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Develop a Master Data Management Practice and Platform

Are you sure you have a master data problem?

  • The volume of enterprise data is growing rapidly and comes from a wide variety of internal and external data sources (e.g. ERP, CRM). When data is located in different systems and applications, coupled with degradation and proliferation, this can lead to inaccurate, inconsistent, and redundant data being shared across departments within an organization.
  • Data kept in separate soiled sources can result in poor stakeholder decision making and inefficient business processes. Some common master data problems include:
    • The lack of a clean customer list results in poor customer service.
    • Hindering good analytics and business predictions, such as incorrect supply chain decisions when having duplicate product and vendor data between plants.
    • Creating cross-group consolidated reports from inconsistent local data that require too much manual effort and resources.

Our Advice

Critical Insight

  • Everybody has master data (e.g. customer, product) but not master data problems (e.g. duplicate customers and products). MDM is complex in practice and requires investments in data governance, data architecture, and data strategy. Identifying business outcomes based on quality master data is essential before you pull the trigger on an MDM solution.

Impact and Result

This blueprint can help you:

  • Build a list of business-aligned data initiatives and capabilities that address master data problem and realize business strategic objectives.
  • Design a master data management practice based on the required business and data process.
  • Design a master data management platform based on MDM implementation style and prioritized technical capabilities.

Develop a Master Data Management Practice and Platform Research & Tools

1. Develop a Master Data Management Practice and Platform Deck – A clear blueprint that provides a step-by-step approach to aid in the development of your MDM practice and platform.

This blueprint will help you achieve a single view of your most important data assets by following our two-phase methodology:

  • Build a vision for MDM
  • Build an MDM practice and platform

2. Master Data Management Readiness Assessment Tool – A tool to help you make the decision to stop the MDM project now or to continue the path to MDM.

This tool will help you determine if your organization has a master data problem and if an MDM project should be undertaken.

3. Master Data Management Business Needs Assessment Tool – A tool to help you identify and document the various data sources in the organization and determine which data should be classified as master data.

The tool will help you identify the sources of data within the business unit and use the typical properties of master data to determine which data should be classified as master data.

4. Master Data Management Business Case Presentation Template – A template to communicate MDM basics, benefits, and approaches to obtain business buy-in for the MDM project.

The template will help you communicate your organization's specific pains surrounding poor management of master data and identify and communicate the benefits of effective MDM. Communicate Info-Tech's approach for creating an effective MDM practice and platform.

5. Master Data Management Project Charter Template – A template to centralize the critical information regarding to objectives, staffing, timeline, and expected outcome of the project.

The project charter will help you document the project sponsor of the project. Identify purpose, goals, and objectives. Identify the project risks. Build a cross-functional project team and assign responsibilities. Define project team expectations and meeting frequency. Develop a timeline for the project with key milestones. Identify metrics for tracking success. Receive approval for the project.

6. Master Data Management Architecture Design Template – An architecture design template to effectively document the movement of data aligned with the business process across the organization.

This template will assist you:

  • Document the current state and achieve a common understanding of the business process and movement of data across the company.
  • Identify the source of master data and what other systems will contribute to the MDM system.
  • Document the target architectural state of the organization.

7. Master Data Management Practice Pattern Template – Pre-built practice patterns to effectively define the key services and outputs that must be delivered by establishing core capabilities, accountabilities, roles, and governance for the practice.

The master data management practice pattern describes the core capabilities, accountabilities, processes, essential roles, and the elements that provide oversight or governance of the practice, all of which are required to deliver on high value services and deliverables or output for the organization.

8. Master Data Management Platform Template – A pre-built platform template to illustrate the organization’s data environment with MDM and the value MDM brings to the organization.

This template will assist you:

  • Establish an understanding of where MDM fits in an organization’s overall data environment.
  • Determine the technical capabilities that is required based on organization’s data needs for your MDM implementation.

Member Testimonials

After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve. See our top member experiences for this blueprint and what our clients have to say.

8.5/10


Overall Impact

$4,000


Average $ Saved

5


Average Days Saved

Client

Experience

Impact

$ Saved

Days Saved

Atlantic Packaging Products Ltd.

Guided Implementation

8/10

N/A

N/A

A lot of useful information and need to go through recording again. Difficult to measure the impact on time and scheduled right now.

Nozom Alkhebrat IT Co.

Guided Implementation

9/10

$4,000

5


Develop a Master Data Management Practice and Platform

Are you sure you have a master data problem?

Analyst Perspective

The most crucial and shared data assets inside the firm must serve as the foundation for the data maturing process. This is commonly linked to your master data (such as customers, products, employees, and locations). Every organization has master data, but not every organization has a master data problem.

Don't waste time or resources before determining the source of your master data problem. Master data issues are rooted in the business practices of your organization (such as mergers and acquisitions and federated multi-geographic operations). To address this issue, you will require a master data management (MDM) solution and the necessary architecture, governance, and support from very senior champions to ensure the long-term success of your MDM initiative. Approaching MDM with a clear blueprint that provides a step-by-step approach will aid in the development of your MDM practice and platform.

Ruyi Sun

Ruyi Sun
Research Specialist
Data & Analytics Practice
Info-Tech Research Group

Rajesh Parab

Rajesh Parab
Research Director
Data & Analytics Practice
Info-Tech Research Group

Executive Summary

Your Challenge

Common Obstacles

Info-Tech’s Approach

Your organization is experiencing data challenges, including:

  • Too much data volume, variety, and velocity, from more and more sources.
  • Duplicate and disorganized data across multiple systems and applications.
  • Master data is pervasive throughout the business and is often created and captured in highly disparate sources that often are not easily shared across business units and applications.

MDM is useful in situations such as a business undergoing a merger or acquisition, where a unique set of master data needs to be created to act as a single source of truth. However, having a unified view of the definitions and systems of record for the most critical data in your organization can be difficult to achieve. An organization might experience some pain points:

  • Failure to identify master data problem and organization’s data needs.
  • Conflicting viewpoints and definitions of data assets across business units.
  • Recognize common business operating models or strategies with master data problems.
  • Identify the organization’s problem and needs out of its master data and align to strategic business needs.
  • Define the architecture, governance, and support.
  • Create a practice and platform for the organization’s MDM program.

Info-Tech Insight

Everybody has master data (e.g. customer, product) but not a master data problem (e.g. duplicate customers and products). MDM is complex in practice and requires investments in data governance, data architecture, and data strategy. Identifying business outcomes based on quality master data is essential before you pull the trigger on an MDM solution.

What is master data and master data management?

  • Master data domains include the most important data assets of an organization. For this data to be used across an enterprise in consistent and value-added ways, the data must be properly managed. Some common master data entities include customer, product, and employees.
  • Master data management (MDM) is the control over master data values to enable consistent, shared, contextual use across systems, of the most accurate, timely, and relevant version of truth about essential business entities (DAMA DMBOK).
  • The fundamental objective of MDM is to enable the business to see one view of critical data elements across the organization.
  • MDM systems will detect and declare relationships between data, resolve duplicate records, and make data available to the people, processes, and applications that need it. The end goal of an MDM implementation is to make sure your investment in MDM technology delivers the promised business results. By supplementing the technology with rules, guidelines, and standards around enterprise data you will ensure data continues to be synchronized across data sources on an ongoing basis.

The image contains a screenshot of Info-Tech's Data Management Framework.

Info-Tech’s Data Management Framework Adapted from DAMA-DMBOK and Advanced Knowledge Innovations Global Solutions. See Create a Data Management Roadmap blueprint for more information.

Why manage master data?

Master data drives practical insights that arise from key aspects of the business.

Customer Intimacy

Innovation Leadership

Risk Management

Operational Excellence

Improve marketing and the customer experience by using the right data from the system of record to analyze complete customer views of transactions, sentiments, and interactions.

Gain insights on your products, services, usage trends, industry directions, and competitor results, and use these data artifacts to support decisions on innovations, new products, services, and pricing.

Maintain more transparent and accurate records and ensure that appropriate rules are followed to support audit, compliance, regulatory, and legal requirements. Monitor data usage to avoid fraud.

Make sure the right solution is delivered rapidly and consistently to the right parties for the right price and cost structure. Automate processes by using the right data to drive process improvements.

85% of customers expect consistent interactions across departments (Salesforce, 2022).

Top-decile economic performers are 20% more likely to have a common source of data that serves as the single source of truth across the organization compared to their peers (McKinsey & Company, 2021).

Only 6% of board members believe they are effective in managing risk (McKinsey & Company, 2018).

32% of sales and marketing teams consider data inconsistency across platforms as their biggest challenge (Dun & Bradstreet, 2022).

Your Challenge

Modern organizations have unprecedented data challenges.

  • The volume of enterprise data is growing rapidly and comes from a wide variety of internal and external data sources (e.g. ERP, CRM). When data is located in different systems and applications, coupled with degradation and proliferation, this can lead to inaccurate, inconsistent, and redundant data being shared across departments within an organization.
  • For example, customer information may not be identical in the customer service system, shipping system, and marketing management platform because of manual errors or different name usage (e.g. GE or General Electric) when input by different business units.
  • Data kept in separate soiled sources can also result in poor stakeholder decision making and inefficient business processes. Some issues include:
    • The lack of clean customer list results in poor customer service.
    • Hindering good analytics and business predictions, such as incorrect supply chain decision when having duplicate product and vendor data between plants.
    • Creating cross-group consolidated reports from duplicate and inconsistent local data requires too much manual effort and resources.

On average, 25 different data sources are used for generating customer insights and engagement.

On average, 16 different technology applications are used to leverage customer data.

Source: Deloitte Digital, 2020

Common Obstacles

Finding a single source of truth throughout the organization can be difficult.

Changes in business process often come with challenges for CIOs and IT leaders. From an IT perspective, there are several common business operating models that can result in multiple sets of master data being created and held in various locations. Some examples could be:

  • Integrate systems following corporate mergers and acquisitions
  • Enterprise with multi-product line
  • Multinational company or multi-geographic operations with various ERP systems
  • Digital transformation projects such as omnichannel

In such situations, implementing an MDM solution helps achieve harmonization and synchronization of master data and provide a single, reliable, and precise view of the organization. However, MDM is a complex system that requires more than just a technical solution. An organization might experience the following pain points:

  • Failure to identify master data problem and organization’s data needs.
  • Conflicting viewpoints and definitions of data assets that should reside in MDM across business units.

Building a successful MDM initiative can be a large undertaking that takes some preparation before starting. Understanding the fundamental roles that data governance, data architecture, and data strategy play in MDM is essential before the implementation.

“Only 3 in 10 of respondents are completely confident in their company's ability to deliver a consistent omnichannel experience.”

Source: Dun & Bradstreet, 2022

The image contains an Info-Tech Thought Model of the Develop a Master Data Management Practice & Platform.

Insight summary

Overarching insight

Everybody has master data (e.g. customer, product) but not a master data problem (e.g. duplicate customers and products). MDM is complex in practice and requires investments in data governance, data architecture, and data strategy. Figuring out what the organization needs out of its master data is essential before you pull the trigger on an MDM solution.

Phase 1 insight

A master data management solution will assist you in solving master data challenges if your organization is large or complex, such as a multinational corporation or a company with multiple product lines, with frequent mergers and acquisitions, or adopting a digital transformation strategy such as omnichannel.

Organizations often have trouble getting started because of the difficulty of agreeing on the definition of master data within the enterprise. Reference data is an easy place to find that common ground.

While the organization may have data that fits into more than one master data domain, it does not necessarily need to be mastered. Determine what master data entities your organization needs.

Although it is easy to get distracted by the technical aspects of the MDM project – such as extraction and consolidation rules – the true goal of MDM is to make sure that the consumers of master data (such as business units, sales) have access to consistent, relevant, and trusted shared data.

Phase 2 insight

An organization with activities such as mergers and acquisitions or multi-ERP systems poses a significant master data challenge. Prioritize your master data practice based on your organization’s ability to locate and maintain a single source of master data.

Leverage modern capabilities such as artificial intelligence or machine learning to support large and complex MDM deployments.

Blueprint Overview

1. Build a Vision for MDM

2. Build an MDM Practice and Platform

Phase Steps

  1. Assess Your Master Data Problem
  2. Identify Your Master Data Domains
  3. Create a Strategic Vision
  1. Document Your Organization’s Current Data State
  2. Document Your Organization’s Target Data State
  3. Formulate an Actionable MDM Practice and Platform

Phase Participants

CIO, CDO, or IT Executive

Head of the Information Management Practice

Business Domain Representatives

Enterprise Architecture Domain Architects

Information Management MDM Experts

Data Stewards or Data Owners

Phase Outcomes

This step identifies the essential concepts around MDM, including its definitions, your readiness, and prioritized master data domains. This will ensure the MDM initiatives are aligned to business goals and objectives.

To begin addressing the MDM project, you must understand your current and target data state in terms of data architecture and data governance surrounding your MDM strategy. With all these considerations in mind, design your organizational MDM practice and platform.

Are you sure you have a master data problem?

About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.

MEMBER RATING

8.5/10
Overall Impact

$4,000
Average $ Saved

5
Average Days Saved

After each Info-Tech experience, we ask our members to quantify the real-time savings, monetary impact, and project improvements our research helped them achieve.

Read what our members are saying

What Is a Blueprint?

A blueprint is designed to be a roadmap, containing a methodology and the tools and templates you need to solve your IT problems.

Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

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Get the help you need in this 2-phase advisory process. You'll receive 6 touchpoints with our researchers, all included in your membership.

Guided Implementation 1: Build a vision for MDM
  • Call 1: Identify what master data management means to the organization.
  • Call 2: Discuss the strategic plans of the business and establish a business context for master data management.
  • Call 3: Determine master data management strategies.

Guided Implementation 2: Create a plan and roadmap for the organization’s MDM program
  • Call 1: Discuss the results of the master data management capabilities evaluation.
  • Call 2: Plan initiatives for master data management.
  • Call 3: Create a roadmap and discuss next steps.

Authors

Ruyi Sun

Rajesh Parab

Contributors

Info-Tech Contributors:

  • Reddy Doddipalli
  • Igor Ikonnikov
  • Irina Sedenko
  • Anu Ganesh
  • Wayne Cain
  • Reddy Doddipalli
  • Imad Jawadi
  • Andy Neill
  • Steve Wills

External Contributors:

  • Selwyn Samuel, Director of Enterprise Architecture, Furniture manufacturer
  • Julie Hunt, Consultant and Author, Hub Designs Magazine and Julie Hunt Consulting
  • David Loshin, President, Knowledge Integrity Inc.
  • Three anonymous contributors
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