Falsifiability
We actively look for the conditions where the solution might fail, not just those where it works.
This is the phase where many stop and where we make the difference. It's not enough that it "seems to work": you must prove it with data, under conditions representative of reality, with acceptance criteria decided in advance. No claim without evidence.
We distinguish two different questions: verification — "are we building it right?" — and validation — "is it the right thing, does it do what's needed?". We run experimental campaigns under conditions close to real ones and compare the results with the model and with the established criteria.
From scientific laboratories we bring a precise discipline in proving things.
We actively look for the conditions where the solution might fail, not just those where it works.
A result counts if it can be repeated by others, with the same procedure: we document it so it can be.
Results undergo an internal peer review, as in research, before being declared valid.
Data that proves performance and reliability, with their margins.
We know under which conditions the result repeats: the basis for industrialization.
Everything tracked and retraceable: useful for quality, audits and patents.
We put scientific method at the service of proof: solid, replicable evidence. See also the Scientific validation.
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