Fifteen years of process mining in Brazil: Current contributions, most used techniques, and challenges

Context: Process mining is a discipline that combines data science (data mining) and process science (Business Process Management - BPM), which has become crucial for large organizations as it enables the discovery, maintenance, and improvement of business processes. Problem: In the context of process mining in Brazil, there is a gap in the consolidated knowledge about the state of the art and the main topics being discussed. Solution: This study aims to understand what are the most frequent process mining techniques and challenges discussed within Brazilian research and the contributions to the advancement of the discipline in the country. IS Theory: This study was conceived under the aegis of Argumentation Theory, presenting information and evidence on selected studies and the results discussed. Method: A systematic literature review (SLR) from the last 15 years on process mining in Brazil was carried out, considering studies with Brazilian affiliation and using searches in scientific databases. Summary of Results: Through the analysis of 153 studies, we identified 9 different groups regarding Brazilian contributions to the advancement of the discipline in the country. By examining the results obtained, the methods applied, and the findings presented in the studies included on the SLR, we identified the most commonly used process mining technique in national research, as well as the main challenges cited by Brazilian authors, notably the need to address log quality. Contributions and Impact in the IS area: This study increases visibility of the current state of process mining research in Brazil in order to highlight new research opportunities within the Brazilian market.