Transcript Document

Leading the Way in Electricity
SM
Enterprise Information Management
Vision &
Strategy
Governance
Architecture
Delivery
OpenSG EIM Task Force
July, 2011
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SOUTHERN CALIFORNIA EDISON
Leading the Way in Electricity
SM
Contents
 Background
 Definition
 Vision
 Guiding Principles
 Approach
 Framework
 Prioritization
 Organization
 Program Structure
 Roles and Responsibilities
 SmartGrid Reference Architecture – Data Services
 Other Related Work
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SOUTHERN CALIFORNIA EDISON
Leading the Way in Electricity
SM
Background
Definition:
EIM is an enterprise program that plans for, manages, structures, and provides information assets
(structured and unstructured) to maximize the value of information for decision making, operations,
and corporate strategy.
Vision:
Create an operating model that , a) optimizes the use of information created, obtained, analyzed, and
acted upon by all stakeholders, and b) serves as the authoritative source for services, shared
components, and practices.
Guiding Principles:
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Minimize the disruption to current efforts
Ensure all efforts are going in the same direction
Ensure consistency and reusability
Minimize redundancy (duplicate efforts)
Ensure value realization
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Leading the Way in Electricity
SM
EIM Framework
Primary Focus
Vision & Strategy
Governance
EIM Core
Processes
Addressed as needed to support
Primary Focus areas
Organization
Data Quality
Vision
Sponsorship
CSFs & KPIs
Data Integrity
Data Security &
Protection
Mission
Stewardship
Data Lifecycle
Management
Structure
(Virtual, Hybrid,
…)
Strategy
Semantics
Management
Information
Architecture
Blueprint
Management
Roles &
Responsibilities
Technologies
(DBMS, CMS,
ETL, EAI, EII,
Data Modeling,
BI/DW,
Collaboration)
Functional
Services
Knowledgebase
& Repositories
Business Value
& Relationship
Management
Standards &
Best Practices
Data Movement
Policies,
Principles &
Tenets
Tools &
Technologies
Database
Management
Goals &
Objectives
Alignment
Master Data
Management
Information
Services (A&R)
Value
Propositions
Structure
Services &
Support
Source: Xtensible Solutions
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SOUTHERN CALIFORNIA EDISON
Leading the Way in Electricity
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EIM Prioritization
HIGH
MEDIUM
LOW
Information Services (A&R)
Data Security & Protection
Master Data Management
Data Governance
Data Quality
Database Management
Semantics Management
Data Integrity
Data Movement
Data Lifecycle Mgmt
Services & Support
Information Architecture
Organization (Roles & Responsibilities, Structure, KPIs, Org Readiness)
Tools & Technologies
Define, Plan, Implement
Define, High Level Plan
Define
Prioritization Scoring
EIM
Foundational
Importance to
Business
Current
Maturity Level
EIM
Foundational
Importance to
Business
Current
Maturity Level
Data Governance
High
High
Low
Semantics Management
High
High
Low
Data Quality
Low
Medium
Medium
Database Management
Medium
Low
High
Data Integrity
Low
Medium
Medium
Master Data Management
Medium
Low
Low
Medium
High
High
Information Services (A&R)
High
High
Medium
Data Lifecycle Mgmt
Low
Medium
High
Services & Support
High
Medium
Medium
Data Movement
High
High
Medium
Information Architecture
High
Medium
Low
Component
Data Security & Protection
Component
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Program Structure
Enterprise Information
Governance
(Business)
Executive Sponsors
(IT)
Program Director
Key Stakeholders
(Business)
Key Advisors
(IT)
Steering Team
Functional
Architectural
Technical
• Prioritization
• Funding
• Escalation
Data Governance
Data Lifecycle Mgmt
Info Services (A&R)
Program Manager
Working Teams
Semantics Mgmt
Info Architecture
Data Movement
Info Services (Tech)
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• Strategy & direction
• Integration
• Marketing & communication
Data Quality/Integrity
Master Data Mgmt
Data Security
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Leading the Way in Electricity
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Roles & Responsibilities
Program Director
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Program Manager
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Single point of accountability for all program activities
Escalation point for program level decisions and issue resolution
Delivery of communications and marketing
Steering Team
• Overall direction setting and decision making
• Operational support to working teams
• Process and governance
• Delivery of communications and marketing
Functional Lead
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Working Teams
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Single point of accountability for all functional activities
Consultation, planning & client service
Requirements gathering & functional solution design
Functional configuration
Integration with BU EIM initiatives & roadmap
Architectural Lead
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Program management and support
Program integration
Strategy development and alignment
Direction setting for working teams
Communications and marketing development
Best practices research
Single point of accountability for all ETAE (architecture &
engineering) activities
Architectural solution design
Integration with Enterprise Architecture
Cross functional impact assessment
Tool capabilities
BU level data architecture
Single point of accountability for all component level activities
Review and assess projects to determine EIM implications
Oversee EIM-related activities on identified projects
Oversee EIM-related activities specific to component build-out
Raise awareness of new EIM-related efforts when discovered
Integrate with other working teams when appropriate
Escalate issues (program and operational) to Steering team as
necessary
Technical Lead
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Single point of accountability for all TDM (technical build and run)
activities
Technical design
Technical build
System maintenance & operation
Patch management
Custodial work (capacity, archival, integrity)
Data security
Tool implementation & support
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SmartGrid Reference Architecture
Data Services
Data Services Synergy Model
Consumers/
Processes
Analytics
System Mgmt
Data
Data Management Services
Data Discovery
Data Indexing and
Reference
Unstructured
Content
Enterprise Application
Data Registration and Life
Cycle Management
Data Services Stack Model
Foundation
B2B
Data Access & Update
Visualization
Consumer Service
Manually entered information
(inspections, readings, etc.)
Network state estimation
Market operations signals
Core
Content Management
Master Data Management
Data Flow Orchestration
Data Manipulation
Data Collection
Geospatial information
Reporting
Electrical Network model
Data Transformation
Data Quality and Integrity
Data Storage
Data Classes
Time Series Data
Event Data
Market operations model
Measurement model
Asset catalogue
CIM/61850 interface
Compatible units
Customer information
Asset data
Premises information
Edge device model
Integration
Data Security
Operational Data
Network measurements
Analysis
Records
Meta Data
messaging
data access
transformation
data synchronization
encryption
master data management
Support Services
Sources
SCADA
MDM
Protection
Equipment
Customer
Interface
Third
Parties
External
Data Feeds
Field
crews
IVR/Call
Center
Enterprise
Application
governance
access control services
transport
semantic model management
storage
message & service definition
Data Management Component Model
Meta Data
Management
Semantic Model
Management
ETL
ESB
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EII
Persistent Data
Storage
Archive
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SmartGrid Reference Architecture
Goals & Principles – Data Services
Master data – element created from one trusted source
Motivations:
• Increased data integrity and reliability
• Cost reduction for managing information and data quality
Implications:
• Consistently invest in, and comply with, the trusted sources
architecture
• Processes engineered to maintain consistent master data
management and consumption
Ensure business decisions are based on information from
appropriate trusted data sources
Motivations:
• Achieve highest degree of integrity and validity for business
decisions
• Minimize IT costs for managing and maintaining data
• Enhance ease of doing business by eliminating manual data
integration, normalization, etc
Implications:
• Practitioners more likely to know what trusted sources exist,
and which ones to use
• Solution teams realize reduced cost benefits using
appropriate trusted sources
Only store copies of data within approved trusted sources
Motivations:
• Achieve highest degree of integrity and validity for business decisions
• Minimize ICT costs for managing and maintaining data
• Enhance ease of doing business by eliminating manual data
integration, normalization, etc.
Implications:
• Practitioners more likely to know what trusted sources exist, and which
ones to use
• Solution teams realize reduced cost benefits using appropriate trusted
sources
• Data currency is in line with business expectations.
Develop data models and a data dictionary for the entire
portfolio
Motivations:
• Improve operational excellence
• Reduce unnecessary transformations of data and related rework
• Enable meta data sharing for exchange and integration
purposes
• Improve future system design and programming projects
• Improved documentation and control mechanisms
Implications:
• Project teams bound by data model/dictionary governance
processes
• Close collaboration between business and IT stakeholders
• Easy access to data model/dictionary given to designers and
programmers
Implement data quality plans for all business solutions
Motivations:
• Maximize data integrity and validity for business operations and
decision making
• Avoid operational disruption due to data errors
• Reduce cost and complexity
Implications:
• Real cost implications associated with avoidance of data quality plans
• Data quality easier to implement and sustain
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Leading the Way in Electricity
SM
Other Related Work
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