Data Governance

Our research shows that Data Governance in practice rarely fails due to a lack of willingness, but because organizations cannot demonstrate what it costs to do nothing, and what is gained by doing it right. In 19 interviews with decision-makers from banking, insurance, technology, industry, energy, and law in Switzerland and Germany, one finding emerged consistently: organisations know that data governance matters. But they cannot measure that value, nor communicate it internally.

The real problem is not a lack of data. It is a lack of language to make that value visible.

We are therefore developing three complementary tools to make that value tangible:

1. Cost-Assessment: What does poor Data Governance cost? Compliance fines, data quality errors, manual corrections, failed AI projects. These costs are real, but often invisible. This instrument quantifies them, providing a solid foundation for investment decisions.
2. Value-Assessment: What does good Data Governance deliver? Time-to-market, AI readiness, new data products, data-sharing capabilities. Offensive benefits that are too rarely measured or communicated in practice.
3. Potential-Assessment: What is the next step worth? A synthesis of both instruments: a context-specific business case tailored to industry, maturity level, and data intensity.

The goal is to give executives and governance professionals a tool that allows them to position Data Governance not as a cost factor, but as a strategic resource.

Value is increasingly created in ecosystems – whether Open Banking, Open Insurance, Smart Energy or IoT – in which data is shared across organizational and industry boundaries. We research how data governance works in such constellations.

What makes them special: unlike within individual firms or on platforms, there is no central orchestrator that sets the rules. Governance emerges polycentrically, through the interplay of regulators, incumbent firms, new market entrants and infrastructure providers. This is precisely what makes data governance one of the central open questions of digital value creation – and with the growing use of AI, it is becoming even more pressing.

Our key insight: data governance is not a downstream compliance task but a strategic capability. It co-determines whether openness leads to value creation or to systemic risk. Those who build it early secure regulatory resilience and influence over standards that are only just emerging.

Read more in our latest article: Teebken, M. & Jung, R. (2026). Data Governance als strategische Fähigkeit: Erfolgsfaktoren in sektoralen und intersektoralen Ökosystemen. HMD Praxis der Wirtschaftsinformatik.

These research themes form the foundation of our bilateral projects with companies and institutions. We support practice partners with scientifically grounded approaches drawn directly from this field of research.