Process Mining

Learn about basic theories of process mining, different tools and performing a process mining analysis.
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This course is part of
Transforming Logistics with Analytics
Arthur van de Molen, Jose Huisman, Dennis Moeke, Arjen Wierikx & Frazen Tolentino Zondervan

About the course

Process Mining can roughly be defined as a data-driven approach to process management. The basic idea of process mining is to automatically distill and to visualize business processes using event logs from company IT-systems (e.g. ERP, WMS, CRM etc.) to identify specific areas for improvement at an operational level. An event log can be described as a database entry that signifies a specific action in a software application at a specific time. Simple examples of these actions are customer order entries, scanning an item in a warehouse, and registration of a patient for a hospital check-up.

Process mining has gained popularity in the logistics domain in recent years because of three main reasons. Firstly, the logistics IT-systems' large and exponentially growing amounts of event data are being stored and provide detailed information on the history of logistics processes. Secondly, to outperform competitors, most organizations are searching for (new) ways to improve their logistics processes such as reducing costs and lead time. Thirdly, since the 1970s, the power of computers has grown at an astonishing rate. As such, the use of advance algorithms for business purposes, which requires a certain amount of computational power, have become more accessible. 

Before diving into Process Mining, this course will first discuss some basic concepts, theories, and methods regarding the visualization and improvement of business processes.

Course subjects

More about the authors

Arthur van der Molen

Arthur van der Molen was a Lecturer and researcher at Rotterdam University of Applied Sciences. "Arthur was a highly skilled specialist in the field of AI." - Dr. Ron van Duin

We dedicate the content of "Transforming Logistics with Analytics" to Arthur van der Molen. Without his knowledge, wisdom, and creativity, we certainly would not have come this far.

We remember him with the deepest respect and admiration.

On behalf of the team, Dr. Dennis Moeke

José Huisman

José Huisman MSc. is lecturer at Fontys ICT in Business Processes. From a business perspective, José is experienced with technology based process improvement in logistics and the manufacturing industry. Innovation is realized by using Process Mining, low-code application platforms and Robotic Process Automation. As a researcher José is involved in the research group High Tech Embedded Software.

Dennis Moeke

Dennis Moeke is professor in Logistics and head of the Research Group Logistics and Alliances at the HAN University of Applied Sciences. He has a special interest in Healthcare- and Data-driven Logistics. In addition, he is also a member of the executive board of the National Centre of Expertise KennisDC Logistiek and represents the HAN in the executive committee of Logistics Valley.

Arjen Wierikx

Ir Arjen Wierikx is a Senior Researcher and Lecturer at HU University of Applied Sciences Utrecht and a Ph.D. candidate at Eindhoven University of Technology. He is acquainted with the Bachelor of Logistics Management and the Master of Data Driven Business, primarily coaching students in their final thesis. Within the research group Process Innovation & Information Systems, his research focuses on making Circular Performance of Organisations measurable and explicating the effect of Digital Technology Strategies on this Performance. Arjen holds an MSc degree in Civil Engineering from TU Delft and a post-hbo degree in coaching from Phoenix. He has a strong background in Logistics, Information, and Change Management. Prior to joining the HU, he worked for TNO and Baan (Infor) and has been running his own consulting firm for over 20 years.

Frazen Tolentino-Zondervan

Dr. Frazen Tolentino-Zondervan is an assistant professor of global value chain management at Amsterdam School of International Business (AMSIB) of Amsterdam University of Applied Sciences. She teaches bachelor and master courses related to sustainability and innovations in global value chain and supply chain management. She participates in academic and practice-oriented research related to supply chain digitalization, circular economy, and data science at international and national levels. Her teaching and research incorporates data driven techniques such as blockchain, data visualization, text mining, and simulation and applies these to solve supply chain related problems.

This publication is part of the project ‘small projects 2022 route transport and logistics' with project number NWA.1418.22.023 which is financed by the Dutch Research Council (NWO).