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An Overview of the Sallie Mae Data Governance Program

An Overview of the Sallie Mae Data Governance Program. DAMA Philadelphia/Delaware Valley Meeting. 3/13/2013. Sallie Mae is the nation’s leading provider of saving, planning and paying for education programs

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An Overview of the Sallie Mae Data Governance Program

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  1. An Overview of the Sallie Mae Data Governance Program DAMA Philadelphia/Delaware Valley Meeting 3/13/2013

  2. Sallie Mae is the nation’s leading provider of saving, planning and paying for education programs Since its founding more than 40 years ago, the company has invested in more than 31 million people to help them realize their dreams of higher education Serving 23 million customers, the company and its subsidiaries manage or service $234 billion in education loans and administer $38 billion in 529 college savings plans Members of its Upromise college savings rewards program have earned $625 million to help pay for college Sallie Mae is a Fortune 500 company with 6,600 employees in 16 locations nationwide Sallie Mae Background

  3. Data Governance & Data Quality: The Foundation for Building Sallie Mae Business Business Objectives Strategic Initiatives DG & DQ Programs

  4. Enterprise Data Management Strategy at Sallie Mae

  5. Laying the Foundation for Data Governance Data Architecture Enterprise Data Definition EDD Project March - July 2006 Data Governance

  6. To define what Sallie Mae means by “Enterprise Data”: • Identify business data by Line of Business (LOB) and develop LOB repositories • Identify data that spans multiple LOBs and develop system-to-data charts for enterprise data • Develop list of enterprise entities/attributes that are candidates for Data Governance • Develop an Enterprise Logical Data Model • Complete the Zachman framework for the data column EDD - Objectives

  7. 7 in-scope Lines of Business (LOBs) 4 in-scope systems Data spread across multiple systems and multiple LOBs resulting in suboptimal mapping EDD – Pre-initiative Stage 21,218in-scope attributes 1,282 in-scope physical entities Entities/Tables Attributes/Columns

  8. Top Down Bottom Up Enterprise Data Definition – Approach Conceptual Data Model (Abstract Level) E.G., Borrower, Organization, Loan Both “top-down” and “bottom-up” approaches to leverage existing information 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

  9. 4 Month Effort (March through July 2006) • Sallie Mae Employee Hours = 1200 • Contractor Hours = 1200 Why so quick? • Centralized Data Management team • Repository based data modeling tool EDD Conclusion Total in-scope physical entities reduced by 71% Total in-scope attributes reduced by 85%

  10. 2006 Change in Marketing Strategy Moving from institution based marketing (schools, lenders) to consumer based marketing

  11. Pilot Project - 7 Data Elements March - July 2006 Pilot Project: 7 DE EDD Project August – October 2006

  12. Understand and document the business issues associated with each of the 7 data elements Identify and document recommended business process and/or IT solution(s) for each of the fields Leverage the lessons learned from this project as input into the formal design of Data Governance • Test and choose from options for key DG processes and organizational alignment approaches 7 Data Elements Project - Objectives

  13. Business Questionnaire - Sample To help frame the issue and understand impacts to each business area

  14. Possible Solution Paths for each Data Element List of 43 Action Items that evolved into an Action Item Summary Document Additional meetings and analyses resulted in: • Updated metadata • Better understanding and communication across LOBs regarding data usage • Approx. 20 business and/or IT changes to be tracked and reported on in a Phase 2 7 Data Elements Project - Output

  15. 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!

  16. DG Program Implementation March - July 2006 November 2006– March 2007 DG Program Implemented Pilot Project: 7 DE DG Program Design EDD Project August – October 2006 April 2007

  17. 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 Data Governance at Sallie Mae VALUE Statement Through horizontal alignment, we can achieve value and solve problems that are impossible in separated vertical silos

  18. Data Governance Cookbook • The Data Governance Program is defined in a Data Governance Cookbookwith an introduction and nine modules • Policy • Organization • Process • Office Administration • Organizational Alignment • Communications • Data Quality • DG and SMPAL • Business Benefits

  19. Sallie Mae is adopting 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 - Governed Data • Level 5 - Matured Data Governance Maturity Levels for Types of Sallie Mae Data

  20. Data Governance Data Quality The Data Governance Strategy Defined Data Ownership EDM component: Data Governance Strategy Focus Supporting Master Data Management, Resolving data issues; Increasing the maturity of data Mission Proactively create and align rules, react to data issues, and provide ongoing stakeholder care Data Stewardship • Strategy • Establish a Data Governance Office (DGO) and a Data Governance Council • Bake Data Governance processes into SLM SDLC and ongoing processes • Establish decision-making and issue resolution processes • Establish a process for defining and monitoring data-related rules • Provide a centralized mechanism for stakeholder communications • Implement a Data Governance Maturity Model and activities • Participate in Enterprise Architecture alignment efforts • Policies • All Enterprise Data is subject to Data Governance and cannot be changed architecturally without approval of the DGO • All initiatives that touch Enterprise Data must involve the DGO during project initiation and design • The Data Governance Council will set priorities for Data Governance efforts; the DGO will define policies and standards and will facilitate and coordinate governance efforts

  21. Sallie Mae Data Governance Policies cover the following areas: Data Governance Organizational Bodies Role of the DGO Data Subject to Governance Project - to - Data Governance Alignment Issue Analysis Process Issue Resolution Stakeholder Care Process and Policy Documentation Project Artifacts and Emails Project - to - Data Governance Alignment Change Control Sallie Mae Data Governance Policies

  22. Business and IT Senior Management Enterprise Data Management (EDM) Strategy Sallie Mae DG/DQ Services Who’s Who? IT Sponsor Business Sponsor Data Governance Council Data Governance Office (DGO) Chief Data Steward and other LOB representatives 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

  23. Strong Business/IT Partnership • Data Governance Office = 3 • Data Quality Services Team = 3 • Data Governance Council • Lines of Business = 18 • Business Data Stewards = 22 • Business SMEs = 17 • IT SMEs = 19 • Data SMEs = 2 Enterprise Participation

  24. 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 Great Stakeholder Care

  25. How DG Works DG Council LOB reps Business DG Council DGO DQS DGO Other Subject Matter Experts (SMEs) (Business, Data, and IT) Project Teams DGO IT Management Track and Communicate Progress

  26. The DGO fosters alignment with the following groups: Business through the DG Council Risk Management/Compliance Information Security Enterprise Data Management (EDM) Enterprise Architecture Project Management Office (PMO) • Project Management • Project Prioritization Best Practice: Checks-and-Balances DG Program Alignment

  27. Sallie Mae is placing more importance on the formal management of its architectures: systems, application, data, business/process, and security Many of the decisions that DG will be asked to help make or enforce lie in the intersection points of multiple architectures. And so,it is important to balance needs in several dimensions: • Between Business and IT • Between multiple business stakeholders • Between the short-term needs of projects and the longer-term needs of architectural integrity • Between different architectural domains Such alignment is considered one of the greatest challenges – and one of the greatest value statements – of governance-facilitated alignment and issue-resolution processes Alignment Within Enterprise Architecture Data Business Process Management Systems Information Security Application

  28. Help resolve DataStewards Identified How Governance Integrated with our SDLC Trigger Send FYI to Stewardsand Modelers, ask PM to include DGO on stakeholder and participation lists (3) Issue Resolution N Add project to watch list Update watch list resolved? Provide status to stakeholders Data Governance Office (DGO) Use Data Governance to escalateand resolve issues Y Determine how the Data Governance Program fits into your SDLC N DataArchitecture resolved? Trigger Y (1) Project Initiation Invoke Data Governance in response to triggers: Modelingissues? On watch-list? Y UpdateDGO Data Modelers Trigger N Performmodeling Update MetadataRepository if needed • EA Assessment • Knowledge that Enterprise Data will be impacted (2) Technical Design Invoke Data Governance during or beforeSD-3 Perform Technical Design ProjectTeam Trigger

  29. Capture as you go! Metrics • 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

  30. What a DG/DQ Program Does for Sallie Mae Increase Revenue Facilitate Private Credit products speed to market utilizing vendor solutions Increase volume available for securitized trusts Improve servicing performance for Dept of Ed contracts = increased SLM volume percentage awarded Manage Cost and Complexity Eliminate data reconciliation efforts and workarounds Reduce operational servicing costs Automate manual processes for Collections using the DQ tool Reduce Risk and Support Corporate Compliance Improve risk management and corp. compliance through DQ and standardization Reduce audit findings due to inaccurate or inconsistent data Improve enterprise communications regarding data issues and solutions

  31. DG Program Metrics Reporting Categories Data Standardization 33% MDM 14% Metadata Support 5% Data Quality 37% Project Support 11%

  32. Document Business Value Metrics • Implemented resolutions for 87% 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

  33. Key is regularly and consistently! To accomplish your goals, you’ll need to address multiple types of communication • Verbal Communications • Data Governance “PR” and Messaging • Trigger-Based Communications • Scheduled Communications • Intranet Site You can have one plan or several, but you should address all these needs Communications

  34. Provide SMEs to protect your own interests as we collect the pieces of the puzzle • WHY? -- So that we do not inadvertently make decisions that you can not live with Participate for 3 reasons: • Protect your interests • Sometimes it is going to be your problems that we will be trying to solve • It is your duty to help the company make money and reduce costs  DG Initial Sound Bite Examples

  35. Presentations to: • Executives (Business and IT) • Middle management (Business and IT) • Business Data Stewards and SMEs • IT SMEs For each presentation: • Identify key messages to deliver • Identify your audience • Decide on “variations” of messages you’ll usually need to deliver • Determine how long you have to present • Ask yourself – What is in it for them? • Use value statements to bring focus to your messages DG Presentations To Infinity…and beyond!

  36. DG/DQ HEADLINE NEWS Wednesday, February 28, 2013 THE BEST SOURCE FOR DG NEWS - DG Since 2006 http://..DivResources/Tech/et/Pages/DG%20Program.aspx Topic Title Goes Here Use another topic here and add a picture image for interest. Change the background color each month, change fonts, find other ways to draw attention to the “article”. DGO – Title for main issue worked this month DQ – Title for main issue worked this month Fill in the details of your main activity for Data Governance. Keep it short to keep their interest. Fill in the details of your main activity for Data Quality. Provide the key details in a couple summary paragraphs. Add a picture file that ties in with your topic

  37. Methods of Communication 1 DG Council • 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 2 3 DGO Mailbox • 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 DG Web Page • Calendar of meeting dates • Meeting agenda and minutes • Participant list • DG issue reports • Documents and presentations • Meeting archives, DG news and announcements DATA_GOV@salliemae.com data_governance/dghome

  38. Data Governance Website

  39. û û Communication is key when you encounter obstacles Some Bumps Along the Way • New management at the executive level • Budget cuts/ loss of staff in 2008

  40. Road To Recovery    Progress continued 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

  41. DQ Program Design and Pilot Implementation March - July 2006 November 2006– March 2007 October-December 2009 July 2010 - Present Monitor data Focus on root cause & prevention DQ Program & Pilot Implementation DQ Program Design DG Program Implemented Pilot Project: 7 DE DG Program Design EDD Project August – October 2006 April 2007 January – June 2010

  42. 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

  43. 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

  44. Continuing To Show Business Value

  45. 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 • Need to maintain data governance vigilance in order to ensure customer satisfaction and data quality

  46. Questions? • For further information, please contact Michele Koch Michele.V.Koch@salliemae.com 703-984-6601

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