Data Mining In a Personnel Selection Process

Abstract

This technology report consists of an investigation of the use of data mining techniques on one of the main fronts of Human Resource Management, personnel selection. It is developed through a case study in a Civil Society Organization, where data mining methods are applied in a personnel selection process. Evaluators of the organization that is being studied indicate that the candidate evaluation process has many selection criteria, with different degrees of importance, and that at the moment of the decision all are considered equal, which brings uncertainties and make the selection more subjective. In this context, the objective of this research is to make selection faster and more efficient by discovering the main selection criteria with the use of data mining. This aims to improve the adherence of selected candidates in accordance with the objectives of the selection, so that it meets more assertively the requirements stipulated by the organization. It also aims to reduce the effort of evaluators in the selection, by reducing time and steps. The results indicate that some evaluation criteria influence decision making more than others, such as the Commitment and Teamwork criteria. These criteria can be used to support decision making of uncertain candidates, as they indicate which characteristics weigh more in the selection. The result of the importance of each criteria in decision making is used throughout the organization, making it faster and more assertive.