shared data and the data governance imperative data and the data governance imperative robert lux...

Shared Data and the Data Governance Imperative

Robert Lux

Managing Director GMAC Global Data Architecture & Delivery

Copyright © 2007 GMAC, LLC. All rights reserved. 2 27-Nov-07Page

Agenda

GMAC Background

GMAC ResCap Merger

Strategic Data Initiative (SDI)

Data Governance

Lessons Learned

Questions & Answers


Robert Lux background

At GMAC Residential Mortgage since 1998• 1998 - EDS Program Director• 2003 - GMAC VP of Data Services

2006 – GMAC ResCap Managing Director of Data Services

2007 – GMAC Financial Services Director of Data Architecture & Delivery

Prior employment:• EDS• Reuters• Reality Online• Globe Ticket• IBM


GMAC Background


GMAC ResCap Background

2006 GMAC ResCap was formed

GMAC’s Residential Mortgage business

Merger of two like-sized companies:• GMAC Residential Funding Corporation (GMAC-RFC)• GMAC Residential Mortgage


GMAC ResCap Background

Merger necessitated the integration of two like-sized, independent entities

Different people, processes, and technology

Each company had its own separate and distinct systems:• Lending• Servicing• Capital markets• General Ledger• HR• Data Warehouses• Etc.

There was a need to integrate the data of the two organizations• Data Services organization was created to address this need


Importance of Data to Financial Services

Two sustaining elements for a Financial Services company:1.Information2.Access to Capital

GMAC Executives rated Data Integrity as Top Priority in a recent survey


Data Happens!


Is this the “Axis of Evil”…


…or is this the “Access of Evil?”

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Dramatic consequences

June 03, 2003 TORONTO (Reuters) -TransAlta Corp. said on Tuesday it will take a $24 million charge to earnings after a bidding snafu landed it more U.S. power transmission hedging contracts than it bargained for, at higher prices than it wanted to pay. [...] the company's computer spreadsheet contained mismatched bids for the contracts, it said. "It was literally a cut-and-paste error in an Excel spreadsheet that we did not detect when we did our final sorting and ranking bids prior to submission," TransAlta chief executive Steve Snyder said in a conference call. "I am clearly disappointed over this event. The important thing is to learn from it, which we've done."

Fannie Mae, which finances home mortgages, stated in a news release of third-quarter financials that it had discovered a $1.136 billion error in total shareholder equity. Jayne Shontell, Fannie Mae senior vice president for investor relations, explained in a written statement, "There were honest mistakes made in a spreadsheet used in the implementation of a new accounting standard."—From PC World

http://www.pcworld.com/article/id,127189-page,1-c,accounting/article.html


Data Issues get worse during an M&A

DRAFT#47

1st & HE LoanInfo

#42 - 1st & HE Loan Info1st & HE Servicing Data

#19 - 1st & HE Conforming Loan 1st & HE Servicing Data

#5 - 1st & HE Loan Info1st & HE Servicing Data

#40 - 1st & HE Loan Info

Retail

PilotLendscape

Direct/Ditech

EclipseEngenious

Homecomings/Broker

MortgageFlex

Retail

CoPilot

Correspondent

WALTEngenious

Institutional

Café 4.0Café 2.2IMS-R

AssetWise

Middleware/Business App

Common Loan Interface (CLI)

Middleware

SwitchCapital Markets

Resi

CMS

Servicing

MortgageServ (LOIS, NELI)

#41 - HE Loan Info


Capital MarketsRFC

Café 2.2IMS-R

Café 4.0Data Warehouse/

ODS/VisionAutomated Pooling

#42 - 1st Loan Info(specific products )

May go through ADI#3 & 49 - 1st & HE

NC Loan Info

CommitmentManagement

Asset Lock Bid Commit

Servicing

SBO

#7 - DailyBack

Interface

#14 & 15 – IMS-R SBOData

#39 - 1st & HE Servicing Data

#38 - HE Servicing Data

#6 - 1st & HEServicing

Data

#48Commitment

Info

Correspondent

Café 4.0Café 2.2IMS-R

AssetWise

#1 - 1st & HELoan Info

Homecomings/Retail

MortgageFlex #4 & 50 1st

& HE NC Loan Info

E-Commerce

ADI

#4 & 50 - 1st & HE NC Loan Info

MasterServicing

HIP

MasterServicing

OtherApps

General Ledger

GLSFinance

SmartStream

#13 - SummaryLedger Entries

Finance

ValuationRVA/RIF

Finance

PeopleSoft

#31

Finance

Gate

#22

#21-DetailedLedgerEntryFile

#46 Sales &Switch

#8 - Loan Updates

#2 & 16 - 1st & HE Servicing Data

#20 - 1st & HE Servicing Data

#2 & 16 - 1st & HEServicing

Data

#35 Café 2.2 Data

#34

#43

#28IMS-RData

#29

#32

#27

#33


#30

#25

#24 - IMS-R DW Data

#37 ManualInterface

#44 - IMS-R Data

#26

Contract IDLookupService

#45- ContractID LookupRequest

#36

#23#51

#52#11

#18ConformingLoan Info(Manual)

#12


#53

#54


GMAC ResCap Data Program – July 2006

-July 2006

Residential Finance Group: Importance versus Effectiveness Gap

- - - - - Importance Ave: 3.82- - - - - Company Gap Ave: 0.67

Strategy and Planning

Enterprise Architecture

Business Case Discipline

Portfolio Management

Value Demonstration

Performance Reporting

Risk Management

Security Policies and Stds

Disaster Recovery and BCP

Availability Management

Life-Cycle Cost Efficiency

Cost Transparency

Requirements Definition

Application Design

Project Mgmt and Execution

Maint. Cost Containment

Vendor Perf Oversight

Vendor Segmentation

IT Staff DevelopmentLeadership Development

Performance Management

Data and Knowledge Mgmt

IT-Enabled Collaboration

Technology Innovation

Process Digitization

3.0

4.0

5.0

0.00 1.00

Governance Performance Measurement and Value DemonstrationSecurity and Business Continuity Planning Infrastructure Delivery and ManagementApplications Delivery and Management Vendor ManagementTalent Management Business Enablement

Impo

rtan

ce

Effectiveness Gap = Importance - Effectiveness

Potentially Over Allocated

Key Strengths High Priorities

OpportunisticImprovement

Survey concluded that Data is of high importance and that it was ineffectively

managed.


ResCap-RFG Average

Benchmark Average

GMAC ResCap Data Program – July 2007

Residential Finance Group: Importance versus Effectiveness Gap - July 2007

Vendor Alignment

Data and Knowledge Management

Cost Transparency

Business Functionality

Technology Innovation

Skills AdaptationLeadership Skills

Business Skills

Project Skills

Technical Skills

Business Case Achievement

System Adoption

Business Case Discipline

Project Delivery

Requirements Definition

User Training

Responsiveness

End-User Support

Technology Provisioning

Availability Management

Business Continuity Planning

Security

Risk Management

Business Liaison Financial Impact

Value Demonstration

Strategy and Planning

Communication

Prioritization Discipline

4.5

5.0

5.5

6.0

6.5

7.0

(0.8) (0.3) 0.3 0.8

Business Partner

Importance

Effectiveness Gap = Business Partner Importance - Business Partner Effectiveness

Key Strengths High Priorities

Low ROIOpportunistic Improvement


Strategic Data Initiative


Strategic Data Initiative - the cast

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Strategic Data Initiative - Approach

Step #1 – Get sponsorship from the top

It’s easier to get everyone marching in the same direction when it comes from the top

Try for the CEO – if that doesn’t work the CFO and COO are your best bets



Step #2 – Focus on Culture during an M&A

Collaborated with a team of Business and IT stakeholders to build SDI

Performed a cultural assessment:

- Human Synergistics OCI



Step #3 – We took a “Best of Both Worlds” (or Reese’s) approach

- Assessed components of both the RFC and RESI data programs

- Used strengths from each one and sought to enhance them

- Where neither was strong brought in outside help

- Your situation may vary – it may make more sense to take an acquisition approach


Strategic Data Initiative - Mission

“The people, process, standards, tools, and procedures that develop a long-term organizational framework and foundation enabling ResCap to manage data as a strategic asset, that will be used as a trusted source of information across the Enterprise.”


Strategic Data Initiative - Deliverables

SDI had three major deliverables:• Establish an Enterprise Data Governance organization• Establish an Enterprise Data Stewardship organization• Establish an IT Data Services organization

DataGovernanceSteering

Committee

WorkingGroup

EnterpriseArchitecture

SDI DataServices

EnterpriseStewardship

Business UnitStewardship

DataArchitecture

DataStewardship

MinimumData

Standards

DataSharing

DataQuality

Meta-DataManagement

DataGovernanceSteering

Committee

WorkingGroup


SDI DataServices


SDI DataServices





DataArchitecture

DataStewardship

MinimumData

Standards

DataSharing

DataQuality

Meta-DataManagement


Strategic Data Initiative - Organization

Business UnitData Steward Manager

Definer Producer User



Note: Business Units may choose to assign one or more associates to fulfill the different data stewardship roles within the business unit.

Business Units Data Stewards(BUDS)

Enterprise Data Stewardship Office (EDSO)

Program Manager Program Staff

Data Governance Working Group (DGWG)

Data Governance Steering Committee (DGSC)

DATA GOVERNANCE



DataGovernance

Roles

EnterpriseData Stewardship

Roles

Business UnitData Stewardship

Roles


Data Governance

Data Governance at GMAC ResCap• Executes and enforces authority over the management of data

assets through Data Quality, Stewardship, and Standards initiatives

• Empowers an organization to define guiding principles, policies,processes, standards and technologies

• Ensures the quality, consistency, accuracy, availability, accessibility, and audit-ability of GMAC’s data

In order to:• Support sustainable growth • Improve investor and client satisfaction• Provide disciplined leadership• Manage and reduce risk

• Streamline operations and improve time to market


Data Governance Purpose

Improve productivity and lower cost of operations by:• Approves, sponsors, and prioritizes all Enterprise Data projects• Managing data so that it is available, complete, timely, and accurate• Defining and enforcing data quality and data integrity standards• Identifying and promoting standard tools and data quality standards

Improve risk posture by:• Establishing data stewardship throughout the organization • Implementing an effective process for escalating, prioritizing, tracking, solving

and reporting on enterprise data risk issues• Establishing rules governing the lifecycle of data• Identifying and utilizing standard tools and access policies to allow for authorized

and verified access to data

Improve organizational effectiveness through• Measuring the effectiveness of Data Governance and its alignment to corporate

goals• Assumes ownership of all Enterprise Data• Owns the Enterprise Data Warehouse and Enterprise Data Repository• Resolves disputes regarding data issues• Manages data quality


Data Governance Organization

Steering Committee • Made up of Senior Business leaders• Maintains ultimate accountability for all facets of Data

Governance• Establishes the Working Group to achieve the Data

Governance goals and objectives

• Reviews results of the Working Group on a regular basis• Meets monthly

Working Group • Two or more business data SME’s from each business area

• Appointed by the Steering Committee member to achieve the Data Governance goals and objectives

• Strives to build consensus across organizational boundaries• Escalates issues to Steering Committee when appropriate

• Meets weekly or more frequently if necessary


Organization Membership

Steering Committee• One Chairperson• One senior manager from each business group in ResCap• Chairperson for the committee is appointed by the Executive

Committee and position is reviewed annually• IT only has one seat – the CIO; all others are business people

Working Group• Facilitator plus one or more representatives for each Steering

Committee member• Facilitator for the Working Group is appointed by the Steering

Committee• Representatives appointed by Steering Committee Member for

their business group• Recognized as experts or SMEs in their line of business • Many are also Data Stewards for their business area


Organization Membership

Asset Management

Banking / Ancillary

Broker

Capital Markets

Consumer Lending

Correspondent

Credit Risk

Finance

GMAC Corporate

Human Resources

Information Technology

Institutional

Legal

Operations Risk

Servicing

Warehouse Lending


Roles and Responsibilities

Steering Committee Chair• Establishes agendas, leads meetings and records results• Facilitates votes on business before the Committee

Steering Committee Member• Ensures effective utilization of the program throughout ResCap

• Votes on business before the Committee, either in person or via proxy

• Appoints Working Group representative(s)

• Works with Working Group representatives and other Steering Committee Members to gauge progress and resolve issues related to Data Governance goals and objectives


Roles and Responsibilities

Working Group Facilitator• Establishes agendas, leads meetings and records results• Works to build consensus and arbitrate disputes• Manages voting process• Escalates issues to the Steering Committee when appropriate

Working Group Member• Effectively represents views of their business or support unit as

well as understands the views and needs of the enterprise

• Implements programs and participates in projects to achieve the Data Governance goals and objectives

• Directs metadata requirements


Decision-making

The Steering Committee operates by simple majority vote of full membership• At least 75% representation (through attendance or proxy) is

required for quorum• Voting can only take place if quorum is achieved• Chairperson has voting and veto privileges • Decisions can result in approval, conditional approval,

rejection, rejection with request for follow-up, or refer to Executive Committee

• Decisions can be appealed by the Steering Committee Member to their Executive Committee representative, who can choose to bring the matter to the Executive Committee for consideration


Decision-making

The Working Group operates by consensus – 100% concurrence is required for approval• Each organization has one vote, regardless of the number of

representatives• Facilitator has no voting privileges

• The group works to define the problem so the decision can result in approved by consensus, rejected with a request to return with additional information, rejected as presented, or escalated to the Steering Committee


Data Governance Accomplishments

Enterprise Data Model• Modified a generic Industry data model to accurately represent our

business

Data Quality• Identified issues with certain calculations in a source system; reviewed

with Credit Policy & Capital Markets; clarified business rules for calcs; source system modified to conform to business rules.

• Initiated a pilot of the Larry English TIQM data quality methodology.

Data Survivorship• Determined the correct System of Record for 572 data elements in the

EDR that could be sourced from either the Origination or Servicing system. In some instances both records were stored for historical purposes.

Data Security• Classified the GMAC Proprietary data elements in the EDR. These are

stored in the Metadata tool and reports which contain these dataelements contain a “GMAC Proprietary” footer.

Data Mart project reviews• Reviewed designs of multiple data mart projects


Data Governance Accomplishments

MISMO support• Ensure that Enterprise data conforms to MISMO XML standards• Actively participate in MISMO Governance

GMAC ResCap Integration Project• Documented the current state data stores and data flows for the

Enterprise• Identified the data requirements for all the Data Consumers – ~7,000

data elements• Consolidated these data requirements – eliminating dupes and

conforming names - ~3,500 data elements• Reviewed the data needs among the Data Producers to optimize builds

of interfaces• Developed a scorecard (13 questions) to determine what data is

strategic• Strategic data to be hosted in Enterprise Data Repository

Enterprise Data Repository (EDR)• Single Source of Truth for our Enterprise Data• Used to build functional data marts• Owned and maintained by Data Governance group

Copyright © 2007 GMAC, LLC. All rights reserved. 36 27-Nov-07Page36

Developed Data Architecture Rules

Enterprise Data Architecture Rules

Data is owned by the corporation

Data is adjudicated by Data Governance

Data is managed by data stewardship

Data is structured and stored based on its behavior and usage

Data is shared and accessed using common methods

Data is not duplicated unless duplication is necessary

Data is secured Meta data is maintained

Data is modeled using naming conventions and standards

Data is managed using approved standards and tools


Consolidating Business Data Requirements

Output• Normalized business data requirements

from ~7000 elements to ~3500 elements

Benefits • Provided data producers a de-duped listing

from which to work

• Provided data producers a single list of consumer data needs so they can determine how to expand their platforms


Scoring Data

Why• Define candidate list of data elements for EDR

• Develop one drop-off point for sharing data with other business units rather than developing many point-to-point ones between them

• Eliminate any subsequent work for producers to address needs fornew consumers

• Sharing data in this way follows many of the enterprise data architecture rules defined by the Data Governance Working Group

What• Score the consolidated list using criteria

developed by the Data Governance Working Group


Scoring Data

13 question scorecard developed to identify Enterprise Strategic data elements


Enterprise Data Repository (EDR)

• Ten data sources

• Target is Enterprise Data Repository (EDR) – all data elements will be conformed & cleansed.

• Single version of the truth for our Enterprise data

• Data marts will be built from EDR

• Enterprise Data Model used to design EDR

• 3NF

• Data Governance “owns” EDR

• 808 data elements to start

• ~800 more being added for NC


Lessons Learned

1. Obtain Senior Executive (CEO if possible) sponsorship for Data Governance

2. Can not underestimate the importance of Culture

3. Choose an approach to merging your Data programs

4. Need a clearly defined strategic mission and program to transform the way you manage data

5. Consolidate Data Architecture & Delivery services –create a single point of accountability for IT Data Delivery in your organization


Potential pit-falls

1. Changes to Executive staff during M&A can derail Data Governance continuity

2. Management Consulting companies don’t know your company as well as you do

3. Data Governance can be perceived as bureaucratic


Questions


Contact Information

If you have further questions or comments:

Robert Lux

Managing Director of Data Architecture & Delivery

GMAC Financial Services

[email protected]

215-734-4205

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