award winning data governance
TRANSCRIPT
Copyright © 2011 Sallie Mae, Inc. All rights reserved.
Dataversity/DGPO WebinarOctober 27, 2011
AN OVERVIEW OF THE SALLIE MAE DATA GOVERNANCE PROGRAM
8/29/2011
Copyright © 2011 Sallie Mae, Inc. All rights reserved.
2Copyright © 2011 Sallie Mae, Inc. All rights reserved.
SALLIE MAE BACKGROUND► Sallie Mae is the nation’s leading provider of saving,
planning and paying for education programs
► Since its founding more than 35 years ago, the company has invested in more than 31 million people to help them realize their dreams of higher education
► Sallie Mae manages $236 billion in education loans and serves 11 million student and parent customers
► Through its Upromise affiliates, the company also manages more than $27 billion in 529 college-savings plans, and is a major, private source of college funding contributions in America with more than $575 million in member rewards
► Sallie Mae is a Fortune 500 company with 8,000 employees in 16 locations nationwide
Copyright © 2011 Sallie Mae, Inc. All rights reserved.
3Copyright © 2011 Sallie Mae, Inc. All rights reserved.
DG & DQ Programs
DATA GOVERNANCE AND DATA QUALITY: THE FOUNDATION FOR BUILDING SALLIE MAE BUSINESS
Operational Alignment Initiatives
Business Objectives
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ENTERPRISE DATA MANAGEMENT STRATEGY AT SALLIE MAE
Data Governance
Data Ownership Data Stewardship Data Quality
Metadata Management
Repository Standards Processes
Data Architecture & DesignBusiness Context Model
Conceptual Data Model
Logical Data Model
Physical Data Model
Provides the creation of management structure for policies and rules governing enterprise data
Implement necessary tools to automate process
Provides documentation of all aspects of the business and technology components of enterprise data
Includes repository building, defining standards, architecture, maintenance process, tool selection
& implementation
Design, development and maintenance of data models at the business context, conceptual, logical and physical level
Represents the data entities, their relationships, attributes, structure and usage
Provides capabilities to support comprehensive EDM services
Data Management Services Definition
Mapping & Conversion Synchronization Exception
HandlingPerformance
Mgmt
Replatforming Integration Movement Matching
Consolidation Quality Analysis Transformation
Backup & Recovery Security Testing Support Access
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Enterprise Data Definition
Data Architecture
Data Governance
LAYING THE FOUNDATION FOR DATA GOVERNANCE
EDD Project
March - July 2006
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ENTERPRISE DATA DEFINITION – APPROACH
6
Both
“top-down” and
“bottom-up” approaches to leverage
existing information
Physical Database Structure
(Detailed Level)
E.G., Borrower table & associated
columns
Top
Dow
n Botto
m U
pConceptual Data Model (Abstract
Level)
E.G., Borrower, Organization, Loan
Logical Data Model (Business Level)
E.G., Borrower Address, Borrower
Phone, School, Lender, Guarantor
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EDD – CONCLUSION
1282
363
0
200
400
600
800
1000
1200
1400
Pre-Engagement Post-Engagement
Entities
7
21218
3127
0
5000
10000
15000
20000
25000
Pre-Engagement Post-Engagement
Attributes
Total in-scope physical entities reduced by 71% Total in-scope attributes reduced by 85%
Entities Attributes
► 4 Month Effort (March through July 2006)► Why so quick?
Centralized Data Management team Repository based data modeling tool
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CHANGE IN MARKETING STRATEGY
2006Moving from institution based marketing (schools, lenders) to consumer based marketing
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DG/DQ PROGRAM TIMELINE
9
Pilot Project:7 DE
EDD Project
March - July 2006
August – October 2006
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DEMONSTRATED BUSINESS VALUE FROM DAY ONE
► DG Pilot project Increased revenue by $2.4M
for the first two years based on an estimated increase of $50M in loan volume
Eliminated costs of $4.8M spent on letters/postage that were replaced by email campaigns
► Don’t be a solution waiting for a problem, find the problem and be the solution to it!
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DG/DQ PROGRAM TIMELINE
11
DG Program Implemented
DG ProgramDesign
Pilot Project:7 DE
EDD Project
March - July 2006
November 2006–March 2007
August – October 2006
April 2007
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COORDINATION AND COOPERATION
► The ability to get the right people together to make decisions and agree on effective action regarding Sallie Mae’s data is never easy
In a complex environment it can feel…IMPOSSIBLE
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MAKING DECISIONS AND TAKING ACTION
► Fortunately, for data-related issues, Sallie Mae has in place: A process to
• Make decisions• With appropriate representation (from LOBs, teams, etc.)• And knowledge (access to subject matter experts in business,
data, and IT)
So they can• Resolve issues• Implement effective changes• Avoid unexpected consequences• Communicate actions
Cutting through the red tape
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DATA GOVERNANCE AT SALLIE MAE
► Data Governance is a discipline, a program, and a key component of the Sallie Mae Enterprise Data Strategy
► Data Governance occurs where Business, IT, and data intersect and includes proactive, reactive, and ongoing efforts
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DATA GOVERNANCE COOKBOOK
► The Data Governance Program is defined in a Data Governance Cookbook with an introduction and nine modules Policy Organization Process Office Administration Organizational Alignment Communications Data Quality DG and SMPAL Business Benefits
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GOVERNANCE MATURITY LEVELS FOR SALLIE MAE DATA► Sallie Mae adopted a Governance Maturity
Model to describe the levels of maturity for its enterprise data
► This model began with best practices from the Data Governance Institute, then was customized to the unique Sallie Mae environment
► This model describes data that is: Level 0 - Ungoverned Data Level 1 - Modeled Data Level 2 - Repository Data Level 3 - Standardized Data Level 4 - Standardized with Known Issues Data Level 5 - Matured Data
16
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THE DATA GOVERNANCE STRATEGY DEFINED
17
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SALLIE MAE DG/DQ SERVICESWHO’S WHO?
Business and IT Senior ManagementIT Sponsor
Business Sponsor
Enterprise Data Management (EDM) Strategy
Data Governance Council
Barbara Deemer and other LOB
representatives
Data Quality Services (DQS)
DQ Core Team
Splits into working groups
Data Governance Office (DGO)
Michele Koch
Data GovernanceData Governance
Subject Matter Experts (SMEs)
Business
Subject Matter Experts (SMEs)
Data
Subject Matter Experts (SMEs)
IT
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HOW DG WORKS
Identify Issues
Research Issues
Make Decisions and Take Action
•
Track and Communicate Progress
DG Council
Business
IT
Project Teams
DGO
Management
DQS
Other Subject Matter Experts
(SMEs)(Business,
Data, and IT)
DGO
DGO
DG Council
LOB reps
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ProjectTeam
Data Modelers
DataArchitecture
DataStewards
Data Governance Office (DGO)
Update watch
list
Provide status to
stakeholders
Trigger
Add project to watch
list
Send FYI to
Stewardsand
Modelers, ask PM to
include DGO on
stakeholder and
participation lists
Trigger
Trigger
Trigger
1. Project InitiationInvoke Data Governance in response to triggers:• EA
Assessment• Knowledge
that Enterprise Data willbe impacted
2. Technical DesignInvoke Data Governance during or before
SD-3 Perform Technical Design
Update MetadataRepository if needed
Performmodeling
On watch-
list?
UpdateDGO
N
Modelingissues?
resolved?
resolved?
Help resolve
N
N
Y
Y
Y
3. Issue ResolutionUse Data Governance to escalateand resolve issues
Determine how the Data GovernanceProgram fits into your SDLC
IDENTIFIED HOW GOVERNANCE INTEGRATED WITH OUR SDLC
20
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THE PERFECT STORM
2007-2008
CREDIT MARKETS
CRASHStaff changes at all
levels
Sale of Sallie Mae falls through
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SOME BUMPS ALONG THE WAY
► Communication is key when you encounter obstacles
22
Budget cuts/
loss of staff
in 2008
New management at the executive level
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ROAD TO RECOVERY
23
Progress continues but at a slower pace without additional staff
Leveraged new enterprise initiatives to show the value of Data Governance
Used an audit to re-seed the DG council and gain support for additional funding
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HEALTH CARE REFORM
2010► FFELP student loan program is abolished
80% of our ability to originate new assets is lost!
► Time for some tough decisions While competitors closed their doors, we aggressively
targeted new products and new customers
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COMPANY TRANSFORMATION
► Executives had confidence in the data needed to make decisions to move the company forward as a result of strong Sallie Mae data management and DG programs
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STRONG BUSINESS/IT PARTNERSHIP
► Data Governance Office = 3
► Data Quality Services Team = 3
► Data Governance Council
Lines of Business = 18
Business Data Stewards = 23
► Business SMEs = 18
► IT SMEs = 25
► Data SMEs = 2
Enterprise Participation
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GREAT STAKEHOLDER CARE
► Serve in a “Trusted Broker” position in all dealings with stakeholders
► Ensure that members of senior management and the DG Council are made aware of potential impacts of decisions put before them
► Arrange for mentoring or coaching of stakeholders as required
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METRICS
Capture as you go!
Pilot project metrics:• Industry standards and publications
• Interviewed business areas
DG Program metrics:• Determine business value
• Define reporting categories
• Determine how to track data issues
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WHAT A DG/DQ PROGRAM DOES FOR SALLIE MAE
Increase Revenue Facilitate Private Credit products speed to market
Increase volume available for the PUT process and trusts
Improve servicing performance for Dept of Ed contracts = increased Sallie Mae volume percentage awarded
Manage Cost and ComplexityEliminate data reconciliation efforts and workarounds
Reduce operational servicing costs
Implement enterprise architecture improvements (e.g. SOA, person matching)
Reduce Risk and Support Corporate ComplianceImproved risk management and corp. compliance through DQ and standardization
Reduce audit findings due to inaccurate or inconsistent data
Improve identification and documentation of identity fraud
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Categories for DG Program metrics
Data Standardization
33%
Data Quality
37%
Metadata Support
5%
ProjectSupport
11%
MDM14%
DG REPORTING CATEGORIES
30
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DOCUMENT BUSINESS VALUE METRICS
► Implemented resolutions for 77% of the data issues since DG Program inception
► Utilized proven techniques for quantifying business value
► Linked business value calculations to financial statement categories
Goal: Focus on solving business problems while always keeping your eye on delivering a first rate DG Program
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COMMUNICATION
Key is regularly and consistently!
► Easy to focus on the day-to-day activities, must focus on communicating the wins and payback
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1
2
3
METHODS OF COMMUNICATION
Decision makers for boundary
spanning data issues
Meets every other Tuesday
Meeting agenda and supporting
documentation posted on web
and sent prior to the meeting
DG Council
DG Web Page
data_governance/dghome
Calendar of meeting dates
Meeting agenda and minutes
Participant list
DG issue reports
Documents and presentations
Meeting archives, DG news and
announcements
Use to send information on new
data issues, pose questions,
comments, and concerns
Mailbox goes directly to:
DGO Program Director
Chief Data Steward
DGO Assistant
DGO Mailbox
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TYPES OF COMMUNICATION
► Mission and value statements
► Elevator speech
► Slogan/Logo
► Status Reports
► Dashboards
► Presentations
TO INFINITY…AND BEYOND!
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DG/DQ PROGRAM TIMELINE
35
DG Program Implemented
DG ProgramDesign
DQ ProgramDesign
Pilot Project:7 DE
EDD ProjectDQ Program
& Pilot Implementation
Monitor dataFocus on
root cause & prevention
March - July 2006
October-December 2009
November 2006–March 2007
July 2010 - Present
August – October 2006
April 2007January – June
2010
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Data Quality Services
The DQ Program:
• Develops DQ management as a core competency
• Improves DQ throughout Sallie Mae
The DG Program:
• Provides guidance, prioritization, and decisions for DQ activities
• Oversees resolution of DQ issues
THE DATA QUALITY PROGRAM AND DG
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KEY DG/DQ ENGAGEMENTS
► Reconciliation projects for Finance
► Loan Acquisition Conversions
► EDW Support
► MDM Support
► New project support
► Metadata support
► Training on DQ tools
► Consulting to teams
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HOW THE DQ PROGRAM SHOWS VALUE AND PROGRESS
► Three categories of metrics are reported State of Data Quality Business Value from Data Quality Data Quality Program Performance
► For each category, a dashboard level status is summarized from detailed reports
► Drilldown information is included as appropriate for the specific metric
Dashboard
Drilldown
Detail
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CONTINUING TO SHOW BUSINESS VALUE
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NEXT STEPS► DG program must evolve and
grow as Sallie Mae continues to redefine itself and expand into new product areas
► Continue to move from reactive to pro-active
► DG/DQ become integral to our core business processes as the environment gets more complex
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LOOKING AHEAD
► Need to maintain data governance vigilance in order to ensure customer satisfaction and data quality
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► For further information, please contactMichele [email protected]
QUESTIONS?
Data GovernanceData GovernanceSolving boundary-spanning issues
by pulling together the pieces of the data puzzle.
Data GovernanceData GovernanceSolving boundary-spanning issues
by pulling together the pieces of the data puzzle.