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Enterprise Information ManagementProgram overview

08-Dec-2009



EIM DRAFT 08-Dec-2009 2

Traditional View of Business Resources

Financial

Human

Material

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)




View of Business Resources Today

Financial

Human

Material

Data

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

Information

Capital

Products

Labor

4

Business ‘SYSTEM’ Model

Resources

Enterprise Information Management

Asset Management

Revenue Management

Work Management

AssetsBusinessFunctions

Customer Management

Distribute& MaintainTransportGenerateProcure

Plan &Market

Financial

Material

Human

Data




Business Integration - a Linkage

Data is the linkage among the processes.

The processes must: Agree on what data has to be shared Share definitions & values unambiguously




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 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.




Why EIM for Utility Business and IT?

Management of Information from Enterprise Perspective(Organizational Discipline, Governance Process)

Management of Information from Enterprise Perspective(Organizational Discipline, Governance Process)

Single-Version- of-Truth(Customer, Work, Asset & Operation)

Single-Version- of-Truth(Customer, Work, Asset & Operation)

Real-time Information needs – Analytical & Operational(Business Insight Analytics)

Real-time Information needs – Analytical & Operational(Business Insight Analytics)

Information Value Management(Profiling, Accuracy, Quality, Re-structuring and Re-factoring)

Information Value Management(Profiling, Accuracy, Quality, Re-structuring and Re-factoring)

Decoupling of information from Applications(SOA requirements, Business Rules, Semantics/meaning)

Decoupling of information from Applications(SOA requirements, Business Rules, Semantics/meaning)

Increased Volume & Velocity of Information(Smart Grid and AMI)

Increased Volume & Velocity of Information(Smart Grid and AMI)

Legacy Data Migration & Replacement(Smart grid, GIS, CIS, etc.)

Legacy Data Migration & Replacement(Smart grid, GIS, CIS, etc.)

Packaged Application Integration needs(Enable Plug & Play Infrastructure, Manage Risks)

Packaged Application Integration needs(Enable Plug & Play Infrastructure, Manage Risks)

Meta Data Management Solutions(Business & System Level –

Definition, Usage, Context, Location)

Meta Data Management Solutions(Business & System Level –

Definition, Usage, Context, Location)

Enterprise Information Modeling(Semantics/meaning, Format, Granularity)

Enterprise Information Modeling(Semantics/meaning, Format, Granularity)

Enterprise Data Services(Exposing Legacy Data,

Complementing SOA Integration)

Enterprise Data Services(Exposing Legacy Data,

Complementing SOA Integration)

Business Drivers

Technical Drivers

EIM Deliverables

EIM Organizational Model(Competency Center)

EIM Organizational Model(Competency Center)

Information Governance Process(Business & IT)

Information Governance Process(Business & IT)

Information Architecture(Enterprise Information landscape)

Information Architecture(Enterprise Information landscape)

Drive

Drive




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.




Context

Inference

Certitude

10

Information - One of the Firm’s Most Valuable Assets

Synthesis

Data

Intelligence

Knowledge

Information

Wisdom

DecreasingVolume

and“Objectivity”

IncreasingClarity

andValue

Knowledge + Synthesis = Wisdom

From Hearing the Voice of the Market by Vincent P. Barabba, Gerald Zaltman

consumptionintervalreading

customer premisesconsumption for billing period

regional consumptionpattern over multiple years

projected energyrequirements based on consumption and weather patterns

energy generation investmentsdemand control/reduction programsconservation initiatives

Intelligence + Certitude = KnowledgeInformation + Inference = IntelligenceData + Context = Information




InfrastructureStore / Transport Data

Peo

ple

IT Application Model

Tra

nsac

tion

Bas

ed Analysis B

ased

People

ApplicationManipulate Data

Business ProcessDefine / Organize Data

Focus on the Data

Data




Data

Run the Business

Operational Reporting

Historical Retention

Information Analysis


Transactional Data Store

Operational Data Store

Historical Data Store

Analytical Data Store

Operational Applications(structured data)

Decision Support Applications

Data is managed and optimized to support it’s intended usage across the enterprise

Daily Business CommunicationsBusiness

Interactions (unstructured content)

Indexing & Search Capability

Business Information Model (Enterprise Semantic Model)




Data


Data organization and retention requirements vary by intended usage

• Subject area oriented

• Integrated

• Volatile• Current

• Atomic level data• Near real-time

availability• No historical data

• Very limited data retention

• Consistent within current context

• Transaction level data

• Real-time availability• Limited historical

data• Limited data

retention• Consistent within

application

• Subject area oriented

• Integrated

• Non-volatile• Time variant

• Atomic level data• Business driven

availability• Historical data

• Lengthy data retention

• Historically consistent

• Business question oriented

• Integrated

• Non-volatile• Time variant

• Aggregate level data• Business driven

availability• Business driven

historical data• Business driven data

retention• Historically

consistent

Transactional Data Store

Operational Data Store

Historical Data Store

Analytical Data Store

(Shared Databases) (ODS)

(Data Warehouses)

(Info Cubes /Data Marts)

Metadata Repository, Data Architecture, Data Quality, SDLC, EAI & ETL tools and processes

• Business process oriented

• Single business function

• Volatile• Current

• Business process oriented

• Single businessfunction

• Non-volatile• Current

• Atomic Level• Historically Consistent

• Varying retention requirements

Operational Applications(structured data)

Decision Support Applications

Business Interactions

(unstructured content)

Indexing & Search Capability





Data


External

Data organization and retention requirements vary by intended usage

Data Integration Processes and Services

Common Data Access Methods

Email WebContent

Notes Documents


Real-TimeTabular

Real-TimeVector

Real-TimeTime Series

NearReal-timeIntegrated

Detail +Aggregation

StaticHistoricalUpdated

Daily

Detail

BusinessQuestionoriented

Historical Daily

BusinessQuestionorientedAggregation




Data


External

Business Process

Infrastructure

Results in increased flexibility, reduced cost and reliable data

Data Integration Processes and Services

Common Data Access Methods

!

!

Email WebContent

Notes Documents

ApplicationsEAM CCS ECM OMAR MED/MIRA IMR

Transactional Analytical


Customer

GIS

Consumption

OperationalReportingData Store

Detail +Aggregation

DataWarehouse

Detail

DataMart

Historical Daily

DataMart

Aggregation




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

EmailFinancialCustomerSerial device/Meter

Time

Dat

a C

ritic

ality

Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7

Online Active data

Nea line / Archive

Offline / Archive

Expired data




Information Lifecycle Management

Online Offline

Live DynamicData

Fixed Content / Reference Data

StorageManagement

ProtectionManagement

ContentManagement

RetentionManagement Data

Disposal

Data Creation




Information Lifecycle Management

Live DynamicData

Fixed Content / Reference Data

Storage Management

ProtectionManagement

ContentManagement

RetentionManagement

• Operational data and content

• “open business”

• Active archive• “business complete”• document archiving

• Data and content backup

• “open business”

• Offline archive• “business complete”

Data Disposal

• Zero business value

Online Offline

Data Creation




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 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 Vision for Consumers Energy (2015)

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.




Where is Consumers Energy today?

Results of Data Management and Integration Maturity Assessment – Nov 2009

1 2 3 4 5

Fragmented

Inconsistency, Redundancy

Apply standards to

individual project phases

Standardized

Consistency, Reuse, Efficiency

Effective use for driving business

strategy

Managed

Pervasive, Leverage of Skills

Information is trusted across the enterprise

Issues not recognized

Opportunistic

Rigid, Low agility

Specific set of users are

realizing value

Competency Center

Information Infrastructure

road map

Formalized DM&I

Initiative

Optimized

Flexibility, Agility, Proactiveness

Custom code

Data Fragments

Tools "chaos"

Standards and bestpractices sharing

Referenced architectures

Data services emerge

Dynamic metadata-driven data

management environment Proprietary

tools

Cost “chaos”

Data consistency

and availability

Funding from business units

on a project-by-project basis

Secure executive

sponsorship

No business sponsor; IT executive in

charge

Effective use across suppliers, customers and

business partners

Fragmented

Inconsistency, Redundancy

Apply standards to

individual project phases

Standardized

Consistency, Reuse, Efficiency

Effective use for driving business

strategy

Managed

Pervasive, Leverage of Skills

Information is trusted across the enterprise

Issues not recognized

Opportunistic

Rigid, Low agility

Specific set of users are

realizing value

Competency Center

Information Infrastructure

road map

Formalized DM&I

Initiative

Optimized

Flexibility, Agility, Proactiveness

Custom code

Data Fragments

Tools "chaos"

Standards and bestpractices sharing

Referenced architectures

Data services emerge

Dynamic metadata-driven data

management environment Proprietary

tools

Cost “chaos”

Data consistency

and availability

Funding from business units

on a project-by-project basis

Secure executive

sponsorship

No business sponsor; IT executive in

charge

Effective use across suppliers, customers and

business partners

We are here




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

Time

Benefits

Number of Projects supported

EIM Functions supported

Staffing to provide services

InformationManagement

MaturityEIM

VisionEIM

Vision




EIM Core Processes

Data QualityData Quality Data IntegrityData Integrity Data Security/ Protection

Data Security/ Protection

Data Lifecycle Management

Data Lifecycle Management

Data Movement

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

Semantic Management

Database Management

Database Management

Master Data ManagementMaster Data Management

Information Services

Information Services

Services & Support

Management

Services & Support

Management

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.

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 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 manage the physical corporate databases and data files.

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. )




EIM Organizational Functions

Information Value

Management

Information Value

Management

Data and Content

Management

Data and Content

Management

Business Information

Management


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

EIMEIM




EIM Organizational Roles

Data and Content Design Data Architecture

Management Data Development

Quality Management Data Quality

Management

Integration and Sourcing Integration Services

ManagementOngoing Support

Data Implementation Database Operations

Management Document & Content

Management Data Security

Management

Data Governance Data Planning Data Management

Information Access Services Reference & Master

Data ManagementMetadata Management

Meta Data Management

Information Value

Management

Information Value

Management

Data and Content

Management

Data and Content

Management


Management


Management

EIMEIM

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