unveiling the business value of master data management the business value of mdm.pdf · :white...

:White Paper: Unveiling MDM Business Value 1

Unveiling the Business Value of Master Data ManagementMaster Data Management (MDM) is a response to the fact that—after a decade of enterprise application integration, enterprise information integration, and enterpriseData warehousing—most large organizations still struggle with redundant and inconsistent data from their corporate databases resulting in operational and reporting issues.

Jose M. TamChief ArchitectFebruary 2010

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Master Data Business Challenges For information and process driven business environments the ability to standardize core enterprise information is

of strategic importance. In most organizations, core information remains in data prisons, preventing a single,

integrated enterprise-wide view of data across applications.

Companies have numerous needs related to their corporate information that over the years have been losing

quality and increasing the complexity to manage it. Several questions arise when a Company needs to support its

business strategies with systems related to master files, such as: Customers, Product, Items, Employees, Cost

Centers and Chart of Accounts, etc:

1. What are systems of records for Customer, Product, and Item masters?

2. How can I access a single view of my customer records and use it to enrich my customer interactions?

3. How do we measure product and service profitability when my product definitions are not consistent?

4. How do I ensure that replicated sources are consistent with the system of record?

5. I have multiple implementations of the same application plus custom applications with their own data

models; how do I exchange data between different applications?

6. Why do we re-invent the wheel for product and customer data when we develop a new application?

Related to these questions about their Master Data NEORIS has found that companies have:

• Inconsistent and complex business rules for the same information

• Poor data quality in their master files as a result of multiple mergers and acquisitions where it has been

difficult consolidated information visibility

• Islands of isolation resulting from lack of organizational integration around Business Units, Geographies

and Functional Silos

• No enterprise-wide leadership ensuring the definition of efficient and effective processes and the

subsequent execution of those processes

• Poor integration between those who define information needs, those who provide the information, and

those who actually use the information

• Inability to effectively translate volumes of data into relevant information

• Lack of standards around data, decision-making, and global roles and responsibilities

• Lack of consistent information across transactional applications

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

• Data fragmentation originated by their growth (organic or by acquisition)


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Customer mandates, regulatory requirements for standards based master data synchronization with trading

partners

As a result, the business costs of inconsistent Master Data are:


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Master Data

“Master Data” is the information required to create and maintain an enterprise wide application, called also a “system of record” for your core business entities in order to capture business transactions and measure results for these entities.


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There are several drivers that can result from Master Data Management initiatives, such as:

• Disparate, uncoordinated enterprise systems

• Serving functional silo needs

• Cross functional inefficiencies

• Disconnected business decisions

• Need for composite processes and applications - SOA

• Competitive advantage – business driver identified

• Referential integrity critical

• Cross “silo” processes and analysis – Internal and External

• Need for complete, richer superset of information

• Expanded capabilities

• Bridge to modern solution sets

• Collaboration with trading partners

• Compliance


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What is Master Data Management?

IT Analysts as Gartner Group and Forrester Research have analyzed data quality and data management

challenges related to MDM, and their definitions are:

“MDM is a workflow-driven process in which business units and IT collaborate to harmonize, cleanse, publish and

protect common information assets that must be shared across the enterprise.” Gartner Group.

Forrester´s reference to MDM is that it operationalizes the acquisition, distribution, and management of core data

entities...

According to Alex Berson and Larry Dubov, MDM is the need to clean up the “old stuff” and create an accurate,

timely and complete set of data needed to manage and grow the business.1

Master Data Management is the framework of processes, applications, and technologies that are followed with

discipline to manage and harmonize the “system of record” and “system of entry” for the data and metadata

associated with the key business entities of an organization.


1 Master Data Management and Customer Data Integration for a Global Enterprise: Alex Berson, Larry Dubov. McGraw-Hill Osborne Media, (May 24, 2007), ISBN-13: 978-0072263497.

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Is MDM Mature?

Gartner group publishes their Hype Cycle curves and in their 2008 version, MDM was classified in the early

adoption stage where the technology has been triggered but it has not been even in the peak of inflated

expectations.

From this point of view, apparently the maturity of MDM is not yet recommendable, and only early adopters should

consider MDM.


visibility

time

Less than 2 years

Years to mantain adoption

as of september 2008

2 to 5 years 5 to 10 years more than 10 years obsolete before plateau

TechnologyTrigger

Peak ofInflated

Expectations

Trough ofDisillusionment

Slope of Enlightenment

Plateau ofProductivity

Enterprise Metadata Taxonomyand Ontology Management

Procurement-CentricMaster Data Management

Enterprise InformationManagement Programs

Master Data Managementof Asset Data

Master Data ManagementSuites

Information-Centric Infrastructures

Entity Resolution and Analysis

Analytical MDM

Multidomain MDM

Master Data Management of Product DataFormerly Product Information Management

Master Data Management for Customer Data

Global Data Synchronization

Data Quality Tools

Enterprise Asset Management

Master Data Governance

Source: White, A., et al. (2008). Hype Cycle for Master Data Management, 2008. Gartner Research

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However, if we see the different components involved in an MDM solution, all components have already passed

the peak of expectations. Integrating them in a framework helps us understand that MDM is more mature, despite

the role that MDM plays .


visibility

time

Less than 2 years

Years to mantain adoption

as of september 2008

2 to 5 years 5 to 10 years more than 10 years obsolete before plateau

TechnologyTrigger

Peak ofInflated

Expectations

Trough ofDisillusionment

Slope of Enlightenment

Plateau ofProductivity

Enterprise Metadata Taxonomyand Ontology Management

Procurement-CentricMaster Data Management

Enterprise InformationManagement Programs

Master Data Managementof Asset Data

Master Data ManagementSuites

Information-Centric Infrastructures

Entity Resolution and Analysis

Analytical MDM

Multidomain MDM

Master Data Management of Product DataFormerly Product Information Management

Master Data Management for Customer Data

Global Data Synchronization

Data Quality Tools

Enterprise Asset Management

Master Data Governance

Source: White, A., et al. (2008). Hype Cycle for Master Data Management, 2008. Gartner Research

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MDM Business Value

Master Data is the backbone of an enterprise information system. A well developed Master Data Management

plan in place allows an enterprise to operate and transact efficiently across channels and departments, with

reduced errors, provide consistent and accurate reporting based on a single version of the truth, make strategic

decisions based on well defined information (no second guesses), and enable a flexible and adaptable

operational structure that can respond to rapid changes.


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NEORIS can help you quickly setup a project structure and keep the momentum going, ensuring fast results. On

a high level, the approach proposed by Neoris follows of the following steps:

1. Understand MDM challenges and design an MDM roadmap and plan.

2. Identify Data Quality requirements, define a remediation plan.

3. Remediate Data Quality.

4. Identify MDM architecture and define synchronization, harmonization and management of MDM.

5. Define Data Governance to manage Master Data.


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