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Automatização de processos na gestão de recursos humanos
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Abstract(s)
A transformação digital dos processos organizacionais tornou-se essencial na modernização da ges-tão das empresas, especialmente na área dos Recursos Humanos (RH), onde a precisão e a eficiên-cia são fundamentais. Este estudo centra-se na otimização dos processos manuais e baseados em papel de registo das folhas de ponto e trocas de serviço na Falck SCI Portugal, através da automati-zação. Com a implementação de um sistema de reconhecimento facial e esquelético, aliado à Au-tomatização Robótica de Processos (RPA), o projeto visa conceptualizar uma forma de melhorar a eficiência operacional, reduzir os erros humanos e promover a sustentabilidade.
A investigação utilizou duas metodologias principais: a Action Research Approach, que permitiu uma colaboração ativa com a organização para identificar desafios e testar soluções, e a Revisão Sistemática da Literatura (RSL), que proporcionou uma base teórica sólida. O estudo identificou os principais problemas do processo atual, como ineficiências temporais, suscetibilidade a erros hu-manos e o impacto ambiental decorrente do uso excessivo de papel.
Foram aplicados dois questionários aos colaboradores para avaliar as perceções sobre o sistema manual atual e as expectativas relativamente à solução automatizada proposta. Os resultados de-monstraram uma insatisfação significativa com o sistema atual e elevadas expectativas em relação à automatização. Os principais benefícios esperados incluem o aumento da precisão dos registos, a melhoria da eficiência operacional e a redução da carga administrativa. Além disso, a automatiza-ção responde às preocupações ambientais dos colaboradores ao eliminar o uso de papel, promo-vendo práticas sustentáveis.
A solução proposta evidencia o potencial das tecnologias emergentes na modernização dos proces-sos de RH, aumentando a satisfação dos colaboradores. Este estudo oferece um modelo prático para a automatização de processos, sublinhando a importância da precisão, eficiência e responsabi-lidade ambiental.
The digital transformation of organizational processes has become essential in modern business management, particularly in Human Resources (HR), where precision and efficiency are paramount. This study focuses on optimizing the manual and paper-based processes of attendance records and shift exchanges at Falck SCI Portugal through automation. By implementing a facial and skeletal re-cognition system combined with Robotic Process Automation (RPA), this project aims to improve operational efficiency, reduce human errors, and enhance sustainability. The research employed two methodologies: the Action Research Approach, which allowed active collaboration within the organization to identify challenges and test solutions, and a Systematic Literature Review (SLR), which provided a solid theoretical foundation. The study addressed key challenges in the current process, including time inefficiencies, human error susceptibility, and the environmental impact of paper usage. Two surveys were conducted with employees to assess perceptions of the current manual system and expectations for the proposed automated solution. Results indicated significant dissatisfaction with the current system and high expectations for automation. Key anticipated benefits include increased accuracy of records, improved operational efficiency, and reduced administrative workload. Additionally, automation aligns with employees' environmental concerns by eliminating paper usage and promoting sustainability. The proposed solution demonstrates the potential of integrating emerging technologies in HR to modernize processes and increase employee satisfaction. This study contributes to the field by pro-viding a practical model for HR process automation, highlighting the importance of precision, effici-ency, and environmental responsibility.
The digital transformation of organizational processes has become essential in modern business management, particularly in Human Resources (HR), where precision and efficiency are paramount. This study focuses on optimizing the manual and paper-based processes of attendance records and shift exchanges at Falck SCI Portugal through automation. By implementing a facial and skeletal re-cognition system combined with Robotic Process Automation (RPA), this project aims to improve operational efficiency, reduce human errors, and enhance sustainability. The research employed two methodologies: the Action Research Approach, which allowed active collaboration within the organization to identify challenges and test solutions, and a Systematic Literature Review (SLR), which provided a solid theoretical foundation. The study addressed key challenges in the current process, including time inefficiencies, human error susceptibility, and the environmental impact of paper usage. Two surveys were conducted with employees to assess perceptions of the current manual system and expectations for the proposed automated solution. Results indicated significant dissatisfaction with the current system and high expectations for automation. Key anticipated benefits include increased accuracy of records, improved operational efficiency, and reduced administrative workload. Additionally, automation aligns with employees' environmental concerns by eliminating paper usage and promoting sustainability. The proposed solution demonstrates the potential of integrating emerging technologies in HR to modernize processes and increase employee satisfaction. This study contributes to the field by pro-viding a practical model for HR process automation, highlighting the importance of precision, effici-ency, and environmental responsibility.
Description
Tese de Mestrado em Informação e Sistemas Empresariais, em associação com o Instituto Superior Técnico, apresentada à Universidade Aberta
Keywords
Automatização de processos Recursos humanos Automatização Robótica de Processos (RPA) Reconhecimento facial Reconhecimento esquelético Eficiência operacional Sustentabilidade Action research Revisão sistemática de literatura Process automation Human resources Robotic Process Automation (RPA) Facial recognition Skeletal recognition Operational efficiency Sustainability Systematic literature review
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