Artikel in Zeitschrift ART-2012-08

Wetzstein, Branimir; Zengin, Asli; Kazhamiakin, Raman; Marconi, Annapaola; Pistore, Marco; Karastoyanova, Dimka; Leymann, Frank: Preventing KPI Violations in Business Processes based on Decision Tree Learning and Proactive Runtime Adaptation.
In: Journal of Systems Integration. Vol. 3(1).
Universität Stuttgart, Fakultät Informatik, Elektrotechnik und Informationstechnik.
S. 3-18, englisch.
Online, 31. Januar 2012.
ISSN: 1804-2724.
Artikel in Zeitschrift.
CR-Klassif.H.4.1 (Office Automation)

The performance of business processes is measured and monitored in terms of Key Performance Indicators (KPIs). If the monitoring results show that the KPI targets are violated, the underlying reasons have to be identified and the process should be adapted accordingly to address the violations. In this paper we propose an integrated monitoring, prediction and adaptation approach for preventing KPI violations of business process instances. KPIs are monitored continuously while the process is executed. Additionally, based on KPI measurements of historical process instances we use decision tree learning to construct classification models which are then used to predict the KPI value of an instance while it is still running. If a KPI violation is predicted, we identify adaptation requirements and adaptation strategies in order to prevent the violation.

Abteilung(en)Universität Stuttgart, Institut für Architektur von Anwendungssystemen
Eingabedatum11. April 2012
   Publ. Institut   Publ. Informatik