How to Get Started with Master Data Management? 9 steps

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By: Sagar Sharma

How to Get Started with Master Data Management? 9 Steps to Consider

Every organization is looking forward to adopting a reliable Master Data Management solution for the centralized storage and management of critical business information.

As the MDM enables stakeholders with a consolidated view of all the data belong from different business entities, they can make the right business decision at the right time. Well, Master Data Management enables brands with several other benefits from a customer point of view and advantages from the operational point of view.

If we consider the current MDM market, then it continues to gain momentum as more and more companies have started understanding the importance of MDM in an increasingly complex and chaotic enterprise information landscape.

Entrepreneurs and IT professionals face many challenges during the adoption and implementation of the MDM solution. But, most of them fail in addressing the issues effectively as they are not able to figure out the right combination of technology and organizational change. Apart from that, you might have other concerns like

  • How to approach MDM?
  • How to select the right tools? (Selection of the MDM tools that address your business requirements and manage your huge enterprise data)
  • Where to start? (Once you select an MDM solution, this is a very obvious question)
  • How you can update you’re your MDM solution? (You need to avail a maintenance process to keep updated your software with the latest features and functionality)

In this post, we will guide you on how you can get started with the Master Data Management by following 9 simple steps.

So, are you ready for the ride? Let’s begin the journey.

9 Steps for Getting Started with Master Data Management

Step 1: Gain Knowledge

Before the implementation of MDM, you need to educate yourself about the basic fundamentals and concepts of the technology. Master Data Management is considered as a relatively new platform, it is one of the rapidly maturing technologies.

By hiring skilled professionals, you can definitely avoid this step. But, if you really want to dig deep into MDM, we suggest you get a better understanding of the following concepts:

Important functionality

Functional Capabilities

  • Data Modeling
  • Data Integration
  • Web services
  • Data quality
  • Business rules
  • Workflow
  • Matching
  • Survivorship
  • Stewardship

Non-functional capabilities

  • High-availability
  • Scalability

Implementing Master Data Management styles

  • Centralized
  • Registry
  • Consolidated
  • Co-existence

MDM domain categories

  • Organizations (customers, vendors, partners, etc.)
  • People (customers, employees, patients, etc.)
  • Things (products, parts, locations, assets, etc.)

Domain-specific needs of master data

All domains do not require MDM solutions that have the same features and functionality. Based on the industry type the configurations of the software get changed. For example; industrial manufactures have different needs than the companies that distribute finished products.

Step 2: Analyze your current data management approach

Every business has more or less data to manage. They manage the data using different systems, applications, or software. The most common data management approaches are:

Data Management in Excel

This is the most common and widely used approach for data management. Most of the small companies prefer to manage their business data in excel sheets. There a few excel based MDM solutions that allow for data management too.

This approach fails when it comes to meeting the increasingly complex business needs. But, it helps define a better solution by providing valuable insights about better master data management.

Managing data in ERP and CRM systems

Large scale organizations to mid sized businesses are using the ERP and CRM system to manage the massive data of vendors, products, customers, etc. These applications are really good for the organization but they cannot match the capabilities of the Master Data Management solution.

Considering an affordable MDM solution

The feature-rich MDM solutions are expensive and they fit into the big budget of large scale organizations. But there are a few platforms like Pimcore that allow small to mid-scale businesses to implement a custom MDM solution as per their specific business needs.

Thus, you need not invest in the features and functionality that are not useful to you. It directly reduces overhead costs for you and makes the solution affordable for your business.

Understand your existing data management efforts to identify the deficiencies in the process and get insights about business problems. Analysis of the gaps and problems helps you in revealing the opportunities for improvement in your existing MDM approach.

Step 3: Define your scopes

Integration of multiple enterprise systems

Organizations manage huge business data of different departments in various applications for every region and each domain. Your data could be available in structures or unstructured form across the multiple systems. To get a consolidated and reliable view of data, you need to define what master data you need to manage.

Consider your business strategy

Master Data Management helps organizations make data-driven strategic business decisions.

There are companies where the management of the organization makes a decision about the critical components of the MDM solution that support their core business strategy. They understand this initiative is very essential to keep everyone in line. Usually, these are large scale organizations that are ready to pay a good volume if they get a robust solution.

Another scenario is, you are an individual or small scale business owner who has a very specific usage of MDM and limited budget.

Surprisingly, most of the organizations fall into anywhere between these two extreme scenarios based on their strategy and budget.

Create an outline about MDM support

As your business grows, you need to scale your MDM solution. You need to invest in the technical support to stay updated with the latest MDM trends and business needs.

Thus, along with investing in a solution, it is very essential for you to invest in building support for it, developing advanced data governance functionality, and organizing the number of complex business process changes.

Step 4: Define a business case for MDM

Most of the organizations take the initiative of Implementing Master Data Management but later on after a year or two they stop investing in it. The reason for this abandonment is budgetary constraints.

Here you want to be pretty clear that Master Data Management is not a project that you can complete in a couple of years. To get the positive results from your initiatives, you need to make sure ongoing and long term investment in MDM.

Instead of focusing on expenses, you need to consider the business benefits you can get from MDM. It helps you with the different business cases such as improve consistency and quality of product data, create a single view of customers, or facilitate the consolidation of different legacy systems into a new ERP application.

When you connect MDM with our business cases you can get better clarity on how it delivers value to your business and helps in cost-saving, revenue generation, and achieving the business objectives.

Step 5: Determine stakeholders of Master Data Management

Identify the people

Once you identify your business case for Implementing Master Data Management, you need to make your investment worth by defining the people across your organization who can take the benefit of MDM.

Operation Department

In most organizations, the operation department is highly affected by the MDM solution as it manages the maximum data related to products and customers. Communicate the benefits of Master Data Management to other stakeholders belong to different departments who will be investing their time and efforts in adopting the MDM.

Sales and Marketing Departments

MDM helps your sales and marketing team by providing them profound insight into customer information, their buying journey, high valued products, and more. It helps them to understand the market trends and accordingly sell and promote the products or services. This directly impacts your conversion rate due to more specific efforts.

Train your staff

Educate your users about the concept of MDM and convey the benefits of the platform to them. The more users you have to use the solution, the more work you need to do to establish seamless communication and coordination between all stakeholders.

Step 6: Execute strong data governance policies

Data governance is all about defining what needs to be done. If you start practicing MDM without determining what needs to be done, there are higher probabilities you will be working on the wrong things. Even if, you are working in the right direction, there are higher chances that the stakeholders will reject your efforts and also deny participating in MDM practices.

How to start with data governance?

When you conduct your first governance council meeting, make sure you are not going to define what a customer or product is and design a process. During this meeting, you need to focus on defining the roles, responsibilities, governance standards, and broad policies.

Later on, the council needs to manage priorities, identify topics, and allocate the highest priority topics to working groups or virtual teams for execution.

During the initial phase of the MDM, the virtual team focuses on data model definition, data process design, and source system analysis. Once the MDM program grows across your organization, you need to pay attention to other topics such as metrics, KPIs, and data quality rules.

Flexible data governance model

There is no one-size-fit-for-all model when it comes to the governance model. Organizations can design and implement the custom model as per their specific needs.

If you own a small business with a team of few people, you need to scale your governance function accordingly. In such a case, you need to go with a multifaceted governance council having various virtual teams. If you have a single stakeholder for MDM, then you can define a governance council consequently.

Step 7: Design a Master Data Management charter

How to start with a charter with MDM deliverables?

If you are conducting the first governance council meeting, you might be unsure how to do it. You need to start by defining the goals for the first MDM charter. You can set expectations by creating a draft about the goals you want to achieve through the MDM program. You need to define and communicate the deliverables to set the tone of the meeting.

How to execute the charter?

If your governance council meeting has multiple members who are performing different operations, then you need to define a more formal and detailed charter. If you only one stakeholder in the meeting, then the charter will be relatively less formal and short.

What are the key elements of an MDM charter?


Getting an overview of MDM and data governance that involves the scale and scope of the stakeholders’ efforts as per the industry and business domains.

Data governance vision/mission/goals/purposes/principles:

Defining the goals that you aim to achieve by determining data governance policies.

Governance membership/structure/roles/responsibilities:

Creating a structure of your governance organization, define roles within the structure, identify the participating members, and map roles of the respective participants with data access.

Meeting Logistics:

Defining meeting locations, attendance, frequency, and other general logistics.


Deciding the platforms (website, email, Wikipedia, etc.) that communicate the governance outcomes to the members and other interested stakeholders.


Creating an outline of the process to collect, prioritize, assigned, and resolve topics in the data governance backlog.


Creating the list of common terms used in the context of data governance and MDM.

Step 8: Select & implement your Master Data Management Platform

You might have a question, why I am considering this step so later. Well, you can choose the MDM tools earlier in this process but there are chances you end up by purchasing and implementing a premature platform that allows you to get started with shortcut planning. Here you might fail in getting the expected results.

When you spend significant time on the above-listed steps and get clarity about them, adoption and implementation of the technology platform to ensure ultimate success. You get a better understanding of your business-specific goals and needs. Eventually, it helps you in selecting the best MDM solution that effectively manages your massive business information.

Step 9: Keep measuring your success on an ongoing basis

This is the last step where you have almost everything in place including business case, funding, the right stakeholders, MDM solution, as well as a growing and active data stewardship community. Once the stakeholders start using the solution, you need to analyze the performance of the MDM solution, employee productivity, and business results.

Once the first phase of the solution is over, you need to measure how the results support the actual business case that you have defined earlier during this process. Make sure it delivers value that you have anticipated while defining the process and implementing the solution.

MDM requires ongoing funding and you need to justify your decision about investing in MDM. If you fail in doing so and the investors will not see any value, you may lose your MDM setup. Thus, it is very essential to measure and communicate MDM performance against its KPIs proactively.

This not only secures your funding but also allows you to shift your enterprise information to a complex and chaotic world of digital data.

Closing Lines

Credencys utilizes Pimcore MDM capabilities to develop and implement the robust custom Master Data Management solution that addresses your specific business needs. We offer a complete range of Pimcore development services start from consultation to design to development to deployment to support & maintenance.

We follow the latest MDM practices to enable businesses with trending MDM solutions. Out experienced Pimcore developers have built MDM solutions for different industry and business types by understanding their objectives and challenges.

Would you like to have a mature MDM solution to manage massive information of your different departments and stakeholders in a well structured and logical way? Talk to our experts for consultation.

Frequently Asked Questions about Master Data Management

What are Master Data Management benefits?

Master Data Management enables a business with a complete, consolidated, and structured view of its massive business data. The key MDM benefits to business are

  • Provides seamless information across all channels
  • Provides a unified master view
  • Helps to better understand the customers
  • Increase trust and accountability of your business data
  • Connects anything and everything

How to create the best Master Data Management strategy?

To create an intelligent master data management strategy for your business, you need to follow five steps as listed below:

  • Assess your business goals
  • Evaluate MDM enabling technologies
  • Maintain architectural consistency
  • Bring the right stakeholders on board
  • Use what worked in the past

What are the latest Master Data Management trends?

You need to consider top MDM trends to create potential and game-changing opportunities for your organizations. The latest MDM trends are:

  • MDM integration with workflows and business processes
  • More industries will adopt master data management
  • AI and Machine Learning in MDM
  • Customized data security solutions to overcome data quality issues
  • Cloud-based MDM deployment will rise

Does Master Data Management help in managing multi-domain data?

Yes, all the MDM platforms allow you to manage your multi-domains data. As we have extensively worked with Pimcore MDM, we utilized its scalable architecture and advanced features like Data quality/semantic, hierarchy management, rich content integration, audit trial, superior connectivity, and workflow management for multi-domain data management.


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