I think there's some degree of nuance that isn't captured with comments like yours. I agree with your comment in principle, but there are interpretations of this method that are too extreme and that's where most of the bad MVPisms come from (and what I assume this blog post is a response to). As with any process, what most people are doing is not what was intended, and so we have to discuss what people are doing more so than the theory.
Data is only as valuable as the insight, understanding and intuition at the disposal of those gathering and actioning the data. There are organisations that truly embrace this idea of "we know nothing, the data will guide us" and they get lost because they're chasing a bunch of numbers for the sake of numbers on weak experiments that don't marry up to anything of meaning.
You need some amount of difficult-to-define "understanding" and "intuition" to be able to turn any learnings (whether gathered from experience or data) into a product: without it, you'll fail, regardless of process. There are many successful products that started out as someone absolutely committed to a belief in what is needed by the market, there are many successful products that were developed by following the data from day one, and likewise there are many unsuccessful products following both patterns.
My personal disdain for MVP-ing is exactly because it is so difficult to get right, and is very easy to get wrong, and it leaves little room for corrective action: I'm sure we all have experience with zombie startups, years old, still frantically "MVPing" everything under the sun. Personally, I'd much rather work within an organisation that has a clear vision about the problem they're trying to solve with flexibility around how it is to be solved, even if it ultimately leads to failure.
Customers lie, but so does data.