Business Process Failure Prediction: a case study

  • Pedro O. T. Mello Federal University of the State of Rio de Janeiro, Rio de Janeiro
  • Kate Revoredo Federal University of Rio de Janeiro, Rio de Janeiro
  • Flávia Santoro State University of Rio de Janeiro, Rio de Janeiro


Business process monitoring aims at maintaining the reliability of process executions. However, the dynamic nature of business processes hinders a proactive scenario in which risk mitigation actions can occur before the facts that put the process at risk. Thus, some premises are necessary such as the identification of situations and patterns in historical data of the processes execution in order to characterize what determined the failures. In this paper, we address the problem of how to identify and detect patterns of behaviors that can lead the processes to a failure situation. As a solution, a combination of well-established techniques from Data and Process Mining fields are applied in a case study of an incident management process. The results obtained open possibilities to a proactive scenario.

Palavras-chave: Data Mining, Business Process, Process Monitoring, Failure Prediction


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MELLO, Pedro O. T.; REVOREDO, Kate; SANTORO, Flávia. Business Process Failure Prediction: a case study. In: SYMPOSIUM ON KNOWLEDGE DISCOVERY, MINING AND LEARNING (KDMILE) , 2019, Fortaleza. Anais do VII Symposium on Knowledge Discovery, Mining and Learning. Porto Alegre: Sociedade Brasileira de Computação, nov. 2019 . p. 89-96. DOI: