In order to get any insight into whether a chosen course of action is working or not, you need to be able to perform some type of measurement. All of these measurements are called metrics. The default single metric that every company has available to them is revenue, but really you want to have feedback loops that provide insight prior to performing a measurement to determine whether you're bankrupt or not. The more precisely you try to measure something, the more uncertainty and error you're going to introduce to your measurements, something that's true for all forms of empirical measurement.
If you point was that companies are generally bad at doing this, or that they often measure the wrong things, or that the process can be abused, or that you should not attempt to measure something beyond a certain level of precision, then I'd agree with you. But to write the entire process off as useless is just as unproductive as the problematic situation you're criticizing.
There's measurements (say, increase in customer retention as a % after a new feature is deployed) and then there's heuristics (discussing the feature with customers to gauge sentiment, being careful not to fall prey to bias or lead the customer's answers).
My point is that an obsession with empiricism can make you think that only #1 is valid evidence and thus use it for qualitative analysis where it should not be used.
Only using metrics for feedback is giving yourself tunnel vision.
If you point was that companies are generally bad at doing this, or that they often measure the wrong things, or that the process can be abused, or that you should not attempt to measure something beyond a certain level of precision, then I'd agree with you. But to write the entire process off as useless is just as unproductive as the problematic situation you're criticizing.