Expertise, data quality and personnel?

An international study by Natuvion and NTT Data Business Solutions on how companies deal with their technical transformation revealed aspects and regional differences that no one had expected. It showed that companies had not expected such a lack of knowledge regarding the implementation of transformation projects and that the quality of the data to be transformed was so inferior. Furthermore, the interviewees were surprised that they had so few qualified personnel available to carry out the technical transformation.

Lack of expertise in the team

34% of companies stated that they were particularly surprised by their own employees' lack of experience in dealing with transformation projects. In each case, 30 percent cited problems with data quality and the acute shortage of employees as surprising findings - they had not expected these aspects to such an extent in advance. However, the assessment and expectations regarding the lack of resources differ from country to country. In Germany and Belgium, 34% were surprised by this, in France as many as 43%. However, the lack of employee expertise and the lack of acceptance of the workforce with regard to digital transformation were also cited as surprising findings by 20% of companies in each country.

The assessment and handling of data quality also differ - both from a regional and industry perspective. 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 37% of companies in the USA were not confronted with such problems. A look at the sectors shows that companies from the automotive and supplier industry in particular did not expect such deficiencies in data quality.

It is striking that a third of the companies that opted for a brownfield approach to digital transformation were more surprised than average by their poor data quality. This suggests that this group assumed a quick and easy "lift & shift" migration. However, when the data quality was checked, it was then discovered that the lack of quality would inevitably place an additional burden on the new system. 31 percent of companies that wanted to migrate according to the brownfield principle stated that they were surprised by their employees' lack of expertise. This shows that companies repeatedly fall prey to the fallacy that the brownfield method is the quickest and easiest option. But here, too, the data must be massively optimized in terms of consistency, quality, structure and layout if it is to be used sensibly afterwards.

One Data Transformation Approach

But what can companies do to successfully implement their transformation projects? On the one hand, they can call in external consultants and transformation specialists who have a high level of experience, the necessary tools, coordination and appropriate personnel. Secondly, they can try to organize their migration in such a way that the various migration methods are brought together centrally and then implemented holistically. The transformation and system migration expert Natuvion has developed its own process for this: the One Data Transformation Approach. It is based on the Natuvion DCS (Data Conversion Server), a flexible migration platform that brings together all migration methods (greenfield, brownfield, selective, hybrid) under one roof. It does not matter from which source technology to which target technology (SAP, Oracle, Infor, Salesforce, etc.) or which deployment platform is used.

The One Data Transformation Approach makes it possible to combine the digital transformation with other projects that would be more complex to implement without this approach. This means that companies not only benefit from a smooth transformation, but also from maximum flexibility as part of their transformation - for example, when introducing a new general ledger, changing the fiscal year or making adjustments to the data model.

The One Data Transformation Approach provides companies with the methodology, tools and expertise for a very wide range of tasks. It can be assumed that migrations - of whatever kind - will take place more frequently in the future. Companies should address the challenges of digital transformation at an early stage in order to prepare themselves for surprises and future-proof themselves. Particularly in light of the fact that valid, digitally available data is playing an increasingly important role in business success, surprises during the transformation should be avoided through good, detailed planning and the involvement of experienced transformation experts.

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