Fine – in the right circumstances.
Most of us use "rules of thumb" in all sorts of areas of our daily lives. "When the needle on the fuel level indicator gets to the red, I know it'll last at least another 20 miles", for example, or "Software with a user interface that's anything other than grey or blue hardly ever gets through the user acceptance testing."
These rough rules, based on experience, are invaluable because they help us to make decisions without further detailed fact-finding: Drivers know they don't need to divert immediately to find a fuel station, and the software designer can save him or herself rework later by making the interface blue or grey in the first place.
But no one expects these rules to be 100% accurate: If the car ran out of fuel in 18 miles, the driver wouldn't be particularly surprised, and if testing showed that users actually liked an application that had a tasteful green interface, the developer might raise an eyebrow, but that would be all.
This is because rules of thumb are only used in situations where the risks associated with using a "good enough" approximation are acceptable. No one would use a rule of thumb such as this fuel usage one for a F1 racing car: They'd do a detailed analysis of the exact amount required to cover the race distance.
The formal term for these rules of thumb is "heuristics". Heuristics are a topic of interest in various fields from computer science to psychology and philosophy, but the principle is the same in all of these.
Because a heuristic is a model which offers only a limited representation of reality, it should only be used when...
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