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MDM Summit 2009 Confidential & ProprietaryCopyright © 2009 The Nielsen Company

The Nielsen Company

July 12, 2009

MDM Summit 2009


Media Reference Strategy

• Overview of Nielsen Company• MDM Vision• Business case – Why did Nielsen embark on this program

– Pain points – Business and IT• Expected benefits• Future goal – Business and IT• Value to Nielsen Customers / Partners• MDM program at Nielsen

– Technology acquisition– Operational strategy – Project prioritization

• Roadmap• Lessons Learned• Q&A

Outline


Credits

• Thank you to the following people for contributing content to this presentation– Alan White (Enterprise Architect, The Nielsen Company)– Kalyan Raman (CTO, The Nielsen Company)– Ken Rabolt (Chief Data Architect, The Nielsen Company)

• Special thanks to our Tibco partners: Inderjeet Singh (VP, GM, Emerging Technologies) and Sidharth Suri (Product Marketing, MDM) for helping develop our MDM vision and for providing this opportunity to present


The Nielsen Company

• 37 Globally integrated companies focused on providing

insights into consumer behavior– Media and Advertising Information Systems (AIS)

– Consumer and Retail Measurement Systems (RMS)

– Emerging Business

– Online, Telecom

– Entertainment (Bookscan, Movies, Soundscan)

– Spectra, Claritas


The Nielsen Company Target Vision

MediaMassStorage

High Volume Processing

Services

Reference data HarmonizedReference data

SDK

Analog TVSet Top Box

Satellite &Digital TV

Cellular TV

Internet Media

Games

DVDs

iPod

VOD

Collect / Harmonize / Integrate

Consumer Behavior

Nielsen API

On Demand Analytics

Secure FileTransfer

Advanced and ReportingAnalytics

Extreme Volume Processing

Service Bureau


• Nielsen Reference Data consist of a set of strictly governed core fundamental data elements that provide the context to the company’s transactional and time series data

– Examples of reference data elements:– Brand, Brand Owner, Advertiser, Vendor, Distributor– Characteristics– Hierarchies– Geographies– Locations, Address, URL– Location where POS occurred– Distributor of Event– Party info to Panelist activities

– Examples of transactional/time series data:– Point Of Sale information– Media Events– Panelist Activities

Reference Data: Nielsen Company


One Global Reference Data Vision – Products And Brands

Global

Broker (synchronization)

ESB (universal translator)

Master/Reference data mgmt, quality, workflow (governance)

Local Systems

100 global operations centers 10


The Problem


EnterpriseReplicated / DistributedSilo’d / Isolated

Product

Audit (Sales)

Business

Campaign

Characteristics

Circulation

Consumption

Currency

Demographic

Exclusion

Geography

Homescan HH

Homescan Person

Impression

Location

Trademark

Media Content

Media Event

Media HH

Media Person

Media Type

Access Panelist

Person / Consumer

PoS

Sample

Shipment

Survey

Time

Traffic

3rd Party

Programming

More Rep

licati

on

ACN Based NMR Based Both

CollectionDevice

Current State - Data Architecture

• Inconsistent data and data quality (redundancy and rework)

• Costs of maintaining and improving the current data structures are growing

• Complexity of the data structures hinders speed to market

• Difficult to exploit existing and emerging market opportunities across business units

Across the Nielsen company today, reference data are generally not managed or leveraged optimally. Pain Points


PEOPLE People People Weekly Magazine

PEOPLE WEEKLY

MAGAZINE

PeopleWeekly

0033385984 000908-000 b3666 60378 G140

THE TIME INC MAGAZINE Time Inc. Time, Inc. Time Inc. N/A

MAGAZINES News-Weeklies

Consumer Magazines Magazine NEWS-

WEEKLIES

Title

Code

Parent

Category

RMS SRDS Brandweek Monitor PlusBrand

Monitor PlusDistributorSource

• Separate Databases• Disparate Sources

• Duplicated Efforts• Different Process

Problem at a Glance


Current state pain - Example

M+ Id’ing researchcoding load

RMS

Syndicatedbest fit load

Id’ing loadresearchcoding

Client viewbest fit

M+ local reference

RMS local reference

•Best fit model

•Inflexible

•Uni-directional

•No custom characteristics


Target State Vision - Example

M+ Id’ing researchcoding load

RMS

SyndicatedBest fit load

Id’ing loadresearchcoding

Client viewbest fit

Id’ing coding research load clientview

Global reference data hub

•One version

•Flexible

•Bi-directional

•Custom characteristics


One Reference System – Expected Benefits

• New Client Delivery Capabilities– Cross country deliverables– Cross service deliverables– Ability to rapidly create new deliverables from Nielsen assets

• Operating Effectiveness– Eliminate duplicated efforts– Eliminate multiple platforms (and their support)– Enable use of best demonstrated practice– Improved quality

The ultimate end state of One Reference System provides tangiblebenefits to our clients, improving our flexibility and quality while reducing our overall costs


Approach


Guiding principles

Page 15

• Address foundation first

• Leverage OOB features

• Integrate globally

• Buy before building

• Reduce number of operations centers and platforms

• Consistency ENFORCED through GOVERNANCE


Operational RequirementsAccessibility• Services

– Searching capabilities– Cleansing, enriching, matching external and internal files – Reporting– Subscription based

• Publish– Real time and scheduled– Content following business rules and “Fit for Usage”– Controls on replication of published data

• Interface– A single integrated zero client foot print application– Multilanguage– Multiple collection points

• Availability– 24/7 with scheduled downtime windows

Content• Domain (Including but not limited to)

– Business Enterprises– Products – Location– Media - People; Titles, Domain Names, Lineups, …

• Attributes– Support of Global and Regional/Business’s attribute views;

• Relationships– Will support relationship between entities

• Hierarchy– Multiple user and client defined hierarchy for an entity

• Versioning – Keep historical version of entities

• Audit trail

Governance• Matching

– Users can configure all matching rules.– Rules are domain and content type specific

• Content– Governance enabled at appropriate level for content types – Governed in real time (in all languages)– Direct impact on “fit for use” entity

• Workflow Management– Integrated– Cater to specific domains and functions;

• Knowledge Management– Integrated content knowledge base– Enable user to provide incremental updates

Security• Access, Ownership and Privacy

– Maintained at field level; (TDLinx licensing, client specific hierarchy)– External users only has access to “fit for use” data.

• Roles and Permission– User are given CRUD and functionality access based upon

roles


Technology Selection Process

Global Business Services

Page 17

Deliver Results

Execute POC

Select Vendors for POC

Compile Qualitative

Results

Distribute RFI

Engage Leading Vendors

Create Scorecard

Research Vendors

Gather Requirements


Essential Evaluation Criteria

•Flexibility– Non-standard reference entities

• Integration with Existing Architecture

•Change Management

•Total Cost of Ownership

Global Business Services

Page 18

Confidential & ProprietaryCopyright © 2009 The Nielsen Company

Topic of Presentation September 11, 2009

Global Reference System Conceptual Architecture

Enterprise Data Warehouses

Mainframes

Files

RDBMS

Web Services

XML Files Excel

LOB Systems (Emerging,

RMS, Media)

Applications & Reports

Third party data services

Process Manager

Information Integration Services

• Extract, Transform, Load

• Abstract and Virtualize

• Federated Access

Messaging Connectivity & Operability FTP, HTTP, etc.Service IntegrationApplication Integration

Master Data Mgmt Services

• Products

• Locations

• Media

• Workflow

• Search

• CRUD

Data Quality Services

• Profile & Analyze

• Standardize & Cleanse

• Matching


One Reference System Technology Architecture

External Data Providers

Retailers, Manufacturers,

Distributors, Advertisers, etc.

StagingData

MetaData

Information Integrity Services

ETL Services

EII Services

Information Integration Services

External Clients

Retailers, Manufacturers, Distributors, Advertisers, etc.

Business Connect

Message Mediation Choreography

Service IntegrationApplication Integration

Publish & Subscribe

Routing

Quality of Service

Transport

Connectivity & Operability

Enterprise Service BusSynchronous/Asynchronous BW/EMS

Master DataBE

CIM

LOB SystemsLegacy, factory, etc.

Reports & Analytics

LOB Users

GI Adapters MFT

iProcess

Workflow

User Interface

LOB Users


Organization


Team Structure

Page 22

Design Office

Build Factory

Products Locations Media

TIBCO CIMTrillium* / NetricsOracleERStudio

DataTIBCO Business StudioTIBCO CIMTIBCO iprocess

ProcessOracle Data IntegratorTIBCO BW, BE, EMS, Smartmapper, Weblogic

IntegrationTIBCO GI

UI

Decomposition / Assembly TeamCIM GI BW, BE ODI Others Build Teams

Functional Specifications Prototypes, Sample content

Physical Design Specifications Data Model, Process Model, Interface design, UI design


How did we prioritize?• How much revenue does the application generate? (business value)• How much does it cost to maintain the application? (resource efficiency) • Is the application necessary to support business functions? • Does the application duplicate functionality of other applications? (potential

candidate for reusable functions, services) • What is the application complexity? (may be used for estimating a time

frame to migrate or rationalize) • How many users connect to the application?• What are the types of users? (may be used for estimating re-training costs

for users) • Application rationalization strategy?

– Maintain, – Consolidate, – Modernize, – Replace, – Retire


Media Convergence Opportunities - Deep Dive Insights

HH/Dem

os

Packa

ges/

Provide

r

Media

Asset

ID

Program

Names Med

ia Dist

ributo

rs

Lineu

ps

Geogra

phies

Advert

iser

data

Device

data

Radio

Station

refere

nce d

ata

• The Media Asset ID (MAID) appears to be a viable entity for a central repository• Program Names and Demographics emerge as areas of opportunity for convergence• Media Distributor was chosen since it provides both quick wins and long term integration

opportunities

xx

x

x

x

x

xxx

x

xxx

x

x

x

x

xx

x

x

xxxxx

x

x

x

xxDMM

xOnlinexxRAM

xxxDigitalPlusxxxTelecom

xVideo CensusxxAd Council

xxNo Audience Left Behind/CW

xxxA2M2 (I2, 3 Screens)


Quick Win Strategy

• Approximately 6 months to build (“quick win”)– Relatively easy to build– Availability of proven reference architecture, patterns, and blueprints– Few systems to consolidate– Low volume of data

• Scalable to other countries

• Flexible to meet current and future requirements

• Supports Internationalization and Localization

• Faster ROI through convergence/divergence– Lower head count requirements– New product capabilities (e.g. Food Service)


Roadmap

• Deliver quick wins in Locations, Media, and Product/Brands in < 6 months

• Assemble build factory

• Establish shared infrastructure

• Build on quick wins

• Expand globally

• Establish governance


Lessons Learned

• Executive sponsorship is key

• Have a big vision – sell a ‘quick win’ strategy

• Deliver incremental value early and often

• “My data is too critical to risk with your program”

• “Sounds great, when you are all done and it works I will use it, but I’m not putting you on my project plan”

MDM Summit 2009 Confidential & ProprietaryCopyright © 2009 The Nielsen CompanyConfidential & Proprietary • Copyright © 2007 The Nielsen Company

Q & A


References

• TIBCO Quantum Leap Team• CIO News: Seven Master Data Mgmt Best Practices• Global Reference Data Convergence Strategy• Rational IQ – Application & Infrastructure Rationalization,

http://www.barometrix.com• Enterprise Master Data Management: An SOA Approach

to Managing Core Information, Allen Dreibelbis et al, IBM Press 2008

• A Business Case for Canonical Integration Model, David Connelly, CEO, Open Application Group, Inc.

• Using Master Data in Business Intelligence, Colin White, BI Research, March 2007


One Global Reference Data System - Objective

Page 30

To provide Global Operations with a consistent business process and technology platform that enables global content and facilitates zero footprint by implementing best demonstrated practices to govern, create, maintain, publish, and analyze data values for all stakeholders while providing theauthoritative source of reference data assets in a flexible and scalable architecture capable of expanding into new markets and services aligning with Nielsen's business strategy

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