Minimizing overprocessing waste in business processes via predictive activity ordering
Verenich, Ilya, Dumas, Marlon, La Rosa, Marcello, Maggi, Fabrizio Maria, & Di Francescomarino, Chiara (2016) Minimizing overprocessing waste in business processes via predictive activity ordering. In 28th International Conference on Advanced Information Systems Engineering (CAiSE2016), 13-17 June 2016, Ljubljana, Slovenia.
Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead.
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|Item Type:||Conference Paper|
|Additional Information:||Proceedings published as: Advanced Information Systems Engineering; Volume 9694 of the series Lecture Notes in Computer Science|
|Keywords:||Business Process Management, Business Process Mining, Business Process Optimization|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > Schools > School of Information Systems
|Copyright Owner:||Springer International Publishing Switzerland 2016|
|Deposited On:||11 Dec 2015 02:03|
|Last Modified:||28 Oct 2016 06:29|
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