IT Incident Solving Domain Experiment on Business Process Failure Prediction

Authors

  • Pedro O. T. Mello Federal University of the State of Rio de Janeiro
  • Kate Revoredo Vienna University of Economics and Business
  • Flávia Maria Santoro University of the State of Rio de Janeiro

DOI:

https://doi.org/10.5753/jidm.2020.2028

Keywords:

Process mining, Data mining, Failure prediction, Case study

Abstract

Business process monitoring aims at maintaining the reliability of process executions. Nevertheless, 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. We argue that understanding failures behavior allows proactive actions. Analysing historical data of processes executions supports the identification of situations and patterns of failure behavior. In this paper, we present an experiment in which a combination of well-established techniques from Data Mining and Process Mining fields are applied to an incident management process. The results obtained show that it is possible to identify failures in order to reach for a proactive risk mitigation scenario.

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Published

2021-02-14

How to Cite

O. T. Mello, P., Revoredo, K., & Maria Santoro, F. (2021). IT Incident Solving Domain Experiment on Business Process Failure Prediction. Journal of Information and Data Management, 11(1). https://doi.org/10.5753/jidm.2020.2028

Issue

Section

KDMILE 2019