Abstract
It is vital to use accurate models for the analysis, design, and/or control of business processes. Unfortunately, there are often important discrepancies between reality and models. In earlier work, we have shown that simulation models are often based on incorrect assumptions and one example is the speed at which people work. The “Yerkes-Dodson Law of Arousal” suggests that a worker that is under time pressure may become more efficient and thus finish tasks faster. However, if the pressure is too high, then the worker’s performance may degrade. Traditionally, it was difficult to investigate such phenomena and few analysis tools (e.g., simulation packages) support workload-dependent behavior. Fortunately, more and more activities are being recorded and modern process mining techniques provide detailed insights in the way that people really work. This paper uses a new process mining plug-in that has been added to ProM to explore the effect of workload on service times. Based on historic data and by using regression analysis, the relationship between workload and services time is investigated. This information can be used for various types of analysis and decision making, including more realistic forms of simulation.
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van der Aalst, W.M.P., Nakatumba, J., Rozinat, A., Russell, N.: Business Process Simulation: How to get it Right? In: vom Brocke, J., Rosemann, M. (eds.) International Handbook on Business Process Management. Springer, Berlin (2008)
van der Aalst, W.M.P., Weijters, A.J.M.M., Maruster, L.: Workflow Mining: Discovering Process Models from Event Logs. IEEE Transactions on Knowledge and Data Engineering 16(9), 1128–1142 (2004)
Bertrand, J.W.M., van Ooijen, H.P.G.: Workload Based Order Release and Productivity: A Missing Link. Production Planning and Control 13(7), 665–678 (2002)
van Dongen, B.F., van der Aalst, W.M.P.: A Meta Model for Process Mining Data. In: Casto, J., Teniente, E. (eds.) Proceedings of the CAiSE Workshops (EMOI-INTEROP Workshop), vol. 2, pp. 309–320 (2005)
Dumas, M., van der Aalst, W.M.P., ter Hofstede, A.H.M.: Process-Aware Information Systems: Bridging People and Software through Process Technology. Wiley & Sons, Chichester (2005)
Juedes, D., Drews, F., Welch, L.: Workload Functions: A New Paradigm for Real-time Computing. In: 10th IEEE Real-Time and Embedded Technology and Applications Symposium Work-In Progress Session, pp. 25–28 (2004)
Montgomery, D.C., Peck, E.A.: Introduction to Linear Regression Analysis. Wiley & Sons, Chichester (1992)
van Ooijen, H.P.G., Bertrand, J.W.M.: The effects of a simple arrival rate control policy on throughput and work-in-progress in production systems with workload dependent processing rates. International Journal of Production Economics 85, 61–68 (2003)
Rozinat, A., Mans, R.S., Song, M., van der Aalst, W.M.P.: Discovering Simulation Models. Information Systems 34(3), 305–327 (2009)
Rozinat, A., Wynn, M.T., van der Aalst, W.M.P., ter Hofstede, A.H.M., Fidge, C.: Workflow Simulation for Operational Decision Support Using Design, Historic and State Information. In: Dumas, M., Reichert, M., Shan, M.-C. (eds.) BPM 2008. LNCS, vol. 5240, pp. 196–211. Springer, Heidelberg (2008)
Song, M., van der Aalst, W.M.P.: Towards Comprehensive Support for Organizational Mining. Decision Support Systems 46(1), 300–317 (2008)
Wickens, C.D.: Engineering Psychology and Human Performance. Harper (1992)
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Nakatumba, J., van der Aalst, W.M.P. (2010). Analyzing Resource Behavior Using Process Mining. 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_8
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DOI: https://doi.org/10.1007/978-3-642-12186-9_8
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