From Questions to Process Improvement: Mastering Process Mining Methods
Description
In this book, we offer a comprehensive and structured guide through the various stages of a process mining initiative. By initiative, we mean a substantial effort to leverage process mining techniques and tools for the analysis and potential improvement of business processes. As such, the book encompasses everything from the initial setup of the initiative to the translation of the analysis results to process improvement. Each phase is supported with methodical approaches grounded in research findings to support organizations in becoming more proficient in their process mining activities. Finally, it will also discuss how an organization can establish process mining as its own capability with the help of a maturity model.
With a strong emphasis on practical applications, this book goes beyond mere methodical support. Every chapter presents at least one real-world application, illustrating the principles with concrete examples and use cases from the public and private sector. This approach not only enhances the learning experience but also provides readers with tangible insights into how process mining can effectively be implemented and leveraged in real business scenarios.
This book will be an essential resource for anyone looking to harness the power of process mining to transform business operations, offering a blend of insightful research and practical, hands-on guidance for successfully executing process mining initiatives.
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Persons
Dr. Iris Beerepoot is an Assistant Professor in Information and Computing Sciences at Utrecht University. Her research focuses on work processes and how they are supported by and recorded in information systems. She published over 50 peer-reviewed articles in leading venues such as BPM, ICPM, Computers in Industry, and the Journal of Biomedical Informatics. She serves on various BPM and ICPM program committees, was awarded the BPM runner-up best dissertation award, and served as guest editor for the BISE journal.
Dr. ir. Xixi Lu is an Assistant Professor in Information and Computing Sciences at Utrecht University. Her research bridges Process Mining and Artificial Intelligence, developing methods to analyze, predict, and optimize complex processes using event data, with applications in healthcare and auditing. She has published over 50 peer-reviewed articles. She received the Best Dissertation Award from the IEEE Task Force on Process Mining in 2020 and serves as a senior member of the BPM and ICPM program committees.
Prof. Dr. Niels Martin is affiliated with the research group Business Informatics of the Faculty of Business Economics at Hasselt University (Belgium). His research topics include process analytics in healthcare, work organization mining, human resource mining, data-driven process simulation and process data quality. He published over 50 peer-reviewed contributions. As an active community member, he is a steering committee member of the Process-Oriented Data Science for Healthcare Alliance and a member of the IEEE Task Force on Process Mining.
Prof. Dr. Luise Pufahl leads the Information Systems professorship at the Technical University of Munich. She earned her PhD in Computer Science at the University of Potsdam and was a postdoctoral researcher at the Technical University of Berlin. Her research focuses on analyzing and automating resource and knowledge intensive business processes, including compliance and ecological sustainability. She has taught BPM and Process Mining for over ten years. She serves on the BISE Editorial Board and published more than 50 peer reviewed articles.
Dr. Francesca Zerbato is an Assistant Professor at Eindhoven University of Technology. She earned her PhD in Computer Science from the University of Verona in 2019. Her research centers on process mining, with a focus on supporting users through analytic provenance. Francesca published over 50 peer-reviewed articles and is PC member for the BPM and ICPM conferences. She serves on the Editorial Board of Artificial Intelligence in Medicine and is Associate Editor for the Journal of Data and Information Quality.
Content
1. Introduction to Process Mining.- 2. Running a Process Mining Initiative.- 3. Setting up a Process Mining Project.- 4. Building an Event Log.- 5. Handling Event Log Quality.- 6. Preprocessing an Event Log.- 7. Mining and Analyzing the Data.- 8. Assessing Process Mining.- 9. Translating Results into Process Improvements.- 10. Establishing Process Mining as Organizational Capability.