Process Automation as a Strategy to Reduce Server Turnover at the Federal Police Regional Office

Authors

DOI:

https://doi.org/10.22279/navus.v16.1983

Abstract

This article addresses the issue of operational efficiency at the Federal Police's Regional Judicial Police Department in Brasília, with a focus on automating the auction processes for seized vehicles. The necessity for enhanced efficiency in these procedures emerged as a response to the fiscal challenges posed by high staff turnover and the inherent complexity of administrative and judicial processes. The objective of this article is to propose the implementation of a semi-automated system to enhance efficiency and reduce turnover in the sector responsible for managing vehicles seized by the Federal Police. A code was developed in the Python programming language to automate manual tasks, including the creation and management of processes in the Electronic Information System, the registration and inclusion of documents, and the generation of official letters. The primary outcomes demonstrate a significant reduction in process execution time, indicating a notable improvement in efficiency and accuracy. The proposed solution streamlines administrative procedures, as well as helping to reduce turnover, offering a more stable working environment and less exposure to human error. In addition to improving operational efficiency, the study provides an understanding of how automation can positively influence human resource management. The implications for society include the implementation of more efficient and transparent public service processes, which will result in faster and more reliable service delivery, thus benefiting the public administration and the population in general.

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Author Biographies

Larissa Ágata Gomes de Moraes, Instituto Federal de Brasília (IFB)

Bacharela em Administração.

Daniel Soares de Souza, Instituto Federal de Brasília (IFB)

Mestre em Gestão Pública.

Pedro Carvalho Brom, Instituto Federal de Brasília (IFB)

Mestre em Estatística.

Josué Pires de Carvalho, Universidade de São Paulo (USP)

Doutor em Administração de Organizações.

Lucas Santos de Oliveira, Instituto Federal de Brasília (IFB)

Especialista em Estatística Aplicada.

Leonardo Garcia Marques, Instituto Federal de Goiás (IFG)

Doutor em Engenharia Elétrica.

Published

2025-02-18

Issue

Section

Articles