Enterprise Information Management Program overview

1. Enterprise Information ManagementProgram overview 08-Dec-2009

2. Traditional View of Business Resources Material Financial Human Financial, Material&Human resources are the traditional critical business resources that must be effectively managed (as described by Adam Smith in the Wealth of Nations) EIM DRAFT 08-Dec-2009

3. View of Business Resources Today Financial Material Data Human Data representing the current state of the Financial, Material & Human resources is used to measure business performance and make decisions – therefore Data should be managed as a critical business resource EIM DRAFT 08-Dec-2009

4. Business ‘SYSTEM’ Model Business Functions Resources Assets Capital Financial Products Material Distribute & Maintain Plan & Market Procure Generate Transport Labor Human Information Data Enterprise Information Management Revenue Management Asset Management Work Management Customer Management EIM DRAFT 08-Dec-2009

5. Business Integration - a Linkage Process Process Process Data Data Data is the linkage among the processes. The processes must: • Agree on what data has to be shared • Share definitions & values unambiguously EIM DRAFT 08-Dec-2009

6. Information Technology Drivers • Utility IT has been trying to become an enabler of business transformation rather than a cost center. Some key areas of focus are: • Program management office and Portfolio management • Comprehensive Enterprise Application (CEA) • Data Center and Infrastructure management • Enterprise integration technology • Business intelligence and Customer portal • Business Process Management (PMTs) • etc. However, what has been missing with all of these investments is a holistic strategy and approach to manage data and information as assets across business silos. Therefore, business continues to “struggle” to get the right information at the right time. EIM DRAFT 08-Dec-2009

7. EIM Definition • Enterprise information management (EIM)is an integrative discipline for structuring, describing and governing information assets, regardless of organizational boundaries or technologies. EIM strives to improve operational efficiency, promote transparency and enable business insight. The broad scope of EIM requires a level of organizational commitment to improve the accuracy, integrity, accessibility and security of information assets. The objective of EIM is to resolve data definition, format and content issues across applications and document stores. EIM DRAFT 08-Dec-2009

8. Management of Information from Enterprise Perspective(Organizational Discipline, Governance Process) EIM Organizational Model(Competency Center) Single-Version- of-Truth(Customer, Work, Asset & Operation) Information Governance Process(Business & IT) Real-time Information needs – Analytical & Operational(Business Insight Analytics) Information Architecture(Enterprise Information landscape) Information Value Management(Profiling, Accuracy, Quality, Re-structuring and Re-factoring) Decoupling of information from Applications(SOA requirements, Business Rules, Semantics/meaning) Meta Data Management Solutions(Business & System Level – Definition, Usage, Context, Location) Increased Volume & Velocity of Information(Smart Grid and AMI) Enterprise Information Modeling(Semantics/meaning, Format, Granularity) Legacy Data Migration & Replacement(Smart grid, GIS, CIS, etc.) Enterprise Data Services(Exposing Legacy Data, Complementing SOA Integration) Packaged Application Integration needs(Enable Plug & Play Infrastructure, Manage Risks) Why EIM for Utility Business and IT? EIM Deliverables Business Drivers Drive Technical Drivers Drive EIM DRAFT 08-Dec-2009

9. EIM Mission Statement To provide integrated enterprise level data and information, managed as a corporate asset, within a standardized and shared infrastructure to facilitate and support integrity of data for daily operations and fact based decision making. EIM DRAFT 08-Dec-2009

10. Information - One of the Firm’s Most Valuable Assets Synthesis Certitude Inference Context energy generation investments demand control/reduction programs conservation initiatives Wisdom projected energy requirements based on consumption and weather patterns Knowledge Decreasing Volume and “Objectivity” Increasing Clarity and Value regional consumption pattern over multiple years Intelligence customer premises consumption for billing period Information consumption interval reading Data Knowledge + Synthesis = Wisdom Intelligence + Certitude = Knowledge Information + Inference = Intelligence Data + Context = Information From Hearing the Voice of the Market by Vincent P. Barabba, Gerald Zaltman EIM DRAFT 08-Dec-2009 10

11. IT Application Model Business Process Define / Organize Data Application Manipulate Data Transaction Based Analysis Based People People Data Infrastructure Store / Transport Data Focus on the Data EIM DRAFT 08-Dec-2009

12. Enterprise Information Management Transactional Data Store Operational Data Store Historical Data Store Analytical Data Store Data Business Information Model(Enterprise Semantic Model) Run the Business Operational Reporting Historical Retention Information Analysis Operational Applications (structured data) Decision Support Applications Daily Business Communications Business Interactions (unstructured content) Indexing & Search Capability Data is managed and optimized to support it’s intended usage across the enterprise EIM DRAFT 08-Dec-2009

13. Enterprise Information Management Transactional Data Store Operational Data Store Historical Data Store Analytical Data Store (Info Cubes / Data Marts) (Shared Databases) (ODS) (Data Warehouses) Data Business Information Model(Enterprise Semantic Model) • Business process oriented • Single business function • Volatile • Current • Subject area oriented • Integrated • Volatile • Current • Subject area oriented • Integrated • Non-volatile • Time variant • Business question oriented • Integrated • Non-volatile • Time variant Decision Support Applications Operational Applications (structured data) • Transaction level data • Real-time availability • Limited historical data • Limited data retention • Consistent within application • Atomic level data • Near real-time availability • No historical data • Very limited data retention • Consistent within current context • Atomic level data • Business driven availability • Historical data • Lengthy data retention • Historically consistent • Aggregate level data • Business driven availability • Business driven historical data • Business driven data retention • Historically consistent • Single businessfunction • Non-volatile • Current • Atomic Level • Historically Consistent • Varying retention requirements • Business process oriented Business Interactions (unstructured content) Indexing & Search Capability Metadata Repository, Data Architecture, Data Quality, SDLC, EAI & ETL tools and processes Data organization and retention requirements vary by intended usage EIM DRAFT 08-Dec-2009 13

14. Enterprise Information Management Real-TimeTabular BusinessQuestionoriented Historical Daily Near Real-time Integrated Static Historical Updated Daily Real-TimeVector BusinessQuestionoriented Aggregation Real-TimeTime Series Detail + Aggregation Detail Data Business Information Model(Enterprise Semantic Model) Common Data Access Methods External Email Notes Documents WebContent Data Integration Processes and Services Data organization and retention requirements vary by intended usage EIM DRAFT 08-Dec-2009

15. Enterprise Information Management Transactional Applications Analytical EAM CCS ECM OMAR MED/MIRA IMR Customer DataMart Historical Daily OperationalReportingData Store DataWarehouse GIS DataMart Aggregation Detail + Aggregation Detail Consumption Business Process ! Data Business Information Model(Enterprise Semantic Model) Common Data Access Methods External ! Email Notes Documents WebContent Data Integration Processes and Services Infrastructure Results in increased flexibility, reduced cost and reliable data EIM DRAFT 08-Dec-2009

16. Not All Data is Created Equal Data criticality depends on the business processes it supports Data of different criticality needs to be stored and moved on to different classes and types of storage over time Data should be deleted when it has zero value to the business Overtime expired data becomes a liability to the business Online Active data Data Criticality Nea line / Archive Offline / Archive Email Financial Customer Serial device/ Meter Expired data Time Year 7 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 EIM DRAFT 08-Dec-2009

17. Information Lifecycle Management Online Offline Storage Management Protection Management Management Data Creation Information Lifecycle Live Dynamic Data Content Management Retention Management Fixed Content / Reference Data Data Disposal EIM DRAFT 08-Dec-2009

18. Information Lifecycle Management Online Offline Storage Management Protection Management Data Creation • Operational data and content • “open business” • Data and content backup • “open business” Live Dynamic Data Content Management Retention Management Fixed Content / Reference Data • Active archive • “business complete” • document archiving • Zero business value • Offline archive • “business complete” Data Disposal EIM DRAFT 08-Dec-2009

19. EIM Scope • All Consumers Energy data and information assets including structured data and unstructured content. • The organization, processes, infrastructure and standards governing management of the enterprise information and content. • Cross organizational roles and responsibilities related to management of the information assets. • Management of information assets through the entire information life cycle from creation through disposal. EIM DRAFT 08-Dec-2009

20. EIM Benefits Business Value Ensures that the CEA investment in common data and process is leveraged for future projects and the business value is maximized thru data governance. Strives to provide a single version of the truth supporting business insight. Enables better business decisions and responsiveness to change by making timely, consistent and accurate information readily available. Efficiency Enables faster and lower cost information delivery by shortening development times and repurposing proven information services. Supports development collaboration thru a shared central metadata repository. Provides a stable data foundation for system integration transparency based on standards and best practices. Data Quality Increases data quality thru ongoing data quality assessments and exception monitoring. Improves the ability to derive consistent information providing the foundation for actionable and timely business intelligence. Builds confidence in the accuracy and relevance of information provided with data lineage traceability. Transparency Promotes common understanding and sharing of information across the enterprise. Instills business ownership and stewardship of the critical information resources. Improves communication and reduces ambiguity within the organization by promoting consistent data definition, format and usage standards. EIM DRAFT 08-Dec-2009 20

21. Data and information is recognized and managed as a valuable corporate resource across organizational and technology boundaries. Information assets are managed through the entire information life cycle (creation, maintenance, access, archive and disposal) using well defined processes. Consistent data definition and understanding provides a common vocabulary for the business. Information is managed and utilized to maximize its benefit in support of the goals of the entire organization. A standardized information infrastructure and processes are implemented supporting data sharing and process integration. Information is readily available through common services on a need to know basis and is secured from unauthorized access. Current, complete and consistent information is readily available providing a ‘single version of the truth’ enabling business insight and fact based business decisions. Consumers Energy Executive management recognizes and embraces the role of EIM in achieving the corporate objectives. EIM Vision for Consumers Energy (2015) EIM DRAFT 08-Dec-2009

22. Where is Consumers Energy today? Results of Data Management and Integration Maturity Assessment – Nov 2009 1 2 3 4 5 We are here EIM DRAFT 08-Dec-2009

23. EIM Implementation Approach • Start small • Show benefits fast • Align with major initiatives • Leverage existing support organizations (DBA, BI/BW, Email Archiving & Search) • Gradually expand scope of projects supported • Gradually increase supported EIM functions EIM Vision InformationManagementMaturity Benefits Number of Projects supported EIM Functions supported Staffing to provide services Time EIM DRAFT 08-Dec-2009

24. EIM Core Processes Data Quality Data Integrity Data Security/ Protection Data Lifecycle Management Data Movement Processes to identify, analyze, improve, and measure the data quality issues and improvement efforts. Processes to identify, analyze, improve, and measure the data integrity issues and improvement efforts. Processes to ensure corporate data and information is secure and protected, and managed according to the corporate policies and regulatory mandates. Processes to govern how to create, classify, update, use, distribute, and archive, and obsolete data and information, for new projects as well as ongoing maintenance. Processes to identify and guide how data should be managed when they are moved around the enterprise and Line of Business systems, applications, and data files. Semantic Management Database Management Master Data Management Information Services Services & Support Management Processes to establish, manage, and use the business and IT semantics (that is business terms and definitions, metadata management, enterprise semantic model management, semantic integration etc. ) Processes to manage the physical corporate databases and data files. Processes to manage the creation, maintenance, distribution, and usage of corporate master and/or reference data entities to support business processes and business transactions with the objectives of improving data quality and integrity, improving data and information accuracy, and reducing process inefficiencies. Processes to establish, maintain, and use actual data and aggregation services in the form of reusable software components for business systems and processes to share and leverage data and information across both transactional and analytical needs. Processes for the EIM program and/or organization to provide functional services and support to the rest of enterprise IT and business organizations and projects. EIM DRAFT 08-Dec-2009

25. EIM Organizational Functions EIM Business Information Management Data and Content Management Information Value Management The key functions of this sub-team are to design the structures and standards that support the effective management, governance and use of information assets across the business. Operationally, it performs data and content design, and identifies data quality requirements. The key functions of this sub-team are to develop and deliver the information infrastructure required to support information as a shared service, Operationally, it performs and provides infrastructure, migration, sourcing and systems support The key functions of this sub-team are to support the organization’s need to maximize the value of it’s information assets. Operationally, this group provides information access support services (such as training and education) and metadata management services (such as data governance support and data lineage). This team leverages combinations of technical, business and training skills EIM DRAFT 08-Dec-2009

26. Data and Content Design Data Architecture Management Data Development Quality Management Data Quality Management EIM Organizational Roles EIM Business Information Management Data and Content Management Information Value Management • Integration and Sourcing • Integration Services Management • Ongoing Support • Data Implementation • Database Operations Management • Document & Content Management • Data Security Management • Data Governance • Data Planning • Data Management • Information Access Services • Reference & Master Data Management • Metadata Management • Meta Data Management EIM DRAFT 08-Dec-2009