Towards a Predictive Model to Forecast Competency Needs in Organizations: Integrating Competency Cluster Associations and Their Future Relevance

IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC), pp. 1–8

Abstract

In the face of accelerated digital and demographic transformations, traditional competency models reveal limitations in their capacity to dynamically adapt for future workforce planning. Existing models, predominantly static, are inadequate for forecasting and strategically aligning competencies in a dynamic environment. This paper presents an approach that extends an existing competency model, creating a dynamic framework to predict the relevance of competencies. Using a qualitative method, competencies are clustered based on their coherence and relevant connections between them are identified. A supplementary quantitative study further determines the expected changes in competency relevance from a practical perspective. The integration of these results into the competency model offers a proactive tool for workforce development and strategic planning.

Authors 6

1. Paula Danhausen Aachen FIR e. V.

   FIR e. V. an der RWTH Aachen

   Affiliation as printed

   FIR e.V. an der RWTH Aachen,Aachen,Germany

2. Nele Schulte-Uebbing Aachen FIR e. V.

   FIR e. V. an der RWTH Aachen

   Affiliation as printed

   FIR e.V. an der RWTH Aachen,Aachen,Germany

3. Steffen Jansing

   Institut für Forschung und Transfer

   Affiliation as printed

   Institute for Research and Transfer, RIF e. V,Dortmund,Germany

4. Julian Schallow

   Institut für Forschung und Transfer

   Affiliation as printed

   Institute for Research and Transfer, RIF e. V,Dortmund,Germany

5. Clara Herkenrath Aachen FIR e. V.

   FIR e. V. an der RWTH Aachen

   Affiliation as printed

   FIR e.V. an der RWTH Aachen,Aachen,Germany

6. Jochen Deuse

   Institut für Forschung und Transfer

   Affiliation as printed

   Institute for Research and Transfer, RIF e. V,Dortmund,Germany