The problem with streetlight science isn't that it relies on easily-measurable proxy variables.

See Douglas Hubbard's book "How to Measure Anything" (and related blog) for a discussion. Basically, he says that in the presence of uncertainty it's better to measure something and then discusses how to do that.

The joke illustrates the streetlight effect: we "tend to look for answers where the looking is good, rather than where the answers are likely to be hiding.

In the Edge Annual Question for 2013 Information Scientist Bart Kosko discusses this in the context of which probability models we tend to use (tl;dr):

30) Bart Kosko fears that, like the drunk looking for his keys in the lamplight because that’s where he can see, we restrict ourselves to just five probabilistic models because they are easier to teach and calculate. The result is that we’re not modeling the world as well as we could be, and the negative effects may especially hamper the Bayesian revolution in probabilistic computing.

Full answer here.