Enterprise Information Management Data Readiness Assessment Webinar August 18, 2009

Agenda Corporate Overview Data Quality - Bigger Issue Than You Might Think Data Quality - Real Life Examples Do You Need A Data Readiness Assessment? What is a Data Readiness Assessment? Conducting a Data Readiness Assessment Data Readiness Component Descriptions Vision & High-Level Requirements Data Quality Assessment Organizational Assessment Process/Best Practice Assessment Enabling Technology Assessment

Corporate Overview

Data Quality - Bigger Issue Than You Might Think

Data Quality - Real Life Examples

Do You Need A Data Readiness Assessment?

What is a Data Readiness Assessment?

Conducting a Data Readiness Assessment

Data Readiness Component Descriptions

Vision & High-Level Requirements

Data Quality Assessment

Organizational Assessment

Process/Best Practice Assessment

Enabling Technology Assessment

Corporate Overview Technology Management Consulting Firm Provide a unique blend of specialty IT services Leverage proven industry expertise in strategy, technology and enterprise performance management Focus on middle and Global 2000 market Founded in 1992 Headquartered in Wakefield, MA 300 Employees, 240 Consultants 600 Clients Large North American Footprint +2,000 Projects Completed to Date Publicly Traded (NASDAQ: EDGW) Organizational Assessment Other Customized Services

Technology Management Consulting Firm

Provide a unique blend of specialty IT services

Leverage proven industry expertise in strategy, technology and enterprise performance management

Focus on middle and Global 2000 market

Founded in 1992

Headquartered in Wakefield, MA

300 Employees, 240 Consultants

600 Clients

Large North American Footprint

+2,000 Projects Completed to Date

Publicly Traded (NASDAQ: EDGW)

Data Quality – Bigger Issue Than You Might Think “ The cost of poor data could be attributed to be anywhere from 10-25% of the total revenues of any organization. The topmost technology reason for customer relationship management (CRM) projects to fail or miss expectations is poor Data Quality.” “ Principles of ROI Development for Data Quality Projects”, by Diby Malakar, Published: January 1, 2008

“ The cost of poor data could be attributed to be anywhere from 10-25% of the total revenues of any organization. The topmost technology reason for customer relationship management (CRM) projects to fail or miss expectations is poor Data Quality.”

“ Principles of ROI Development for Data Quality Projects”, by Diby Malakar, Published: January 1, 2008

Data Quality – Bigger Issue Than You Might Think “ The Data Warehousing Institute estimates that data quality problems cost U.S. businesses more than $600 billion a year.” - “Principles of ROI Development for Data Quality Projects”, by Diby Malakar, Published: January 1, 2008

“ The Data Warehousing Institute estimates that data quality problems cost U.S. businesses more than $600 billion a year.”

- “Principles of ROI Development for Data Quality Projects”, by Diby Malakar, Published: January 1, 2008

Data Quality – Bigger Issue Than You Might Think “ Data quality management is one of the greatest challenges of information technology. According to the experts, the cost of poor data quality can reach as high as 15- to 25-percent of operating profit.” - “http://www.tdwi.eu/fortbildung-zertifizierung/onsite/courses/data-quality-fundamentals.html

“ Data quality management is one of the greatest challenges of information technology. According to the experts, the cost of poor data quality can reach as high as 15- to 25-percent of operating profit.”

- “http://www.tdwi.eu/fortbildung-zertifizierung/onsite/courses/data-quality-fundamentals.html

Data Quality – Real-Life Examples A telecommunications firm lost $8 million a month because data-entry errors incorrectly coded accounts, preventing bills from being sent out An insurance company lost hundreds of thousands of dollars annually in mailing costs due to duplicate customer records An information services firm lost $500,000 annually and alienated customers because it repeatedly recalled reports sent to subscribers due to inaccurate data A large bank discovered that 62% of its home-equity loans were being calculated incorrectly, with the principal getting larger each month A health insurance company in the Midwest delayed a decision support system for two years because the quality of its data was “suspect” A global chemical company discovered it was losing millions of dollars in volume discounts in procuring supplies because it could not correctly identify and reconcile suppliers on a global basis A regional bank was unable to calculate customer and product profitability due to missing and inaccurate cost data Source: Data Warehousing Special Report: Data Quality and the Bottom Line, http://www.adtmag.com/article.aspx?id=6321&page

A telecommunications firm lost $8 million a month because data-entry errors incorrectly coded accounts, preventing bills from being sent out

An insurance company lost hundreds of thousands of dollars annually in mailing costs due to duplicate customer records

An information services firm lost $500,000 annually and alienated customers because it repeatedly recalled reports sent to subscribers due to inaccurate data

A large bank discovered that 62% of its home-equity loans were being calculated incorrectly, with the principal getting larger each month

A health insurance company in the Midwest delayed a decision support system for two years because the quality of its data was “suspect”

A global chemical company discovered it was losing millions of dollars in volume discounts in procuring supplies because it could not correctly identify and reconcile suppliers on a global basis

A regional bank was unable to calculate customer and product profitability due to missing and inaccurate cost data

Do You Need a Data Readiness Assessment? “ Our users don’t trust the data” “ We have data quality issues that never seem to get resolved” “ The data is not actionable when the users finally get access to it” “ Our organization has decentralized operations and does not manage centralized applications/ environments well” “ We know we have data quality issues, but we don’t know the extent or impact” “ We don’t know if we have the right staff/skills to support a move to an enterprise reporting platform” “ We know we need to better leverage our data, but we don’t know how to get started”

“ Our users don’t trust the data”

“ We have data quality issues that never seem to get resolved”

“ The data is not actionable when the users finally get access to it”

“ Our organization has decentralized operations and does not manage centralized applications/ environments well”

“ We know we have data quality issues, but we don’t know the extent or impact”

“ We don’t know if we have the right staff/skills to support a move to an enterprise reporting platform”

What is a Data Readiness Assessment? A Data Readiness Assessment is a focused review of an organization’s ability to support centralized reporting and analytics Organizational Assessment Data Quality Assessment Other Customized Services Enabling Technology Assessment Process/ Best Practice Assessment Data Readiness Assessment

A Data Readiness Assessment is a focused review of an

organization’s ability to support centralized reporting and analytics

Benefits

Conducting a Data Readiness Assessment A Data Readiness Assessment is a focused review of an organization’s ability to support centralized data. It can be applied to an existing environment or a “green field” environment A Data Readiness Assessment has 4 core components Organizational Assessment Process/Best Practices Assessment Enabling Technology Assessment Data Quality Assessment A Data Readiness Assessment is highly customizable to your unique needs Other focus areas can be added depending on the your organization’s unique needs

A Data Readiness Assessment is a focused review of an organization’s ability to support centralized data. It can be applied to an existing environment or a “green field” environment

A Data Readiness Assessment has 4 core components

Organizational Assessment

Process/Best Practices Assessment

Enabling Technology Assessment

Data Quality Assessment

A Data Readiness Assessment is highly customizable to your unique needs

Other focus areas can be added depending on the your organization’s unique needs

Conducting a Data Readiness Assessment Conduct Evaluation Vision and High-Level Requirements Organizational Assessment Enabling Technology Assessment Process/Best Practices Assessment Data Quality Assessment Assessment Output Assessment Results and Scorecard Summary Recommendations Areas for Additional Focus Additional Areas of Focus

Vision and High-Level Requirements Determining the end-state business capabilities that need to be supported by the centralized data environment GOAL Conduct Kick-Off Meeting with Key Business and IT Stakeholders Conduct Facilitated Working Sessions with Key Business and IT Stakeholders Prepare Vision and High-Level Requirements Summary Document MAJOR ACTIVITIES Presentation that Outlines: The end state vision for the business capabilities that need to be supported by the centralized data environment The high-level requirements for end-state reporting and analysis capabilities TYPICAL DELIVERABLE

Conduct Kick-Off Meeting with Key Business and IT Stakeholders

Conduct Facilitated Working Sessions with Key Business and IT Stakeholders

Prepare Vision and High-Level Requirements Summary Document

Presentation that Outlines:

The end state vision for the business capabilities that need to be supported by the centralized data environment

The high-level requirements for end-state reporting and analysis capabilities

Data Quality Assessment Determine the quality of key data critical to making business decisions GOAL Conduct facilitated working sessions to determine the data elements to include in the assessment Determine the business data quality rules to apply Conduct up to 3 passes of the data quality processing Review interim results and revise business rules as necessary Conduct a formal review of the assessment results MAJOR ACTIVITIES Data Quality Scorecard and Assessment Report: Scorecard detailing the results of the assessment Details of any data quality issues found and related summary recommendations for remediation TYPICAL DELIVERABLE

Conduct facilitated working sessions to determine the data elements to include in the assessment

Determine the business data quality rules to apply

Conduct up to 3 passes of the data quality processing

Review interim results and revise business rules as necessary

Conduct a formal review of the assessment results

Data Quality Scorecard and Assessment Report:

Scorecard detailing the results of the assessment

Details of any data quality issues found and related

summary recommendations for remediation

Organizational Assessment Assess the current organization structure, capabilities and ability to support a centralized data environment GOAL Conduct facilitated working sessions/interviews with key stakeholders and subject matter experts within the data governance and data management functions Review current staffing and skill set mix of the governance and data management functions Review documentation related to development, production support, data management and governance MAJOR ACTIVITIES Presentation that outlines: Assessment results by organizational component Areas for future focus or further investigation Summary recommendations TYPICAL DELIVERABLE

Conduct facilitated working sessions/interviews with key stakeholders and subject matter experts within the data governance and data management functions

Review current staffing and skill set mix of the governance and data management functions

Review documentation related to development, production support, data management and governance

Presentation that outlines:

Assessment results by organizational component

Areas for future focus or further investigation

Summary recommendations

Process/Best Practices Assessment Assess the current processes, standards and best practices against those required to support a centralized data environment GOAL Conduct facilitated working sessions/interviews with key stakeholders and subject matter experts Review enterprise and key departmental processes, best practices and standards Review key data management processes, standards and best practices Review enterprise processes for data quality, data stewardship and data security MAJOR ACTIVITIES Presentation that outlines: The assessment results by area Areas for future focus or further investigation Summary recommendations TYPICAL DELIVERABLE

Conduct facilitated working sessions/interviews with key stakeholders and subject matter experts

Review enterprise and key departmental processes, best practices and standards

Review key data management processes, standards and best practices

Review enterprise processes for data quality, data stewardship and data security

Presentation that outlines:

The assessment results by area

Areas for future focus or further investigation

Summary recommendations

Enabling Technology Assessment Assess the enabling technologies used to support reporting and analytics in a centralized data environment. GOAL Evaluate the enabling technology currently used against the required reporting and analysis capabilities The evaluation will be performed by business intelligence domain, including: Data Integration (including Data Quality) Data Storage Reporting and Analytics Metadata/Master Data Management Data/User Access MAJOR ACTIVITIES Presentation that outlines: The assessment results by business intelligence domain Areas for future focus or further investigation Summary recommendations TYPICAL DELIVERABLE

Evaluate the enabling technology currently used against the required reporting and analysis capabilities

The evaluation will be performed by business intelligence domain, including:

Data Integration (including Data Quality)

Data Storage

Reporting and Analytics

Metadata/Master Data Management

Data/User Access

Presentation that outlines:

The assessment results by business intelligence domain

Areas for future focus or further investigation

Summary recommendations

Why Edgewater Extensive subject matter expertise in data warehousing, business intelligence and enterprise management Comprehensive EIM Reference Capabilities Map provides foundation for strategy, assessment and implementation of data warehouse and business intelligence solutions Formalized offering for assessing data readiness Balance in focus between process/best practices, organizational constructs and enabling technologies Apply deep industry specific knowledge in the execution of the data readiness assessment All of our consultants are onshore We are vendor independent

Extensive subject matter expertise in data warehousing, business intelligence and enterprise management

Comprehensive EIM Reference Capabilities Map provides foundation for strategy, assessment and implementation of data warehouse and business intelligence solutions

Formalized offering for assessing data readiness

Balance in focus between process/best practices, organizational constructs and enabling technologies

Apply deep industry specific knowledge in the execution of the data readiness assessment

All of our consultants are onshore

We are vendor independent

Thank You For Joining Us!!! To learn more about Edgewater’s Data Readiness Assessment, contact: Mike Faloney Enterprise Information Management Practice Director 804 399-4214 [email_address] Q & A