Data quality is causing problems for companies

Study Transformation: Poor data quality is causing problems for German companies

25.09.2024 Responsible editor: Konstantin Pfliegl 2 min reading time

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Data quality, resources and know-how: A study by Natuvion and NTT Data Business Solutions on dealing with digital transformation shows where there are still problems.

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Lack of expertise, too few staff and inadequate data quality – an international transformation study by Natuvion and NTT Data Business Solutions reflects the challenges that companies repeatedly fail to face when it comes to digitization. As part of the study Almost 1,300 transformation managers worldwide were asked which difficulties particularly surprised them during the course of their transformation projects.

Too few qualified employees for the transformation

For example, 34 percent of companies said they were particularly surprised by their own employees’ lack of experience in dealing with transformation projects. 30 percent each cited problems with data quality and the acute shortage of employees as surprising findings.

However, the extent of the lack of resources varies from country to country. In Germany and Belgium, 34 percent were surprised by this – in France, the figure was as high as 43 percent. But the lack of employee know-how and the lack of acceptance of the workforce with regard to digital transformation were also cited as surprising findings by 20 percent of companies.

German companies struggle with data

A look at the assessment and handling of data quality shows that there are regional differences. Those responsible for transformation in Germany, America, Italy, Spain and Belgium were significantly more surprised by the poor quality of their data than the other countries. It is striking that in the USA, 37 percent did not expect such problems.

But a look at the industries also reveals differences in expectations regarding data quality. Here, companies from the automotive and supplier industries in particular said that they had not expected a data quality deficiency of this magnitude.

It is striking that a third of the companies that used a so-called brownfield approach to digital transformation were more than surprised by their poor data quality. The brownfield approach involves migrating to new systems without interrupting existing processes. This suggests that this group expected a quick and easy lift-and-shift migration. When the data quality was checked, however, it was determined that the lack of quality would inevitably result in an additional burden on the new system.

In addition, 31 percent of companies that wanted to migrate using the brownfield principle said they were surprised by the lack of know-how among their employees. This shows that companies are often under the misconception that the brownfield method is the easiest option – but here too, the data must be restructured if it is to be used sensibly afterwards.

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