Towards a taxonomy for business capabilities determining data value

Data and its valuation have gained vital significance in academia and enterprises, coinciding with diverse data valuation approaches encompassing various layers, dimensions, and characteristics. This paper assesses data value determination through a business capability lens based on the TOGAF standard. The paper encompasses (a) constructing a Data Valuation Business Capability (DVBC) taxonomy and (b) validating the taxonomy using two existing data valuation concepts from academia. The methodology involves information systems taxonomy development techniques backed by a previously conducted systematic literature review of 64 articles. The resultant taxonomy comprises four business capability layers, nine dimensions, and 36 characteristics. These layers and dimensions offer business, technology, and organizational perspectives, reflecting the interdisciplinary nature of data valuation alongside an enterprise architecture. Characteristics within these layers and dimensions are either exclusive or non-exclusive based on their contents. The compiled findings meet both objective and subjective quality criteria. The implications of the DVBC are multifaceted, influencing scholars and professionals alike. Scholars gain a cohesive tool enhancing transparency in the extensively debated data value domain, fostering linkages among information systems, enterprise architecture management, and data management. This empowers the progress in developing comprehensive data valuation concepts. Additionally, professionals may employ the DVBC taxonomy as a lighthouse and guiding tool, fostering internal dialog on data valuation. This entails elevating data valuation to a pivotal business capability, necessitating collaborative, regular assessment, and enhancement involving business and technological stakeholders. By adopting this taxonomy, the challenge of consistently determining data value can be effectively addressed in both academia and enterprises.