Mr. Seebacher, what is master data in an industrial environment?

Michael Seebacher: Master data is the basis of all processes in an ERP system. In the industrial environment in particular, there is a wealth of different master data that forms the main basis of products and services and the associated business processes. If the master data is incorrect or incomplete, the defined process comes to a standstill.

Regardless of whether they are small or medium-sized companies, many find master data maintenance difficult. Why is this the case?

Seebacher: The smaller the company, the smaller the workforce and the number of knowledge carriers. Many tasks are placed in the hands of less knowledgeable people. Master data maintenance is often neglected as a result.

Larger companies, on the other hand, often lack the necessary organization and defined responsibilities.

In 90% of companies, the topic of master data is given too little attention and priority. The effects of low-quality data are often only noticed late or ignored for a long time.

In many cases, the complexity and quantity of data is due to the growth of companies. For time and budget reasons, harmonization and cleansing are given lower priority in the integration process and are usually scheduled for a later date. The devil is in the detail - and here in the ongoing business process; the longer it takes, the more data is added and the more unruly it becomes to deal with it.

In manufacturing companies in particular, the volume and interdependencies of data make it very difficult and complex.

When do companies realize that they need to take action?

Seebacher: Many companies usually only take action when additional work and costs can be attributed to data quality. Employees need longer to prepare data. Whether production interruptions, problems with deliveries, customs penalties due to missing or incorrect information, delays in invoicing - the effects are manifold and naturally have an impact on the quality of goods or services and therefore also on business partner satisfaction and trust.

In almost all SAP projects, the area of master data is addressed at an early stage and the potential for optimization is often identified. When we talk about implementation projects, we always recommend that our customers give master data sufficient attention, resources and, above all, priority. This begins with analyses of the existing data, continues with cleansing and harmonization and ends with the establishment of defined structures and processes.

How should an SME approach master data maintenance? Where should the company start?

Seebacher: Data analysis, cleansing, harmonization and structured data maintenance processes must always be an integral part of ERP projects and must be seamlessly integrated into daily business life and continued. If a company recognizes a need for action

It is important to gain an overview and record the current data inventory.

Clear goals must be set - how do you want to continue working with the findings, what do you want to achieve in the end and what is necessary for this?

A jointly developed structure, a coordinated approach to data maintenance with clearly assigned tasks and clearly defined responsibilities are the key to successful and high-quality master data.

It is important that the organization is prepared for this and is also supported.

What prerequisites must be created for this?

Seebacher: Master data management starts in the organization and must be supported and lived by everyone involved. Resources and means must be made available for this and the will and courage to change are essential.

The most important thing, however, is the clear allocation of tasks and the definition of those responsible or decision-makers in matters of master data.

How does CNT support this?

Seebacher: Every project that we support as CNT requires special handling of data from the upstream systems and effort in the implementation or cleansing and maintenance in the SAP system.

We support our customers with our many years of experience in SAP implementation and rollout projects. Our experts in master data management offer CNT best practice tools for data analysis, cleansing, governance processes, data transfer (migration) and data verification. These tools have been tried and tested many times and can also be used in the validated environment of the life sciences industry.

As a holistic implementation partner, we support our customers in master data projects of all kinds, regardless of the source system, and assist them in using the tools and experience mentioned above.