07182006_DAMA_Dallas_Institutionalize_Your_Data.ppt

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Institutionalize Your Data:

Designing and Implementing a Dynamic Blueprint for Data Governance and Management

Julianna Sakamoto, Senior Manager, [email protected]. 650-385-5010

Provided for DFW DAMA Meeting on July 18th – 11:30 am to 1:30pm

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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, [email protected], cell: 415-407-4817

• Informatica Team

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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

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Importance of Dynamic Blueprint to Data Governance and Management

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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.”

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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

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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

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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?

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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

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Expanding the Definition of Data Governance

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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

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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

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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

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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

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Best Practices for Securing Endorsement and Program Initiation

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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

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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

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Financial Services Customer Case Study For Data Governance and Management

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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

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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

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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

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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

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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

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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

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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

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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



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

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Revenue- SUSTAIN FOCUS AREA 1 EFFORT


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



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



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

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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


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



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



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

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Initiative Engagement – Start to Finish and Expand Scope

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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

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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

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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

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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

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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

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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

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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

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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

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• 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.

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• 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

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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

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• 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


Steering Committee

IT S

trate

gy a

nd

Arc

hit

ect

Team

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• 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

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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

07182006_DAMA_Dallas_Institutionalize_Your_Data.ppt

Technology

data management cornerstone

risk management

data governance source

certifying data

data integration

data quality

datadriven approach

new reality data governance