AN OVERVIEW OF THE SALLIE MAE DATA GOVERNANCE PROGRAM

Transcription

1 AN OVERVIEW OF THE SALLIE MAE DATA GOVERNANCE PROGRAM DAMA Day Washington, D.C. September 19, /29/2011

2 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 2

3 DATA GOVERNANCE AND DATA QUALITY: THE FOUNDATION FOR BUILDING SALLIE MAEBUSINESS Business Objectives Operational Alignment Initiatives 3

4 ENTERPRISE DATA MANAGEMENT STRATEGY AT SALLIE MAE Data Governance Data Ownership Data Stewardship Data Quality Provides the creation of management structure for policies and rules governing enterprise data Implement necessary tools to automate process Metadata Management Repository Standards Processes Business Context Model Data Architecture & Design Conceptual Data Model Logical Data Model Physical Data Model 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 Data Management Services Definition Mapping & Conversion Synchronization Exception Handling Performance Mgmt Replatforming Integration Movement Matching Provides capabilities to support comprehensive EDM services Consolidation Quality Analysis Transformation Backup & Recovery Security Testing Support Access 4

5 LAYING THE FOUNDATION FOR DATA GOVERNANCE Data Architecture Enterprise Data Definition March - July 2006 Data Governance EDD Project 5

6 Top Down ENTERPRISE DATA DEFINITION APPROACH Both top-down and bottom-up approaches to leverage existing information Conceptual Data Model (Abstract Level) E.G., Borrower, Organization, Loan Logical Data Model (Business Level) E.G., Borrower Address, Borrower Phone, School, Lender, Guarantor Physical Database Structure (Detailed Level) E.G., Borrower table & associated columns Bottom Up 6

7 EDD CONCLUSION 4 Month Effort (March through July 2006) Why so quick? Centralized Data Management team Repository based data modeling tool Entities Entities Attributes Pre-Engagement 363 Post-Engagement Pre-Engagement Total in-scope physical entities reduced by 71% Total in-scope attributes reduced by 85% 3127 Post-Engagement

8 CHANGE IN MARKETING STRATEGY 2006 Moving from institution based marketing (schools, lenders) to consumer based marketing 8

9 DG/DQ PROGRAM TIMELINE March - July 2006 EDD Project Pilot Project: 7 DE August October

10 BUSINESS QUESTIONNAIRE -- SAMPLE Course of Study Our Business Unit: Our Pain When our group accesses these fields using the following system (e.g., CLASS, Eagle II, CDDB) we experience the following problems which we assume are a result of the following root cause Our Input Our group updates this data using the following channels (website, call center, etc.) many times/day once/day once/week once/month less frequently We review the quality of this data using the following methods many times/day once/day once/week once/month less frequently Our Understanding of Issues We don't know whether active capture of course of study is occurring We don't know whether this data is required or variable strongly disagree disagree not sure agree strongly agree 10

11 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 campaigns Don t be a solution waiting for a problem, find the problem and be the solution to it! 11

12 DG/DQ PROGRAM TIMELINE March - July 2006 November 2006 March 2007 EDD Project Pilot Project: 7 DE DG Program Design DG Program Implemented August October 2006 April

13 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 13

14 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 14

15 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 15

16 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 16

17 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 17

18 THE DATA GOVERNANCE STRATEGY DEFINED 18

19 SALLIE MAE DG/DQ SERVICES WHO S WHO? Business and IT Senior Management IT Sponsor Business Sponsor Enterprise Data Management (EDM) Strategy Data Governance Council Barbara Deemer and other LOB representatives Data Governance Office (DGO) Data Governance Michele Koch Splits into working groups Data Quality Services (DQS) DQ Core Team Subject Matter Experts (SMEs) Business Subject Matter Experts (SMEs) Data Subject Matter Experts (SMEs) IT 19

20 HOW DG WORKS Identify Issues Research Issues Make Decisions and Take Action DG Council LOB reps Business DGO DQS DG Council Project Teams IT DGO Other Subject Matter Experts (SMEs) (Business, Data, and IT) DGO Management Track and Communicate Progress 20

21 IDENTIFIED HOW GOVERNANCE INTEGRATED WITH OUR SDLC Data Stewards Data Governance Office (DGO) Data Architecture Data Modelers Project Team Trigger Trigger Trigger Trigger Add project to watch list Send FYI to Stewards and Modelers, ask PM to include DGO on stakeholder and participation lists 1. Project Initiation Invoke Data Governance in response to triggers: EA Assessment Knowledge that Enterprise Data will be impacted 3. Issue Resolution Use Data Governance to escalate and resolve issues Modeling issues? N Help resolve resolved? resolved? Perform modeling Update watch list Determine how the Data Governance Program fits into your Y SDLC N N Y Y On watchlist? 2. Technical Design Invoke Data Governance during or before SD-3 Perform Technical Design Provide status to stakeholders Update DGO Update Metadata Repository if needed 21

22 THE PERFECT STORM Sale of Sallie Mae falls through 22

23 SOME BUMPS ALONG THE WAY Communication is key when you encounter obstacles 23

24 ROAD TO RECOVERY 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 reseed the DG council and gain support for additional funding 24

25 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 25

26 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 26

27 STRONG BUSINESS/IT PARTNERSHIP Enterprise Participation 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 27

28 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 28

29 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 29

30 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 Manage Cost and Complexity Eliminate data reconciliation efforts and workarounds Reduce operational servicing costs Improve servicing performance for Dept of Ed contracts = increased Sallie Mae volume percentage awarded Implement enterprise architecture improvements (e.g. SOA, person matching) Reduce Risk and Support Corporate Compliance Improved 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 30

31 DG REPORTING CATEGORIES Metadata Support 5% Data Standardization 33% Project Support 11% Data Quality 37% MDM 14% Categories for DG Program metrics 31

32 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 32

33 COMMUNICATION Key is regularly and consistently! Easy to focus on the day-to-day activities, must focus on communicating the wins and payback 33

34 METHODS OF COMMUNICATION 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 data_governance/dghome 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 Calendar of meeting dates Meeting agenda and minutes Participant list DG issue reports Documents and presentations Meeting archives, DG news and announcements 34

35 TYPES OF COMMUNICATION Mission and value statements Elevator speech Slogan/Logo Status Reports Dashboards Presentations 35

36 DG/DQ PROGRAM TIMELINE March - July 2006 November 2006 March 2007 October-December 2009 July Present EDD Project Pilot Project: 7 DE DG Program Design DG Program Implemented DQ Program Design DQ Program & Pilot Implementation Monitor data Focus on root cause & prevention August October 2006 April 2007 January June

37 THE DATA QUALITY PROGRAM AND DG Data Quality Services The DG Program: Provides guidance, prioritization, and decisions for DQ activities Oversees resolution of DQ issues The DQ Program: Develops DQ management as a core competency Improves DQ throughout Sallie Mae 37

38 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 38

39 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 39

40 CONTINUING TO SHOW BUSINESS VALUE 40

41 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 41

42 LOOKING AHEAD Need to maintain data governance vigilance in order to ensure customer satisfaction and data quality 42

43 QUESTIONS? For further information, please contact Michele Koch Data Governance Solving boundary-spanning issues by pulling together the pieces of the data puzzle. 43