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NRC Publications Archive Archives des publications du CNRCThis publication could be one of several versions: author's original, accepted manuscript or the publisher's version. / La version de cette publication peut être l'une des suivantes : la version prépublication de l'auteur, la version acceptée du manuscrit ou la version de l'éditeur. For the publisher's version, please access the DOI link below./ Pour consulter la version de l'éditeur, utilisez le lien DOI ci-dessous. Systems, Man and Cybernetics, Part C., 38, 6, pp. 745-756, 2008-11-01 A business process intelligence system for enterprise process performance management Tan, W.; Shen, W.; Zhou, B. The material in this document is covered by the provisions of the Copyright Act, by Canadian laws, policies, regulations and international agreements. Such provisions serve to identify the information source and, in specific instances, to prohibit reproduction of materials without written permission. For more information visit http://laws.justice.gc.ca/en/showtdm/cs/C-42
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AbstractBusiness process management systems traditionally focused on supporting the modeling and automation of business processes, with the objective of enabling fast and cost-effective process execution. As more and more processes become automated, customers are increasingly interested in managing process execution. This paper presents a set of concepts and a methodology towards business process intelligence using dynamic process performance evaluation, including measurement models based on ABM (Activity Based Management) and a dynamic enterprise process performance evaluation methodology. The proposed measurement models support the analysis of six process flows within a manufacturing enterprise including activity flow, information flow, resource flow, cost flow, cash flow, and profit flow, which are crucial for enterprise managers to control the process execution quality and detect problems and areas for improvements. The proposed process performance evaluation methodology uses time, quality, service, cost, speed, efficiency, and importance as seven evaluation criteria. A prototype system supporting dynamic enterprise process modeling, analysis of six process flows, and process performance prediction has been implemented to validate the proposed methodology.