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Master Data Management –The Nationwide ExperienceMaster Data Management –The Nationwide Experience
Lance Lance DacreDacre –– Director, Data GovernanceDirector, Data Governance
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AgendaAgenda
Finance FOCUS projectFinance FOCUS project
Master Data ManagementMaster Data Management
Data GovernanceData Governance
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Assessment of Finance FunctionAssessment of Finance Function
Availability of Financial Information– Management lacks easy and timely access to needed financial information.
Obtaining basic information can be difficult and labor intensive.
Comparability of Financial Information– Financial information and results of different business units and segments are
often difficult to compare without substantial manual intervention to address data accuracy and consistency.
Finance Function Efficiency– Decentralized, duplicative and non-standard financial processes and systems
add cost, require manual intervention, and are expensive to maintain and operate.
Finance Function Effectiveness– Extensive reconciliation and transaction processing activities are manually
intensive adding to finance function expense. These, and similar, activities often distract staff from business analysis and advisory efforts.
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FOCUS VisionFOCUS Vision
FOCUS should address the significant improvements needed in the eight core process disciplines of finance to achieve the future vision.
• Business Planning
• Capital Optimization
• Risk Management
• Analysis & Interpretation
• Accounting & Reporting
• Finance Organization Management
• Stakeholder Management
• Policy Management
World Class
Reliable& Consistent
EfficientlyManaged
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Pre-FOCUS StatePre-FOCUS State
Between the various business, FOCUS looked to consolidate:– 14 General Ledgers– 20 Charts of Accounts– 12 Reporting Tools– 17 Financial Data Repositories– 300,000 Excel Spreadsheets– 75% of Finance Resources Dedicated to Transactional
Activities– 25% of Finance Resources Dedicated to Analysis and
Insight
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The Pillars of Finance FOCUSThe Pillars of Finance FOCUS
People– Finance Shared Service Center
Processes– Data Governance
Technology– Common Use Applications
Information– Single Version of the Truth
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Conceptual View of the Finance Systems ArchitectureConceptual View of the Finance Systems Architecture
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Financial System ToolsFinancial System ToolsIntegrated Back Office(FOCUS Environment)
Meta Data Repository
Finance Users
Data Providers -Source Systems . Info Delivery .
. Structures .
Regulatory Reports
Managemt Reports
Standard Reporting
Tools
OLAP & Analysis
Tools
Data Integration . ERP .
ERPdata
. Calc Engines .
Risk Analytics
Extract
Load
Staging
Transform
Derive
Validate
Calc enginedata
Allocations
Budget/ Planning
Consol-idation
Module “Operational”
Reporting
Recon
Exception Mgmt
Open Items
Forecast
Common Transport Processes
Scheduling and job controls
GL
ARPO
APTrsy
AM
Ledger “Flash”
Reporting
Module “Operational”
Reporting
FinanceData
Warehouse
Finance Data Marts
Subject Data Marts
Other Extracts
Manual entries
eFIN PO
eFIN AP
eFIN AM
eFIN AR
Source 1
Source 2
Source n
PCIO sources
. . .
Source 1
Source 2
Source n
NF sources
. . .
Other sources. . .
Reference
data
Monetary
data
Stats &
DriversLaptops
Workstations
Reference Data Repository
Land
ing
Are
aE
TL S
ervi
ces
Por
tal_
_
ePRO
Informatica
Maestro
PeopleSoft
PeopleSoft
Hyperion
Teradata
Essbase
Analyzer
Kalido
Websphere
Harvest
PeopleSoft Portal
Custom
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MDM ChallengesMDM Challenges
People– Business Owner Buy-In– Technology Owner Buy-In
Process– Lack of Institutional Experience– Lack of Clear Industry Definition and
DirectionTechnology– Vendor Support– Component Integration
Information– Aggregating and Cleansing
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Master Data ContentMaster Data Content
How do we define Master Data? What is our Scope?
Key ComponentsDimensions – Financial and Non-Financial
Hierarchies – Standard Hierarchies – Alternate Hierarchies
Business Rules
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Master Data Statistics at NationwideMaster Data Statistics at Nationwide
84 Dimension Tables– 28 Dimensions have reporting hierarchies
• 26 Standard Hierarchies• 53 Alternate Hierarchies
Approximately 200 Translation Tables for over 250 interfaces
Over 1,100 Reference Data Tables
Over 175 unique attributes across all dimensions and growing
7-10 attributes per dimension on average
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Change ProcessChange Process
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Data GovernanceData Governance
Data Governance is currently responsible for the quality and integrity of Nationwide’s financial data.– Provide a mechanism to maintain and
control key reference and metadata used in financial processes, reports and analysis
– Reports through the Controllership function
Key Governance Roles– Gatekeeper– Communicator– Advocate– Analyst
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Data GovernanceData Governance
Data Design Standards & Policies
Data Governance
Business Rules/Interfaces
Master DataManagementMetadata
Reporting
DemandManagement/
ChangeControl
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Lessons LearnedLessons Learned
Align strong executive leadership to the projectLook end to end– Centralized business rules engine up front– Centralized MDM repository for external consumers
Establish Data Governance– Strong metadata and policies– Build data stewardship that encourages ownership of
data
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DiscussionDiscussion