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Business Process Intelligence

Business Process Intelligence

M. Castellanos, A.K. Alves de Medeiros, J. Mendling, B. Weber, A.J.M.M. Weijters
Copyright: © 2009 |Pages: 25
ISBN13: 9781605662886|ISBN10: 1605662887|EISBN13: 9781605662893
DOI: 10.4018/978-1-60566-288-6.ch021
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MLA

Castellanos, M., et al. "Business Process Intelligence." Handbook of Research on Business Process Modeling, edited by Jorge Cardoso and Wil van der Aalst, IGI Global, 2009, pp. 456-480. https://doi.org/10.4018/978-1-60566-288-6.ch021

APA

Castellanos, M., Alves de Medeiros, A., Mendling, J., Weber, B., & Weijters, A. (2009). Business Process Intelligence. In J. Cardoso & W. van der Aalst (Eds.), Handbook of Research on Business Process Modeling (pp. 456-480). IGI Global. https://doi.org/10.4018/978-1-60566-288-6.ch021

Chicago

Castellanos, M., et al. "Business Process Intelligence." In Handbook of Research on Business Process Modeling, edited by Jorge Cardoso and Wil van der Aalst, 456-480. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-288-6.ch021

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Abstract

Business Process Intelligence (BPI) is an emerging area that is getting increasingly popular for enterprises. The need to improve business process efficiency, to react quickly to changes and to meet compliance is among the main drivers for BPI. BPI refers to the application of Business Intelligence techniques to business processes and comprises a large range of application areas spanning from process monitoring and analysis to process discovery, conformance checking, prediction and optimization. This chapter provides an introductory overview of BPI and its application areas and delivers an understanding of how to apply BPI in one’s own setting. In particular, it shows how process mining techniques such as process discovery and conformance checking can be used to support process modeling and process redesign. In addition, it illustrates how processes can be improved and optimized over time using analytics for explanation, prediction, optimization and what-if-analysis. Throughout the chapter, a strong emphasis is given to describe tools that use these techniques to support BPI. Finally, major challenges for applying BPI in practice and future trends are discussed.

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