Business Process Intelligence

Author:

Castellanos M.1,Alves de Medeiros A.K.2,Mendling J.3,Weber B.4,Weijters A.J.M.M.2

Affiliation:

1. Hewlett-Packard Laboratories, USA

2. Eindhoven University of Technology, The Netherlands

3. Queensland University of Technology, Australia

4. University of Innsbruck, Australia

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.

Publisher

IGI Global

Cited by 40 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. For Loan Processing a Fuzzy Process Mining;Journal of Advanced Research in Natural and Applied Sciences;2023-09-20

2. Creating business value with process mining;The Journal of Strategic Information Systems;2022-12

3. A Query Language for Workflow Logs;ACM Transactions on Management Information Systems;2022-06-30

4. Supporting Process Mining with Recovered Residual Data;Lecture Notes in Business Information Processing;2020

5. Modellgestützte Prozessanalyse;Prozessmodellierung mit ARIS®;2019

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