The Role of Data Governancein a
Successful CDI Platform Initiative
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The Speaker
Kanon CozadSenior Vice PresidentDirector of Application DevelopmentUMB Bank, n.a. [email protected]
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UMB: Background
• UMB offers complete banking and related financial services to both individuals and business customers.
- UMB’s vision : To be recognized for the unparalleled customer experience.
• Over $8 Billion in Assets
• Over 3700 associates
• Over 140 branch locations in 8 states
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Project Challenge
UMB’s CDI Platform Initiative:
Provide a 360-degree, holistic view of UMB’s customer relationships
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Business Drivers:
• Increase efficiencies of our front line associates by consolidation of customer data.
• Improve cross sale opportunities by consolidation of current product offering and identification of complimentary products.
• Empower our associates to fulfill UMB’s mission:- To know our customers and anticipate their needs; advocate and advise;
innovate and surprise.
Technical Drivers:
• Multiple sources of customer information; multiple versions of the truth.
• Difficult existing customer aggregation routines.
• Wanted a more flexible technical platform on which to build.
Compelling Business & Technical Drivers
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Overview of UMB’s Solution
• IT Systems– Acquired systems for customer relationship management (CRM)
and customer data integration (CDI) from Oracle.•Consolidated legacy applications and customer data into these.
– Acquired system for customer data quality from Trillium.• Improved customer data, didn’t just consolidate it.
• Business Organizations– Established data stewardship program to identify and prioritize
applications and data for consolidation and improvement.– Established data governance process to help break down
organizational silos and share customer data as an enterprise asset.
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Overview of UMB Data Governance Process
• Business process priorities are identified– Then translated into technology that can enable these.
•Technology selected is either already in place or new.– Change is facilitated
• Including changes to both sales processes and technology
• The focus is on sales processes, for now– The primary goal is to transform the sales process.– Formerly, it was organized per line of business (LOB).– Going forward, sales processes reach across LOBs.
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Project Process:
• November 2004 UMB identified need for new Enterprise CRM solution
• Completed Vendor/Partner analysis; chose Siebel SFA as front line system and Siebel Universal Customer Master (UCM) as CDI platform
• Went live in March 2006 with 726 users.
• Plans to roll out to over 1000 users by end of 2007
Project Process
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Project Challenge
The solution…
Establishing the baseline
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Hogan CustomerInformationFile
Hogan Demand DepositsHogan
Time Deposits
SHAWConsumer &CommercialLoans
Hogan RPM(RelationshipPricing Model)
Global Plus(Trust)
FDRCredit Cards(monthly feed)
CorporateReference Database
InvestmentBanking
BrokerageInsurance
Mutual FundsSafe Keeping
MAINFRAMEPreprocessing
MQ
Nightly Edge System Processing
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UCM
MQ
CRM
Automatically Update an existing
Best Version Record
Manual (Data Stewardship)
Create New Best Version Record
Trillium Data Matching Engine
Best Version Records
Best Version Records
Inserts from Edge System
Delta Loads
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CRM
SR
Best Version RecordsData Layer
Business Object Layer Presentation Layer
Main FrameWeb Services
Edge System
Service Request Data Flow
UMB Call Center
Delta Loads into UCM
Staging Tables
UCM Tables(Final
Representation)
Trillium UCMInterface
MQ Series
Organization or Individual Records
For Insert or Update
TrilliumDirector
TrilliumCleanser
TrilliumMatcher
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TrilliumDirector
TrilliumCleanser
TrilliumMatcher
Trillium Director
Directs the flow of Requests coming to and from the UCM Connector intoEither the Cleanser or Matcher.
Trillium Matcher
Using the pre-selected records from the UCM Connecter, the Matcher has Match Routines Combined with rules based around Profile informationto determine if a Staging record matches a record already in UCM Base tables.
Routines analyze the following:•Organization/Individual Name Components•Address Components (House #, Street, city, State, Zip)•Social Security / Tax Id•Date of Birth•Phone Number
Trillium Cleanser
Cleanses Profile data. Also uses a process called Geocoding to analyze and correct Address Related components. Additionally,Mix cases Profile components(i.e. PETER DESILVA would be mixed
cased to Peter deSilva)
Profile Components that are cleansed:
•Name (Business Name, Suffix, Prefix, First, Last, etc.)•Address (Street Name, City, State, Zip (zip+4), Country•SSN / Tax-Id Cleansing (formats all SSN’s to ‘#########’format. Additionally, if SSN is determined to be invalid, it records it to ‘000000000’
•Creates a Candidate code using Profile data used to help determine what records are sent to Matcher.
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UCM Insert Process Flow
Insert UCM ConnectorCall to Cleanser
Trillium Cleanser• Standardize Names• Fix Address Components• Mix Case• Format/Standardize SSN• Create Candidate Code
Trillium Director
Get all records from base where either SSN
or Candidate CodeEquals the SDH (staging) record
Trillium Director
Trillium MatcherUse match routines and rules to determine if SDH record isequal to any UCM Baserecords.
Trillium will return 1 of 3 possibilities:•Match•Suspect•Fail
MatchResult
MatchMerge SDH Cleansed record into UCM Base record using survivorship rules. Survivorship rules drive the updates (if any) to profile components.
FailInsert Cleansed SDH Record into UCM Base as new Customer
SuspectA suspect is 1 of 2 instances.1 - The SDH record was close but not exact
enough for an auto-merge. Key components may have been slightly different.
2 - The SDH record matched to multiple UCM baserecords and could not determine the best version record to merge into.
In any of these cases, the SDH record goes intoData Stewardship. The UCM interface has an Application that allows the Business Units to Merge/Link the SDH record into the best version in UCM.
Staging
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Data Stewardship
The role of Data Stewards
• Evaluate Matching rules and compliance to data policies
• Testing of system upgrades and how they affect data quality
• Manual override of cleansing rules to address anomalies
• Communication of merge criteria to front end users• Validate merge and unmerge request from front
end users
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Data Governance
• Definition: Data Governanace (DG) is usually manifested as an executive-level board or committee that institutes and enforces policies and procedures for the business use and technical management of data across the entire organization.
• At UMB, DG provides the roadmap Translates to practices through entire enterprise, not just one LOB
– Integrates oversight efforts in order to set standards.
• At UMB data governance provides direction; data stewardship puts direction into action.
• UMB uses Compliance as a Trojan Horse.
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Data Governance
• Business Drivers for DG:– Compliance– Auditable data for regulatory reports– Leverage data as a corporate asset– Make cross-LOB dependencies more efficient
• Technical Goals for DG:– Control the use of data– Improve data– Share data more broadly– Cross-functional change management and proposal
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Plans for the Future
• Review data governance policy to make sure it addresses emerging communications methods.
• Identify further external sources of data to help complete the customer profile.
• Use consolidated data to profile our customers and deliver product offerings appropriate to their buying patterns.
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Wrap-up
And there you have it…
?
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The Speaker
Kanon CozadSenior Vice PresidentDirector of Application DevelopmentUMB Bank, n.a. [email protected]