Authors: Mr. Shrikant Karampuri, Dr. P. Jeyanthi
Abstract: The fast development of technologies, automation, and digitalization processes have led to a considerable disruption of how workforce planning is traditionally performed and have created a significant gap between the skills of the existing workforce and the skills that will be necessary in the future for the success of organizations. The process of competency mapping which includes the identification, evaluation, and alignment of skills with strategic goals is extremely important to ensure future readiness via skill development. This paper introduces a new approach to the competency mapping using artificial intelligence, which utilizes NLP algorithms for skill extraction from unstructured sources (resumes, job descriptions, and performance evaluations), GNNs for skill adjacency and competency modeling, and BKT for prediction of the evolution of individual skills. When applied to a database of 50,000 employees in a multinational technology company, our approach yields an accuracy of 89.7% for skill extraction, 82% for skill adjacencies, and 76% for the prediction of future skill gaps. The proposed approach allows us to create personalized learning paths and reduce time-to-competency by 34% in six months.
DOI: https://doi.org/10.5281/zenodo.20411976
