I often think of Pareto efficiency in terms of decision making. The closer you get to the Pareto frontier (of the space of possible solutions), the harder it is to make any decision Pareto efficient. Meaning for almost all decisions, you’re going to have to sacrifice something. For instance when you do a big refactoring of a system it’s easy to get hung up on trying to preserve all features while adding a few new ones. In reality this is going to be extremely hard or impossible. If you can do it possibly it’s because you forgot to include some other axis in your analysis, like code complexity. It’s like pushing a balloon into a box. loss aversion may sometimes be explained by people trying to make Pareto efficient decisions. My conclusion from this silly example is that you should really think twice before assigning the responsibility of a functional area to a single person. A simple model for why buying decisions are so hard is that it involves Pareto effiency – market economy will drive out all TV’s that are dominated, leaving only the TV’s on the Pareto frontier. That makes it a lot harder as a consumer because now every choice will become a trade-off. Whereas in something like clothing there’s a lot of dimensions, so you should expect a more fragmented market.