Predicting Deadline Transgressions Using Event Logs
Effective risk management is crucial for any organisation. One of its key steps is risk identification, but few tools exist to support this process. Here we present a method for the automatic discovery of a particular type of process-related risk, the danger of deadline transgressions or overruns, based on the analysis of event logs. We define a set of time-related process risk indicators, i.e., patterns observable in event logs that highlight the likelihood of an overrun, and then show how instances of these patterns can be identified automatically using statistical principles. To demonstrate its feasibility, the approach has been implemented as a plug-in module to the process mining framework ProM and tested using an event log from a Dutch financial institution.
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- 1.Adriansyah, A., van Dongen, B.F., van der Aalst, W.M.P.: Conformance checking using cost-based fitness analysis. In: 2011 15th IEEE International Enterprise Distributed Object Computing Conference (EDOC), pp. 55–64. IEEE (2011)Google Scholar
- 2.Bose, R., van der Aalst, W.M.P.: Context aware trace clustering: Towards improving process mining results. In: Proceedings of the SIAM International Conference on Data Mining, SDM, pp. 401–412 (2009)Google Scholar
- 3.International Organization for Standardization. Risk management: vocabulary = Management du risque: vocabulaire (ISO guide 73), Geneva (2009)Google Scholar
- 6.Rousseeuw, P.J.: Robust estimation and identifying outliers. In: Handbook of Statistical Methods for Engineers and Scientists, ch. 16. McGraw-Hill, New York (1990)Google Scholar
- 7.Standards Australia and Standards New Zealand. Risk management: principles and guidelines (AS/NZS ISO 31000:2009), 3rd edn., Sydney, NSW, Wellington, NZ (2009)Google Scholar
- 9.van Dongen, B., Crooy, R., van der Aalst, W.M.P.: Cycle time prediction: When will this case finally be finished? In: On the Move to Meaningful Internet Systems: OTM 2008, pp. 319–336 (2008)Google Scholar