Using process mining to generate accurate and interactive business process maps

W.M.P. Aalst, van der

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

27 Citations (Scopus)
1 Downloads (Pure)

Abstract

The quality of today’s digital maps is very high. This allows for new functionality as illustrated by modern car navigation systems (e.g., TomTom, Garmin, etc.), Google maps, Google Street View, Mashups using geo-tagging (e.g., Panoramio, HousingMaps, etc.), etc. People can seamlessly zoom in and out using the interactive maps in such systems. Moreover, all kinds of information can be projected on these interactive maps (e.g., traffic jams, four-bedroom apartments for sale, etc.). Process models can be seen as the "maps" describing the operational processes of organizations. Unfortunately, accurate and interactive process maps are typically missing when it comes to business process management. Either there are no good maps or the maps are static or outdated. Therefore, we propose to automatically generate business process maps using process mining techniques. By doing this, there is a close connection between these maps and the actual behavior recorded in event logs. This will allow for high-quality process models showing what really happened. Moreover, this will also allow for the projection of dynamic information, e.g., the "traffic jams" in business processes. In fact, the combination of accurate maps, historic information, and information about current process instances, allows for prediction and recommendation. For example, just like TomTom can predict the arrival time at a particular location, process mining techniques can be used to predict when a process instance will finish.
Original languageEnglish
Title of host publicationBusiness Information Systems Workshops (BIS 2009 International Workshops, Poznan, Poland, April 27-29, 2009. Revised Papers)
EditorsW. Abramowicz, D. Flejter
Place of PublicationBerlin
PublisherSpringer
Pages1-14
ISBN (Print)978-3-642-03423-7
DOIs
Publication statusPublished - 2009

Publication series

NameLecture Notes in Business Information Processing
Volume37
ISSN (Print)1865-1348

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