
Standardized
Defined
Distributed
Shared
Defined
Hybrid
Shared
Defined
Centralized
Phase 5: Conduct an Initiative EngagementStep 4: Establish Resource and Team Model - 1
Integration Competency Center Models
Central Services
Shared Services
Technology Standards
Best Practices
Benefits
Project Silos
Project Optimization
Leverage knowledge
Consistency Resource optimization
Control
Technology
Processes
Organization
For Initiative Engagement, while investment returns
vary by environment, gradual move toward
Shared Services may often yield better results
41
• 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
Inner working of the data stewardship activities
Lead for the Subject Area
Team Lead
Business Analyst
IT/Data Governance Metric Experts
Business Subject Matter Expert
Data
Inte
gra
tion
Expert
(s)
/R
eso
urc
e (
s)/
ICC
Data Stewards
Phase 5: Conduct an Initiative EngagementStep 4: Establish Resource and Team Model - 2
Steering Committee
IT S
trate
gy a
nd
Arc
hit
ect
Team
42
Phase 5: Conduct an Initiative EngagementStep 4: Establish Resource and Team Model - 3
• 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
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
43
Phase 5: Conduct an Initiative EngagementStep 5: Measure and Control Goals
• 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
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 – don’t make a huge change – incremental ones only
44
Phase 5: Conduct an Initiative EngagementStep 6: Transition to Expand Scope - 1
• 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
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
45
Phase 5: Conduct an Initiative EngagementStep 6: Transition to Expand Scope - 2
Governance Steering
Committee
Audit
Legal
Compliance
Privacy
Risk Management
Financial Reporting
Key Subject Areas / Lines of Business
DepartmentalBU
Extended Partners
Integration Competency Center (ICC)
Corporate IT
Program Direction
Technology Enablement
Operational Areas
Select specific areas of implementation
RealignImplement
Assess
Go Live
Measure
• Re-alignment • Buy-in• Resourcing • Role augmentation• Deployment• Training• Hand-off
Implement
Assess
Go Live
Measure
Realign
46
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
47
Concluding Remarks
48
PowerCenter 8 - Platform for Automating Data Governance and Management Tasks
Infr
astr
uct
ure
Ser
vice
sS
ecur
ity, H
igh
Ava
ilabi
lity,
Sca
labi
lity
Met
adat
a S
ervi
ces
Met
adat
a R
epos
itory
(S
eman
tic
Cat
alog
) E
xcha
nge,
Dat
a Li
neag
e,
Impa
ct A
naly
sis,
Dat
a S
tew
ards
hip
Delivery ServicesWeb Services, Messaging, JDBC, ODBC
Integration ServicesData Profiling, Data Cleansing, Data Transformation,
Data Movement, Data Federation
Access ServicesPackaged apps, Mainframe, RDBMS, Msg. Systems, Flat Files
(Structured, Unstructured & Semi-structured Data)
To
ols
Adm
in T
ools
, Dev
elop
er T
ools
, M
etad
ata
Too
ls, A
naly
st T
ools
Web ServicesBI Tools Portals
INTERNAL EXTERNALDATA CONSUMERS
Applications ApplicationsProcesses
Applications Databases Messages Flat Files XML Unstructured Data Mainframe
DATA SOURCES
JMS Web Svc SQL JDBC WebSvc
49
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
50
Q&AOpen Discussions
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