preCEP: Facilitating Predictive Event-Driven Process Analytics

Schwegmann Bernd, Matzner Martin, Janiesch Christian


Zusammenfassung
The earlier critical decision can be made, the more business value can be retained or even earned. The goal of this research is to reduce a decision maker's action distance to the observation of critical events. We report on the development of the software tool preCEP that facilitates predictive event-driven process analytics (edPA). The tool enriches business activity monitoring with prediction capabilities. It is implemented by using complex event processing technology (CEP). The prediction component is trained with event log data of completed process instances. The knowledge obtained from this training, combined with event data of running process instances, allows for making predictions at intermediate execution stages on a currently running process instance's future behavior and on process metrics. preCEP comprises a learning component, a run-time environment as well as a modeling environment, and a visualization component of the predictions.

Schlüsselwörter
Event-driven Process Analytics, Business Activity Monitoring, Complex Event Processing, Business Process Management, Operational Business Intelligence



Publikationstyp
Aufsatz (Konferenz)

Begutachtet
Ja

Publikationsstatus
Veröffentlicht

Jahr
2013

Konferenz
International Conference on Design Science Research in Information Systems and Technology (DESRIST)

Konferenzort
Helsinki, Finland

Buchtitel
Design Science at the Intersection of Physical and Virtual Design: Proceedings of the 8th International Conference DESRIST 2013

Herausgeber
Brocke Jan vom, Hekkala Riitta, Ram Sudha, Rossi Matti

Erste Seite
448

Letzte Seite
455

Band
7939

Reihe
Lecture Notes in Computer Science

Verlag
Springer

Ort
Heidelberg

Sprache
Englisch

ISBN
978-3-642-3882

DOI

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