The PredicTeams project aims to develop a practice-oriented framework for predictive competence management for agile teams that enables companies to manage the transition to agile teamwork in digital work environments. Concrete goals are in detail:
● Identification and operationalisation of competencies for agile teamwork in the context of digital working environments and the provision of a database with instruments for measuring relevant competencies
● Method for simplifying the survey process of competence assessment using semantic language analysis
● Methodology for the analysis of competence profiles
● Show-case applications for the recording of competencies with the help of semantic text analysis and for the analysis of competency profiles on the basis of fuzzy-set qualitative comparative analysis
● Models and methods as well as a guideline for the design of a predictive competence management and future-oriented teamstaffing
The goals are achieved by taking up state-of-the-art measuring instruments and methods in the field of human resources and organisational research as well as empirical methodology, developing them further, adapting them for use in companies and testing them based on test data, evaluating data on employee competencies, and in some cases collecting new data to significantly reduce dimensions. Exemplary data analyses will be implemented and evaluated. In addition to the identification of the most important competencies, the procedure for recording competencies is to be radically simplified, with a written statement once a year on the ongoing survey using language assessment and text analysis. The planned measures will provide the basis for a time-efficient, state-of-the-art survey and analysis of competencies in companies. The methods and models to be developed should enable companies to operate predictive competence management instead of administrative competence management in the future. The project is both practically and scientifically innovative, since predictive HR analytics is much discussed, but is still in its infancy.
The project is conducted in the context of the technology cluster it's OWL . It is supported by the Ministry for Economics, Innovation, Digitalization and Energy of NRW. The project is funded with 2.4 mio Euro.