MDM Workshop 02-Case Studies & Business Benefits [לקריאה בלבד] [מצב תאימות]

DataDelta Master Data Management (MDM) Workshop

Session 2:Session 2:MDM Case Studies & Business Benefits

Aaron ZornesChief Research Officer

Ed AllburnPresident & CEOChief Research Officer

The MDM [email protected]

President & CEODataDelta, [email protected]

DataDelta MDM Workshop - Copyright © 2007 DataDelta, Inc. 1

Build vs Buy

• Data structures & business t b l

Value of Integration Exceeds Value of Build/Buyprocesses must be supremely

flexible• Underlying IT infrastructure

Exceeds Value of Build/Buy

ETL EAI MDI

V l f• Underlying IT infrastructure must enable new business models V

alu

e Value ofIntegrating Applications

• Policies/process flows must integrate in ways previously problematic Time

Value ofBuilding

Applications

problematic

EAI = enterprise application integrationETL = extract-transform-load

MonolithicApps

Client/ServerApps

SOA/Web Services

MDI = master data integrationSOA = service-oriented architecture

Global competition mandates


Global competition mandates a wide variety of new business styles

Business Drivers 2008-09

• Just-in-time 21st century business d l d t b th ilit & Agile Enterprisemodels mandate both agility &

integration across enterprise to – Provide higher profitability

Agile Enterprise

Self-Directed– Reduce operations costs – Increase accuracy of regulatory

compliance

Self-DirectedService

M&A“Ready”

Integrated

• Emergence of “demand chains” mandates synergetic approach across both “party” & “product” master systems

“Ready”

Rapid

Risk Mgmt

Co opetitionboth party & product master systems via common business services

• M&A as a business strategy

RapidNPI

Co-opetition

“Demand”Chains

Contemporary business strategies mandate flexible


Contemporary business strategies mandate flexible infrastructure –propelling MDM into “Top 10” initiative

‘Top 5’ Justifications for MDM Initiatives

1. Catalyzes market leadership & dominance2. Provides increased ROI by “leveraging / rationalizing existing

infrastructure”3. Significantly increases shareholder value4. Provides a disruptive technology for new business models5. Enables compliance & regulatory reporting


MDM Catalyzes Market Leadership & Dominance

• Maximizes walletshare across product lines & BUs– Upsell via sticky bundles– New markets via cross sell to existing customer base

• Increases understanding of large customers by grouping all buying• Increases understanding of large customers by grouping all buying orgs into B2B or B2C hierarchy

• Enables integrated customer analytics – i.e., profitability analysis, lifetime value

• Enables “co-opetition” & electronic storefront models – e.g., B2B2C by integrating partner data with internal dataintegrating partner data with internal data

• Protects brand integrity by increasing customer satisfaction due to more focused marketing & service campaigns – e.g., “blended agent”

bilitcapability• Actualizes “consistent customer treatment” by blending channels to

deliver common customer experiences


p

MDM Provides Increased ROI by “Leveraging Existing Infrastructure”

• Enables integration of new & old channels – e.g., collections, f d t t t ith ki k ATM IVR & li lf i

Existing Infrastructure

fraud, contact centers with kiosk, ATM, IVR & online self-service• Minimizes architectural complexity to simplify application

solution design, deployment, & maintenance g , p y ,• Reduces number of interfaces between applications &

increasing reuse factor to save substantial integration costsI i f t t fl ibilit d t l t h ll• Improves infrastructure flexibility and control to enhance overall system performance

• Accelerates ROI of enterprise CRM solutions p• Reduces overall project risk through increased flexibility &

centrally managed architecture


MDM Significantly Increases Shareholder Value

• Drives costs of “dirty data” out of the info supply chain• Accelerates revenue growth via more intelligent cross-sell & up-sell

enabled by complete understanding of customer (profile, accounts & interactions) to leverage bundling opportunities& interactions) to leverage bundling opportunities

• Facilitates quick scales of economy in mergers & acquisitions (M&A) – e.g., shortening customer, desktop, & billing integration

ftimeframes while providing scalability to support rapid assimilation of new block of customers

• Measures, manages & grows “customer information” as a key , g g ycorporate asset

• Drives fundamental operational savings & efficiencies – e.g., “once & done” enterprise wide services for key customer processes such& done enterprise-wide services for key customer processes such as account changes (name, address)


MDM Provides a Disruptive Technology for New Business Models

• Enables self-directed customer experience for sales & serviceP i i h i t t d 21 t t l h i

New Business Models

• Provisions hyper-integrated 21st century supply chain – e.g., outsourced manufacturing, outsourced service (“he who owns master reference data, dominates supply chain”)

• Automates customer transactions that flow across systems• Enables contingency planning for future technologies – e.g.,

biometrics smartcards etcbiometrics, smartcards, etc.• Provides much more than “just another customer interface”

– 21st century business application development platform– Service-oriented architecture – a.k.a, “first foray into SOA”– Web services– Integrated analytics– Integrated analytics– Near real-time materialization


MDM Enables Compliance & Regulatory Reporting

• Centrally manages privacy preferences for consistent rules of visibility & titl tentitlements

• Enhances “evergreening” of customer data accuracy – e.g., continuous customer data improvement by providing self-directed customer care p y p gportals … which in turn integrate customer info across business units

• Enables regulatory reporting compliance– i.e., large customers’ material events (SOX BASEL II)events (SOX, BASEL II)

• Facilitates compliance with AML, OFAC, USA PATRIOT, et al


Industry-Specific MDM Requirements

• Financial services providers (FSPs)Financial services providers (FSPs)• Communications services providers (CSPs)• Life sciences / pharmaceutical• Government• Healthcare• High-technology manufacturing (t.b.d)

• Manufacturing (discrete, process)• Retail (t.b.d)

• Hospitality (t.b.d)


Early adopters of MDM solutions include: FSPs, CSPs, Pharma & High-Tech Manufacturing

Why Market-Leading FSPs Adopt MDM

• Optimize customer profitability• Increase operational efficiencies• Increase operational efficiencies • Enhance regulatory compliance• Improve overall BIp• Deliver ROI on CRM initiatives • Provide “infrastructure

ti li ti ”rationalization”• Facilitate growth-by-M&A

FSPs must transform from customer-hostile, batch


,business model to give customers actionable 360º

view in “near real time”

Banking MDM Requirements

Facilitate growth-by-M&A Increasingly complex business models (B2B2C) as “electronic

Business Drivers Technology Challenges

Comply with privacy mandatesImprove compliance – e.g., AML, BXA, CIP 326, OFAC, SOX, …

models (B2B2C) as “electronic storefronts”Demand for “near real-time” data lineage

Increase sales productivity by modeling corporate hierarchies & structures of B2B customers

data lineageRationalizing complex & dynamic business & individual hierarchies

Improve real-time portfolio view for both wealth management & internal risk management

Hacker-proof customer data protectionHigh-RAS (reliability, availability, g

Increase customer satisfaction (retention/upsell) by streamlining routine customer maintenance

g ( y yscalability) nature of mission-critical infrastructure

cus o e a e a ceReduce IT infrastructure costs

Customer view must prevail over product view as higher margin

BXA - Bureau of Export AdministrationCIP 326 – Customer ID Program of USA PATRIOT Act

OFAC - Office of Foreign Assets Control


Customer view must prevail over product view as higher margin customers dictate common set of products & services via rapid

adoption of MDM

Retail Banking – Business Objectives

• Provide single view of customerProvide single view of customer– Across all channels – Across all products

• Reduce operational costs• Improve cross-selling• Improve net credit loss• Improve net credit loss• Increase marketing lift• Manage privacy centrally• Provide operational view for Basel II compliance• Provide improved customer service

St li t i• Streamline account opening process


Retail Banking – Technical Requirements

• Proven performance & scalability• Service-oriented architecture• Ability to handle complex hierarchies• Ability to integrate to existing infrastructure• Ability to integrate to existing infrastructure• Open architecture – J2EE compliant• Proven functionality for services layery y• Existing CIF co-existence & eventual replacement strategy


Retail Banking – Key Drivers

• Improve cross-selling & campaign liftImprove cross selling & campaign lift– “Operationalize” marketing data– Leverage service interactions into sales opportunities by following

up on current campaigns

• Regulatory compliance– Providing operational view of customer into existing data

warehouse for Basel II compliance– Ability to store privacy preferences at a true enterprise levely p y p p


Banking MDM Scorecard:“Top 5” Business Drivers & Technology ChallengesTop 5 Business Drivers & Technology Challenges


Credit Card Issuer MDM Requirements

Aggregation within industry –exacerbated by big commercial banks

Integration of new & old channels –e g collections fraud contact centers with

Business Drivers Technology Challengesexacerbated by big commercial banks emulating major monolinesHeavy reliance upon direct mail marketing & inherent increased

e.g., collections, fraud, contact centers with kiosk, ATM, IVR & online self-serviceContingency planning for future technologies – e.g., biometrics, marketing – & inherent increased

fraud riskImprove compliance – e.g., AML, BXA, CIP 326 OFAC SOX

smartcards, etc.Complex hierarchy mgmt – e.g., household-level risk mgmtScalability e g ability to integrate new326, OFAC, SOX, …

Support future business objectives –e.g., M&A

Ensure consistent customer service

Scalability – e.g, ability to integrate new block of customersInfrastructure costs of integrating new data sources & channelsEnsure consistent customer service

across all channelsPrivate label cards needing lifestyle event based differentiationevent-based differentiationReduce IT infrastructure costs

Challenge is to mo e to po tfolio le el integ ation despite the


Challenge is to move to portfolio-level integration despite the politics & technology inertia

Credit Card Issuer MDM Scorecard:“Top 5” Business Drivers & Technology ChallengesTop 5 Business Drivers & Technology Challenges


Insurance MDM Requirements

Facilitate growth-by-M&A Expand use of incumbent application systems ( CRM)

Business Drivers Technology Challenges

Comply with privacy mandatesIncrease deep understanding of data quality & reliability issues

application systems (e.g., CRM) via enterprise customer identity service (universal key) across all applications q y & y

related to claims & fraudEmbrace frequent regulation & de-regulation cycles – e.g., HIPAA, NPI

ppIncrease flexibility to add new channels, data sources, touch points, etc. via SOAregulation cycles e.g., HIPAA, NPI

Accommodate growing technical patchwork of proposed legislation –e.g., NHIN

High-RAS (reliability, availability, scalability) nature of mission-critical infrastructure Hacker proof c stomer datag ,

Reduce IT infrastructure costsHacker-proof customer data protection

Ins e s need to mo e to “high to ch” se ice model he ein

HIPAA - Health Insurance Portability & Accountability ActNHIN - National Health Identification Number

NPI - National Provider Identifier


Insurers need to move to “high touch” service model wherein near real-time channel integration is critical

Insurance MDM Scorecard:“Top 5” Business Drivers & Technology ChallengesTop 5 Business Drivers & Technology Challenges


Top 5 Vendors’ Mindshare within Financial Svcs

CDI Institute MarketPulse™ Survey 347 Global 2000 IT Organizations (November 2004)

DWL Customer

82%

85%

hare

ce

s

Siebel Universal Customer Master

45%1

ndor

Min

dsnc

ial S

ervi

c IBM Client Information IntegrationSolution

Sanchez CRM

2%

3%

CD

I Ven

Fina

n

ISI Synchronous

0% 20% 40% 60% 80% 100%


% Responses

Communications Services Provider Requirements

Consolidation (M&A) Abilit t bl d h lBusiness Drivers Technology Challenges

Consolidation (M&A)Deregulation/re-regulationIncreasingly "portable" customersSelf-directed service to drive down

Ability to blend channelsComplex supply chainsOnerous regulatory mandatesSelf-directed service to drive down

customer care costsReal-time marketing & integrated campaign management using

di ti l ti

Extreme scalability in call centers, provisioning, etc.Flood of data due to ‘datapredictive analytics

Fraud detectionBill presentation

Flood of data due to data services’“Plan anywhere, build anywhere” investment strategies in newinvestment strategies in new technologies that enable quicker new product introduction (NPI) at lower cost without sacrificinglower cost without sacrificing quality

Telco evolution will be radical as intense competition in wireless, LD, Internet & local service commoditizes products & slashes profits


Internet, & local service commoditizes products & slashes profits –not to mention VoIP

Top 5 CDI Vendors’ Mindshare within TelcoCDI Institute MarketPulse™ Survey

347 Global 2000 IT Organizations (November 2004)

DWL Customer

15%

16%

dsha

retio

ns Oracle Customer Data Hub

3%

5%1

endo

r Min

dco

mm

unic

at

Initiate Systems Identity Hub


2%

3%

CD

I Ve

Tele

c Siebel Universal Customer Master

Ascential Enterprise Integration Suite

0% 5% 10% 15% 20%


% Responses

Survey Overview: “ROI Strategies for CSP’s M&A”

• 10+ North American CSPs – e.g., cable carriers moving into telephony CLECs

Tactical ROI• Saving substantial integration costscarriers moving into telephony, CLECs,

ILECs, LD carriers, wireless, & conglomerates

– 100% with > 1M subscribers

Saving substantial integration costs• Improving flexibility & control to enhance

overall system performance • Accelerating time-to-market of CRM, SCM, & 100% with > 1M subscribers

– 50% > 5M subscribers• >75% are investing in CDI in support of

stated corporate target to reduce “level

PIM solutions• Reducing overall project risk

stated corporate target to reduce level of infrastructure investment” with 49% stating CDI to be either important or critical to this outcome

Strategic ROI• Understanding & predicting customers’

behaviors Id tif i & d fl ti tit ’critical to this outcome

• 30% had COTS software for CDI installed with the remainder actively evaluating an enterprise-wide solution

• Identifying & deflecting competitors’ moves • Integrating supply chains with key business

partners • Forecasting & acting on new opportunities asevaluating an enterprise-wide solution

COTS = commercial, off-the-shelf software

Forecasting & acting on new opportunities as a “first mover”


M&A demands comprehensive & integrated profiles

CDI MarketPulse™ Findings: “Corporate Issues”How do you RANK your company's DESIRED STRATEGIC RESULTS resulting from M&A?

75%

61%

Corporate alignment

Increase customer satisfaction and retention

92%

75%

75%

1

Increased operational efficiencies

Increased profitability

M k d i

Source: MDM Institute 1H2005 MarketPulse™ Survey of 12 North American CSP’s IT Organizations

100%

92% Market dominance

g

0% 20% 40% 60% 80% 100%

% Responses

For strategic M&A, “Market dominance” cited twice as often as next highest ranked “Increased profitability”, “Increased operational efficiencies” &


p y , p“Corporate alignment”

CDI MarketPulse™ Findings: “Marketing Issues”How do you RANK your company's DESIRED “MARKETING” OUTCOMES resulting from M&A?

71%Enable product bundling

Expedite time to mkt of new products

57%

63%

1

Systematize analytics to enable LTV mktg

Evolve to R/T mktg campaign mgmt

Source: MDM Institute 1H2005 MarketPulse™ Survey

18%

43% Enable solution selling

of 12 North American CSP’s IT Organizations

0% 10% 20% 30% 40% 50% 60% 70% 80%

% Responses

“Enable product bundling” 50% more important as “Systematize analytics to determine customer, segment,

bundle, & product line profitability” – yet 60% expect CDI


, p p y y psolution to integrate with BI or enterprise DW during first year

CDI MarketPulse™ Findings: “Technology Issues”

How do you RANK your company's MAJOR TECHNOLOGY CHALLENGES resulting from M&A?

50%

83%

Legacy app ingtegration (CRIS, LEIS, LEIM,USOCs)

Business process/workflow integration

D t b /d t d l i t ti

17%

42%

50%

1

Database/data model integration

Scalability

SOA for business services infrastructure

15%

17%

Source: MDM Institute 1H2005 MarketPulse™ Survey of 12 North American CSP’s IT Organizations

0% 10% 20% 30% 40% 50% 60% 70% 80% 90%

% Responses

of 12 North American CSP’s IT Organizations

“Legacy application integration (CRIS, LEIS, LEIM, USOCs)” rated at least 33% more important than “Business process/workflow

integration” & “Database/data model integration”


CDI MarketPulse™ Survey Findings

• CSPs must acknowledge state-of-IT-affairs resulting from continuous M&AM&A

• CDI provides proven means to insure ROI of M&A – especially in CSP industry with historically fragmented customer & product master DBsMarket leading CSPs are planning to apply CDI as disruptive• Market-leading CSPs are planning to apply CDI as disruptive technology to “outmarket & outservice the competition”

• “Build vs. buy” has become “buy mega vendor” vs. “buy best of breed” ITO d t d t f h CDI l tias ITOs are mandated to move away from home-grown CDI solutions

to COTS solution• During 2005-06, CSPs will focus on deploying data-centric CDI

i f id ifi d i l i linfrastructure to provide unified customer view across multiple channels & LOBs

• During 2006-08, CSPs will move to process-centric CDI infrastructure to deliver increasingly accurate, complex & just-in-time unified customer views to enable bundle mktg & self-directed customer care

CSP evolution will be radical as intense competition in wireless, LD,


CSP evolution will be radical as intense competition in wireless, LD, Internet, & local service commoditizes products & slashes profits –

not to mention VoIP

Pharma/Life Sciences Business Imperatives

• Improve productivity of pharma sales reps

360° View of Customerreps

• Coordinate sales & operations planning via common infrastructure & goals/metrics Contracte Specialty

Primary Care Physicians

goals/metrics• Increase customer/physician

acquisition, retention & profitabilityR d i f t

Contracted

Accounts

Specialty Physicians

HealthCare• Reduce info management

overload/costs• Prepare for uncertain future

CareProfessional

Group Purchasin

g Orgs

Pharmacy Directors &

OtherInfluencers

Wholesalers / Speciality

Distributors

Recent survey indicates physicians need info to make more informed buying decisions – but only about 1/3 consider pharma sales reps impt sources; 1/3 found sales visits helpful, addt’l 1/3 want more

t ti li i l d t / l l t t ti


current comparative or clinical data/analyses relevant to practices, plus objective info on usage & side effects

Life Sciences / Pharma Technology Challenges

CRM alone is not enoughDW+CRM is not enoughImportance of flexible workflowDis-intermediated data sources

Data service providers (IMS, NDC, AMA - cleansing, matching issues)Industry standard identifiers (IMS, DEA, state licensing) not always accuratey ( , , g) y

Where does content mgmt system end & where does the structured data mgmt start?

Market-leading Pharmas must unify physician/customer information f l i l & b i i i b d d l


from multiple systems & business units in a robust data model specific to pharmaceutical industry

Improve Productivity of Pharma Sales Reps

• Enable sales reps to improve sales effectiveness by leveraging client sales histories & profile info from diverse sourcesclient sales histories & profile info from diverse sources

• Automatically capture physician info during sales meetings• Spend more time in the field – serving physicians – rather than in p g p y

the office recording & analyzing meeting results• Enable physicians to make more informed purchasing decisions by

offering customized product info evidence gathered thru clinicaloffering customized product info, evidence gathered thru clinical research, & comparative analyses of medicines

• Ensure more effective territory mgmt to yield more successfully market & sell products thru efficient call handling & better cross-channel communication & coordination

Making sales reps more productive, requires a complete picture of the physician profile, mktg activities, etc. – database-centric quasi


the physician profile, mktg activities, etc. database centric quasi batch CDI is first step

Coordinate Sales & Operations Planning Via Common Infrastructure & Metrics

• Monitor real-time performance of sales force to quickly make strategic & tactical adjustments necessary to meet sales goals &

id d t d t i t

Common Infrastructure & Metrics

provide adequate product inventory• Employ RFID technology & the EPC Network to improve info

mgmt in pharma supply chain• Make M&A work via vital agglomeration of customer & supplier• Make M&A work via vital agglomeration of customer & supplier

master data• Integrate IT infrastructure of diverse acquisitions• Leverage info insights & relationships to expedite & enhance• Leverage info, insights & relationships to expedite & enhance

product intro & adoption • Overcome cultural obstacles to creating better collaboration

between Clinical & Marketing organizations• Insure supply chain integrity protection for producer & patient (&

everyone in between)• Protect the pharma enterprise involved in ever more

complicated contracts with external partnerscomplicated contracts with external partners

CDI needed that not only provides excellent support for sales reps,


CDI needed that not only provides excellent support for sales reps, but also makes customer info available to marketing, R&D & supply

chain functions

Increase Customer/Physician Acquisition, Retention & Profitability via Closed Loop Marketing

• Enable creation of segment-specific drug detailing aids

& Profitability via Closed Loop Marketing

• Deliver custom detailing to physicians thru field sales channel• Collect responses to product messages at point of customer interaction • Analyze responses to further refine marketing campaigns based on• Analyze responses to further refine marketing campaigns based on

real-time feedback• Design & manage sophisticated campaigns, incl medical events &

mailings

Closed-loop marketing capabilities align mktg & sales business processes, enabling companies to target & segment customers,


p , g p g g ,design & execute mktg campaigns, & analyze customers' responses

to product messages

Reduce Information Mgmt Overload/Costs

• Manage exploding amount of data Pharma Info Overloada age e p od g a ou o da aproduced in every part of pharma enterprise

– CAPA, RFID & ECM data– 21 CFR Part 11– HIPAA

• Share & store discovery & development

Supply Chain & Mfg Data: CAPA, RFID,

& ECM

Data Protection & Privacy Initiatives:

21 CFR Part 11 & HIPAA

Very Largedata in environment with onerous legal requirements for data retention & mgmt

• Generate structured analysis out of

Very LargeData Base(s)

unstructured content• Manage outsourced clinical trials

– Complexity is that some tasks but not all

Clinical & Marketing

Datap yare outsourced for given trial

Both physician & consumer data are intricately related as part of


Both physician & consumer data are intricately related as part of information asset programs which must keep regulatory risk &

validation costs to a minimum

Prepare for Uncertain Future

• Leverage digital packaging (RFID, ECM) for compliance monitoring & supply chain optimi ationoptimization

• Optimize consumer self-service – Apply advanced technologies to expedite info sharing via guided search, co-browsing,

tetc.• Helps consumers benefit from full range of info about health issue they’re researching • Enables pharma to deliver targeted info to customers at precise moment needed or requested

Examples: medical education; disease mgmt; patient compliance; product awareness– Examples: medical education; disease mgmt; patient compliance; product awareness• Drive & manage regulatory compliance across diverse legal domains• Prepare for increased outsourcing of both commoditized & specialized functions • Exploit strategic opportunities created by bioinformatics/ nanotechnology• Leverage re-importation trends


CDI growth + Pharma growth = CDI 2

Legacy Pharma “Info Supply Chain”

SMG SAPContractingAMA

SalesTargetsSome sources flow

to ODS & DW

ODS CARS

DEA STL

to ODS & DW

IMS

OSPSome sources arenot integrated

DW

SiebelCall

Center Web

Events

DW

Wh l l F d G t

DendriteSome sources flow straight to the DW

Wholesaler Fed Govt

Front OfficeODS = operational data storeDW = data warehouse


Back Office

External Source

DW data warehouseCARS = xxxx “Treading water …”

Contemporary Pharma “Info Supply Chain”

SMG SAPContracting AMA

Sales Targets

HIN

CDI CARS

g

DEA STL

g

Registry/HubIMS

OSP

Siebel Events

All *reference* dataActiveData

Warehouse

Call Ctr Web

Dendrite

flows through CDI Registry/Hub

Wholesaler Fed Govt

Front Office


Back Office

External Source“Future-proofed …”

Top 5 Mindshare within LifeSci/Pharma


43%

65%

hare

nces

Siperian Master Reference Manager


18%1

ndor

Min

ds/ L

ife-S

cie n

Dendrite Nucleus

3%

5%

CD

I Ven

Phar

ma Ascential Enterprise Integration Suite

IBM DB2 Information Integrator

0% 10% 20% 30% 40% 50% 60% 70%


0% 10% 20% 30% 40% 50% 60% 70%

% Responses

Government MDM Requirements

• Self-service to drive down customer service costs Integrated

• Integration of transactional, unstructured, geospatial, & demographic data to optimize public services (& national security)

Analytics

(& national security)• Imperative placed on most

government agencies to collaborate & share info

PrivateData

PublicData

CDI& share info• Newly-created enhanced knowledge

repositories, tools, & processes critically needed for meeting new

CDIcritically needed for meeting new public policy requirements

• Need to positively ID & track individuals across languages & cultures

DerivativeDatag g

Government entities must apply citizen data integration best practices from private industry – while using extreme caution


practices from private industry while using extreme caution concerning privacy & security

Mission-Critical Citizen Data Integration (CDI)

• Key technologiesAnonymous entity resolution

• Key vendorsI iti t S t– Anonymous entity resolution

(name classifier & hunter)– Business intelligence (perpetual

analytics)

– Initiate Systems– Language Analysis Systems– MetaMatrixanalytics)

– Dynamic scoring– Link analysis (° of separation)

MetaMatrix– Salford Systems – SAS

– Grid scalability– Data mining

Text mining

– SPSS– Superstructure

S t R h &– Text mining– Real-time report streaming– Voice/text analysis

– Systems Research & Development

– The Distillery y

Additional challenges for gov’t include: scalability (scale, # & h i f ) “ l l ” f b l l k f


heterogeneity of DBs), “very large scale” turf battles, lack of national ID in US, supra-politics

Regulatory Juggernaut & U.S. Initiatives

• Klinger-Cohen ActOffi f F i A t

• In-Q-Tel venture capital fundDi it l ll ti t• Office of Foreign Assets

Control (OFAC)• Bureau of Export

• Digital collection system 1000 (FBI's “Carnivore”)

• CAPWIN project for the pAdministration (BXA) lists of sanctioned governments, organizations individuals

p jmetro District of Columbia region emergency response systemorganizations, individuals

• USA PATRIOT Actsystem

• Terrorist Threat Integration Center

During 2004-05, government will be stressed to analyze citizens’ behaviors to support national security initiatives – & will increasingly

t t i l IT t f “ t id th b ” thi ki & b t


turn to commercial IT sector for “outside the box” thinking & best practices

Top 5 CDI Vendor’s Mindshare within Public Sector



5%

6%

hare


Ascential Enterprise Integration Suite

4%1

ndor

Min

dsbl

ic S

ecto

r


1%

3%

CD

I Ven Pu

b

MetaMatrix Server

ObjectStar Enterprise CDI

0% 1% 2% 3% 4% 5% 6%


0% 1% 2% 3% 4% 5% 6%

% Responses

Why are Healthcare Providers/Payers Adopting CDI?

• Optimize customer profitability “Most other economic t h d IT t• Increase operational efficiencies

• Enhance regulatory compliance

sectors have used IT to become integrated &

more efficient. H lth t b• Improve overall BI

• Deliver ROI on CRM initiatives • Provide “infrastructure rationalization”

Healthcare, too, can be transformed.” Leonard D. Schaeffer, • Provide infrastructure rationalization

• Facilitate growth-by-M&AChairman & CEO

WellPoint Health NetworksKeynote Address at 2004

Health InformationHealth Information Technology Summit

Clearly, healthcare payers don’t know enough about their “customers” — physicians, members, & employers – i.e., healthcare

h t b h d t i i b


payers have not been pushed on customer service issues because they historically were near-monopoly in their geographies

Healthcare Payer/Provider CDI Requirements

Ongoing consolidation straining capacity of b t h t i

Need to react intelligently & instantly to changing “customer”

Business Drivers Technology Challengesbatch-centric processesCorporate boards & investors reluctant to provide capital for major up-front investments

instantly to changing “customer” information such as claims processing & medical mgmtRequirement for deepinvestments

Frequent regulation & de-regulation cycles – e.g., HIPAA & NPI, NHINShorter economic ”product” lifecycles – e g

Requirement for deep understanding of data quality & reliability issues as it relates to eligibility, claims, & fraud

Shorter economic product lifecycles e.g., FSAsIncreased competition -- e.g., offshore Rx fulfillment, NFPs becoming “for profit”

Necessity for a enterprise data model across disparate sources & applications to support complexity of healthcare business modelg

Morphing member base demographics –aging “baby boomer bubble”, “Gen X”, etc. Ever increasing QoS expectations

of healthcare business model

HIPAA - Health Insurance Portability & Accountability Act

Healthcare master customer data must be the most accurate, up-to-the-minute source of customer information & must feed downstream

y yNPI – national provider identifier

NHIN - national health identification number


the minute source of customer information & must feed downstream systems (e.g., claims processing) as well as external vendors.

Healthcare Payer/Provider CDI Scorecard:“Top 3” Business Drivers

CDI Institute MarketPulse™ Survey 12 Healthcare Payer IT Organizations (January 2005)

Top 3 Business Drivers

Increase customer satisfaction and

75%

iver

s

Increase customer satisfaction andretention

Increase profitability

92%1

Bus

ines

s D

r

Create operational efficiencies

100%

CD

I B

0% 20% 40% 60% 80% 100%

% R


% Responses

Healthcare Payer/Provider CDI Scorecard:“Top 3” Technology Challenges

CDI Institute MarketPulse™ Survey 12 Healthcare Payer IT Organizations (January 2005)

Top 3 Technology Challenges

Increase flexibility to add new

92%

halle

nges

Increase flexibility to add newprocesses via service-orientedarchitecture

Integrate with legacy applications anddatabases

100%

100%1

chno

logy

Ch

Provide extreme scalability in datavolumes

100%

CD

I Tec

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Case Studies, Challenges & Lessons Learnedg

Book interviews - early findings & emerging trends:

• Cross-section of interviews from our forthcoming book

F i th t h h d j t ti• Focus on in-the-trenches, hands-on project execution

• Avoided traditional academic case study interviewsAvoided traditional, academic case study interviews

• Asked “What kinds of surprises & challenges did you face, and how did you overcome them?”


Book Interviews: Surprises & Challengesg

Asked “What kinds of surprises & challenges did you face, and how didAsked What kinds of surprises & challenges did you face, and how did you overcome them?” – in areas such as:

• People: Execs, co-workers, vendors, consultants, analysts

• Process: Data Stewardship & Data Governance cooperation dispute• Process: Data Stewardship & Data Governance, cooperation, dispute resolution

• Technology: Vendor selection, implementation, integration

Data: Sources (internal & external augmentation & referential) ETL• Data: Sources (internal & external, augmentation & referential), ETL, Data Quality, Match & Merge logic, etc.


Book Interviews – Other Topics

Other general topics:Other general topics:• Project goals & Key Results/highlights• Who uses/depends on the results where & how?• When was value delivered & how was it measured?• Single "Big Bang" project or multi-stage phased implementation?

B i C & E ti S• Business Case & Executive Sponsors• Project Ownership, Management & outside assistance• Solution Description (people, process, technology & data)Solution Description (people, process, technology & data)• Surprises & Lessons Learned


Book Interviews - Responses

• People focused on topics of greatest interest to them

• Generally a 1-hour phone call

• Call for more interview volunteers!– Any project stage– Short 1-hour callShort 1 hour call– Can be anonymous


Interviews: Early Findings & Emerging Trendsy g g g

This presentation focuses on a subset of keyChallenges, Surprises and Lessons Learned in:

• Business Case

• Data Quality• Data Quality

• Data Governance

• Other Major Surprises & Lessons Learned


Early Findings & Trends: Business Casey g

• SIs & consultants can add strong value even at this initial stage by enhancing structure & credibility

“Phase Implementations” are proving easier to win funding and• Phase Implementations” are proving easier to win funding and successfully execute

• CDI-MDM now being so widely identified as a critical strategic business objective that some business cases are coming from, instead of being sold to Sr Mgmt (e g “Why aren’t we doing thisinstead of being sold to, Sr Mgmt (e.g. Why aren t we doing this yet?”)

• But mid-level mgmt sometime using business case to avoid support (“I need a business case justification before I can change my priorities”)


y p )

Early Findings & Trends: Data Qualityy g y

• You are guaranteed to find new problems & issues, despite past investments in data quality

Extensive data profiling early is essential• Extensive data profiling, early, is essential

• Trust, but verify, “trusted” third-party data sourcesust, but e y, t usted t d pa ty data sou ces– Extensive data profiling is again warranted– Ensure vendor’s definitions map to your definitions

“Total employees” by subsidiary or total hierarchy?• “Total employees” – by subsidiary or total hierarchy?• “Total revenue” – by subsidiary or total hierarchy?

• “Match Accuracy” is different, but highly dependent upon, data quality


Early Findings & Trends: Data Governancey g

• Sometimes success can occur without a formal Data Governance program & full-time Data Stewards

But in general the more complex the environment (# data siloes• But in general, the more complex the environment (# data siloes, # LOB users) the more important to have formal Data Goverance to resolve conflicts

• Data Governance requires data domain experts (business users) who are a scarce resouce and thus guaranteed to have frequentwho are a scarce resouce and thus guaranteed to have frequent priority conflicts

• Strong value being reported from metadata tools (as opposed to “just using Excel to define & map fields”)


Early Findings & Trends: Surprisesy g

• Internal Education & Project PR– Not just during business case, but ongoing recruitment– Not just for initial collaboration recruitment, but also to help maintain

positive momentum & excitement around projectpositive momentum & excitement around project– Not just internal use, but recruited by Aaron Zornes for future CDI-

MDM Summit (leverage that work for more value)Leverage CDI MDM Summit material for own ppt– Leverage CDI-MDM Summit material for own ppt

• Sophisticated metadata managementp g– More than just “mapping fields in Excel”– More than just a “web wrapper around Access”

More Sr Mgmt is more often recognizing the value of modern– More Sr Mgmt is more often recognizing the value of modern, sophisticated metadata tools in the business case


Case Study:y

Case Study:A Major International Financial Institution


Business Case

BackgroundBackground• 2006 started CDI project with $7M budget• 32 global customer data sources• Encouraging results half-way through• Realized opportunity to address other problems

D id d t “t k thi t th t l l”• Decided to “take this to the next level”• Use full data governance and full data management• Opportunity to save lots more moneyOpportunity to save lots more money


Business Case

Business case:Business case:• Analyzed all 2007/08 data projects• Determined cost of siloed approach of $22M• Estimated could deliver for $14M over 2 years via CDI-MDM• 1 “data champion” developed case in just 2 months

Full time time job– Full-time time job– get the numbers, crunch them, validate them, get rates from vendors, create

ppts, etc.– Had to press for numbers – used sponsor name for meeting leverage “X will

be facilitating the meeting for CIO…”– Some people would panic at thought of their local data silo eventually going

away


Data Qualityy

“Oh God, let me give you an example of the kinds of things we wereOh God, let me give you an example of the kinds of things we were finding:”

One of the groups only had a 40% 30% complete address• When asked, response was “when missing, we use our HQ address”• Controller response “Are you out of your mind? We can’t calculate our• Controller response Are you out of your mind? We can t calculate our

taxes and we’ll be fined!”

“So the process they were doing locally could have caused a major impact to the tax group and nobody knew about it and the dollar amount put on top of that could have been huge in fines.”amount put on top of that could have been huge in fines.


Data Governance

Created a full “Data Management Program Guide”:• mission statement, guiding principles, goals, all the different business

drivers, etc. bible for moving the program forward• bible for moving the program forward

• included all the key processes:– how we get datag– how manage source system analysis– data quality issues

Escalation– Escalation– data definition via council meetings

• All documented in full detail– Make it very easy for people to clearly understand roles and

responsibilities of who’s doing what and when


Data Governance

Full escalation process established to address conflicts:• “My business doesn’t operate that way, that’s not the way I report my

numbers to my boss” – Local Business“This is the way it’s supposed to be that’s the way we report our• This is the way it’s supposed to be, that’s the way we report our numbers to the street” – Enterprise

Steering committee• One of the first things done

D fi d h i i f h fi k l• Defined the organization as one of the first key goals• Started meeting even before program 100% formalized• Established full escalation hierarchyEstablished full escalation hierarchy


Data Governance

Data Governance Hierarchy• Steering Committee (8 people, monthly) - program decision rights

makers around funding, prioritization, staff and escalation issuesData Governance Council: reps from legal tax credit finance audit• Data Governance Council: reps from legal, tax, credit, finance, audit, stocks, etc. (6 people, on demand) - data decision rights group that is purely making decisions on data, data policies, etc

• Subcommittee - a representative of the council yet at a lower level…someone who has more hands on experience with certain issues based on the subject of the dayj y

• Data Management Team– Business “data champion”– IT manager– Project managers, data stewards, data warehouse architects, ETL


Surprises & Lessons Learned

• Early success with initial customer hub project was critical“Wasn’t just about creating a customer hub because anybody can buy a

product and load data”

• Value in understanding:– how good or how bad the data was– how good or how bad the processes were around that data,– how inconsistent people within different groups and different systems treat

customer data

• True top down type governance – exec sponsor(s) making sure that l d t d th ’ itt dpeople understand they’re committed

“We couldn’t do this from the bottom up, it would never work. There are too many people in the organization over the last couple of years where the


culture has been:‘I am a local business unit. I can dictate the way I run my business’”


• Time was main concern (needed people dedicated full-time)– Key subject matter experts (understand & define financial terms, definitions

& calculations) and not take them away from their job

• End of month/qtr/yr – no longer top priority, but still had to keep moving forward

• Can’t leave meetings without having some kind of a path for getting results and accountabilityresults and accountability.

• Analyze & understand “trusted source” as well as own data

• Technology – “no one package does everything”


Case Study:y

Case Study:A (different) Major International Financial Institution


Business Case

BackgroundBackground• Replacing 2 old, legacy Customer Information Files (CIFs)

– Operational CIF - at the individual level– Analytical CIF (Marketing) – at the household level

• 2006 (3-4 months) high-level business requirements• 2006 (3-4 months) high-level business requirements

• 2007 detailed requirements & project launch

• Phase 1 – Operational CIF onlyO l t– Only one source system

– More simple, individual-only matching (no hierarchical householding)


Business Case

Business CaseBusiness Case• Strong Sr Mgmt support allowed faster, general business case –

detailed, long-term ROI wasn’t required

• But middle mgmt less satisfied with strategic value– Often challenged for hard ROI numbersOften challenged for hard ROI numbers– Focused on adding value now instead of 1 year from now

• Phase 2 – Incorporate Analytical CIF– More complex hierarchical household matching– More likelihood of conflicts = greater need for governanceMore likelihood of conflicts = greater need for governance– Defering data augmentation until Phase 2


Data Qualityy

• A single, source system used for decadesA single, source system used for decades

• Everyone assumed there were no surprises left in data

• In fact, there were a number of surprises

“Originally we had no intention of doing much data profiling, but in hindsight that was a bad decision . . .”g

“A lot of people in the project understand the technology but don’t understand the data and how it’s used on a day to day basis acrossunderstand the data and how it’s used on a day to day basis across our channels and across our users.”


Data Governance

“Phase 1 only has one source system the legacy CIF people are used toPhase 1 only has one source system, the legacy CIF people are used to using . . .”

• Currently do not have a Data Steward (in IT or Business)

Still h h d t l j t t hi & i• Still have had some struggles on just matching & merging– Resolved with weekly all-day meetings over a couple months

• Data Steward & more formal governance planned in future phase



• Data Profiling – first & foremost

• Business Case – stick to top handful of benefits (you can drive yourself crazy with a thousand different benefits)yourself crazy with a thousand different benefits)

• Executive support is criticalecut e suppo t s c t ca– It’s not a 12-24 month project and then your done.– It’s a 10-20 year investment

• Lay out strategy long before you start anything else (several people over 3-4 months))



• Planned tightly controlled rollout in 2008 (users, dependencies, etc)– but everyone now saying “me first!”

D f i l it t Ph 2 (h h ldi t ti• Defering complexity to Phase 2 (householding, augmentation, analytical support, etc.) – Greatly helped maintain focus & delivery deadlines– “one of the best things we’ve done in hindsight”

SIs may want to do things the quickest and easiest way which might• SIs may want to do things the quickest and easiest way which might not be the best way for us long term

• Had to ask Sr Mgmt to step in a couple times early on to resolve priority disputes for data domain experts’ time


Case Study:y

Case Study:A (3rd) Major International Financial Institution


Business Case

Background:• Already had a centralized database• Loading a lot of data making broadly avail to the org• Originally only planned a simple “Data Steward” program• But quickly realized that there was a lack of governance throughout

the organization on datat e o ga at o o data

Business Case:• (some) Sr Mgmt realized need to transition from being just a “data

steward team” to providing data governance for the entire organizationg

• Used “grass root” support of middle-mgmt peers to help convince their bosses


Data Qualityy

• “We identified some major issues where the same field in the database is being use for four or five purposes… “database is being use for four or five purposes…

• “difficult to measure quality - we’re fighting every step”

• “if you really want quality data – it’s going to take years, it’s an iterative processiterative process.


Data Governance

• Already had an executive steering committee

• Trying to maintain independence of the business and technologybut partnering with both groups in order to get things done– but partnering with both groups in order to get things done

• Domain steward – 1 for each system of recordy– updated job descriptions so it becomes part of their ongoing

responsibility, such as maintaining metadata, and then it’s reflected within their annual performance appraisal.p pp

“The great thing is the way we’ve set up our governance structure b it t i l d th t k thbecause it goes to a single person and that person can make the decision rather than trying to get together 40 bodies”



• Get the governance structure set up and bought intoA i t d t l i l ll f t d t t– Appropriate processes and controls in place as well, from metadata to rolls and responsibilities

– Defining Data Stewards is not enough

• Pull in an SI to help get it done– “No sense bleeding through things you could have someone come in and g g g y

in 3-4 weeks, jump start your program by 24 months.”– Also helped in terms of credibility - more reassurance to Sr Mgmt

• Invest significant resources in metadata repository– Plan more time, effort & tools than “just mapping fields in Excel”

“You’re always at risk of losing that smart guy who knows how the system works and what each one of those elements meant. As soon as that guy walks out the door you lose all of that history ”


as that guy walks out the door, you lose all of that history.

Case Study:y

Case Study:A Major Health Insurance Company


Business Case

BackgroundBackground• Started as a “Data Warehousing” project• Evolved into an enterprise “Single Customer View” project• Early results were disappointing & hurt credibility• Uncovered need to resolve internal priority conflicts

350+ d d lt d• 350+ users depend on results every day


Business Case

Business case:Business case:• Fundamental issue of “same” reports from different departments

providing different numbers• Informal business rules could change “on-the-fly” within departments, so

even reports from the same department may not agree month-to-month• Started as a focused Marketing effort to prove value for taking the nextStarted as a focused Marketing effort to prove value for taking the next

step at the enterprise level• Driven by Director of Business Intelligence• Implemented over a series of 3 project to incrementally achieve

integration via “transition hubs”


Data Qualityy

“Shoot the Messenger”Shoot the Messenger

Initial release revealed true magnitude & scope of problems:• Tremendously hurt confidence of project results• Increased motivation & justification for more dept silos

V d f th d d t il t l bl• Vendors further encouraged dept silos to solve problems“we can do it faster...”


Data Qualityy

“Why do you think there are problems when we’re doing fine on the frontWhy do you think there are problems when we re doing fine on the front end?”

Determined key cause was conflict of fundamental priorities between front-end & back-end of business

• Front: #enrolls, #claims processed, #calls = min dataFront: #enrolls, #claims processed, #calls min data• Back – actuaries, underwriters, utilization analysts, marketing need

way more data = more keystrokes to tie things together

“When you have million dollar claims coming through, it just takes one error to have a major impact”error to have a major impact


Data Governance

• Start trying to resolve rogue DMs through consensus, but ended up needing Exec mandate

• But mandate required early, document success of resolving DQ issues from initial projectissues from initial project

• Convinced Chief Actuary to present DQ issues, business impact & solution strategy to other VPs

• Saw light bulbs go on around the room “oh, we better help out here”• Senior VP mandate enabled us to shut down new DM efforts early



• “The Single Customer View is seen as a pain in the ass sometimes”• Still fight some of the same battles of departments trying to build

private data martsShould have done better expectations management for DQ• Should have done better expectations management for DQ

• Took surprising effort to get the message out about what we were doing to address DQ

• Importance of translating DQ & Single Customer View errors into “business impact” (not just # of errors)

• Training for new employees• Training for new employees

“Jane resolved 10 problems while the new guy created 5 new ones”p g y


Session End

Questions & Answers


MDM Workshop 02-Case Studies & Business Benefits [לקריאה בלבד] [מצב תאימות]

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