An Innovative Approach for Personnel Positioning

Abstract

The contribution of the paper is the building of a model to predict the proper employees’ allocation in the Greek public sector. To acknowledge the set and weights of criteria upon which our model feeds data, a validated questionnaire was developed and used to conduct a primary quantitative survey amongst HR departments and employees of state organizations in Greece. On the acquired findings, several experiments were administered using linear and machine learning tools, aiming to replace time consuming and subjective procedures, followed by many organizations. Concluding, data classification algorithms are proposed to predict the best matching of employees, giving as inputs personnel qualifications as well as job specifications, leading to a model based on J48, a decision tree algorithm.