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Process mining: software comparison, trends, and challenges

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Abstract

Process mining is the confluence between data mining and business process management, which is a growing and promising research topic. From process execution event logs, process mining focuses on understanding end-to-end processes and helps provide more significant findings. In this paper, a brief review of each of the main stages (discovery, conformance, and enhancement) of the process mining and low-code automation platforms for business processes are stated. Also, it provides an analysis of the 16 most prominent process mining software as well as an in-depth taxonomy considering 55 features. From this comparison, a subset of software obtained the best scores for process discovery while others for process simulation. Finally, trends and a set of challenges for process mining are pointed out.

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Notes

  1. http://appian.com.

  2. http://appian.com/resources/resource-center/analyst-reports/gartner-peer-insights-enterprise-low-code.html.

  3. www.kofax.com/products/totalagility.

  4. www.g2.com/categories/robotic-process-automation-rpa.

  5. www.promodel.com/products/ProcessSimulator.

  6. www.gartner.com/reviews/market/process-mining.

  7. www.celonis.com/ems/platform/planning-and-simulation.

  8. www.celonis.com/intelligent-business-cloud/machine-learning.

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    Octavio Loyola-González

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Loyola-González, O. Process mining: software comparison, trends, and challenges. Int J Data Sci Anal 15, 407–420 (2023). https://doi.org/10.1007/s41060-022-00379-0

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