What is ERP Master Data Management? Types & List (2023)

For ensuring the quality of your ERP system, master data management is a crucial process. ERP Master data describes the basic information about your business processes and entities and is essential for accurate reporting and analysis. This blog post will discuss what master data ERP is, why it is important, and how to manage it effectively. In addition, we’ll examine how to build a successful ERP master data management plan.

ERP Master Data Management
Master data in ERP

What is ERP Master Data Management?

ERP Master Data Management are software packages that include several modules: finance, sales and distribution, materials management, manufacturing and production control, human resources, plant maintenance, and quality management. An ERP system’s main feature is that all its components are integrated. Due to the integrated nature of the operation, a few master tables are frequently referenced throughout the system and databases by numerous applications, functional areas, and locations. The quality of data entered into master tables is an essential element in the success or failure of an ERP system.

ERP Master Data is the practice of centrally managing key enterprise data assets common to multiple business units or processes. The goal of MDR is to ensure that consistent and accurate data is available throughout the enterprise to support mission-critical business functions.

ERP Systems & Master Data Management

ERP Master Data Management systems’ functionality is continuously expanding and becoming more sophisticated. However, ERP solutions – there are differences from manufacturer to manufacturer – frequently only map the essential tools for master data management basics. This may be observed in the case of finding duplicates. If an ERP data management system’s search function only allows for exact phrases, master data records with variant spellings or in distinct formats are frequently missed. Furthermore, this increases the chance of duplicate records being generated. Furthermore, many ERP systems may miss the fine details regarding data access authorizations and tracing. However, such features and more can be included in a company-wide master data management solution.

Collection and managing ERP Master Data

Organizations collect and manage ERP Master Data in different ways. Some companies develop in-house tools to supplement their ERP systems, while others purchase or lease third-party software applications. Still, other organizations outsource all or part of their Master Data Management processes and data maintenance activities. No matter which routes an organization takes, it must have a plan for collecting, managing, and maintaining its ERP data management.

Standard benefits:

  • ERP data management is essential for accurate reporting and analysis.
  • The Master data describes the basic information about your business processes and entities.
  • Master data management is a critical process for ensuring the quality of your ERP system.
  • Master data management framework & process.
  • Best practices for ERP master data management strategy.

Types of ERP Master Data

ERP Master Data can be classified into six types:

1. Operational data:

This type of data is required for the day-to-day operations of an organization. It includes customer names, addresses, product descriptions, and financial transaction records.

2. Reference data:

This type of data supports operational data. It includes information such as codes and definitions used to classify operational data. For example, reference data may include a list of customer types or product categories.

3. Business Partner Master Data:

The customer profile is divided into eight segments: customer, delivery, shipment, invoicing (to the customer), payment method (customer), the parent company of the client, and country location. The supplier role is filled in the first part of the URL, which begins with “supplier.” The following parts are marked as optional and contain the information needed by buyers.

4. Item Base Data:

This ERP data management contains the following attributes: Item category group, unit of measure, number range intervals for sales document type, storage location, gross weight, and net weight.

5. Financial Master Data:

  • Attributes in this Master Data include:
  • General ledger account.
  • Customer/vendor account group.
  • Tolerances for customer/vendor line items.
  • Payment terms.

Related article: What is Financial Master Data? How to Manage it?

6. Employee base data:

Some attributes in this Master Data include employee group, country grouping for payroll area, personnel area/subarea, and wage type structure.

What problem does ERP Master Data solve?

ERP Master Data Management systems provide a single, centralized repository for all of an organization’s critical data. This data can support multiple business processes, including financial reporting, customer relationship management, and supply chain management.

An ERP Master Data Management system can help organizations solve many different problems, such as:

  • Ensuring the accuracy of data across multiple business processes
  • Reducing the amount of time needed to complete manual tasks
  • Improving decision-making by providing easy access to timely and accurate information

Why ERP master data management is important

ERP Master Data Management systems are critical for the success of any organization that relies on an ERP system to run its business. Without a system to manage your master data, you risk inaccurate reporting, decreased productivity, and lost opportunities.

ERP Master Data Management is critical because it allows businesses to certify the accuracy of their information, enhance efficiency, and make better judgments. Aside from assisting an organization in making sound decisions and answering crucial questions, master data management has many additional advantages. Here are a few:

  • Reduced errors and redundancies: Master data in ERP plays the role of backbone for this software system. When it’s not well managed, you’re likely to run into errors and redundancies that can cause a host of problems, from decreased productivity to financial losses.
  • Improved decision-making: Master data management can give you a clear picture of what’s going on in your business at any given time. This allows you to better choose where to spend money and how to improve operations, as a result of your knowledge.
  • Greater efficiency: Master data management can help you automate manual tasks and streamline workflows. This can free employees to focus on more productive tasks and help you save time and money.
  • Enhanced customer service: Master data management can help you better understand your customers and provide them with the personalized service they crave.
  • Improved compliance: Master data management can help ensure that your business complies with regulations. This can protect you from costly fines and penalties.

ERP master data management framework & process

All data is correct and semantically consistent thanks to a master data management framework. The first part is generating a basic master data record, which you must afterward update.

Creating a master data record:

You’ll need to gather data from various sources, including ERP systems, CRM systems, and manual processes. Once you have this data, you’ll need to clean it up and standardize it. This will help ensure that your master data is accurate and consistent.

Maintaining a master data record:

Once you’ve created a master data record, you’ll need to keep it up-to-date. This can be done by regularly reviewing and updating your records. You should also consider implementing a process for managing changes to your master data.

Best practices for ERP master data management strategy

Modern master data management includes tools, techniques, and best practices to ensure that all involved parties can trust the quality of data-driven insights as well as their speed of action.

There are a few best practices that organizations should follow when implementing an ERP Master Data Management system:

  • Create a data governance framework: This will help you ensure that your data is accurate and consistent.
  • Implement a data quality management process: This will help you identify and fix errors in your data.
  • Develop a data strategy: This will help you determine which data is important to your business and how to best manage it.
  • Harness AI and ML: These technologies can help you automate tasks and improve the quality of your data. Some ERP MDM solutions and tools offer these capabilities to automate the process of validating new data for accuracy, matching it with current records, and reconciling them.
  • Manage multiple domains in one instance: Master data can be divided into different domains, such as customer data, product data, and supplier data. It’s important to manage these domains in one instance to ensure consistency across your data.
  • Manage master data in the cloud: Data from various applications may be brought together, matched, combined, and cleaned effectively, easily, and at scale thanks to cloud platforms. They also include advanced security and automatic updates.
  • Ensure that your company’s data is well managed: It’s easier to enforce rules and compliance, define, validate, and monitor business rules and master data attributes, thanks to a single source of master data with centralized data governance in one solution.

It’s a never-ending process, not a one-time project. As your company expands, so will the amount of data it creates. However, these MDM procedures become far more efficient with cloud-based intelligent technology, tools, and workflows.


ERP Master Data Management (MDM) is a process of gathering, cleaning, and maintaining data from multiple sources. Having an accurate and up-to-date master data record is important to make well-informed decisions about your business.

An ERP MDM system can help you save time and money by automating tasks and improving the quality of your data. To get the most out of your ERP MDM system, follow these best practices: create a data governance framework, implement a data quality management process, develop a data strategy, harness AI and machine learning, manage multiple domains in one instance, manage master data in the cloud, and ensure that your company’s data is well managed. Mastering these best practices will help you keep your data clean, accurate, and consistent.

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