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Reviewer: Donald Rajinder Chand

Business process management (BPM) is a new area of information technology (IT) that deals with the effective management of business processes. Unlike other process methodologies, such as business process improvement (BPI), business process re-engineering (BPR), and Six Sigma, that put a process under a microscope to improve its performance, BPM is a management approach that uses process technology to dynamically align the operational processes to changes in a firm's strategy. Within BPM, process mining is a set of tools and a methodology for extracting and shaping the process model that is embedded in an operating business process. Specifically, it uncovers process models from the real-time events data generated from the operational business processes. Because process models developed in BPI, BPR, and Six Sigma are idealized in the sense that the model contains information that is relevant to the specific process initiative, they often do not match the implemented business process over time. Thus, a need exists for extracting process models embedded in operating business processes. Based on decade-long research on process mining at the Eindhoven University of Technology in the Netherlands, van der Aalst presents in this book the purpose, role, methods, and tools of process mining. The book is divided into five parts. The first part discusses the kind of data needed to organize and generate an event log of an operating business process. Part 2 first introduces a basic algorithm that shapes a first-level process model in Petri net notation from the control flow information in the event log of an operating business process. It introduces and illustrates the notion of soundness of a process model. Then, it shows how, if the resources that perform the activities are captured in the event log, we can adapt data mining techniques to construct a resource-based process model from the event log data. In Part 3, the author shows that process mining has many more uses and much more value than process discovery. It can be used for checking conformance to organizational standards and government/societal regulations, detecting deviations from norms and standards, and predicting delays and supporting decision making. In Part 4, the author discusses how to use ProM, a process mining tool, and structure the model development processes into four phases: extracting, constructing a control flow model, creating an integrated process model, and organizing operational support. The fifth part is a set of reflections on zooming-in and zooming-out process model layers similar to Google Maps. Because the book introduces the reader to the research that gave birth to the field of process mining, it is not an easy read. It is best suited for mathematically mature graduate students and researchers. BPM practitioners need to study this book, too, because it introduces crucial business process improvement, conformance, and optimization concepts. Online Computing Reviews Service