Build a model you can question

A polished view can make uncertain information look more authoritative than it is. We prefer a model that gives people a reason to ask better questions.

Keep the source close

For each important input, record its origin, owner, update frequency and known limitations. Distinguish measurements from estimates and user-entered assumptions. A visitor should not have to guess which is which.

Show what is missing

Missing data is information about the model’s limits. An empty reading should not quietly become zero. A stale measurement should not appear current. Design these states deliberately and agree how they affect a decision.

Review the connection to reality

Choose practical checks with domain experts. Compare selected records with the physical system and inspect cases where the model behaves unexpectedly. Document what was tested and what remains uncertain.

A model becomes more useful when its users can question it. Traceability and explicit uncertainty make that possible.