TY - BOOK
T1 - Using process mining to learn from process changes in evolutionary systems
AU - Günther, C.W.
AU - Rinderle-Ma, S.
AU - Reichert, M.
AU - Aalst, van der, W.M.P.
AU - Recker, J.
PY - 2006
Y1 - 2006
N2 - Traditional information systems struggle with the requirement to provide flexibility and process support while still enforcing some degree of control. Accordingly, adaptive process management systems (PMSs) have emerged that provide some flexibility by enabling dynamic process changes during runtime. Based on the assumption that these process changes are recorded explicitly, we present two techniques for mining change logs in adaptive PMSs; i.e., we do not only analyze the
execution logs of the operational processes, but also consider the adaptations made at the process instance level. The change processes discovered through process mining provide an aggregated overview of all changes that happened so far. This, in turn, can serve as basis for integrating
the extrinsic drivers of process change (i.e., the stimuli for flexibility) with existing process adaptation approaches (i.e., the intrinsic change mechanisms). Using process mining as an analysis tool we show in this paper how better support can be provided for truly flexible processes by
understanding when and why process changes become necessary.
AB - Traditional information systems struggle with the requirement to provide flexibility and process support while still enforcing some degree of control. Accordingly, adaptive process management systems (PMSs) have emerged that provide some flexibility by enabling dynamic process changes during runtime. Based on the assumption that these process changes are recorded explicitly, we present two techniques for mining change logs in adaptive PMSs; i.e., we do not only analyze the
execution logs of the operational processes, but also consider the adaptations made at the process instance level. The change processes discovered through process mining provide an aggregated overview of all changes that happened so far. This, in turn, can serve as basis for integrating
the extrinsic drivers of process change (i.e., the stimuli for flexibility) with existing process adaptation approaches (i.e., the intrinsic change mechanisms). Using process mining as an analysis tool we show in this paper how better support can be provided for truly flexible processes by
understanding when and why process changes become necessary.
M3 - Report
SN - 978-90-386-0866-2
T3 - BETA publicatie : working papers
BT - Using process mining to learn from process changes in evolutionary systems
PB - Technische Universiteit Eindhoven
CY - Eindhoven
ER -