TY - GEN
T1 - Analyzing resource behavior using process mining
AU - Nakatumba, J.
AU - Aalst, van der, W.M.P.
PY - 2010
Y1 - 2010
N2 - 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.
AB - 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.
U2 - 10.1007/978-3-642-12186-9_8
DO - 10.1007/978-3-642-12186-9_8
M3 - Conference contribution
SN - 978-3-642-12185-2
T3 - Lecture Notes in Business Information Processing
SP - 69
EP - 80
BT - Business Process Management Workshops (BPM 2009 International Workshops, Ulm, Germany, September 7, 2009. Revised papers)
A2 - Rinderle-Ma, S.
A2 - Sadiq, S.
A2 - Leymann, F.
PB - Springer
CY - Berlin
ER -