JB Sastry

Chief Architect, DW- GE Money

May 15, 2007

MDM for a Consistent View of Customers

CDI/MDM initiatives are NOT IT initiatives

They need to solve prevailing or future business problems

Sponsorship is critical

It is a progressive roadmap

Each step has validation-quality cycles associated

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Our Customer Centric Enterprise

LegalBarriers

ContractualObligations

Strategic Imperatives

Compliance Management Framework

CustomerCentric

Processes

Examples of contractual barriers – retailer contracts; no mix and merge of specific retailer data

Legal examples- can not use house hold info for adverse action

Can not use customer data from Acxiom for adverse actions

Define to ensure what exact customer oriented processes are being catered to: How do thes efit into over all organizational strategies

Make the investment work toward integrated joint strategies- avoiding business functional siloes is more of a dream than a reality

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Customer- 360 [ x ‘n’]

Relationship-1

Relationship-2

Relationship-3

Contacts

Triggers

Addresses

Life Evt Scores

Finance and Capital Mkts

Delinquency Mgt

Legal & Compliance

Channel & Contacts Mgt

Fraud & Money Laundering

Risk Mgt

Sales/Mktg

Profitability

Self Svc Apps

Many customer touch points

Many customer management aspects

Many customer oriented biz functions

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Examples of Customer Centric Processes

Risk Management:

Channel/Contacts Mgt:

Delinquency Mgt:

Preference & Privacy Mgt:

Fraud and Money Laundering:

Vintage Analysis

Preferences and Contact Optimization

Treatment Optimization

Extended Operationalization

Suspicion Triggers

Increasingly and stunningly the customer centric information is finding place in predictive models

Analytical models are becoming sophisticated and processes richer due to customer level data injection

Creative applications are emerging suggestive of DW- Info Mgt Maturity rise

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Key Goals of Master Data

A solution that collates, maintains and

provides organizational Master Data to

operational systems as needed in a

standardized manner.

It has built in data governance and

synchronization mechanisms to ensure

appropriateness is maintained consistently.

Some industry definitions

Key words- standardization, governance, synchronization

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Quality and Data GovernanceensuresReference

Access enables Agility

Synchronization(With OLTP) Guarantees currency

Enterprise-wide DataIntegration

MDM Characteristics

Multi-tiered systems facilitate access points in line with consumption

Often, access is the main leverage used by biz siloes to proliferate “irrational data exuberance”- to steal a phrase from the redoubtable mr. greenspan

Value of information is compromised (enhanced) by data quality

Without enterprise-wide integration, customer centricity is a lost cause

By far the most complex piece of the puzzle: App and Data Integration come together.

Watch out for complex data flows across multiple tiers

Data ownership and stewardship policies a must to avoid unbridled chaos

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Extracting the Master DataProviders: Source systems, Comm Channels, Web Logs, Bureaus…

Data

InformationProcess

Enablers: Meta Data, Data Quality/Profiling, Master Data …

Tools: DWs, ETL, OLAP, Data Mining,…

Integrators: Strategic information integration, Tactical Referencing, Behavior Modeling, Strategy Bldg, Optimization,.…

Processors: Rules Engines, CDI, App work flow, SOA,…

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A Multi-tiered Data Mgt Solution

Data Staging Systems

Model &Strategy Data

PerformanceMetrics

BureauMeasures

Time Series

AnalyticsAnalytics

Acct Level

Cust Level

Acct Behavior

Cust Behavior

Ops & Coll.

CLV

Acct History

TransactionAccount Apps & Scores

Cust

RiskData Mart

CRMData Mart

OPSData Mart

FinData Mart

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Operational Data systems that are refreshed from DW servicing the Master Reference Data Tier

The DW-MDM Bridge

Three forms of Master Data-

Analytic

Operational

Actionable- e.x. Contacts; Offers

DWHETL Mappings

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The Information ‘Package’

Raw Data

Meta Data:Lineage, Linkage, Definitions, Logistics and Morphosis

Data Quality:Accuracy, Timeliness, Relevance, Completeness, Trustworthiness and Meaning

x + = Information

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Corner-Stones of Customer MDM

Identity

Mappings

Behavior

Meta-Information

Extremely diverse ‘aspects’ of behavior dependent upon the particular biz function’s outlook

Contact mgt, cost mgt (delq), cross sell, ….

Organizational motto of “Know thine data”

Meta information could be exhaustive- a thankless information assembly that is only sporadically used

Often the most neglected area of DW builds due to typical cost/time over runs

Standardized tools and processes for cleanse-match-merge routines

Structured approaches

Naming conventions

Data Stewardship crucial for success

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Integrating the Customer Information

Divergent, Atomic

Data Streams

AccountLevel

Consolidation

Customer- 360View

Behavior Modeling & Strategy

Acct Financials, Trending and Tracking

Customer- Demographics, Contacts, Preferences, …

Master Ref

Actionable BI

RulesC

leanse

- D

edup-

Matc

h-

Unify

Mostly this means customer level analysis but account level execution and tracking

Integration funnels on both sides of the account-level data usage

Expensive and painful system builds call for iterative production implementations for self-sustained projects

Aim for ‘Bursts of ROI’ realization

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Getting Organized for MDM

Evolve a Solution Framework

Find the Champion

Encourage Sponsorship

Create RoadmapsData Stewardship

Governance Board for change control

Build Domain Expertise

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Contact Information

• If you have further questions or comments:

Brahmaiah S Jarugumilli [JB]

jbsastry@yahoo.com