Often underestimated: The quality of master data is a topic of quality management!

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In the context of Industrie 4.0, data is the new gold of enterprises and oil for competitiveness. In the age of digitalization, high quality data is essential. Master data is of particular importance in this context, as it forms the basis for digital products and services.

Even small deficiencies in master data, such as an incorrect delivery address, incorrect material masters or incorrect spare parts stocks can have massive effects in complex manufacturing processes in mechanical engineering. It is therefore important to consider whether quality management should establish a data quality management system that monitors and optimizes master data.

In many companies, the quality of master data can still be improved, which means that immense potentials can still be raised. For years, companies have invested in quality management systems to align processes with customer requirements. But these approaches have been applied comparatively little to the quality of the data. For this reason, the VDMA Quality Management Working Group in cooperation with ProduktionNRW has devoted itself to this topic. A workshop on data quality management was held at the TechnologieZentrumDortmund on 27 February 2020.

The quality of data is a topic of quality management

"A characteristic feature of master data is that it is not updated permanently but periodically and forms the basis for many operational processes," says Dr Frank Bünting, Deputy Head of Department at VDMA Business Advisory. "Often the necessary attention is not paid to the quality of this data, although permanent data maintenance and the rules and processes introduced for this purpose can make an enormous contribution to safeguarding the company".

The fact that the quality of data is not only a pure IT issue, but also a topic for the QMpeople is also demanded by DIN EN ISO 9001:2015, a standard that aims to consider, evaluate and avoid risks that could endanger the company at an early stage. Point 2.3.6.4 of the standard states that companies should "ensure that data and information are sufficiently precise, reliable and secure".

Necessary specifications and procedures

For precise and reliable data, quality management should first determine which data are important for the company. Furthermore, criteria for data quality must be established, responsibilities must be defined and it must be determined how data quality should be measured.

As a first step, however, Dr Bünting recommends creating the conditions to be able to maintain better data. This includes training all employees and raising awareness of the importance of maintained data. Tools for users must be fault-tolerant and user-friendly. A company-related filtering out of relevant data or even partially automated processing should be defined in advance. What is particularly important is a success control for the work done: monitoring should be carried out in the company to communicate the progress of the work. Also conceivable in this context are gamification systems such as success rates for those who intensively maintain address data or other data. In the further course of his presentation, Dr Bünting reported on what makes a good process key figure and what requirements apply to key figures for controlling processes.

Results of the workshop are to be further developed

"The workshop has shown that many companies are still far from having reached their goal on this topic. I am therefore pleased that we were able to give the quality managers the appropriate impetus for their work today. After all, data quality is becoming increasingly important in the context of digitization," concludes Dr Bünting. In the workshop the participants worked out various problems regarding the quality of master data using Ishikawa diagrams. The working group wants to push the topic further and use the results of the workshop for recommendations for action for master data management in quality management.

Further Information

Organizer

The event was offered by the VDMA NRW in cooperation with ProduktionNRW. ProduktionNRW is the competence network for mechanical engineering and production technology in North Rhine-Westphalia and is managed by VDMA NRW. ProduktionNRW sees itself as a platform for networking, informing and marketing companies, institutions and networks among themselves and along the value chain. Substantial parts of the services provided by ProduktionNRW are funded by the European Regional Development Fund (ERDF).