5 Questions For Wil van der Aalst on His Process Mining Book
Prof. dr. Wil van der Aalst is widely regarded the “godfather” of process mining. He started process mining research at the Technical University in Eindhoven about twelve years ago. Recently, he published the first book on this topic, which is aptly titled “Process Mining”.
We had the privilege of reading drafts of this book, and it is really hard not to recommend it for everyone interested in process mining. Wil is one of the fewer academics writing in an accessible and down-to-earth manner, without skimping on clarity or scientific rigor, and without hyperbole. The book covers the fundamentals and basics of process mining, and gives a comprehensive overview about the state of the art of the field.
Wil was kind enough to answer five questions about his new book for us. He explained why BI is not really intelligent, who this book is for, and why you should read it.
Interview with Wil van der Aalst
Anne: This is the first book on process mining. I know that both academics and professionals have been waiting for a book on process mining. For whom did you write this book?
Wil: The initial goal was to write a shorter less technical book primarily focusing on professionals. However, while writing it became clear that the topic cannot be introduced without giving concrete definitions and examples. Therefore, the book does not shy away from technical details. As Einstein said: “Everything should be made as simple as possible, but no simpler”. As a result the book is interesting for both academics and professionals.
Anne: You make the point that most Business Intelligence systems are rather un-intelligent. What do you mean by that?
Wil: The problem of new technologies and tools in the field of Business Process Management (BPM) and Business Intelligence (BI) is that they are presented as silver bullets able to solve notoriously difficult problems with little effort. In reality such technologies seldom live up to their expectations as there is no such thing as a free lunch.
BI tools tend to be data-centric while providing only reporting and dashboard functionality. They can be used to monitor and analyze basic performance indicators (flow time, costs, utilization). However, they do not allow users to look into the end-to-end process. Moreover, despite the “I” in BI, most of the mainstream BI tools do not provide any intelligent analysis functionality.
Anne: You distinguish between ‘Lasagna’ processes, which are more structured, and ‘Spaghetti’ processes, which are unstructured. Where do you find them and how is process mining different for these two types of processes?
Wil: Lasagna processes are relatively structured and the cases flowing through such processes are handled in a controlled manner. Therefore, it is possible to apply all of the process mining techniques presented in the book (also more advanced techniques such as prediction and short-term simulation). Spaghetti processes are the counterpart of Lasagna processes. Because Spaghetti processes are less structured, only a subset of the process mining techniques described in the book are applicable. However, the potential process improvements may be much more substantial.
Spaghetti processes are typically encountered in product development, service, resource management, and sales/CRM. Lasagna processes are typically encountered in production, finance/accounting, procurement, logistics. The structuredness of processes also varies from industry to industry, e.g., processes in healthcare tend to have more variability than processes in manufacturing.
Anne: Which aspect of process mining deserves more space than it gets in your book and why?
Wil: The initial goal was to write a book of 200 pages. In the end the book was more than 350 pages. As a result, the book is comprehensive and self-contained. Although the book shows various examples of process mining results based on numerous real-life event logs, it would have been good to present a few case studies in more detail. Moreover, the relationship to Visual Analytics could have been discussed in more detail.
Anne: If someone is completely new to process mining, what would you hope is the biggest take-away point for that person?
Wil: Event data is omnipresent, thus enabling evidence-based BPM. Process mining combines techniques from data mining and process modeling and analysis. As a result, it is possible to analyze and improve business processes based on facts rather than fictive PowerPoint diagrams.
The threshold to start a process mining project is low. Therefore, it is best to experience the “magic” of process mining using data from your own organization. The book shows how this can be done and provides pointers to the software needed to start discovering and improving processes based on facts rather than fiction.
Preview and additional material
If you want to take a closer look at the book, here is the table of contents and an online preview of the book.
You can also download slides for every chapter in the book. Furthermore, all event logs and models that are used in the book are available here.
Update: Take a survey now and win the book!