• English
  • Deutsch
  • Log In
    Password Login
    Research Outputs
    Fundings & Projects
    Researchers
    Institutes
    Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Konferenzschrift
  4. Scenario-based prediction of business processes using system dynamics
 
  • Details
  • Full
Options
2019
Conference Paper
Title

Scenario-based prediction of business processes using system dynamics

Abstract
Many organizations employ an information system that supports the execution of their business processes. During the execution of these processes, event data are stored in the databases that support the information system. The field of process mining aims to transform such data into actionable insights, which allow business owners to improve their daily operations. For example, a process model describing the actual execution of the process can be easily extracted from the captured event data. Most process mining techniques are ""backward-looking"" providing compliance and performance information. Few process mining techniques are ""forward-looking"". Therefore, in this paper, we propose a novel scenario-based predictive approach that allows us to assess and predict future behavior in business processes. In particular, we propose to use system dynamics to allow for ""what-if"" questions. We create a system dynamics model using variables trained on the basis of the past behavior of the process, as captured in the event log. This model is used to explore the effect of possibly applied changes in the process as well as roles of external factors, e.g., human behavior. Using real event data, we demonstrate the feasibility of our approach to predict possible consequences of future decisions and policies.
Author(s)
Pourbafrani, M.
Zelst, S.J. van
Aalst, W.M.P. van der
Mainwork
On the Move to Meaningful Internet Systems. OTM 2019 Conferences. Proceedings  
Conference
International Conference on Cooperative Information Systems (CoopIS) 2019  
International Conference "Cloud and Trusted Computing" (C&TC) 2019  
International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE) 2019  
DOI
10.1007/978-3-030-33246-4_27
Language
English
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Contact
© 2024