Capitalize in order to anticipate retirements

With the help of i2Kn, this firm created a decision tree mapping the process of an expert capable of solving a complex production chain problem. Anticipating the departure of this person from the company will allow for his or her knowledge to be preserved and used even after he or she has left the company.  


Company: A company specialized in glass production, transformation and distribution.

Need: An expert is able to describe every flaw observed in the glass and can detect the origin of the problem all the while preserving production yield figures. The goal here is to capitalize on the expert’s capacity, simply from studying a photo of the flaw, to determine the right solution pathway and adjust the materials according to the factory’s technical parameters.

The difficulty lies in the modeling of the various scenarios of technical and scientific reasoning.


The expert is interviewed in order to record his or her thought pathway and build a causality tree.

The final goal is that the database will re-transcribe the expert’s knowledge in production chain problem resolution.


The intelligent database i2Kn was built and tested with new arrivals on the resolution of a complex problem already identified by the company. Using i2Kn, the test participants followed the decision tree created by the expert and reached a solution.


Preserve a company’s knowledge heritage and hand down a powerful complex problem-solving approach.

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