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 organization. Only together can business and IT meet the organizational, technical and legal aspects.

Increasing organizational complexity

In the past, data processing was primarily viewed through the lens of the age of industrialization; indeed, an entire industry of technical service companies was often named after it. As with mass production, the focus was primarily on standardizing and automating processing processes to reduce unit costs. The requirements for processing information have expanded significantly since then and the pure analysis of efficiency is now only a partial aspect. The new things to consider are:

• With digitization, the company is no longer just striving to speed up or reduce the costs of an existing process through automation, but is also questioning the organizational processes themselves.
• By establishing master data management, companies implement the once only principle. Each information should only be collected and entered exactly once. All other consequences of the new finding are triggered automatically.
• Improving the customer/user experience is increasingly perceived as an important potential for attracting and retaining customers. On the one hand, customers should not be unnecessarily bothered with questions which, if properly organized, the company could definitely answer itself. At the same time, processing is increasingly personalized and individualized by creating suitable user profiles that are optimally tailored to the needs and characteristics of individual users.
• With the increasing volume of data to be processed, classic software developments are increasingly reaching their limits and are being supplemented by statistical methods and artificial intelligence methods.
• Society and politics are increasingly aware of privacy issues and are calling for the responsible use of personal data. With the new data protection law, there is also effective regulation on this.

While various 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, regardless of whether through master data management or profiling methods, are not in natural harmony and require various organizational and technical accompanying measures in order to be permitted. It is clear that the new aspects mentioned primarily have organizational and legal effects, while technology is primarily required as an implementation partner to provide support.

What are the benefits of establishing data management?

Traditionally, companies optimize their organization by managing their business processes. Methods such as value stream mapping or IT-supported process mining are used for this purpose. Traditional process management, also anchored in quality management standards such as ISO 9001, is widespread and proven. Isn't that completely enough?

Well, information that is processed in the business process also plays a role in process management. However, they play a supporting role. Putting on data management glasses means taking a further perspective on the organization, which can reveal potential for improvement in the data. It is definitely not a substitute for process management, but an additional perspective that makes certain additional insights easier.

It is also worth mentioning that all companies must keep a record of data processing in view of the new data protection law or the GDPR and must also document personal data processing and transfer. Accordingly, a certain amount of effort has recently been made in this direction anyway. Accordingly, it seems quite reasonable that if this analysis must already be carried out, it can also include other issues with additional benefits.

Central elements of data management

The management of data is within a framework which, on the one hand, is oriented by strategic management and, on the other hand, is based on a foundation of design principles, architectures and methods.

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

On the part of the governance organization, most process owners are already tasked with optimizing processes. In addition, the role of data owners is becoming increasingly important here. Data owners are responsible for data collection and must also ensure, for example, the rights of data subjects in terms of data protection or the preparation of data protection impact assessments appropriate to the situation.

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About the author

Stefan is a managing partner at linkyard. He has more than 20 years of experience in software development and IT. He studied computer science (Swiss Federal Institute of Technology). Dipl. Ing. FH) and later business administration with an Executive MBA in General Management. In addition to his continuing education in the management, project management, auditing (information security, quality management), business development and system engineering sectors, Stefan holds certifications in the areas of requirements engineering, project management (Hermes, SAFe), risk management and Atlassian.

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

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