You have a target that you can't measure directly, hence you measure a proxy. That only works for as long as people don't game it and aim for the proxy instead of the actual target. Also, in addition, at least in research every statistician worth their salt knows that their proxy is not the actual thing and only their best effort at approximating it, hence in good studies, limitations of the methodology are extensively discussed.
Importantly, the moment you realise that your proxy is being gamed, you need to switch proxy.
I think this is only one example of this annoying trend of pretending to be "data-driven" by coopting numbers and fancy statistics without also adopting everything we know about uncertainty and how we can quantify it. "Data" in many businesses often implies a level of clarity ("look, the graph always goes up") that often does not actually exist and I suspect that this can be hard to understand for certain types of managers.
Output metrics chosen correctly also tend to represent things that the team/person has a reasonable degree of control over. For example, a developer KPI probably shouldn't be number of new customers because that's something they have vanishingly little control over, especially at an individual level.
The problem is that those things that a number of different teams are contributing to are probably the thing that the company cares about.
If there's a single KPI and all the reward is tied to that without any balance, sure that will be gamed.
But if there is a well-defined, appropriately complex reward function aligned with the utility of whatever the organization delivers to the outer world, I would consider that a positive.