#169 Unlocking Efficiency Gains Through Process Mining with Wil van der Aalst and Cong Yu, Chief Scientist and VP Engineering at Celonis

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Dec 28, 2023

In this insightful conversation, Wil van der Aalst, a leading expert in process mining and Chief Scientist at Celonis, joins Cong Yu, VP of Engineering for AI at Celonis. They dive deep into how process mining uncovers hidden inefficiencies in organizations by analyzing event data. Key topics include the transformative power of predictive analytics, the importance of conformance checking, and the integration of AI technologies. They also discuss successful implementations and the future potential of process mining tools to revolutionize industry practices.

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INSIGHT

Process Mining vs. Data Mining/ML

Process mining is a unique technology, different from data mining or mainstream machine learning.
It mixes processes and data, making its algorithms unique and focusing on process improvement.

ADVICE

Starting Point for Process Mining

Start with standard financial processes like purchase-to-pay or order-to-cash when implementing process mining.
These have known data availability and common problems, providing an easy entry point and valuable experience.

ANECDOTE

BMW's Use of Process Mining

BMW, a major car manufacturer, uses process mining to analyze over 50 processes, demonstrating the wide applicability of the technique.
This ranges from car painting and servicing to financial processes, showing how diverse processes can benefit.

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Regardless of profession, the work we do leaves behind a trace of actions that help us achieve our goals. This is especially true for those that work with data. For large enterprises where there are seemingly countless processes happening at any one time, keeping track of these processes is crucial. Given the scale of these processes, one small efficiency gain can leads to a staggering amount of time and money saved. Process mining is a data-driven approach to process analysis that uses event logs to extract process-related information. It can separate inferred facts, from exact truths, and uncover what really happens in a variety of operations.

Wil van der Aalst is a full professor at RWTH Aachen University, leading the Process and Data Science (PADS) group. He is also the Chief Scientist at Celonis, part-time affiliated with the Fraunhofer FIT, and a member of the Board of Governors of Tilburg University.

His research interests include process mining, Petri nets, business process management, workflow management, process modeling, and process analysis. Wil van der Aalst has published over 275 journal papers, 35 books (as author or editor), 630 refereed conference/workshop publications, and 85 book chapters.

Cong Yu leads the CeloAI group at Celonis focusing on bringing advanced AI technologies to EMS products, building up capabilities for their knowledge platform, and ultimately helping enterprises in reducing process inefficiencies and achieving operational excellence.

Previously, Cong was Principal (Research) Scientist / Research Director at Google Research NYC from September 2010 to July 2022, leading the NYSD/Beacon Research Group, and also taught at NYU Courant Institute of Mathematical Sciences.

In the episode, Wil, Cong, and Richie explore process mining and its development over the past 25 years, the differences between process mining and ML, AI, and data mining, popular use cases of process mining, adoption from large enterprises like BMW, HP, and Dell, the requirements for an effective process mining system, the role of predictive analytics and data engineering in process mining, how to scale process mining systems, prospects within the field and much more.

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