Let me throw in what might be a useful term: "unobservable".
Take, for example, the standard deviation of a time series. We can certainly make estimates of it, but the actual volatility is unobservable directly, we can only see its effects. A large chunk of statistics is, in fact, dedicated to making estimates of unobservable quantities and figuring out whether these estimates are any good.
Another useful term is "well-defined". For example, look at inflation. Inflation in general (defined as "change in prices", more or less) is not well-defined and different people can (and do) propose various ways to quantify it. But if you take one specific measure, say in the US a particular CPI and define it as a number that comes out of specific procedure that the BLS performs every month, then it becomes well-defined.
Just to nitpick, the standard deviation of a time series is not even well-defined unless we know that the series is stationary. In Shalizi's words, "if you want someone to solve the problem of induction, the philosophy department is down the stairs and to the left". If it were well-defined (e.g. if the time series were coming from some physical process with rigidly specified parameters), it would be just as observable as the mass of the moon, i.e. indirectly. That would fit my criteria for a "true number".
I guess that for me a "tru...
If you believe that science is about describing things mathematically, you can fall into a strange sort of trap where you come up with some numerical quantity, discover interesting facts about it, use it to analyze real-world situations - but never actually get around to measuring it. I call such things "theoretical quantities" or "fake numbers", as opposed to "measurable quantities" or "true numbers".
An example of a "true number" is mass. We can measure the mass of a person or a car, and we use these values in engineering all the time. An example of a "fake number" is utility. I've never seen a concrete utility value used anywhere, though I always hear about nice mathematical laws that it must obey.
The difference is not just about units of measurement. In economics you can see fake numbers happily coexisting with true numbers using the same units. Price is a true number measured in dollars, and you see concrete values and graphs everywhere. "Consumer surplus" is also measured in dollars, but good luck calculating the consumer surplus of a single cheeseburger, never mind drawing a graph of aggregate consumer surplus for the US! If you ask five economists to calculate it, you'll get five different indirect estimates, and it's not obvious that there's a true number to be measured in the first place.
Another example of a fake number is "complexity" or "maintainability" in software engineering. Sure, people have proposed different methods of measuring it. But if they were measuring a true number, I'd expect them to agree to the 3rd decimal place, which they don't :-) The existence of multiple measuring methods that give the same result is one of the differences between a true number and a fake one. Another sign is what happens when two of these methods disagree: do people say that they're both equally valid, or do they insist that one must be wrong and try to find the error?
It's certainly possible to improve something without measuring it. You can learn to play the piano pretty well without quantifying your progress. But we should probably try harder to find measurable components of "intelligence", "rationality", "productivity" and other such things, because we'd be better at improving them if we had true numbers in our hands.