Discovering Causal Factors Explaining Business Process Performance Variation

• Published in: Advanced Information Systems Engineering Vol. 10253; pp. 177 - 192
• Main Authors: Hompes, Bart F. A., Maaradji, Abderrahmane, La Rosa, Marcello, Dumas, Marlon, Buijs, Joos C. A. M., van der Aalst, Wil M. P.
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Performance analysis; Process mining; Root cause analysis
• ISBN: 3319595350; 9783319595351
• ISSN: 0302-9743; 1611-3349; 1611-3349
• DOI: 10.1007/978-3-319-59536-8_12

Business process performance may be affected by a range of factors, such as the volume and characteristics of ongoing cases or the performance and availability of individual resources. Event logs collected by modern information systems provide a wealth of data about the execution of business processes. However, extracting root causes for performance issues from these event logs is a major challenge. Processes may change continuously due to internal and external factors. Moreover, there may be many resources and case attributes influencing performance. This paper introduces a novel approach based on time series analysis to detect cause-effect relations between a range of business process characteristics and process performance indicators. The scalability and practical relevance of the approach has been validated by a case study involving a real-life insurance claims handling process.