3 questions for Ursula Frank on data-driven business models

Dr. Frank, Head of R+D-Cooperations at Beckhoff Automation GmbH & Co. KG

Copyright: © Beckhoff Automation GmbH & Co. KG
Munich, 7 November 2025

Boosted by Industrie 4.0 and the accompanying digitalisation, companies at all levels have access to an increasing amount of data. Now creativity is needed to use this data in a beneficial way and thus develop digital and data-driven business models. For example, data can be used as the basis for automated or at least supportive decision-making, optimisation of existing processes, expansion of existing products and services, or development of innovative products and services. It is also conceivable to market the data itself or data-related analysis and consulting services. Depending on the approach chosen and the company, a wide variety of successes can be achieved.

For example, the use of AI-supported data analysis tools and smart services, such as a ‘health index,’ can increase productivity and reduce downtime. Expert knowledge can be provided directly via remote access, supported by AR and VR technologies. In addition, B2B platforms offer easy access to smart services from various providers. For companies, the use and/or provision of digital and data-driven business models results in efficiency gains in production, logistics and business processes, as well as the opportunity to tap into new market potential. Overall, digital and data-driven business models offer considerable potential for securing and expanding competitiveness in the long term.

Small and medium-sized enterprises are often leaders and unique in their industry and market. Their uniqueness is reflected in their business models, business processes, technologies and standards. Across all companies, this leads to a wide variety of technologies, processes and standards being used. In order to ensure the competitiveness of these companies, it is important to preserve their uniqueness while providing them with easy and affordable access to digital and data-driven business models.

To this end, suitable standards for interfaces and processes must be defined from a data technology perspective. In addition, rules for the exchange of data must be defined that leave data sovereignty with the companies and enable them to protect their core know-how. Furthermore, revenue models are required that offer sufficient benefits for all participants in the value creation network under consideration. Another challenge is that many small and medium-sized enterprises lack employees with sufficient skills in data technologies and hybrid service bundles who can proactively plan and implement digital and data-driven business models. Due to limited resources, especially in small and medium-sized enterprises, it is crucial that solutions are simple, pragmatic and can be implemented with little effort.

Many companies are reluctant to participate in projects that require large investments and do not offer them any immediately apparent benefits – especially in economically challenging times. To counteract this, it is important to lower the barriers to entry. Smaller, clearly defined, short-term projects with a manageable number of partners are helpful. These can become flagship projects and encourage others to follow suit, possibly supported by low-threshold funding formats. Within these projects, digital and data-driven business models should be promoted that can be implemented with little effort and generate added value for the participating companies in a timely manner. It is crucial that companies can use their usual standards for handling data, that simple interoperability between systems is possible and that IT security is guaranteed. If data sovereignty remains with the companies and data use is transparent, this creates trust and acceptance. Taking limited resources into account, easy-to-use rules for data usage and pricing promote the implementation of digital and data-driven business models.

Overall, politicians and scientists need to work closely with industry to develop and make available the necessary technologies, regulations and solutions, and to provide suitable training and further education opportunities.