DocumentCode :
2064068
Title :
Mixed-initiative management of dynamic business processes
Author :
Rubinstein, Zachary B. ; Corkill, Daniel D.
Author_Institution :
Dept. of Comput. Sci., Univ. of New Hampshire, Durham, NH, USA
fYear :
2003
fDate :
23-25 June 2003
Firstpage :
39
Lastpage :
44
Abstract :
Managing and participating in complex, dynamic business processes is difficult due to their inherent uncertainty, which undermines the predictability necessary for efficient planning and execution. Effective management of these processes hinges on the ability of the manager to recognize unanticipated difficulties in the process execution, determine the causes of the anomalies, and implement remedies. Current process-management approaches respond reactively to process dynamics, if they deal with them at all. In this paper, we present the ProME process-management environment, focusing on how human process managers and participants interact with a dynamic, online model of executing dynamic processes to proactively manage and operate in dynamic business processes. We show how having the best information available about a process and its future can provide managers with the time needed to detect and understand impending process anomalies and to develop and implement effective interventions. Furthermore, we show enabling managers how to update the model of executing processes and having the effects of those modifications to be pushed to the relevant participants reduces the time it takes to implement remedies, ProME was used in a commercial product for managing design processes in the automotive and aerospace industries.
Keywords :
business continuity; decision support systems; management of change; resource allocation; scheduling; ProME; aerospace industry; anomaly cause; automotive industry; business-process representation; commercial product; decision-support system; design process; difficulty recognition; dynamic business process; dynamic interaction; human process manager; inherent uncertainty; mixed-initiative management; online model; predictability; proactive management; process dynamics; process execution; process planning; process-management environment; resource allocation; scheduling; Aerodynamics; Business; Environmental management; Fasteners; Humans; Process design; Process planning; Product design; Uncertainty; Vehicle dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing in Industrial Applications, 2003. SMCia/03. Proceedings of the 2003 IEEE International Workshop on
Print_ISBN :
0-7803-7855-5
Type :
conf
DOI :
10.1109/SMCIA.2003.1231341
Filename :
1231341
Link To Document :
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