Embedding Data‐Related Competences into Knowledge and Process Management: A Bibliometric Reconstruction and Integrative Framework

ABSTRACT

Data‐intensive organisations increasingly depend on competences that allow data to be interpreted, shared and translated into organisational action. Research on data skills, analytics capabilities and digital transformation has expanded rapidly, yet the knowledge and process mechanisms through which data‐related competences become organisationally consequential remain dispersed across several literatures. This article addresses this issue through an integrated bibliometric and interpretive analysis of 1346 publications indexed in Scopus and Web of Science, complemented by a targeted full‐text examination. The study combines descriptive profiling, co‐citation analysis, factorial analysis, thematic mapping and keyword evolution to reconstruct the intellectual and conceptual structure of competence‐centred research in data‐intensive contexts. The findings reveal three connected conceptual areas concerning competence development, organisational mobilisation and organisational outcomes. Integrating these patterns with the theoretical and full‐text evidence, the article develops the Data‐Related Competence Mobilisation Framework around three core components, namely data‐related competence development, knowledge‐and‐process embedding and value realisation, while adaptive renewal operates as a feedback logic connecting organisational outcomes with subsequent changes in competences and embedding arrangements. The study contributes to knowledge and process management research by theorising knowledge‐and‐process embedding as the mechanism through which data‐related competences become organisationally usable, actionable and value‐relevant.