Abstract
In this paper we introduce the intelligent Executable Product Model (iEPM) approach for the autonomous optimization of service industry’s business processes. Instead of using a process model, we use an Executable Product Model (EPM). EPMs provide a compact representation of the set of possible execution paths of a business process by defining information dependencies instead of the order of activities. The flexibility that EPMs provide is utilized by intelligent agents managing the execution with the objective to optimize the Key Performance Indicators (KPIs) under consideration of the operating conditions. This paper demonstrates the practical application method of the iEPM approach as intelligent BPM engine where agents autonomously adapt their behavior in accordance to the current operating conditions for optimizing KPIs. The advantages of this method are discussed and statistically analyzed using a simulation based approach and the business process “new customer” found in banking.
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Kress, M., Seese, D. (2010). Autonomous Optimization of Business Processes. In: Rinderle-Ma, S., Sadiq, S., Leymann, F. (eds) Business Process Management Workshops. BPM 2009. Lecture Notes in Business Information Processing, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12186-9_12
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DOI: https://doi.org/10.1007/978-3-642-12186-9_12
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