Data Governance Capabilities

In today's digital age, new technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), and Data Analytics (DA) have transformed data into key corporate assets (Leghemo, 2025; Abraham, 2023; Yebenes, 2022; Baijens, 2022; Fadler & Legner, 2021,2022; Jagals,2021; Janssen et al., 2020). The emergence of these technologies also introduces challenges and the need for data legislation (Otto,2022). However, although the importance of high-quality data grows and data have become valuable assets, organisations have few assessment models available to govern data assets within their organisations (Otto, 2022; Lis & Otto, 2021; Otto, 2007; Khatri, 2010). Moreover, even fewer of these models have been validated in practice and only in a single organisation. Additionally, validating assessment models is a challenge in research in itself (Tarhan, Turetken, & Reijers, 2016).
To address this gap, our research goal is to design and validate a Data Governance Capabilities reference model. Organisations may use this model as a reference for designing assessment models to learn the data governance (DG) status quo. They require this knowledge to implement targeted data governance improvements that enhance the value of their data assets.
To design such a reference model, we employ the Design Science Research approach combined with qualitative research methods. Before constructing this reference model, we define key definitions to establish a common language and construct a Generic Capabilities Reference Model. Subsequently, we identify Data Governance Capabilities (DGCs) through a series of literature studies. To validate the identified DGCs in practice, we conduct case studies in large organisations that are operationalising the DGCs. Additionally, to empirically validate the entire DGC model, we conduct a multiple-case study in three large organisations. To achieve this, we design an approach that utilises the operationalised reference model, followed by an evaluation of the perceived usefulness and ease of use of the DGC model.
As a result of our research, we identified 34 distinct DGCs in literature, which we validated in 19 large organisations. After constructing the DGC reference model using these DGCs, we empirically validated it through a multiple-case study involving three large organisations.
Our DGC reference model contributes to the existing body of knowledge. This is because it is the most comprehensive and first DGC reference model validated in multiple organisations on usability and ease of use, and it is one of the few capability models being validated empirically. Additionally, our research provides organisations with a DG Capability reference model for constructing DG assessment models and a method to empirically validate the designed assessment models.