40 Int. J. Reasoning-based Intelligent Systems, Vol. 6, Nos. 1/2, 2014 Copyright © 2014 Inderscience Enterprises Ltd. Using data mining in the selection process of high performance managers Edilson Ferneda* Universidade Católica de Brasília, Mestrado em Gestão do Conhecimento e Tecnologia da Informação, SGAN 916, Módulo B, Sala A-115, 70.970-160 Brasília, DF, Brazil E-mail: eferneda@pos.ucb.br * Corresponding author Hercules A. do Prado Universidade Católica de Brasília, Mestrado em Gestão do Conhecimento e Tecnologia da Informação, SGAN 916, Módulo B, Sala A-115, 70.970-160 Brasília, DF, Brazil and Embrapa – Empresa Brasileira de Agropecuária, Brazil E-mail: hercules@ucb.br Alexandre G. Cancian Sobrinho Universidade Católica de Brasília, Mestrado em Gestão do Conhecimento e Tecnologia da Informação, SGAN 916, Módulo B, Sala A-115, 70.970-160 Brasília, DF, Brazil E-mail: alexandre.gcs@hotmail.com Remis Balaniuk Universidade Católica de Brasília, Mestrado em Gestão do Conhecimento e Tecnologia da Informação, SGAN 916, Módulo B, Sala A-129, 70.970-160 Brasília, DF, Brazil and Tribunal de Contas da União, Brazil E-mail: remis@ucb.br Abstract: The selection of high performance managers involves a significant level of subjectivity. Aiming at reducing this subjectivity and mitigating possible losses, many approaches have been proposed to select the candidates that best fit into a given position. However, defining what are the most important features for a good personnel performance is still a problem. This paper details the ideas and results presented in two previous works that describe an approach, based on data mining techniques, to help managers in this process. A classifier, built over the combinatorial neural model (CNM), is described that takes as dependent variable the performance of managers as observed along their careers. As independent variables, we considered the results of well-known psychological tests (MBTI and DISC). The rules generated correlate psychological profiles of novice managers and the quality of their work after some years. These results enable a better management of people selection and allocation. Keywords: knowledge-based systems; combinatorial neural model; CNM. Reference to this paper should be made as follows: Ferneda, E., do Prado, H.A., Sobrinho, A.G.C. and Balaniuk, R. (2014) ‘Using data mining in the selection process of high performance managers’, Int. J. Reasoning-based Intelligent Systems, Vol. 6, Nos. 1/2, pp.40–48.