Tomada de decisão no transporte de cargas: impacto da análise de dados no gerenciamento de riscos

Abstract

In the information age, data plays a strategic role in organizations by enabling faster and more informed decision-making. In the road freight transport sector, the use of operational data obtained from tracking systems is essential for identifying risks and planning preventive actions. This study aims to analyze how data analysis can contribute to risk management and support decision-making in cargo transportation. The research was conducted through a case study at Total Conecta de Logística, a company operating in several regions of Brazil. The data were extracted from the company’s monitoring systems and analyzed using Power BI, along with the application of quality management tools such as the Pareto Chart, 5 Whys, and 5W2H. The adopted methodology is applied in nature, with both quantitative and qualitative approaches and a descriptive focus. The results showed that over 76% of the incidents were related to driver behavior, highlighting the need to review training and control processes. Data analysis made it possible to identify recurring failures, map risk areas, and propose corrective actions that led to more effective decisions. The study demonstrates that Business Intelligence tools can transform large volumes of data into useful information, bringing improvements to operational safety, company performance, and risk management. The research also offers relevant contributions to the academic field.