The value of data is becoming increasingly important for companies. At the same time, new types of data processing increasingly require a more systematic framework organisation. Only together can business and IT do justice to the organisational, technical and legal aspects.

Increasing organisational complexity

Data processing used to be viewed primarily through a lens of the industrialisation era, indeed an entire industry of technical service companies was often named after it. As with mass production, the primary focus was on standardising and automating processing operations to reduce unit costs. The needs around the processing of information have expanded significantly since then and the pure efficiency consideration is now only a partial aspect. New aspects to be considered are:

• With digitalisation, the company is no longer just aiming to speed up or reduce the cost of an existing process by means of automation, but is also questioning the organisational processes themselves.
• With the establishment of a master data management, companies implement the once-only principle. Each piece of information should only be collected and entered once. All further consequences of the new knowledge are triggered automatically.
• The improvement of the customer/user experience is increasingly perceived as an important potential for customer acquisition and retention. On the one hand, customers should not be unnecessarily bothered with questions that the company could answer itself if it were organised correctly. At the same time, processing is increasingly personalised and individualised by creating suitable user profiles that are optimally aligned with the needs and characteristics of the individual users.
• With the increasingly high volumes of data to be processed, classic software developments are increasingly reaching their limits and are being supplemented by statistical procedures and artificial intelligence methods.
• Society and politics are increasingly aware of the privacy issue and demand responsible handling of personal data. The new Data Protection Act also provides effective regulation in this regard.

While different aspects complement each other well, there are also conflicts of interest. For example, the interests of data protection and the trend towards increasing linking of data sets, whether through master data management or profiling methods, are not in natural harmony and require various organisational and technical accompanying measures to be permissible. It is clear that the new aspects mentioned above primarily have organisational and legal implications, while technology is primarily called upon to provide support as an implementation partner.

What are the benefits of establishing data management?

Traditionally, companies optimise their organisation by managing their business processes. Methods such as value stream mapping or IT-supported process mining are used for this purpose. Classic process management, also anchored in quality management standards such as ISO 9001, is widespread and proven. Is that not enough?

Well, information that is processed in the business process also plays a role in process management. However, they take on a secondary role. Putting on the data management glasses means that another perspective is thrown on the organisation, which can reveal potential for improvement around the data. It is definitely not a replacement for process management, but an additional perspective that makes certain additional insights more easily possible.

It is also worth mentioning that all companies must keep a register of data processing with regard to the new data protection law or the GDPR and must also document data processing and disclosure with reference to persons. Accordingly, a certain effort must be made in this direction recently anyway. Accordingly, it seems to make sense that if this analysis already has to be done, it can also include other questions with additional benefits.

Central elements of data management

The management of data is located within a framework that is on the one hand aligned with strategic control and on the other hand is based on a foundation of design principles, architectures and methods.

In each case, a specific data stock is at the centre of the considerations. A distinction must be made between the roles of operational data management and the data governance organisation. Each of these roles has its own perspective with its own questions. For example, especially in the case of master data that is managed centrally for several offices, questions often arise regarding the exact semantics or data stewardship, i.e. ensuring appropriate quality assurance and maintenance.

On the part of the governance organisation, most process owners are already tasked with optimising the processes. In addition, the role of data owners is gaining in importance. The data owners are responsible for the data collection and must, for example, also ensure the rights of the data subjects in terms of data protection or the situation-appropriate creation of data protection follow-up assessments.

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About the author

Stefan is Managing Partner at linkyard. He has more than 20 years experience in software development and IT. He studied computer science (Eidg. Dipl. Ing. FH) and later business administration with a degree as Executive MBA in General Management. In addition to his further education in the sectors of management, project management, auditing (information security, quality management), business development and system engineering, Stefan holds certifications in requirements engineering, project management (Hermes, SAFe), risk management and Atlassian.

Due to his part-time work as a lecturer for information security and project management at a university of applied sciences, Stefan is the ideal contact person for risk and security management as well as for trainings in project management. In his career, Stefan has held positions such as Head of Business Unit, Project Manager, Software Architect and Software Engineer.

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