Comment by godelski

  > A forest is much less efficient than a mall and yet, the forest might still be more important.

This is a good example of a very common problem: data isn't objective, it needs to be interpreted. Metrics will give you information, but they aren't the full story. That's why Goodhart's Law is so prolific. You can't just look at data and act on it without context. It depends what your actual goals are. And a huge part of that is that we have to consider how much we value things, especially things that haven't already been assigned monetary value. Sure, we can assign monetary value to things like a forest (economists do this), but it would also be wildly inappropriate to just accept those estimates as cold hard facts void of interpretation too. What's the saying? Reality has a surprising amount of resolution.

In a weird twist of irony our efforts to be lazy end up costing us a lot of work. But that's also because there's two types of lazy: short term and overall work. We used to say we want to hire programmers that are lazy because they'll find the most efficient way to do something. But now we don't revere that kind of lazy, we like the kind of lazy that procrastinates. Do the quick cheap thing now, telling ourselves that we'll make it better in the future, knowing that's a lie. That pattern isn't unique to programming, it's just marshmallows.