© Talend 2014 1

Workshop: Overcoming the Five

Challenges of your MDM journey Presented by: Didier Josephine & Jean-Michel Franco

© Talend 2014 2

Your Interlocutors

Jean-Michel Franco Director, Product Marketing

Didier Joséphine Sales Engineer, MDM expert

Key Facts about Talend

• Founded in 2006

• 400 employees in 7 countries

• Highly scalable integration solutions addressing Big Data, Application Integration, Data Integration, Data Quality, MDM, BPM

• Dual HQ in Los Altos, CA and Paris, France

• Open Core business model

• Subscription license

• Services & training

2007 2008 2009 2010 2011 2012 2013

© Talend 2014 3

OVERCOMING THE FIVE CHALLENGES

OF YOUR MDM JOURNEY

Master Data Management 101 The five challenges to deliver on the promises of MDM - Modeling Agility: creating the single version of the truth - Data Accuracy: managing the data quality - Lines of Business Accountability: establishing data stewardship - Data Accessibility: Connecting enterprise sources and beyond - Master Data Actionability: connecting to processes, real time Outlook and future trends Wrap-up

© Talend 2014 4

Master Data Management is a

cornerstone for data-driven processes

Know Your Customer

Know Your Products

Know Your Suppliers

© Talend 2014 5

Talend

MDM

Customers

Suppliers

Products

Assets Agencies Stores

Organiza-tions and Reference

Data

Employees

MDM is about creating and managing the

golden records of your business

What ?

(44%)

Who ?

(33%) How ?

(21%)

Where ?

(3%)

Number sources : Gartner

© Talend 2014 6

Definition

Master data management (MDM) is the process of creating a single point of

reference for highly shared types of data, including customer, products,

suppliers, sites, organizations and employees.

Master data management requires companies to create a single view of their

shared master data asset. It then links together multiple data sources, and

ensures the enforcement of policies for accessing and updating the master

data, handling data quality and the routing of exceptions to people.

This “Data Stewardship” capability allows the lines of businesses to take

ownership of the content they need for their data centric processes. Once a

single view is created, that data can be operationally applied, and eventually

in real-time, to business problems and opportunities.

MDM is a strategic initiative for data-driven organization seeking to improve

business results such as better customer experience and service, increasing

cross-sell and up-sell revenue, and streamlining supply chains.

© Talend 2014 8

The journey from Data Integration to Information

Governance

From a fully IT driven model… …to a federated and collaborative

responsibility model

IT Lines of Business

Evo

lutio

n p

ath

From Data Management… …to Information Governance

© Talend 2014 9

The Business cases for MDM

M&A and restructuring

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360° Views

Managed Data Accuracy

Collaborative Data

Governance

Information Accessibility

Information Accountability

MDM Platform

Governance, Risk Compliance and fraud mgmt.

Just-in-time and lean operations

Customer centric

processes

Customer Experience

Management

Time to market

© Talend 2014 10

MDM : why change? why now? And how ?

Source : Gartner 2014 survey Enterprise Information and MDM

MDM is a hot topic

• in top 3 initiative for 50% of IT execs

There is a urgent need to refresh current processes linked to master data

• Ratings of the current capability: 3,6 on 7 ; average for 79%; poor for 21%

A lot of companies have engaged, but most are at early steps

• 61% still on planning/prototyping phases

Only 49% have a clear business case

• and 31% through an ROI model

© Talend 2014 11

Why MDM ?

https://info.talend.com/tdwinextgen.html

© Talend 2014 12

So Where to start your journey to data

governance ?

Define your business needs and your roadmap

Set up your stewardship organization

Design the platform

Engage your MDM programs

© Talend 2014 13

Turning MDM from a discipline to a program

“The biggest observed change entails a shift from organizations viewing MDM as an abstract discipline to treating it a tangible program. The successful organizations exhibit the later” Bill O Kane

Discipline Program

Vision What can be done What we will do

Goals Monolithic and long term Incremental and Time-Phased

Metrics General Specific to each project/process

Governance What is quality data How to fix it

Organization Data Stewardship Accountability and leadership

Technology Keeping the golden records

Promoting collaboration and communication

Sources : Gartner maturity model and MDM presentations

© Talend 2014 14

Organizing for MDM : best practices

1. State the problem you're trying to address.

2. Determine the project's mission and business value, and link the initiative to actionable insights.

3. Devise a good IT strategy.

4. Business users must take full ownership of the master data initiative.

5. Align success criteria for MDM across the organisational chart

6. Pay attention to organizational governance and change management.

7. Develop Master Data Services for Application Integration

8. Map business needs to technology acquisition

https://info.talend.com/mdmlisttdwi.html

http://www.informationweek.com/big-

data/big-data-analytics/7-master-data-

management-project-best-practices/d/d-

id/1107222

© Talend 2014 17

OVERCOMING THE FIVE CHALLENGES

OF YOUR MDM JOURNEY

Master Data Management 101 The five challenges to deliver on the promises of MDM - Modeling Agility: creating the single version of the truth - Data Accuracy: managing the data quality - Data Accessibility: Connecting enterprise sources and beyond - Lines of Business Accountability: establishing data stewardship - Master Data Actionability: connecting to processes and application, real time Outlook and future trends Wrap-up

© Talend 2014 18

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Key objectives for successful MDM

design

Modeling Agility

Data

Accuracy

Data steward-

ship

Data

Integration

Data actionability

• Unified views

• Embedded Rules and

Controls

• Role based access

• Creating master

data services

• Connecting to

systems, real time

• Profiling for new data

sources

• Standardization & matching

• Quality analytics and control

• Authoring and user

interfaces

• Tasks management &

resolution

• Workflows and BPM

• Integrating and cross

referencing internal

systems

• Augmenting with external

data

MDM

© Talend 2014 19

Modeling your data

Key steps to consider

• Creating the data model

• Defining the business rules

• Defining Data Validation controls

• Defining the roles , and the security

Mo

de

ling

Man

agin

g th

e

dat

a q

ual

ity

Enabling s

tew

ard

ship

Inte

gra

ting &

pro

pagati

ng t

he d

ata

Opera

tionalizin

g

the m

ast

er

data

© Talend 2014 20

Organizing for MDM: Defining the implementation

Style

MDM

ERP CRM

COTS

DWH

Consolidation

MDM

ERP

SFA

CRM

DWH

Centralized

MDM

CRM

E-Commerc

e

Marketing

DWH

Coexistence

MDM

ERP

SFA

CRM

DWH

Registry Less Intrusive Most MDM Configuration Most ESB Configuration

Less Intrusive Standard MDM Configuration

More Intrusive Standard MDM Configuration Optional ESB Configuration

Most Intrusive Moderate MDM Configuration Required ESB Configuration

© Talend 2014 21

Modeling best practices

Functional

Engage heavily the LOBs in the designing effort Reach consensus ASAP on the data definition of golden record Start at the core and keep it simple, then expand Make the model as self explanatory as possible for the business users, and document your business glossary Create your own primary key Manage the design and validation phase carefully, as changing a data model at run time once the data is populated may be a tedious exercise Leverage views and roles for usability

Value:

➜ Establish sustainable foundations for your MDM model

➜ Establish the cornerstone for collaboration (Stewardship and IT integration)

Technical

Create an internal permanent key for Master Data records Define modeling standards and respect them Use a graphic Case tool for the design Establish naming rules Reuse definition, rules and patterns Anticipate the performance impact of controls, enrichment and propagation rules

© Talend 2014 22

Managing the Data Quality

Key steps to consider

• Data Profiling

• Collect the referential to enriching the data

• Defining parsing, standardization, validation

• Defining the matching and survivorship

• Building Address validation rules

Modeling

Man

agin

g th

e d

ata

qu

alit

y

Enable

ste

ward

ship

Inte

gra

ting &

pro

pagati

ng t

he d

ata

Opera

tionalizin

g

the m

ast

er

data

© Talend 2014 23

Use case: Growing the Business With an

Extended Product Portfolio

Challenge:

• Extend the direct supply catalog with a long tail through an online marketplace with millions items

• Delegate administrative task related to product introduction to supplier through a self-service portal

Key capabilities needed :

• Close the gap between the back end application (supplier self service) and the existing front end (Customer facing MDM for product data)

• Data quality and stewardship • Data and application Integration

Value:

• Increased revenue through better exposure of features, benefits and reviews

• Streamlined product on-boarding

© Talend 2014 24

Data Quality best practices

Functional Know your data before starting the design: content, availability volume, typology, reliability, reference data Understand the information supply chain: who creates, imports, update, consumes (and when/where…) Establish strong collaboration with stewards in charge of manual resolution to fine tune your matching algorithms iteratively Define business and project metrics to be monitored over time, in order to size the data stewardship efforts and to show the progress

Value:

➜ Illuminate the data quality problems and its impact for lines of business

➜ Establish clear metrics for measuring the progress and success of the MDM program

Technical

Use a data profiling tool Integrate the data quality rules as gatekeepers in your data integration process Understand the constraints and objective that are behind the matching policies, including performance, impact of mismatches, cost of manual efforts… Anticipate the need for adjustments, including for undoing redoing data resolution activities

© Talend 2014 25

Synchronizing with the existing systems

in batch or real time

Key steps to consider

• Batch/real time, Bulk or incremental load, propagation : defining the integration policies

• Integrating with applications: internal, cloud based, external

Modeling

Managin

g t

he D

ata

Quality

Enable

ste

ward

ship

Inte

gra

ting &

pro

pagati

ng t

he d

ata

Opera

tionalizin

g

the m

ast

er

data

© Talend 2014 26

Challenge:

Support hyper growth of members in a non profit and highly regulated healthcare market

Re-engineering customer facing processes

Use case: Re-engineering member relationship

in a heavily regulated environment

Key capabilities need:

Start with strong Data quality and data reconciliation capabilities Manage external data standards and connect in real time with exchanges in the healthcare industry Implement workflow driven processes for customer facing activities (on-boarding, claims, billing…)

Value:

• Compliance (with HIPAA regulations) • Scalable processes to meet hyper growth (+250%

members acquisition rate) • Lower TCO and automated processing

© Talend 2014 27

Integration best practices

Functional

Define the integration architecture and the decision criteria to inform data integration scenarios for each source and targets

Design the integration layer as a moving object that will have to evolve on a regular basis, with its own lifecycle (new systems to connect, upgrades…)

Use design mechanisms like publish and subscribe or Master data services to avoid dependencies between system and have clear segregation of duties

Value:

➜ A shared service to bring trusted data across your IT trough a well defined and rapid to deploy process

➜ Manage change info your MDM program and take advantage into new sources of data and accelerate the roll-out of new applications

Technical

Invest on productivity and change management tools, since this makes a substantial part of your TCO

Identify the volume now…and for the future

Identify the MDM multiple environments

Define procedures for Delivery between environments

Integration Services

Data StagingMetaDataRepository

Web Layer

Hybris

TCP/IP - Kereberos

Legend

Customer Data Management – Static Architecture

Integration Services

BatchAdaptors

Real-timeAdaptors

Real time data

services

File based

MasterRepository

@ComRes

ACDS

Pega

Tracs

VisionData Quality Services

Talend Integration Platform

Parsing& enrichment

(Experian)

MatchingServices Batch data

services

Data Layer

Master Data Governance

TalendAdministration

Data QualityDashboard

MigrationAdaptors

Standardisation Services

Inte

grat

ion

Lay

erActive

Directory

SOAP over JMS

GetCustomerDetailsCore

GeCustomerinteractions

CreateCustomer

UpdateCustomer

PublishCustomer

GetCustomerEngagements

GetCustomerProfile

SearchCustomer

MatchCustomer

PublishCustomerMerge

Inte

grat

ion

Lay

er

MatchCustomerBulk

SOAP over Http

Talend ESB

© Talend 2014 28

Engage your Lines of Businesses

Key steps to consider

• Organize data stewardship tasks by roles

• Managing the day to day tasks related to master data

• Accessing and authoring the master data

• Defining the workflows for collaborative authoring

Modeling

Managin

g t

he D

ata

Quality

Enable

stew

ard

ship

Opera

tionalize

the m

ast

er

data

Opera

tionalize

the m

ast

er

data

© Talend 2014 29

Use case: Monetizing content and increasing

ARPU in the media industry

Challenge:

• Manage 28,000 hours of multimedia content delivered monthly from 340 content providers to 75 million households

Value:

• Increase ARPU (Average Revenue Per User) and improved customer experience with data to promote the movies

• Decreased costs and time for adding new content to the movie catalog

Key capabilities needed :

• Start with Data Integration and data quality to deliver quickly an improved centralized catalog

• Progressively replace a non intrusive a posteriori process to reconcile data and manage errors with a reengineered collaborative process driven by workflows

© Talend 2014 30

Best practices for Data Stewardship

Functional

Define and document the data governance policies (incl inventories roles, permissions, workflows)

Make sure that the lines of businesses are engaged and accountable

Define clear roles & tasks for data stewards and define their working environment and workflows accordingly ;

Engage the data stewards early in the project, well before the training and roll-out phase

Value:

➜ Engage the lines of business in the success of data centric initiatives

➜ Organize for a MDM roll-out and continuous improvement

Technical

Integrate the people driven tasks related to data authoring, validation and correction into the overall landscape, rather than as a separate flow

Target the right environment for the right roles (designers, data stewards, authors and contributors, end users)

© Talend 2014 31

To BPM or not to BPM ?

Functional ➜ Clearly identify the actors ➜ Nominate champions for roles and involve them in

the project to define the processes and activities ➜ Use agile methodologies to define the workflows

and interfaces ➜ Carefully design the users interface ➜ Leverage Business Activity Management for alerts

and continuous improvement

When to use BPM in MDM projects ?

MDM has the lead for data authoring Lines of businesses are highly engaged Business users are involved in the authoring process -> need for guided procedures There are clear links between MDM and business processes (e.g.: onboarding a customer/employee, referencing a product…).

Technical

Use a BPM tool that can go beyond pure MDM authoring capabilities

Keep it simple and anticipate frequent change since people centric processes are subject change and to deal with exception much more frequently that automated processes

Don’t underestimate efforts and time related to the user interface

Value: • Re-engineer your processes with a data centric

approach

© Talend 2014 32

Making MDM actionable

Key Capabilities

• Integrate Master Data Services real time into processes

• Bring context into applications such as Big Data, web or Mobile Applications

Modeling

Managin

g t

he D

ata

Quality

Enable

ste

ward

ship

Inte

gra

ting &

pro

pagati

ng t

he d

ata

Opera

tionalizin

g

the m

ast

er

data

© Talend 2014 33

Best practices for Operationalizing the

Master data

Functional

Identify the touch points where you need to integrate MDM data services, and prioritize the roll out interactively.

Define metrics to show the business impact, e.g. on transformation rates, click rates…

Understand the performance and availability impact of invoking MDM real time for the external applications

Define a small set of reusable, well documented master data services

Connect your master data to your Big Data via Entity Resolution to boost the relevance of your bog data analytics

Value:

➜ 360 view are populated at the right time, right place, when insights or actions are needed.

Technical

Closely integrate this capability into your existing enterprise service bus capability

Define Service level agreements for the MDM services and monitor them closely

Create sets of tests cases to industrialize and automate the testing capabilities

MDM

Business Applications

Mobile Applications

Big Data

Web applications

© Talend 2014 34

Use Case Bring Actionable Customer Data across

Touch Points in Travel & Transportation

Challenge:

Drive loyalty and customer retention in an industry disrupted by digital transformation

Key capability needed:

• Fast & easy collection, cleansing and reconciling of data for 15 million customers

• Definition of Master data services to bring customer context and progressive delivery across touch points in a real time mode

Value:

➜ Improved marketing, sales and service through knowledge and personalization

➜ Better transformation rates, cross sell/upsell ➜ Multi-Channel consistent Customer

Experience

© Talend 2014 35

Example in CRM: the customer data platform Multiple customer touch point, many innovative offers, but broken

customer journeys

Customer Data

Platform

© Talend 2014 36

Building the « customer data platform » to get

a true Customer 360° view…

Customer Data

Platform

© Talend 2014 37

From customer 360 view to the

customer timeline Get the

loyalty card

Clicks for

The coupon

Receive a

promotion

Orders

On line

Complain

Searches

For television

Connect

to wifi

Search

In amazon

Acquires

television

© Talend 2014 38

From clickstream to customer analytics and to real time recommendations

From analytics to actionable recommendations

• Create personalized journeys - Personalization for outbound marketing (e-mails, SMS,

mobile notifications…)

- Real time recommendations for inbound marketing (mobile, web…)

- Next best actions for the field (contact center, clienteling at the point of sales…)

• Customer touch-points are integrated iteratively into real time scenarios

• Business benefits: Sales efficiency is improved, and every marketing activities (campaigns, promotions…) can be measured at a very fine grain -> click rates, transformation rates, campaign effectiveness…

© Talend 2014 39

OVERCOMING THE FIVE CHALLENGES

OF YOUR MDM JOURNEY

Master Data Management 101 The five challenges to deliver on the promises of MDM - Trends and wrap-up Wrap-up

© Talend 2014 40

Trends in MDM

Ten priorities to guide organizations into next generation MDM

1. Multi-domain MDM

2. Multi department, multi application MDM

3. Bi-directional MDM

4. Real time MDM

5. Consolidating multiple MDM Solutions

6. Coordination with other disciplines

7. Richer Modeling

8. Beyond Enterprise Data

9. Workflow and Process Management

10.MDM solutions build atop vendor tools and platforms

Source : TDWI next generation MDM

Key technologies challenges for next generation MDM

1. Complex relationships

2. Mobile

3. Social

4. Big Data

5. Time-travel

6. Cloud

7. Action enablement

8. Real time

9. Extreme scalability

10.Proactive, integrated governance

Source : The MDM Institute

© Talend 2014 41

Thank your for your attention

Overcoming the Five

Challenges of your

MDM journey

Contact us:

jfranco@talend.com

djosephine@talend.

com

Learn more:

www.talend.com.p

roduct/mdm