Top 10 Process Mining Books

This Top 10 list has been inspired by Joel at the Kaizone, a  content portal for lean books, blog posts and some fantastic resources. To take a look at his full list of the top 100 lean & OpEx blogs, click here.

For a selection of case studies, White Papers, reports, presentations & more, why not take a look at our original BTOES Insights content, or our excellent premium contributor content? Or for some wider reading, take a look at the Top 10 Operational Excellence Books.

Process Mining: Data Science in Action

By Wil M. P. van der Aalst

"This is the second edition of Wil van der Aalst’s seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes several additions and updates, e.g. on inductive mining techniques, the notion of alignments, a considerably expanded section on software tools and a completely new chapter of process mining in the large. It is self-contained, while at the same time covering the entire process-mining spectrum from process discovery to predictive analytics.

After a general introduction to data science and process mining in Part I, Part II provides the basics of business process modeling and data mining necessary to understand the remainder of the book. Next, Part III focuses on process discovery as the most important process mining task, while Part IV moves beyond discovering the control flow of processes, highlighting conformance checking, and organizational and time perspectives. Part V offers a guide to successfully applying process mining in practice, including an introduction to the widely used open-source tool ProM and several commercial products. Lastly, Part VI takes a step back, reflecting on the material presented and the key open challenges. 

Process Mining in Healthcare: Evaluating and Exploiting Operational Healthcare Processes

By Ronny S. Mans, Wil M. P. van der Aalst and Rob J. B. Vanwersch

"What are the possibilities for process mining in hospitals?  In this book the authors provide an answer to this question by presenting a healthcare reference model that outlines all the different classes of data that are potentially available for process mining in healthcare and the relationships between them. Subsequently, based on this reference model, they explain the application opportunities for process mining in this domain and discuss the various kinds of analyses that can be performed."

Process Mining in Action: Principles, Use Cases and Outlook

By Lars Reinkemeyer

"This book describes process mining use cases and business impact along the value chain, from corporate to local applications, representing the state of the art in domain know-how. Providing a set of industrial case studies and best practices, it complements academic publications on the topic. Further the book reveals the challenges and failures in order to offer readers practical insights and guidance on how to avoid the pitfalls and ensure successful operational deployment.

Process Mining: Discovery, Conformance and Enhancement of Business Processes

By Wil M. P. van der Aalst

"More and more information about business processes is recorded by information systems in the form of so-called “event logs”. Despite the omnipresence of such data, most organizations diagnose problems based on fiction rather than facts. Process mining is an emerging discipline based on process model-driven approaches and data mining. It not only allows organizations to fully benefit from the information stored in their systems, but it can also be used to check the conformance of processes, detect bottlenecks, and predict execution problems."

A Primer on Process Mining: Practical Skills with Python and Graphviz

By Diogo R. Ferreira

"The main goal of this book is to explain the core ideas of process mining, and to demonstrate how they can be implemented using just some basic tools that are available to any computer scientist or data scientist. It describes how to analyze event logs in order to discover the behavior of real-world business processes. The end result can often be visualized as a graph, and the book explains how to use Python and Graphviz to render these graphs intuitively. Overall, it enables the reader to implement process mining techniques on his or her own, independently of any specific process mining tool. An introduction to two popular process mining tools, namely Disco and ProM, is also provided. In this second edition the code snippets have been updated to Python 3, and some smaller errors have been corrected."

Bio-inspired Methods for Business Process Mining and Optimization

By Chifu Viorica Rozina, Pop Cristina Bianca & Salomie Ioan

"This book provides an overview on how biologically-inspired meta-heuristics can be applied to solve optimization problems encountered in the business process management domain. Thus, the book integrates, in a unitary approach, a set of biologically-inspired methods proposed by the authors, methods which address the problems of business process mining and business process optimization. The book is intended to be used by researchers, PhD students or Master students in Computer Science interested in learning how to apply biologically-inspired meta-heuristics in the domains of business process mining and business process optimization."

Applications and Developments in Semantic Process Mining

By Kingsley Okoye

"This book explores the need for the effective management of data across different process domains and the need for the enhancement of process mining results and analysis..."

Interactive Process Mining in Healthcare

By Danny Greefhorst & Erik Proper

"This book provides a practically applicable guide to the methodologies and technologies for the application of interactive process mining paradigm. Case studies are presented where this paradigm has been successfully applied in emergency medicine, surgery processes, human behavior modelling, strokes  and outpatients’ services, enabling the reader to develop a deep understanding of how to apply process mining technologies in healthcare to support them in inferring new knowledge from past actions, and providing accurate and personalized knowledge to improve their future clinical decision-making."