If you have a lot say fifty, hundred, two hundred variables it is almost impossible to get most optimal score in all of them.
I will call it low-dimension problem vs. high-dimension problem
When you look for a perfect wallet that is a low-dimension problem, you may be able to find something perfect that scores the highest in all dimensions.
When you look for a partner, that is an example of high-dimension problem, and there may be like two hundred variables that you optimize for it may be impossible to find a partner that scores optimal in most of them.
Therefore the more dimension the problem has the more ready for being okay with not-ideal, with compromise one need to be.
Title: Approaching few-variable multi-variable problem. Should I use dimensions more vs. variables less