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In this book, an automatic technique to identify potential causes of failures in business processes by extending Process Mining algorithms is proposed. Initially, in our technique, the original event log is filtered into two logs, the former with successful cases and the latter with failed cases. Then, behavioral patterns are extracted from both event logs using the Performance Sequence Diagram Analysis algorithm, which was selected because it considers both control flow (the order in which activities are performed) and time (tasks' duration and waiting times between tasks) features. Another important feature of this algorithm is that process's data is not lost, allowing -in a later comparison- to apply Data Mining classification techniques to find data patterns that could explain certain failures in the process. Finally, both sets of patterns are compared using a method that we have called Behavioral Pattern Conformance. The differences found represent potential causes of failures in business processes.
About the author
I was born in Arequipa, a beautiful city on the south of Peru. I studied my PhD at Pontificia Universidad Católica from Chile. My topics of interest are: Process Mining, Data Mining, Business Process Management and Information Systems.I am a professor at Santa María Catholic University, teaching: BPM, Business Intelligence and Data Bases.
