Developing a model-based method that automatically identifies appropriate training courses for employees affected by digitalization

The ongoing digital transformation and the increasing dynamism of labour markets necessitate that organisations continuously adapt their workforce's competencies. Nevertheless, a considerable number of organisations encounter difficulties in systematically identifying future competency requirements, aligning employee development with strategic objectives, and deriving individualised development measures based on reliable competency data. Existing approaches to this issue are often piecemeal, and therefore lack an integrated perspective on competency development. The present dissertation investigates the manner in which an integrated approach to strategic, data- driven, and individualised competency development can be designed and implemented within organisations. Utilising a Design Science Research methodology, a holistic approach was developed that combines strategic competency planning, automated competency analysis, and competency profile enhancement. The results demonstrate that future competency requirements can be systematically derived from organisational transformation initiatives, translated into individualised development recommendations, and continuously refined through the integration of additional competency information. The proposed approach combines Enterprise Architecture Management, standardized competency taxonomies, competency analytics, and data-driven profile enhancement into a coherent framework for competency development. The dissertation makes a significant contribution to both research and practice by providing an integrated reference framework that supports organisations in aligning workforce development with future competency requirements in a strategic, data-driven, and individualised manner.