How to Optimize Your Company-Wide SAP Master Data Management

Correct SAP master data is a prerequisite for digital and automated business processes. Companies that display their business processes on the basis of ERP systems such as SAP should therefore not underestimate the effort that is needed to maintain their master data. Incorrect or outdated data causes problems when it comes to processing SAP applications – and in the worst case, can bring your business processes to a complete standstill.

Every company that displays its business processes in SAP should address the following questions:

• SAP master data workflow: Have you established a process whereby you regularly and ideally automatically check your master data for errors and duplicates?
• SAP master data governance: Are the responsibilities for master data maintenance clearly defined in your organization and do all the employees involved know what to do and when?
• SAP master data management best practices: Do you rely on established standards for your company-wide SAP master data management and thereby lay the foundation for the successful digitalization of your business processes?

In this blog post you’ll learn why you should think about your company-wide master data management (MDM) processes and how to optimize, streamline and accelerate your SAP MDM.

As the volume of data explodes, MDM has developed into one of the most exciting areas in the global IT market. We expect MDM solutions to generate annual growth rates of more than 15 percent and an annual sales volume of around 15 billion euros by 2026. This all confirms that master data management has reached the top of the IT agenda in many companies.

This is only to be expected, because data-driven business models in times of digitalization rely primarily on functioning master data management. The structured maintenance of master data relating to objects such as customers, products, financial transactions, suppliers and business partners is becoming the core task of companies. On the one hand, this is a logical consequence of the digital transformation that has occurred in almost every industry. On the other hand, optimizing SAP master data is a prerequisite for the digitalization of business processes.

Avoid High Costs Due to Incorrect Master Data

Effective master data management in companies has the task of providing business processes and SAP transactions with consistent and correct master data. The follow-up costs of having incorrect master data are enormous. This is because a great deal of effort is required to repair the SAP system once outdated or redundant data has flowed into it. This extra labor can be completely avoided with an MDM process that has been optimized from the outset.

Master data management in SAP is anything but a trivial matter. A material master data record in SAP MM alone contains up to 1,000 individual fields.

Incorrect master data has catastrophic consequences, particularly in logistics and production processes. Duplicates and unmaintained master data in SAP can lead to incorrect deliveries and material bottlenecks, which in turn can cause considerable disruptions to your business processes in materials management. Your employees must ultimately use manual workarounds to minimize the repercussions so that customer satisfaction is not threatened and follow-up costs are kept to a minimum.

Master data management in SAP is anything but a trivial matter. A material master data record in SAP MM alone contains up to 1,000 individual fields. Maintaining and continuously optimizing SAP master data thus requires the establishment of comprehensive SAP master data governance and the implementation of a predominantly automatic workflow.

From applying for new materials to optimizing SAP master data across plants, companies can reap the benefits of a structured four-step process. This process has proven its worth, especially for MDM tasks in logistics and production:

• Step 1 – Master data creation when requesting new materials: If an engineer needs a new material, they enter the basic master data directly into an SAP input screen tailored to their role. With the help of the SAP material master views, non-relevant fields are not even displayed, which helps to avoid errors when the material is being created. If required, additional documents and specifications can be attached to the request.
• Step 2 – Release into the master data center: A central department in your organization is responsible for checking and releasing newly created master data records in SAP. This SAP master data center receives new requests via an automated workflow – it checks this and, if necessary, returns it back to the applicant if the initial data record contains errors.
• Step 3 – Check for master data redundancies: SAP applications can be checked for duplicates with the help of digital add-on solutions. If there is suspected redundant master data, the solution will notify your SAP master data center of this. Your employees can then complete the check and update the incorrect master data record.
• Step 4 – Global SAP master data governance: One of the biggest challenges in master data maintenance is the cross-site MDM in distributed organizations. While some data fields are globally valid, others differ from plant to plant. Thanks to special solutions, different plant views can be defined and the solution will automatically create the relevant views for the defined plants.

By linking such a four-level MDM workflow with your SAP system, you can ensure that the risks and follow-up costs resulting from incorrect master data are kept to a minimum. Particularly in times of digitalization, master data management is becoming the supreme discipline for companies that rely on the automation of logistics and production processes.

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?

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

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. 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 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.