Abstract
Process mining combines a number of techniques that allow analyzing business processes solely through event logs. This article is a continuation of the research carried out in [1] to analyze data based on the postal distribution of products in the Argentine Republic between the years 2017 and 2020. The results obtained initially showed that 85% of the shipments made comply with the process correctly. Cases that did not fit within the model were also quickly identified, and recurring problems were found, which facilitates analysis for process improvement. The most common problems were traces that do not follow task order, excess movements or missing movements, and traces that comply with the process but take too long. In this article, a performance analysis was added to discover traces that, despite correctly following to the process, have operational deviations due to an excessive time to complete. These techniques are intended to be added to the process through early alerts that warn about the existence of such situations, which would help improve service quality.
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Martinez, V., Lanzarini, L., Ronchetti, F. (2022). Distribution Analysis of Postal Mail in Argentina Using Process Mining. In: Pesado, P., Gil, G. (eds) Computer Science – CACIC 2021. CACIC 2021. Communications in Computer and Information Science, vol 1584. Springer, Cham. https://doi.org/10.1007/978-3-031-05903-2_11
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DOI: https://doi.org/10.1007/978-3-031-05903-2_11
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