MDM Best Practices

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MDM

DM

A Supplement to

Produced by SourceMedias Custom Media Solutions

June 2008

Master Data Management

Project Management ChallengesWith A Changing Landscape


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It is not t adancd stat otcnolog but ratr t prssing

nds o businss tat as brougtmastr data managmnt (MDM)to t or.

Contnts

4

89


And i IT is to proid t ngin or MDM, it is businsstat must b t drir and naigator to tak MDM to its dsird dstinations. T man

complitis and rquirmnts o MDM can lad us to orlook a simpl trut: It is not

and nr will b ITs job to tll t businss ow to run t businss. Tror it is up

to t businss to dfn its own cor comptncis, its primar lrs o comptiti

dirntiation and mak sur t MDM program springs dirctl rom ts. Tcnolog

b itsl will work as dsignd; t gratr canc o ailur lis in lack o ortougt and

t compting intrnal intrsts tat caus dlas, scop crp and projcts tat do not

answr to prdfnd goals and masurs o succss.

Industr Bst Practics

Sponsors

02 DataDelta

09 Exeros

11 D&B

12 DataLever

Project Management Challenges

with a Changing Landscape

MDM

Milestones

The Intrinsic Value of


A Supplement to DM Review Produced by SourceMedias Custom Media Solutions 3


4/12

MDM is not a tcnolog markt,

but a businss capabilit.1 MDM is mor tan tcnolog; it is about

data gornanc, data ownrsip and an ongoing program to maintain

a singl rsion o t trut or critical corporat data.

A Supplement to DM Review Produced by SourceMedias Custom Media Solutions

Project ManagementChallenges with aChanging Landscape

1

T political natur o MDM plains the importance o data governance,but governance alone is not enough to undertake an MDM initiative. While large IT

projects in the past, such as customer relationship management (CRM) and enterprise

resource planning (ERP), have involved both IT and business teams and required both

IT application implementation and change management, these projects ran in parallel,

with the IT teams ocused on the implementation and the change management team

preparing the users or the system.

Project management or these projects through implementation and delivery has

resided within the IT organization, with the business side providing the requirements.

MDM reverses this paradigm. Business not only owns the requirements, they also own

the data, the ongoing data stewardship and, most importantly, the project management

o the MDM initiative.

Thereore, to address the project management challenges in an MDM initiative,

it is necessary to create a ramework including project management best practices,

technological advances, data requirements and a blend o methodologies rom change

management, business process reengineering and IT application implementation.

Successully delivering projects on time has always been a challenge. Project

management methodologies are well documented and continue to evolve to address

the challenges. The Project Management Institute (PMI) and body o knowledge guide

(PMBOK) are excellent sources o reerence material on the subject. With this in mind,

six key points are vital to the success o your MDM project.

Us succsss in projct managmnt,

suc as a projct managmnt ofc

(PMO), as part o our MDM initiati.

Initiatives such as the ormation o a PMO to

document and disseminate knowledge o what

works within and across projects have real,

quantiable benets. Companies that implemented

successul PMOs achieved 80 percent ROI and 20

percent reduction in project time.2 2Lrag sric-orintd arcitctur (SOA) and

on-dmand tcnologis to acclrat projct

dlir ia consolidation and rus o srics.

In the early 2000s, both Gartner and Forrester Research put

CRM project ailure rates greater than 70 percent. More recently,

technological improvements such as on-demand deployment

models are contributing to better implementation results: 59.3

percent o on-demand CRM projects are implemented in three

months or less compared to 15.6 percent or on-premise. Also,

76.5 percent o on-demand projects are on budget, compared

to 43.7 percent or on-premise.3 Additionally, SOA allows a

number o technologies to work together in an MDM initiative.

4

B Tim OSullian


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3MDM will sit data ownrsip to t

businss sid o t organization, putting

ocus on a data mtodolog.

Prior to MDM, data needs were typically

ullled by each department maintaining

their own silo o inormation and/or

requesting a snapshot o data rom a data

warehouse maintained by IT. Centralized

data was owned and maintained by IT.

Data needs oten lack a methodology or

preparation and analysis. But, at the core

o the methodology is data.

4Bring t popl aspct rigt up ront in an MDM initiati.

Enterprise projects such as ERP involve a lot o change. Change management

reers to the eort it takes to manage people through the emotional ups

and downs that inevitably occur when an organization is undergoing massive

change.4 At the core o change management is people.

The preparation steps or a change management project include executive

sponsorship, selecting a change agent, orming a transition team, perorming

assessment activities and developing a transormational vision. The transitionteam serves as a liaison between the end users and the development teams

and perorms tasks such as implementing processes and training users

o the system. The change agent leads the change project and requires a

mixture o good project management skills to keep projects on track and good

leadership skills to motivate and evangelize or the project with passion.

56

Trat implmntation as a subprojct ld b IT, and pand t

scoping stp wit principls rom cang managmnt and BPR.

The crucial steps in the liecycle o an IT implementation project are

typically: scope, planning, execution, control and closure.5 Flexibility,

common sense and communication within this ramework are critical or

successul project delivery.

During the scoping phase, the systems and their requirements or

eatures are identied and the business requirements are gathered. The

project deliverables are broken down into manageable tasks, resource

assignments and milestones. These projects are typically

led and managed by IT.

continued

Both a business sponsor and an ROI case or the projectare needed or continued executive support during the liecycle. A steering

committee working at a strategic level guides the project, and project

management ocuses on the execution o the plan within the constraints o

time, resources and scope. At the core o IT implementation is execution

getting the project completed on time. Implementing MDM is still relatively

new to organizations, compared to implementing ERP or CRM.

MDM is a program inoling ongoing data stwardsip and procss

rnginring, using lssons larnd rom businss procss

rnginring (BPR).

BPR is also an enterprise-wide undertaking to dramatically improve

customer service, cut operational costs and make the organization more

competitive. The preparation step involves building cross-unctional teams

and identiying the objectives.

The main activities break into the ollowing steps: Mapping and analyzing

the as is processes, designing the to be processes and implementing

the reengineered processes. Following implementation, BPR enters a

cycle o continuous improvement through ongoing measurement and

review. At the core o BPR are processes.


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A Supplement to DM Review Produced by SourceMedias Custom Media Solutions6

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CangManagmnt

DataNds

IT Application

Implmntation

BusinssProcss

Rnginring

ContinuousImpromnt

Data Gornanc Council PMO Data Procsss Standards

MDM is the ramework o processes and technologies aimed

at creating and maintaining an authoritative, reliable, sustainable,

accurate and secure data environment that represents a single

version o the truth.6 This denition reinorces the point that MDM

is a blend o data, processes and technology.

Data implies data requirements, data analysis and data

integration. Technologies are required to provide a data hub; data

proling; data quality; matching/cleansing; extract, transorm

and load; enrichment; and application integration unctionality.Processes are required or the operational workfows and rules or

managing a single version o the truth.

Extended processes are required when integrating the spokes,

such as a marketing database, customer service, ERP and CRM,

with the MDM hub.

So what is at the core o MDM? Weve seen that in change

management it is people, in BPR it is processes and with technology

it is execution. In MDM, it is all o those, plus data and data

ownership. And data ownership brings a lot o politics into the

project management mix.

When embarking on an MDM initiative, the initial step resembles

a change management project where building a team (in this case,

the data governance council), perorming assessment activities

and dening the vision and objectives are the main undertakings.

During this step, the organization should lay the oundation or

the project management o the MDM initiative. As a best practice,

business should have ownership and leadership or the MDM

initiative.

The change agent will come rom the business side, will possess

both project management and leadership skills and will have overall

project management responsibility. At the MDM Summit conerences,

we heard a number o cases where ormer IT olks transitioned to

the business side, and consultants were oten used to assist the

organization in the transormation. In the next step, business asserts

itsel as the owner o the MDM initiative and takes control o the

specications and analysis o data.

With data at the core o the initiative, a methodology or data needs

and ongoing data stewardship or data preparation and analysis will

have to be adopted. As companies already have data, technologies,

business processes and rules or data management, the impact o

the MDM initiative will need to be analyzed. Cross-unctional teams o

business analysts, IT and data gurus will ollow a BPR methodology

and design the to be processes and business rules.

The implementation step will adopt the IT implementation

methodology, and IT will have much clearer objectives within the MDM

ramework.

The nal step in the MDM ramework resembles BPR. The MDM

initiative enters a cycle o continuous measurement and review

as part o the ongoing data stewardship that is undamental to a

successul MDM initiative.

A blend o existing methodologies and best practices are directly

applicable to MDM initiatives. Adopting a ramework will acilitatethe project management o the initiative.

Underlying the MDM initiative is a data governance council.

Data governance is a process ocused on managing the quality,

consistency, usability, security and availability o inormation.7

While data governance is a continuous eort ater the MDM

implementation, it is also a crucial part o a successul MDM

implementation and must be embedded into the project plan.

The best advice on how to include data governance in the project

plan is to include milestones that, when achieved, can be pointed to

as data governance successes. This way the organization sees the

impact o MDM and appreciates its importance when a continuous

post-implementation eort is required.

By adopting existing project methodologies and working data

governance into project plans as milestones, a ramework or the

project management o an MDM initiative emerges that addresses

the political, technological and data stewardship challenges.

No matter how small the initial MDM project is scoped, putting the

MDM ramework in place rom the start will get the project o the

ground successully. Regardless o which approach an organization has

taken to date on an MDM initiative, it is possible to get back on

track once the path orward is better understood and a ramework

is adopted. Reerences:1. Hannah Smalltree. Gartner and Forrester reute master data management system claims.

SearchDataManagement.com, December 5, 2006.2. Forrester Research cited by Paul R. Astiz. IT Project Management Oce. PMI-SSC

presentation, October 12, 2005.3. Jim Dickie and Barry Trailer. On-Demand Versus On-Premise CRM: Are There Perormance

Dierences? CSO Insights, 2006.4. Dunleavy et al., 1998, cited in Michelle M. Sieber and Fui Hoon (Fiona) Nah. A Recurring

Improvisational Methodology or Change Management in ERP Implementation. Proceedingso the Americas Conerence on Inormation, 1999.

5. Margo Visitacion. Project Management Best Practices: Key Processes and CommonSense. Giga Inormation Group, Inc., January 30, 2003.

6. Mike2Wiki. Master Data Management Solution Oering. mike2.openmethodology.org,retrieved March 11, 2008.

7. Alex Berson and Larry Dubov. Master Data Management and Customer Data Integrationfor the Global Enterprise. New York: McGraw-Hill, 2007.

Tim OSullivan is a vice president and partner at Hub Solution Designs, Inc., a consulting rmthat helps its clients to develop and execute high-impact master data management and data

governance strategies. He may be reached at [email protected].

Figure1:

MDMFramework


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www.mdm-summit.com | 800.803.3424 | 212.803.6093

MDM Summit Fall 2008 returns to New York City

heres what our past attendees told us:

MDMSummitFALL 2008

Presented by:

SAVE THE DATE!

Network with Enterprise Architects, MDM Project Leaders, Data Stewardsand more at the largest gathering of MDM Professionals in the World!

O C T O B E R 1 9 - 2 1 , 2 0 0 8HILTON NEW YORK | NEW YORK, NY

For sponsorship and exhibit information, please contact Tony Carrini

at 212-803-8547 or [email protected]

A fantastic conferenceon what is becomingthe next big thingin IT0Robert Zegrac,

Group Manager, National City

Great Networking!Overall, a greatexperience!James Cisler,

Manager, Master Data, Stryker

This conference is agreat way to see whatvendors are doing.Mark Evans,

Senior CDI Consultant,

Experian

Great Conference! Ienjoyed learning and

networking with leadingvendors in this space.TJ Adler,

IT Account Manager, AAA of

Northern California

This has been a verygood conference for meto get an understandingof MDM/CDI, toolsand technologiesavailable.Carol Young,

Business Data Architect,

Lexmark

Good Conference.Lots of Information.Deven Dhulia,

Solution Architect,

Hewlett-Packard


8/12


On o t goals o mastrdata managmnt (MDM) isto maintain a singl

The Intrinsic Value ofMaster Data Management

accss point to spcifd data sts,

thereby creating a single view o inormation. Whether customers, products or other

entities, organizations may struggle to measure the actual benets o consolidating and

centralizing data to have a single viewpoint o data. Beyond the ability to use a centralized

access point to gain a better perspective o what is going on in the organization,

organizations are always required to provide an account o the nancial benets o new

IT initiatives. Within MDM, business intelligence (BI), business process management

(BPM), etc., the immediate return on investment is not always seen. Unortunately, some

organizations choose not to look beyond immediate nancial gains when seeking to

implement new solutions or change the way they currently do business.

B Lndsa Wis

continued on page 10


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TOP 5 JUSTIFICATIONS FOR MDM INITIATIveS

1. Catalyzes market leadership and dominance.

2. Provides increased ROI by leveraging and rationalizingexisting inrastructure.

3. Signicantly increases shareholder value.

4. Provides a disruptive technology or new business models.

5. Enables compliance and regulatory reporting.

LeSSONS LeARNeD Q4 2007

Promote MDM as essential business strategy with IT deliverables

to leverage high-value inormation used repeatedly across many

business processes.

Position MDM as an enabler of key business activities such as

improving customer communication and reporting rather than

as an important inrastructure upgrade.

Begin MDM projects focused on either customer centricity or

product/service optimization.

Plan for multientity MDM solutions evolving from early adopter

status into competitive business strategy during 2008-2009.

STRATeGIC PLANNING ASSUMPTIONS

Markt maturation: By 2012, the market or enterprise MDM

solutions (sotware and services) as both strategic initiatives and toreresh aging legacy MDM capabilities will exceed $3 billion (U.S.).

Skills: Throughout 2009-10, skill shortages will greatly infame

project costs as demand or data stewards, enterprise data

architects and individuals with data governance experience

outstrip market supply.

Analtics: During 2008, the convergence o MDM and business

intelligence (BI) will accelerate as enterprises leverage MDM

concepts in a BI context. Additionally, by 2012, inline and real-

time analytics derived rom MDM-enabled aggregation o both

transactional and historical data will have become a major

source o sustainable competitive dierentiation or Global 5000

enterprises.

MDM conrgnc: By 2012, enterprises without an overall

long-term MDM strategy run the ironic risk o building MDM silos.

Bottom-lin planning assumption: Invest in data governance and

architecture or long-term MDM sustainability and ROI.

Excerpted rom Milestones on the MDM Roadmap or 2008-09 by the MDM Institute.

MDM MilstonsAt t spring 2008 MDM Summit in San Francisco sponsord b T MDM Institut and DM Riw, Aaron

Zorns, oundr and ci rsarc ofcr o T MDM Institut, addrssd t topic o Milstons on t

MDM Roadmap in is knot basd on rsarc rom is Global 1000 clints. K fndings includ:


10/12

T managmnt omaster datatouches more than just the inormation that

is maintained. By creating data repositories

that refect business unctions, organizations

can develop views o data that give users

access to the inormation required to do their jobs

eectively and eciently.To better understand the business benets o

MDM, it is important to recognize an organizations

general inormation inrastructure and how

silos o data have been ormed within

organizations, creating a splintered

view o what is occurring within the

organization. Then it is possible to

understand the benets o the creation

o a centralized repository o data

regarding both the inormation accessed

and the business benets that go beyond data.

Fracturd Inormation viws

Due to the nature o inormation architecture and the development

o enterprise inormation systems, the general structure o data is

that it exists in silos across the organization. Beore the concept

o centralized data stores, many systems were developed to meet

a business unction without taking into account the big picture.

Consequently, with the addition o new systems, data storage

volumes and the number o transactions grow exponentially. This

means that in many organizations, several disparate systems

exist that contain similar inormation but dont interact with other

relevant systems within the organization. In addition to this lack o

interaction, duplicate data may be processed in dierent systems,

creating duplicate work or end users and dierent data structures.

This adds to the diculty o looking or and identiying like data

across the organization.

The bottom line is that each system only gives a ractured

view o what is occurring within the organization. For instance, a

customer relationship management (CRM) system may not have

all o the account inormation o their customers, rom buying

habits and payment histories to product preerences. Dierent

bits o inormation that reside in disparate systems, when brought

together, create a ull view o the customer. Add to this data quality

eorts to standardize data views and to create a consistent

view o data across the organization, and the beginnings o MDM

are created.

Although MDM solutions give organizations central access

points and a 360-degree view o data and entities, actual ROI is

not always easy to quantiy. Ater all, quantiying better customer

service or identiying a decrease in product cycle times and tying

that to an MDM initiative may not be intuitive or organizations.

MDM Bnfts eplord

There are many benets or organizations choosing to implement

an MDM solution that result rom creating a consolidated view o

data. To identiy the ROI associated with MDM, some key benets

should be highlighted that go beyond the consolidation o data

toward increasing eciencies within organizations and lowering the

cost o doing business.The most obvious benet o customer data integration (CDI)/

MDM solutions is the creation o a single customer view. By creating

a centralized access point o contact to customer, product or other

orms o data, not only are organizations able to gain a better overall

view o business entities and what is occurring with accounts, but

also, data quality eorts become consistent. For organizations

trying to attain one view o entities, the ability to ensure data quality

throughout the organization means that consistency o business

rules, data cleansing and the standardization o business processes

will become an ingrained process within the overall environment.

Despite the act that there is a constant ocus on business

pains and a push to ocus on business rather than data, an

organizations healthy business environment depends upon the

data that supports it. Thereore, having strong data quality eorts

in place helps organizations maintain healthy inormation systems,

identiy how systems across the organization interconnect and

enable better BPM. Although IT benets are important, business

benets are also relevant. Using customer data as an example,

end users can provide better service quicker, thereby increasing

customer retention and satisaction.

Because o compliance and the need to maintain specic data

sets and output on a regular basis, MDM enables organizations to

manage the processes essential to meet compliance requirements.

This, in turn, translates into the ability to plan and budget more

eciently. With a broader understanding o what is occurring within

the organization, nancial processes can oer a more complete

view o the organization.

Finally, building an MDM solution enables organizations to

develop and maintain a strong data governance program. Because

all o the mechanisms have been put in place, data governance

becomes a natural extension o an MDM implementation.

Focusing on valu

Whether by ocusing on business or IT, the values o MDM are

numerous. Actual implementation o an MDM solution is process

and resource intensive as well as continual based on the need

or constant data quality and business process improvements.

However, these eorts enable organizations to have a synchronized

and 360-degree view o the data that helps drive their business

success.


Lyndsay Wise is an industry analyst or business intelligence. For more than seven years, shehas assisted clients in business systems analysis, sotware selection and implementationo enterprise applications. Wise also conducts research o leading technologies, productsand vendors in business intelligence, marketing perormance management master datamanagement and unstructured data.

continued rom page 8


11/12


Todays options or ensuring an accurate and

trusted view o data regarding customers, prospects,

suppliers, partners, and sales rely on some orm

o data integration to optimize and link databases

rom CRM, ERP,--data warehouses, customer support

and contact center systems, websites and other

disparate sources. Unortunately, many o these

implementations have only an internal view o

inormation. They attempt to nd the truth about

current conditions by consolidating and resolving

only the data already maintained by the company.

Every day, however, tens o millions o changes

take place within customer, prospect and supplier

organizations, and these changes are typically

invisible to the data integration eort, resulting in

highly incomplete and stale data. Even the largest

companies nd that maintaining a continuously

accurate view o their data is a daunting task. Too

much is happening too ast, and they just dont

have the systems and resources to keep up.

Fortunately, theres a better way.

The FIRST STeP:

AGGReSSIveLy USe ReFeReNCe DATA

Many leading corporations have taken a valuable

rst step toward being able to maintain continuously

up-to-date and accurate data. They have chosen to

use a provider o external reerence data, such as

D&B, to validate and correct their internal data. In

most cases, they periodically re-submit the data to

the external provider so new updates to the reerence

inormation can be incorporated. This reresh also

ensures each entity is accurately identied and

the structural linkages to other entities, such as

subsidiaries and parents, are also accurate.

By treating reerence data as a snapshot,

however, these companies typically rely on irregular,

point-in-time interaction with the external data, and

within days, the accuracy o their internal data

and the value they gain rom that accuracy starts

to diminish.

The SeCOND STeP:

MAKe The DATA AND

The TeChNOLOGy INTeLLIGeNT

In order to maintain continuously accurate data

that can condently be relied upon to drive daily

business processes and decisions, organizations

must nd a way to link their internal data sources

with their external reerence data provider so they

can build a continuously updated set o master

records.

To do this requires a new, tight level o integration

between the internal data integration technology,

the external reerence data, and the data

governance capability. Such an approach results

in consistently better identication o entities

and linkages, enables superior use o the data

or targeting programs, and makes it possible to

introduce capabilities or immediately inorming the

business o any changes to key records, building ar

more agility and responsiveness into the business.

The ThIRD STeP:

TAKe The SIMPLeR APPROACh

I your approach has too many pieces, drains IT

resources, takes too long to implement, and pushes

out return on investment beyond the horizon, it will

be extremely dicult to und, especially in todays

uncertain economy. To get unding or a project

today, you must demand a simple, solutions-driven

approach based on the real-world business need

or the data.

At D&B, we believe that the simple approach

delivers more value aster. Thats why weve built

a pre-integrated layer between the reerence data

and the data integration technology that makes

implementation easy and can begin delivering value

within a matter o weeks. Interested? Visit us at

www.purisma.com.

The Need for Intelligent Data And How to Get It

Man critical compan initiatis, suc as top-100 customr programs, sgmntd markting and

dmand gnration, customr-princ optimization, and supplir portolio managmnt, rquir

intgratd, rsold, and optimizd data sourcs to nsur dcisions and actions ar basd on anaccurat pictur o t businss.


12/12

OveRCOMING COMPLex DATA ChALLeNGeS

The diculty in showing quick success is that

the data and necessary business rules/logic are

very complex. Typically, the integration o data

and ensuring its ftness or business use consume

50-70% o project time and budget. Identiying and

resolving entity inormation relating to customers

and products is based upon extensive reerence

data and knowledge bases that are not easily

replicated. The ability to understand hidden

inormation and relationships buried in data is a

daunting computational challenge.

In addition to correctly identiying inormation,

uzzy matching o inormation within or across

sources is a very complex and difcult task. Matching

dierent sources- or even matching within a source-

is made dicult by inexact representations o the

same thing or similar representations o dierent

things. Normal database joins cant overcome these

natural language variations. Having sophisticated

algorithms that overcome these problems, along

with other common errors like nicknames, alternate

rm names, dierent spellings, and data entry errors

is a key attribute o a reliable and extensible MDM

strategy.

Perormance and accuracy o matching algorithms

is paramount- missed matches or alse matches

create risk, miss potential value, and signicantly

reduce the trust o business data owners. Matching

is one o the hardest yet most critical attributes

in creating trusted master data. Thus matching

accuracy and capabilities should be a critical

evaluation and selection criteria.

FUNCTIONAL CAPABILITIeS

In addition to entity identication and uzzy

matching, there are a number o other key unctions

that create greater business value with master

data. Providing a single integrated platorm that

oers a graphical interace and out o the box best

practice project accelerators dramatically increases

sta productivity and ROI. Oering an interace that

supports the eorts o both business users (who

have unmatched domain expertise) and technical

users (who understand technology capabilities and

limitations) accelerates eorts toward inormation

sharing and collaboration.

Oering these sophisticated yet easily used

capabilities in a very high perormance platorm

ensures that current or uture data volumes will not

overwhelm your MDM system. Technology that can

be deployed in batch mode or initial master data

build and then urther deployed as a common

data service or universal access, extends value.

Accommodating customer inormation whether

B2B or B2C, as well as product inormation is

very useul. Properly handling address inormation

or correct billing or marketing eorts, as well as

geospatial inormation or tasks like tax or risk

assignment, or nd closest applications, adds

urther value to corporate data.

ABOUT DATALeveR

With an 80%+ win rate in competitive bakeos,

and perormance up to 25X that o competitive

technology, DataLever is a leading provider o

business value ocused MDM technology.

Companies with large data volumes and/or

complex business rules like AAA, AIG, Acxiom,

Equiax, Experian, the US Department o Veterans

Aairs, and Time Warner Cable rely on DataLever.

We provide a ree data test/POC to show how

quickly the most accurate view o your data can

drive your success.

[email protected]

Quick Win Lasting Success

Wil MDM is iwd as a critical businss imprati, proiding sort trm businss alu is

somting tat as bn difcult to nonistnt. Gtting accurat, trustwort data ncssar to

dri ig qualit dcisions and campaigns is complling to businss sponsors. Dmonstrating tat

ig qualit intgratd inormation can b dlird in das rom disparat, otn duplicatd data

dos wondrs in nancing businss sponsor bu-in. Tis is spciall tru in todas businss

climat, wr t abilit and dsir to start a multi-million dollar, multi-ar ort witout a k

businss drir is traordinaril difcult. Sowing arl dlir o ig qualit, ig impact data

is k to winning businss support.

A S l P d d b S M d C M d S l

MDM Best Practices

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