A OVERVIEW OF THE SALLIE MAE D GOVERNANCE · PDF filePhysical Database Structure (Detailed...

Copyright © 2011 Sallie Mae, Inc. All rights reserved.

DAMA DayWashington, D.C.

September 19, 2011

AN OVERVIEW OF THE SALLIE MAE

DATA GOVERNANCE PROGRAM

8/29/2011

Copyright © 2011 Sallie Mae, Inc. All rights reserved.Copyright © 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

2


DATA GOVERNANCE AND DATA QUALITY:

THE FOUNDATION FOR BUILDING SALLIE MAE BUSINESS

3

Operational Alignment Initiatives

Business Objectives


ENTERPRISE DATA MANAGEMENT

STRATEGY AT SALLIE MAE

4

Data Governance

Data Ownership Data Stewardship Data Quality

Metadata Management

Repository Standards Processes

Data Architecture & Design

Business 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 Handling Performance Mgmt

Replatforming Integration Movement Matching

Consolidation Quality Analysis Transformation

Backup & Recovery Security Testing Support Access


Enterprise Data Definition

Data Architecture

Data Governance

LAYING THE FOUNDATION FOR

DATA GOVERNANCE

5

EDD Project

March - July 2006


ENTERPRISE DATA DEFINITION – APPROACH

6

Both

“top-down”

and

“bottom-up”

approaches

to leverage

existing

informationPhysical Database Structure

(Detailed Level)

E.G., Borrower table & associated columns

To

p D

ow

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


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


CHANGE IN MARKETING STRATEGY

2006

8

Moving from institution based marketing (schools, lenders) to consumer based marketing


DG/DQ PROGRAM TIMELINE

9

Pilot Project:

7 DEEDD Project

March - July 2006

August – October 2006


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

many

times/day once/day once/week once/month

less

frequently

(website, call center, etc.)

We review the quality of

this data

many

times/day once/day once/week once/month

less

frequently

using the following

methods

Our Understanding of Issues

strongly

disagree disagree not sure agree

strongly

agree

We don't know whether active capture of course of

study is occurring

We don't know whether this data is required or variable

10


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!

11



12

DG Program

Implemented

DG Program

Design

Pilot Project:

7 DEEDD Project

March - July 2006

November 2006–March 2007


April 2007


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

13

In a complex environment it can feel…IMPOSSIBLE


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

14

Cutting through the red tape


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


DATA GOVERNANCE COOKBOOK

16

► 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


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


THE DATA GOVERNANCE STRATEGY DEFINED

18


SALLIE MAE DG/DQ SERVICES

WHO’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


Data


IT

19


HOW DG WORKS

20

Identify IssuesResearch 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


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

Stewards

and

Modelers,

ask PM to

include

DGO on

stakeholder

and

participation

lists

Trigger

Trigger

Trigger

1. Project Initiation

Invoke Data

Governance in

response to

triggers:• EA

Assessment• Knowledge

that Enterprise Data willbe impacted

2. Technical Design

Invoke Data Governance during or before

SD-3 Perform Technical Design

Update Metadata

Repository if needed

Perform

modeling

On

watch-

list?

Update

DGO

N

Modeling

issues?

resolved?

resolved?

Help

resolve

N

N

Y

Y

Y

3. Issue Resolution

Use Data

Governance

to escalate

and resolve

issues

Determine how the Data Governance

Program fits into your SDLC

IDENTIFIED HOW GOVERNANCE INTEGRATED

WITH OUR SDLC

21


THE PERFECT STORM

2007-2008

22

Sale of Sallie Mae falls through


SOME BUMPS ALONG THE WAY

► Communication is key when you encounter obstacles

23


ROAD TO RECOVERY

24

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


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


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


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

27

Enterprise Participation


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


METRICS

Capture as you go!

29

Launch Internet Explorer Browser.lnk

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


WHAT A DG/DQ PROGRAM DOES FOR

SALLIE MAE

30

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


Categories for DG Program metrics

Data Standardization

33%

Data Quality37%

Metadata Support

5%

ProjectSupport

11%

MDM14%

DG REPORTING CATEGORIES

31


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

32

Goal:

Focus on solving business

problems while always keeping

your eye on delivering a first rate

DG Program


COMMUNICATION

Key is regularly and consistently!

► Easy to focus on the day-to-day activities, must focus on communicating the wins and payback

33


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

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

[email protected]

34


TYPES OF COMMUNICATION

► Mission and value statements

► Elevator speech

► Slogan/Logo

► Status Reports

► Dashboards

► Presentations

35



36

DG Program

Implemented

DG Program

Design

DQ Program

Design

Pilot Project:

7 DEEDD Project

DQ Program

& Pilot

Implementation

Monitor data

Focus on

root cause &

prevention

March - July 2006

October-December 2009

November 2006–March 2007

July 2010 -Present


April 2007January – June

2010


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

37


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


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

39

Dashboard

Drilldown

Detail


CONTINUING TO SHOW BUSINESS VALUE

40


NEXT STEPS

41

► 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


LOOKING AHEAD

► Need to maintain data governance vigilance in order to ensure customer satisfaction and data quality

42


► For further information, please contact

Michele Koch

[email protected]

703-984-6601

QUESTIONS?

43

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.

mailto:[email protected]

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