Using Graph Algorithms for Skills Gap Analysis

Abstract

With the development of graph databases, organizations can utilize this technology to enhance human capital allocation by better understanding and connecting employee skillsets with the requirements of positions. Specifically, by storing data in the form of a knowledge graph, organizations are enabled to profile the competencies of their employees and optimize the deployment of human capital to the company’s objectives. This study explores data provided by a large engineering organization which merges employee data, including project assignment and skills, with a public library of competency profiles from O*NET. The objective is to explore employee skills profiling, optimize project staffing, and identify employees best suited for upskilling through the use of graph databases and machine learning algorithms. The findings show that knowledge graphs present an opportunity for organizations to better understand their workforces and more optimally allocate and strengthen their human capital.