mdm mistakes & how to avoid them!

Confidential & Proprietary • Copyright © 2009 The Nielsen Company

MDM – Master Data Mistakes and How to Avoid Them!

05/19/2010 MDM-DQ University

06/07/2010 Data Governance Annual Conference &

International Data Quality Conference

June 16, 2010 Confidential & Proprietary

Copyright © 2009 The Nielsen Company

Abstract

Data is an important asset to many companies and leveraging that data

properly can result in operational and IT cost savings as well as drive business growth. Furthermore, managing strategic data assets is foundational to a service oriented architecture, which in turn facilitates

business process management.. These statements make master data management an enticing proposition for many executives but to achieve these results, a proper examination and evaluation of the risks affecting

such a decision must be performed.

When considering master data management, a proper due diligence

effort should consider the business drivers, expected benefits, costs, resources, vendors, data profiling, integratability, infrastructure, social norms, and the new operating model. MDM is more than a single

product or process, rather, it is an ecosystem of products, processes, people and information. When executed properly, a master data management initiative can provide both savings and revenue

opportunities and fewer quality escapes.

Alan White Enterprise ArchitectChief Technology OfficeThe Nielsen Company Phone: 813.366.4184Mobile: 813.417.2946www.nielsen.com



Master Data Mistakes…

• Not leveraging your master data as an enterprise asset• Lack of master data management (MDM) education• Not instituting an Information Governance Board• Inability to identify and articulate your data quality needs• Failure assessing MDM needs and planning appropriately• Neglecting to put into place proper communication paths• Improper evaluation and selection process• Inability to identify an architecture and method for accessing data• Modeling for your MDM initiative as an afterthought• Failure to manage expectations on all facets of an MDM initiative• Trying to “boil the ocean” instead of attaining a “quick win”• Ignoring MDM best practices and principles• Not providing continuous business engagement• Planning without requirements for success



• Master Data– “Master data is the consistent and uniform set of identifiers and extended

attributes that describe the core entities of the enterprise – and are used across multiple business processes.” – Gartner

• Governance– “The way we make and set on decisions about managing a shared

resource for the common good.” [1]

• Master Data Management (MDM)– MDM comprises a set of processes and tools which allow the creation,

management, and distribution of master data throughout the organization.

• Data Governance– “Data governance is the political process of changing organizational

behavior to enhance and protect data as a strategic enterprise asset.” [1]

• MDM must start with data governance.

Working definitions



Master Data, an Enterprise Asset

• “First, your company must reach a collective understanding that master

data in an enterprise is a common asset, and that it is not being

effectively used to the greatest benefit of the organization.” [1]

•Source: Information Management Magazine

• “The specific approaches

that can solve the specific

problems of master and

reference data

management must be set

within a strategy of the

overall management of

enterprise information.”

Realize master data is a common asset



Educate stakeholders on MDM!

• Successful efforts start with a thorough understanding of MDM by all stakeholders throughout the organization.

• Excellent resources are available for learning the business, technical, and organizational aspects of MDM. – See Resources

• Learning should include MDM governance, data quality, methods-of-use, implementation styles, and information as a service.

• Stakeholders will need to keep in mind that MDM is a strategic initiative with phased implementations.



Foundation should be built on accurate data

•Source: Zoomix

•Source: TCS



• Define the scope and aspects of master data that will be managed

based on business goals and/or regulatory requirements

• Decide who makes the decisions for master data, how the governing

body is organized, and the processes to be followed

• Distribute the decisions about what will and will not be done and what

will and will not be encouraged when using master data

• Assign responsibilities for implementing the processes, policies, and

procedures to the shared resource

• Monitor the use of master data and the master data itself in order to

assess the effectiveness of the policies and procedures

Put in place an Information Governance Board to…



Information Governance Board in practice

• Define Data Stewardship Activities– Set data quality (DQ) rules, validate and enforce them– Define data domain values for key attributes – Set up business rules– Set up security and privacy rules

• Build standard and repeatable processes to govern data– The processes here are rules (not business rules) that outline how data is

reconciled, or how a DQ rule is promoted– Ensure there is a clearly outlined escalation path for resolving data related

problems• Write policy, standards, and data related requirements

– Data quality rules– Naming conventions (in domain and logical models, but not physical models)– Business rules that are common over the enterprise– Security and privacy rules

• Establish architecture and method for Master Data access– Access schema– SOA or manual request– File interchange formats •Source: [7]


Copyright © 2009 The Nielsen CompanyPage 10

180GR

180 GR

180 G

0180

180180G

000180

Within the same product class, the same

characteristic may be coded as many times as

required in order to meet internal needs

=Across categories, the same attribute or

characteristic might have different names and

its values may be different

Country 1

Packaging Packaging Pack Type

Mineral Water Glass Bottle Glass Bottle

Juices Bottle Bottle

Water Softeners Bottle Refill Bottle Refill

Laundry Detergents Plastic Bottle Plastic Bottle

Country 2

Understand your data quality needs

• Verification• Standardization• Enrichment• Recognition• Versioning

• Survivorship• Consolidation• Matching• Classification• Correlation

• It is important to perform structural and semantic profiling to truly understand your data quality needs and to properly estimate the effort required to improve the data quality

•Source: Nielsen Global Operations




Articulate your data quality needs

ClassificationMetadataReconstruction

Accurate Matching

•Source: Zoomix



• Project Drivers– Understand current state of the organization– Identify key business and technical drivers– Articulate the need for MDM

• Stakeholder Management– Determine initial and ongoing stakeholders

needed– Gain commitment across relevant business &

technical areas

• Project Scope– Understand the current landscape surrounding

master data– Business processes– Organizational capabilities– Methods of use

– Define what the target should be

Assess your MDM needs and plan properly

•Source: [1]



• Operational Efficiencies– Lower IT costs– Reduced time to market– Faster implementation– Best demonstrated practices– Reduced operational footprint

• Value Creation– New opportunities with existing customers– Designating high-value and low-value customers– Retaining customers– New information products (when data is your core competency)

• Data Risk Management• Regulatory Compliance

Assessment & PlanningProject Drivers

•Source: [1]



Challenges• Lack of consistent information

across transactional systems

• Lack of automated processes or controls to validate and manage data

• Growth creates data fragmentation

• Customer mandates and regulatory compliance for standards based master data synchronization with business units & partners

Business Impacts• Inability for IT to innovate quickly

and cost effectively to support

business mandates

• Downstream data errors are

much more costly to fix than

errors fixed at their source

• Information re-work requires a

lot of expertise and support

• Breakdowns in transactional

processes





EXTRUDED CRISPS

Item Identifier

CARDBOARDBARBEQUEPROCTER & GAMBLE 8257002274

Packaging MaterialRecipe FlavorBrand OwnerUPC

CAN/BARBEQUECONFECTIONERY & SNACKS

PROCTER & GAMBLE CO

PRINGLES POTATO CHIPS CAN/BARBEQUE

1159

variantpccMajorparentDescriptionbrandDescriptionproductCode

P&G0461 SNACK FOODS-POTATO

BBQPRINGLES REGULAR BBQ 56 GM

5610010056

MANUFSubPCFLVRItem DescriptionUPC

SNACKS FOODS-POTATO

Product Category

CARDBOARD

Packaging Material

BARBEQUEPRINGLES POTATO CHIPS

PROCTER & GAMBLE

5610010056

FlavorItem DescriptionBrand OwnerUPC

Europe

US

Canada

GoldenRecord

For illustrative purposes only





• Executive Sponsors– Chief Information Officer or proxy– Chief Information Security Officer or proxy– Chief Technology Officer or proxy– Lines of Business executive sponsors

• Business/Operations– LOB resource owners– Business data stewards– Business analysts

• IT Architecture and Operations– Strategist– Enterprise architect– Data architects– Solution architect(s)

Assessment & PlanningStakeholder Management

•Source: [1]



• The MDM Executive Team should:– Provide oversight for the MDM project– Commission an MDM project team of business

analysts, data stewards, architects, and data integrators to create the MDM roadmap

– Set up a management and decision making structure for the MDM project team

• The MDM Project Team should:– Define the project scope and the characteristics of

your organization’s MDM governance practice– Collect information on master data quality, existing

business processes, workflows, event notifications, data models, quality rules, & security controls

– From a governance perspective, begin to answer the critical questions regarding the data to be stored, sources of data, current systems, data stores, and processes


•Source: [1]


Copyright © 2009 The Nielsen CompanyPage 18

Initiative Leader

Build Factory

LeadLocations Lead

Program Management Tech Build

Products &

Brands Lead

Media Lead

Design Office

Lead

Operations

Production

Quality LeadHR Partner

Consulting

Partner

App Dev Program

Manager

Finance Partner

Operations Program Manager

Products Content

Lead

Locations Lead

UAT LeadEnd State

Planning Lead

Products Platform

Lead

Media Lead

Lead Program

IntegratorGovernance

Leader


•Source: Nielsen MDM Executive Team

June 16, 2010

LATAM

NA

GC

API

WEU

EEU

MEA

Regional Hub

Local System

Global System

•Zero footprint client

•Synchronization

•Data Governance

•Workflow

•Business Rules

•Data Quality

•MDM as a Service

Assessment & PlanningProject Scope



Deliver

Results

Evaluate your options; including buy vs. build

Compile

Quantitative

Results

Distribute

RFI

Engage

Leading

Vendors

Create

Scorecard

Research

Vendors

Gather

Requirements

Execute POC

and POT

Select

Vendors for

POC/POT

Compile

Qualitative

Results



Accessibility

• 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; (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

Gather your requirements



What to ask for, look for, and prove – high level

• Be sure you and the vendor agree on what out-of-the-box and configurable/modifiable means.

• Often times OOB is misinterpreted to mean that the feature is available without any configuration or modification.



What to ask for, look for, and prove – detailed



Evaluating your options



Determine your implementation style



MDM approaches

• Single-copy approach– Changes made directly to master data– Guarantees consistency– Applications have to be modified

• Multiple copies, single maintenance– Single master copy, changes sent to

copies stored locally at source– Applications can only change data not part

of master data– Reduces application changes– Learning curve for users

• Continuous merge– Copies stored locally where applications

can change master data– Local changes are sent to the master,

where they are merged– Changes to master are sent to source

systems and applied to copies– Minimal (maybe no) source system

changes– Update conflicts may be difficult to

reconcile

UI

Local

Media

Products Locations

Local Local

MDM Application

Application

Global Repository



Conceptual Sync Approach (Consolidation)

Global

Region

Current Transition

Target

• Current State – Separate IMDB Instances

• Consolidate IMDB system data into MDM

Hub & Apply Global Characteristics

• Retire legacy systems incrementally



Conceptual Hybrid Approach (Federation)

North

America

Local Chars

LATAM

Local Chars

Europe

Local Chars

Global

Global

Products,

Chars, & Values with

keys to local

564CA IMDBxxxGilletteMach356473

897ProdRefxxxCoca ColaVault67546

456NIMDBxxxKraftTriscuit34567

235EIMDBxxxGeneral MillsTotinos12345

KeySystemGlobal CharParentBrandGlobal ID

• No synchronization

• Hybrid Architectural Style (Transaction & Registry) begins evolutionary approach

• Global hub stores global chars & local keys for federated access to local products/chars

• Virtual consolidated view is

assembled dynamically

• Converge systems

• Retire legacy systems incrementally

Example Only



Conceptual Architecture

Enterprise Data Warehouses

Mainframes

Files

RDBMS

Web Services

XML Files Excel

LOB Systems (MSci, Claritas,

RMS, Media)

Applications & Reports

Third party data services

Process Manager

Information Integration Services

• Extract, Transform, Load

• Abstract and Virtualize

• Federated Access

MessagingConnectivity & 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



Duopoly of Master & Reference Data

Execution Engine

Data Management

User Interface

Products^ Rules* Custom Chars* Hierarchies*

Business Process

Products

Web Services

Web Services

1 Snapshot of filtered products

2 Navigation of products

(e.g. hierarchy)

1

2

Outputs

^ Reference Data

* Master Data

Rules interface

Rules managementRules implementation

Parser Parser



• Common Information Model– Object Oriented modeling

– Reusable data types, inheritance, operations for validating data

– Hierarchical– Nested data types with ability to declare

behaviors on data– Relational

– Manage referential integrity constraints

• Canonical Model– Business rules and format specifications– Standard view of data for an organization– Mapping back to application view

• Operating Model– “Describe how your organization will govern,

create, maintain, use, and analyze consistent, complete, contextual, and accurate data values for all stakeholders.” [4]

– The most important set of models

Model for your MDM initiative

•Source: [6]



Manage expectations on all facets of MDM

• MDM software is not the “silver bullet”; it is often times one of many

components in a LOB system

• MDM is usually a strategic initiative that involves a high degree of

coordination across several Lines of Business

• When estimating costs one should consider hardware, software,

resources, training, consulting, travel, etc.

• Skills should include systems integration, data quality, programming,

data architecture, data stewardship, business process, etc.

• People, processes, and politics are at the core of any MDM initiative!



To provide Global Operations

with a consistent business process and technology platform that enables global content and implements best demonstrated practices to

govern, create, maintain, publish, and analyze data values for all stakeholders while providing the authoritative source of data assets in

a flexible and scalable architecture capable of expanding into new markets and services aligning with Nielsen's business strategy

Think Big, Start Small; Don’t Boil the Ocean



Europe

NA

LATAM

Track 1 - Consolidate

•Design common data structure

•Map source and target systems

•Perform initial data load

•Synchronize SOE with SOR

Track 2 - Harmonize

Europe

NA

LATAM

•Reconcile Global Content

•Determine rules for products

•Apply Global Characteristics

•Synchronize SOR with SOE

€IMDBNA

LATAM

Track 3 - Centralize

•Develop global user interface

•Replace SOE with global SOE (starting with Europe)

Legend

Incremental Deliverables

Track 2

Track 3

Track 1

Each track in in this phased implementation approach builds upon one another and provides incremental value to the business.

Track 1:

•Provides the foundation for global convergence by defining the global content schema (common information model).

•Aligns with the global publication strategy.

Track 2:

•Facilitates global content harmonization via global characteristics and value administration.

•Aligns with the global data integration strategy.

Track 3:

•Replaces the local user interfaces and business processes with one global interface using best demonstrated practices

•Is part of the Global Operations convergence strategy

Think Big, Start Small; Don’t Boil the Ocean



Apply MDM best practices and principles

• Executive sponsorship should be and remain actively involved

• Business people must be involved and must collaborate with IT

• Project management and organizational change management should be in place

• Open communication across organization must be present

• The operating model should drive processes

• Processes should be enforced through automation

• Processes should be built to support continuous improvement

• Access to master data should occur at the MDM service interface layer

• Data models should be extensible to allow changes as needed to meet requirements

• Processes should be flexible for changing business process as the business dictates



Engage the business with incremental successConsumers

Legacy

Master Data

User Interface

Phase



Create decision and escalation paths

• Identify parties and define their

roles and responsibilities

• Ensure that all parties have the

information necessary to fulfill

their responsibilities

• Define the communication

process, escalation process

and decision making process



Planning for success and on-time delivery

• Strong leadership

• Skilled resources• Team composition• Shared accountability

• Achieve parallelism

• Continuous development• Training as necessary• Business availability

• No calendar or scope creep



…and how to avoid them

• Identify and leverage your master data assets• Educate stakeholders on MDM• Put in place an MDM governance board• Understand and articulate your data quality requirements• Involve data and enterprise architects in your MDM strategy• Create decision and escalation paths• Proper evaluation and selection process• Determine your implementation style• Model for your MDM initiative• Manage expectations on all facets of MDM• Think big, start small; don’t boil the ocean• Apply MDM best practices and principles• Engage the business with incremental success• Plan for success



Questions



References

1. Enterprise Master Data Management: An SOA Approach to Managing Core Information, Allen Dreibelbis et al, IBM Press 2008

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

3. Seven Master Data Mgmt Best Practices, Hannah Smalltree, News Writer05 Jul 2006 | SearchDataManagement.com

4. Modeling the MDM Blueprint Series, James Parnitzke, Applied Enterprise Architecture, 2009 | PragmaticArchitect.wordpress.com/

5. Information service patterns, Part 4: Master Data Management Architecture Patterns, Allen Dreibelbis et al, 29 Mar 2007 | IBM.com

6. Canonical Data Model: Design Challenge, Steve Hoberman, Information Management Magazine 01 Aug 2008 | information-management.com

7. Information Governance Board Charter and Approach, Jay Noh, 2008, The Nielsen Company

8. Master Data Management (MDM) Hub Architecture, Roger Wolter, Microsoft Corporation, Apr 2007 | MSDN Library