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This session focuses on upcoming transition planning, EA performance assessment, and ongoing enterprise data architecture activities, discussing the EPA Transition Strategy and Sequencing Plan and the importance of leveraging architecture intelligence.
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United States Environmental Protection AgencyOffice of Environmental InformationEnterprise Architecture ProgramDecember 2007 EA Working Group SessionDecember 13, 2007
Agenda Today’s session will focus on upcoming transition planning, EA performance assessment, and ongoing enterprise data architecture activities
EPA Transition Strategy and Sequencing PlanHistorical Perspective and Analysis Historically, EPA’s Transition Strategy and Sequencing Plan has centered on IT Investments and technology architecture • EPA structured these products to help manage system development efforts and inform future investment decisions. As an overview, they included: • A listing of milestones by IT investment (CPIC Majors and Lites) • Identification of Enterprise Tools / Services associated with each investment milestone • Projected and actual completion dates for investment milestones • Alignment of IT investments to EPA architectural segments • Criteria for which IT investments to include • consisted of: • Mission Criticality • External Use/Public Access • Regulatory/Compliance-Related • PMA-Associated • Registry Dependent • System Life Cycle Phase • Expected Data Sharing Sample Inclusions/ Exclusions
EPA Transition Strategy and Sequencing Plan:Moving towards a Business-Focused Transition Approach Source: FEA Practice Guidance, November 2007 http://www.whitehouse.gov/omb/egov/documents/FEA_Practice_Guidance_Nov_2007.pdf
EPA Transition Strategy and Sequencing PlanLeveraging Architecture Intelligence Your support and our joint activities this past year have positioned the Agency to mature toward a business-focused approach Business Area Transformation Frameworks
EPA Transition Strategy and Sequencing PlanShowing a line of sight
EA Performance and Value MeasurementOverview EA value measurement centered on documenting EA value to Agency decision-makers and identifying opportunities to improve EA support • Goals of EA value measurement include: • Demonstrating the value of the Agency EA program • Highlighting the influence of EA on strategic and operational decisions • Identifying opportunities to improve EA products and services • Justifying the allocation of agency resources to the development and use of architectural products • Fulfilling opportunities to improve EA products and services as well as enhance customer service • One of the primary challenges of EA value measurement is to demonstrate a cause-and-effect relationship between actions within the EA program and improvements to Agency performance
EA Performance and Value MeasurementPerspective-Based Performance Assessment EPA’s EA Value Measurement Framework embraces a comprehensive approach to assess performance from three perspectives
EA Performance and Value MeasurementEA Value Measurement Framework We are establishing an EA Value Measurement Framework to identify performance indicators and metrics under each perspective
Data Architecture:Presentation Highlights The Role of Data ArchitectureKevin Kirby, Data Architect Presentation Highlights • EPA Enterprise Architecture Conceptual Framing • Business Drivers of Data Architecture • DAMA’s Data Management Functions • FEA’s Data Reference Model (DRM) • DRM’s Data Strategy Framework • Next Steps
Enterprise Architecture Segments • Segment priorities beginning in FY06 are highlighted with an asteric (*) • EPA selected Records Management as its FY07 priority segment Core Mission Area Segment Enterprise Service Segment Business Service Segment Partner Views
What Information is needed to support Business Functions? Place-basedInformation Indicator and Trend Data Ecological/ Human Health Indicators Ambient Conditions Performance and Progress Facility Emissions Interpretive Information SourceInformation
Data Management Functions Data Architecture, Analysis & Design Unstructured Data Management Data Quality Improvement Database Administration Data Stewardship, Strategy & Governance Reference & Master Data Management Data Security Management Data Warehousing & Business Intelligence Metadata Management
FEA Data Reference Model How do I exchange Data? Query Points Exchange Packages Data Sharing Registries How do I Find and access Data What does the Data Mean? MetaData Data Context Data Description Taxonomies
Data Strategy Framework Business & Data Goals drive The Rule: All 3 pillars are required for an effective data strategy. Governance Data Strategy Information Sharing/Exchange (Services) Data Architecture (Structure) Goals drive; governance controls; structure defines; and services enable data strategy.
Next Steps in Developing a Data Management Strategy • Define Communities of Interest around core data sharing • Develop vision and Goals for Enterprise Data Architecture • Develop Communication Outreach Materials • Define / Form a Data Advisory Committee (DAC)- Develop DAC Vision document- Develop DAC Charter • Define / Publish an Enterprise Data Management Strategy
Data Architecture Contacts John Sullivan Chief Architect US EPA/OEI 202 566-0328 sullivan.john@epa.gov Kevin Kirby Data Architect US EPA/OEI 202 566-1656 kirby.kevin@epa.gov
Contact Information If you have any questions about the information presented today please contact one of the following individuals John Sullivan EPA Chief Architect 202.566.0328 (office) sullivan.john@epa.gov Joanna Hugney PPC EA Program Manager 703.748.7094 (office) jhugney@ppc.com