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From Mess to Mesh - With data products to greater corporate success I Series: Data heroes

Video contribution

March 26, 2024

The interview with Dr. Andreas Böhm, founder and CEO of One Data, was all about data products. As part of our "Data Heroes" series, he discussed the importance of data products and how companies can increase the value of data through decentralized responsibility with host Dr Gero Presser.

Data products: Decentralized responsibility for better decisions

Andreas Böhm discovered his passion for data early on in his career and recognized the potential to increase the value of data for companies. He founded his first company in the field of statistics consulting at the age of 23, long before buzzwords such as data science and big data were known. With his company One Data, which he founded around ten years ago, he is pursuing the goal of making data much more usable and helping companies to become more efficient and make sustainable decisions based on data.

When asked what exactly the idea of data products is, Andreas Böhm emphasizes the aspect that with this approach, data is not seen as a waste product, but as an active part of the value creation process. For example, whoever is responsible for the personnel in a company is also responsible for ensuring that the data on the workforce is properly maintained. In other words, data is treated like a product that is provided to the organization.

"This decentralized change is the important aspect that makes a huge difference here," says Andreas Böhm. "The biggest change compared to centralized approaches is the mindshift in terms of who provides data and who makes which decisions with which data."

Decentralized data organization and governance

Andreas Böhm sees a major advantage of decentralized data organization in the improved quality of the data. As the data is generated and maintained by the people who are responsible for it in the specialist departments, errors can be avoided and data quality ensured. Decentralized responsibility also creates an increased awareness of data throughout the company. Efficiency is also increased, as decisions can be made more quickly and there is no need to wait for IT to provide new data.

To ensure that data also comes together in a decentralized organization, a central team can provide governance and an overview. Transparency about the existing data and its availability is crucial in order to enable an overall view and to be able to use the data effectively. A data catalog can be helpful here, as can tools and platforms that make the data usable for business users.

As a concrete example of how the use of data products in companies can create added value, Andreas Böhm cited a company that was able to improve comparability and increase efficiency through decentralized production monitoring across different plants. It was also possible to optimize central key figures or inventory management by connecting decentralized data products. These examples show how data products can help solve complex problems in global organizations and ensure sustainable profitability.

The trending topic of data mesh and the future of data products

Finally, there was a discussion on the trending topic of data mesh in connection with data products. According to Andreas Böhm, data mesh is an interesting approach, but it can be complex to implement from an organizational perspective. Nevertheless, he sees a valuable idea of data mesh in the data product concept: "The beauty of this idea is that you can simply start in a specialist area by focusing on a few small, tangible data products and not having to introduce this process throughout the entire company." This is why data products also make sense in companies that are centrally organized without having to move towards mesh immediately.

As far as the future of data products and the further development of One Data is concerned, Andreas Böhm points to the methodologies and capabilities of large language models (LLM), which have already been incorporated into the product. He believes that LLMs bring a high increase in productivity for business users: "I believe that large language models can be an extreme support in speeding up the process of getting the data you need to make decisions. The use of large language models really is a game changer." However, he emphasizes that the focus should always be on customer benefit.

He sees the future development in the democratization of data and decisions by enabling specialist departments to do things that they could not do before using large language models. "This is a significant change in how people will deal with data."