The applicability of Process Mining to determine and align process model descriptions

Authors Arjen Maris, Roland Bijvank, Pascal Ravesteijn
Published in Proceedings
Publication date 19 June 2016
Research groups Artificial Intelligence
Type Lecture

Summary

From the article: Within the HU University of Applied Sciences (HU) the department HU Services (HUS) has not got enough insight in their IT Service Management processes to align them to the new Information System that is implemented to support the service management function. The problem that rises from this is that it is not clear for the HU how the actual Incident Management process as facilitated by the application is actually executed. Subsequently it is not clear what adjustments have to be made to the process descriptions to have it resemble the process in the IT Service Management tool. To determine the actual process the HU wants to use Process Mining. Therefore the research question for this study is: ‘How is Process Mining applicable to determine the actual Incident Management process and align this to the existing process model descriptions?’ For this research a case study is performed using Process Mining to check if the actual process resembles like the predefined process. The findings show that it is not possible to mine the process within the scope of the predefined process. The event data are too limited in granularity. From this we conclude that adjustment of the granularity of the given process model to the granularity of the used event data or vice versa is important.

On this publication contributed

  • Arjen Maris
    • Researcher
    • Research group: Process Innovation and Information Systems
  • Roland Bijvank
    • Researcher
    • Research group: Artificial Intelligence
  • Pascal Ravesteijn | Professor | Process innovation and information systems
    Pascal Ravesteijn
    • Professor
    • Research group: Process Innovation and Information Systems

Language English
Published in Proceedings
Key words Proces mining, Data analysis, Data analyse

Arjen Maris

Arjen Maris

  • Researcher
  • Research group: Process Innovation and Information Systems