A lot of people think that the work is done when they have a process be visualized in their process mining tool and a nice dashboard is built. Nothing could be further from the truth and our guest today, Sebastian Kotulla, talks with us about why that is. To bridge the gap between visualizing data/information to knowledge as the result of the analysis Lean techniques can be applied.

Sebastian has a strong focus on and passion for digital solutions to support business transformation such as virtual factories, computer vision, AI, process mining and engines. As Lean Six Sigma Black Belt and Prosci Certified Change Practitioner he's used to run and consult in transformational initiatives from concept to successful implementation.

In this episode of the podcast we are talking about:

Sebastian’s background
Define - (DMAIC and how to apply this to process mining, CRISP framework, leading and lagging indicators)
Analysis (flow is key in Lean, different types of waste (TIMWOODS), Process Mining gives the reference points for the Control phase, Theory of constraints / bottlenecks, most of the problems are outside of the discovered process model!)
How to prioritize which process to choose
How to do the analysis - first look to define the problem (time analysis, Gemba)
Fishbone to structure hypotheses (manual cluster analysis) - Find the story in your analysis, five Whys to find the systematic problems
FMEA analysis risk analysis > risk simulation
Design of experiments - statical method on how to design an experiment and then make predictions from the result; understand input variables better
Advanced analysis
A practical project example

Sebastian can be found on LinkedIn here: https://www.linkedin.com/in/sebastian-kotulla-1645ab88/ and also be contacted via email: sebastian@digitalprios.de.

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Dan Murata

The AI-powered Podcast Player