The document outlines a comprehensive framework for managing data and improving business models in various sectors, emphasizing the importance of master data management (MDM) and data governance. It highlights the challenges faced due to data silos, poor data quality, and the need for collaboration between IT and business functions to enhance data value. Additionally, it suggests strategies for quantifying data value and establishing a data governance framework to ensure successful implementation and improved decision-making.

1. Mazhar LeGhari
Building for Success: The Foundation for
Achievable MDM

2. Impact of Business Models and Data
Commercial Retail Wealth Capital Business Residential Data Individual Group Investments
Understand Impact of Business Models on Data
Loans Mortgages Investments LL Mobile Data Life Medical Pensions
On-Boarding, KYC, Risk, Privacy, AML Orders, Billing, Retention, Service Illustration Mgmt, Cases, Underwriting Policy
Integration Bus/SOA Integration Bus/SOA Integration Bus/SOA
Customer Illustrations
Billing Profile
Customer contacts Cases
Credit Profile
Meta Corporate contacts
Loyalty Profile Underwriting
Portfolio Risk Profiles
Reference Loans
Survey responses
Payment data Policies
Financial Terms Claims
Transactional Analytical
ABC Inc John Smith ABC Inc John Smith ABC Inc John Smith
XYZ Inc Jane Smith XYZ Inc Jane Smith XYZ Inc Jane Smith
Loans Savings Services Cases Policy
Accounts
Terms Credit Card Agreements Claims Premium
Services
Core Credit Call
Loans Policy Claims Billing Orders Commissions Products Funds Agency
Mktg ODS
Banking Card Centre
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3. Information Architecture Challenges
Commercial Retail Wealth Capital Business Residential Data
Business
Business Silos
Lack of Business Involvement
Loans Mortgages Investments LL Mobile Data
Lack of Data Value Positioning
On-Boarding, KYC, Risk, Privacy, AML Orders, Billing, Retention, Service
Customer Billing Profile Business/IT
Portfolio Credit Profile
Process Driven Data Focus
Loans Loyalty Profile
Financial Terms Survey responses Policies and Procedures
Various Data Terms & Meanings
ABC Inc John Smith ABC Inc John Smith
XYZ Inc Jane Smith XYZ Inc Jane Smith
Loans
IT
Savings Services Accounts
Terms Credit Card Agreements Data Fragmentation & Silos
Services
Poor Data Quality
Core Credit
Loans Policy Claims Billing Orders
Banking Card
Mktg ODS Project Delays
Data Integration Challenges
ODS DWH
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4. Traditional Information Management Approach
Retail Corporate Call Center
Integration Bus/SOA
Just In Time during Data Migration
Application Driven Approach Profile Cleanse De-Duplicate CRM
CRM
Billing Calls
Mktg.
Profile Cleanse De-Duplicate Loyalty
Loans ERP
Profile Cleanse Profile Cleanse De-Duplicate EDW
De-Duplicate
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5. Avoid Risks: Facilitate Business & IT Collaboration
Retail Corporate Call Center
Data Value Chain Data Governance
Sales Marketing Service
Terms Rules Data Semantics
Integration Bus/SOA
Analyze Evaluate Monitor Data Stewardship
Profile Cleanse De-Duplicate CRM
CRM
Billing Calls
Mktg.
Profile Cleanse De-Duplicate Loyalty
Loans ERP
Profile Cleanse Profile Cleanse De-Duplicate EDW
De-Duplicate
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6. Understand Who Needs What
DEPARTMENTS
Sales
Marketing
Finance
Risk and Compliance
Strategy Office
Field Operations
6
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7. Quantify Value: Leverage Use Cases
Industry Driver: Compliance
Source: TowerGroup, From High Street to Main Street…Finding business value in compliance spending,11-2010
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8. Quantify Value: Leverage Use Cases
Business Function: Marketing
Source: TowerGroup, 11-2010
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9. Quantify Value: Conduct Value Chain Analysis
High
Prepare Web & Deploy Service
High business Customer
Online Data Customer Recovery
value but Profitability
Contacts
modest data
availability or High value
quality. Products & to multiple
Fraud Data Campaigns Categories business
Make the
initiatives/
Business Value
investment
available data
Service
KPIs
Demographics
Social Media High ability
Transactions Product to deliver,
Profitability but modest
Churn business
Low business value. “Bolt
benefits, data Branch G/L Data on” to other
unavailable or Profiles Product business
too dirty Utilization initiatives
Defer Consider
Low
1 5
Low
Data Availability High
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10. Establishing Data Governance Framework
Corporate
P Strategic Priorities: Voice of the Business Drivers: At-Risk Projects: Data
Drivers
Customer; Compliance Mandates, Quality Improvement; Operational
R Mergers & Acquisitions Efficiencies
O Business
G Data Decision-
Framework Guiding Decision
R Governance making
A
Principles Rights
Process Charter Bodies
M
& Policy Data Stewardship Roles & Tasks
O
V Data
E Data Data Metadata Data Data Security &
R
Management Requirement Architecture Management Quality Administration Access
Rights
V
S Data People: Council, Stakeholders, Meeting Agendas
I
Governance
G Process: Metrics Definition, Workflow, Council By-Laws
H Execution Mechanisms: Stewardship Dashboards,
T
Process Workflow Automation, Data Profiling Tools
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11. Positioning Value: Focus on Business Drivers
Don’t Boil The Ocean
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12. Avoid Risks: Define Scope
Customer On-Boarding
Customer Centricity
Corporate Customers Segmentation
Core Retail Customers Marketing
Banking Counterparties
Customer contacts
Loans Corporate contacts
Customer 360
Portfolio
Credit Loans
Card Financial Terms Hub
Suppliers
Policy
Insured Exposure Compliance Reports
Brokers Compliance Solvency II Applications
Claims Citizen Records Broker Book of Business
Life Time Value
As Is Data Management Approach To Be Data Management Approach
Supply Chain, Procurement, Asset Maintenance
Location/Site Products Assets Supplier Product Catalogs
ERP Asset Data Mastering
Supplier On-Boarding/Rating
Hub
ERP
Location/Site Hub
Inventory
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13. Use Case: New Data Challenges in Financial Services
Operational Impact of Regulations
VS.
Data Driven Approach
Application Driven Approach
Source:2013 , SAS Institute Inc. All rights reserved.
Copyright © TowerGroup, From High Street to Main Street…Finding business value in compliance spending,11-2010

14. Use Case: Consolidation of Customer Data in Telecoms
One of the biggest challenges facing today’s telecommunications providers is the
ability to sift through the massive volumes of detailed customer and network usage
data in order to provide an end-to-end picture of their network, financial and customer
behavior. In today’s hyper-competitive marketplace, those with the best data will win.
TM Forum: Power of Questioning Everything About Your Business
VS.
Data Driven Approach
Application Driven Approach
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15. Information Management Landscape with MDM
Commercial Retail Wealth Capital Business Residential Data Sales Marketing Service
Data Management Landscape with MDM
Loans Mortgages Investments LL Mobile Data Customer Care Web Call Centre
On-Boarding, KYC, Risk, Privacy, AML Orders, Billing, Retention, Service Loyalty, Profitability, Campaigns
Integration Bus/SOA Integration Bus/SOA Integration Bus/SOA
Customer Sales revenues
Billing Profile
Customer contacts Customer segments
Credit Profile
Meta Corporate contacts
Loyalty Profile Promotion history
Portfolio Campaign responses
Reference Loans
Survey responses
Payment data Customer value scores
Financial Terms
Transactional Analytical
ABC Inc John Smith ABC Inc John Smith ABC Inc John Smith
Hub Hub Hub
XYZ Inc Jane Smith XYZ Inc Jane Smith XYZ Inc Jane Smith
Loans Savings Services Offers Demographics
Accounts
Terms Credit Card Agreements Segment Campaigns
Services
Core Credit Call
Loans Policy Claims Billing Orders CRM Products ERP DWH
Mktg ODS
Banking Card Centre
Copyright © 2013 , SAS Institute Inc. All rights reserved.

16. Avoid Risks: Summary
Don’t Boil The Ocean
Commercial Retail Wealth Insurance Sales Distribution Service
Executive Sponsorship
Business Focused
Loans Mortgages Policy Orders Suppliers Procurement
Data Governance Framework
Build Foundation for Data Governance Framework & Master Data Data Stewardship
• Define • Design • Evaluate
• Discover • Control Scope for Success
• Execute
Understand Complexity
Build Roadmap
ABC Inc John Smith ABC Inc John Smith
XYZ Inc Jane Smith XYZ Inc Jane Smith Address Data Silos
Loans Savings Services Accounts
Terms Hub Hub Improve Data Quality
Credit Card Agreements Services
MDM for Trusted Data
Core Credit
Loans Loans Claims Policy Policy
Banking Card Agency Cases Take the Phased Approach
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17. Mazhar LeGhari
mazhar.leghari@sas.com
@LinkedIn
Twitter - @mleghari
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