Statistical Tests and Association Measures for Business Processes

IEEE Transactions on Knowledge and Data Engineering, pp. 1–15

Abstract

Through the application of process mining, organisations can improve their business processes by leveraging data recorded as a result of the performance of these processes. Over the past two decades, the field of process mining evolved considerably, offering a rich collection of analysis techniques with different objectives and characteristics. Despite the advances in this field, a solid statistical foundation is still lacking. Such a foundation would allow analysis outcomes to be found or judged using the notion of statistical significance, thus providing a more objective way to assess these outcomes. This paper contributes several statistical tests and association measures that treat process behaviour as a variable. The sensitivity of these tests to their parameters is evaluated and their applicability is illustrated through the use of real-life event logs. The presented tests and measures constitute a key contribution to a statistical foundation for process mining.

Authors 4

1. Sander J. J. Leemans Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen

2. James M. McGree

   Queensland University of Technology

   Affiliation as printed

   QUT Brisbane

3. Artem Polyvyanyy

   The University of Melbourne

   Affiliation as printed

   University of Melbourne

4. Arthur H. M. ter Hofstede

   Queensland University of Technology

   Affiliation as printed

   QUT Brisbane