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Advisor(s)
Abstract(s)
Os seres humanos não são capazes nem de absorver toda a informação disponível nem de prever todas as consequências dos seus atos. Deste modo, implementar métodos para extração de conhecimento das bases de dados pode auxiliar nos processos de tomadas de decisão. O propósito desta tese foi o de estudar os objetivos, os desafios e as oportunidades que os métodos de Data Mining oferecem à Gestão de Recursos Humanos. O estudo empírico foi realizado entre dezembro de 2019 e março de 2020. Três grandes empresas e uma pequena e média empresa, em Portugal, foram entrevistadas. Outras fontes secundárias foram também analisadas. Para completar o estudo, realizou-se um caso de estudo de um processo de recrutamento e seleção, sendo aplicado o coeficiente Gower’s Distance numa base de dados real. Os resultados do estudo permitirão perceber quais (1) os propósitos, (2) os desafios e (3) as oportunidades que surgem da aplicação de métodos de DM. Do estudo foi percetível que a aplicação destes métodos na Gestão de Recursos Humanos não é uma prioridade para as empresas. Para investir nestes métodos mais sofisticados com o DM, as empresas precisam de averiguar quais os desafios éticos e os problemas relacionados com a privacidade que podem surgir. Precisam, ainda, de ter uma equipa com profissionais com diferentes formações. Contudo, se as empresas tiverem dados fiáveis e atualizados e acompanharem o progresso tecnológico, o investimento na análise de dados permitirá acrescentar valor a cada processo assim como o crescimento no mercado.
Humans cannot absorb all the information available and predict all the consequences. Hence, implementing methods to extract knowledge from databases may guide in the decision-making process. The thesis aimed to study the purposes, the challenges and the opportunities that Data Mining methods offer to Human Resources Management. The empirical study was conducted between December of 2019 and March of 2020. Three large companies and one SME, in Portugal, were interviewed. Additionally, another secondary source was also included. Also, a Recruitment and Selection Case Study was conducted through an application of an algorithm step, the Gower’s Distance coefficient, in a real database. The findings will be used to promote understanding regarding the (1) purposes, (2) challenges, and (3) opportunities that may arise from the use of DM methods. From the empirical study was possible to understand that the application of DM methods in HRM is not a priority for most of the companies. To invest in more sophisticated methods, as DM methods, companies need to face privacy and ethical challenges and have an analytical team with people from different backgrounds. However, if companies achieve a set of requirements concerning data and monitor technological progress, the investment in data analytics will allow them to add value to each process and to keep continued growth in the market.
Humans cannot absorb all the information available and predict all the consequences. Hence, implementing methods to extract knowledge from databases may guide in the decision-making process. The thesis aimed to study the purposes, the challenges and the opportunities that Data Mining methods offer to Human Resources Management. The empirical study was conducted between December of 2019 and March of 2020. Three large companies and one SME, in Portugal, were interviewed. Additionally, another secondary source was also included. Also, a Recruitment and Selection Case Study was conducted through an application of an algorithm step, the Gower’s Distance coefficient, in a real database. The findings will be used to promote understanding regarding the (1) purposes, (2) challenges, and (3) opportunities that may arise from the use of DM methods. From the empirical study was possible to understand that the application of DM methods in HRM is not a priority for most of the companies. To invest in more sophisticated methods, as DM methods, companies need to face privacy and ethical challenges and have an analytical team with people from different backgrounds. However, if companies achieve a set of requirements concerning data and monitor technological progress, the investment in data analytics will allow them to add value to each process and to keep continued growth in the market.
Description
Keywords
Extração de conhecimento de base de dados Gestão de recursos humanos Processos de tomada de decisão Knowledge discovery in databases Data mining Human resources management People analytics Decision-making processes