The science behind
the ELICIT method

During his doctoral research at the University of Twente, Wouter Schotborgh investigated how to extract valuable experiential knowledge from an expert’s mind. He discovered that with just  110 targeted questions, you can record how an expert performs their work. This discovery proved to be the seed of ELICIT.
Read about the discovery here

12 years of scientific research

600+ knowledge models created

110 targeted questions,
5 interviews of 2 hours

Wouter Schotborgh
Founder

Two hundred experts,
one pattern

At first glance, the experts Wouter spoke with had little in common. One develops wafer steppers, another maintains a three-stage steam turbine. The work experience of the experts ranged from a few years to over 49 years.
None of these experts could easily explain or write down their own knowledge to colleagues, because they largely act intuitively. They process dozens of signals simultaneously, weigh them based on years of experience, and then reach a decision that they can hardly reconstruct afterwards.  

Wouter discovered that every expert is exceptionally good at recognizing whether something is going right or wrong, and knowing what needs to happen next. That combination—signal and action—forms a cause-and-effect chain. Not a collection of loose tips, but a structure.

That structure proved to be reducible every time to a knowledge model containing the most essential parameters. Decades of experience, summarized and recorded in a digital knowledge model containing an expert’s decision-making knowledge.

From discovery
to method

Every process, every machine, and every function requires a different kind of knowledge. Therefore, Wouter continued to work on modeling the decision-making logic for various knowledge domains. Wouter translated his discovery into a method that was repeatable for every factory, every industry, and every expert.
In just 5 structured interviews with experts, the ELICIT method maps out the essential knowledge and decisions regarding a process or machine.

Many people react skeptically when we tell them this. Five interviews for thirty years of experience?! This works because we focus on an expert’s decision-making logic: How do you know it is correct? What do you see? And what do you do then? In this way, we extract decision-making knowledge from the expert’s mind in a structured and efficient manner.

Proven more than 600 times

On average, 110 targeted questions are needed to uncover the core of someone’s experiential knowledge. Our knowledge analysts know exactly which questions those are, and we have already applied this more than 600 times.

The result of these interviews is a structured digital knowledge model of someone’s experiential knowledge: usable for everyone, directly available on the shop floor, and available in more than 30 languages.

View the results