The Importance of Company-Wide Master Data Governance for SAP Users

Companies are processing ever increasing amounts of data from a wide variety of sources (keyword: Internet of Things). The most important type is master data, which contains basic information about customers, suppliers, employees and products. It forms the basis for the digitalization and automation of business processes. Used correctly, businesses can leverage data to better respond to customer requirements and changes in the market.

However, incorrect data can lead to wrong decisions and cause considerable damage. If personal data is not handled in a legally compliant manner, companies could even find themselves in legal difficulties.

This is why organizations today need a strategy for the correct management and processing of master data. Data governance provides the necessary framework for this. In this blog post, you will find an introduction to the topic and learn why no company can afford to do without data governance in times of digital transformation.

What Is Data Governance?

Data governance is the comprehensive handling and management of all data processed in a company. It consists of guidelines and procedures that guarantee the quality, protection and security of data. Furthermore, it is intended to ensure that legal requirements are always met.

However, data governance is not a one-off project that can be implemented and ticked off your to-do list. Rather, it is a continuous process. Depending on the size of the organization,   individual people, often called Data Governance Officers or Chief Data Officers or even entire departments are responsible for overseeing the data governance.

What Does Data Governance Seek to Achieve in Companies?

Core tasks of data governance

The primary goal of data governance is to maintain and further enrich internal company knowledge. In addition, the following should be achieved:

  • Data quality: All data should always be up to date, complete and readily available.
  • Data maintenance: Data must be enriched and corrected if necessary.
  • Data protection: Confidential personal data must be protected against unlawful use.
  • Data security: Unauthorized access, reading or deletion of data must be prevented.
  • Data compliance: Companies must comply with legal requirements as well as internal company and industry standards.

Many companies work with ERP applications that already meet some of these objectives. For example, SAP canregulate who has access to specific master data, preventing unauthorized access. However, SAP’s standard product does not offer a complete solution for data governance.

Why You Can’t Afford to Do Without Data Governance

In times of digital transformation, correct master data is essential to ensure that companies maintain their agility and ability to react to changing circumstances. These four reasons underscore the importance of data governance.

1. Avoid errors and follow-up costs

We would like to explain the damage that unclean data can cause using the example of material master data. It forms the basis for many essential processes in production and logistics.

To create material master data records correctly in SAP, up to 600 fields must be filled in. Creating and maintaining these data records involves numerous departments and even external stakeholders such as customers and suppliers. Coordinating all the parties involved poses a genuine challenge.

Without a transparent process for creating and maintaining master data, most errors remain undetected, which can lead to serious consequences. For example, if the wrong material is ordered, completion dates can be delayed. This can cause significant economic damage for organizations.

2. Serves as the basis for the successful digitalization of business processes

Our long-standing experience has taught us that poorly maintained data is one of the main reasons why digitalization projects fail. Many companies have invested in ERP systems such as SAP in order to drive the digitalization of their processes. However, SAP can only be fully effective if clean master data is available.

The next step in the digitalization process is the use of analytics and artificial intelligence. These tools also require clean master data in order to make accurate predictions. In the worst case, incorrect data can become the basis for wrong decisions.

3. Work in a legally compliant and secure manner

Special attention should be paid to personal data, such as customer and employee master data. The General Data Protection Regulation (GDPR), which lays down the principles for processing personal data, applies within the European Union. Companies must prove compliance with this regulation. If these principles are not implemented in a legally compliant manner, companies can expect penalties of up to 4% of the total annual turnover generated worldwide.

4. Data volumes and complexity set to increase

The growing connectivity of devices in the Internet of Things provides a continuous stream of data that must be processed in the shortest time possible. Estimates suggest that a whopping 175 zettabytes of data will be available worldwide by 2025, which will only add to the complexity of data management.

Greater connectivity and complexity also means that even minor errors in master data can trigger unexpected chain reactions. Incorrect data therefore poses an even greater risk for companies.

The First Steps to Data Governance in a Company

The first challenge is to properly embed data governance into the corporate structure. It must be clear that master data management is not purely an IT task. All departments that work with data are involved. Then, you can follow these three steps.

1. Begin with one area

Depending on the size of the business, implementing a company-wide data governance project can be a mammoth task, especially when there are countless types of data and stakeholders that need to be involved. So where should you start?

We recommend beginning with an area where optimization can have a great impact. For many companies, this is material master data. Once you have gained some initial experience, it will be easier to transfer the data governance standards to other areas.

2. Determine the current status

To begin with, the status quo of data management in the company must be mapped. You should ask questions like: Who is the owner of the master data? Who manages the master data? And who has access rights? When it comes to material master data, the process of creating and maintaining data records must be examined with particular care.

3. Establish data governance processes

The next step is to define processes that describe how your data should be backed up, protected, stored and archived. This includes guidelines on how certain data may be used and which persons or departments are authorized to perform which actions. Furthermore, control processes are required to ensure the continuous monitoring of compliance and adherence to legal requirements.

Digital Solutions Facilitate Data Governance

Master data management is extremely complex, especially in SAP environments, and doesn’t just present a challenge for occasional users. Until now, SAP has not offered a simple, standardized data governance process. However, there are specialized software solutions, such as EASY Master Data Management for SAP, that can assume this role instead.

They ensure transparent processes and enhanced data quality. With an easy-to-use interface, they reduce the administrative workload while automated processes minimize data maintenance work for employees.

Would you like to find out more? Our white paper covers all you need to know about the challenges of materials management and how you can use digital tools to eliminate the biggest stumbling blocks. Download it here.


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