Here is an example: target metrics are heavily manipulated and people don't really want to know what's going on. At my first job the Director of Product would change the way a target KPI was measured every few months but would not back-propagate the changes, the end result was that to upper management the product always looked good, because the product owner would just redefine the metric in a way that made the numbers go up. This was at a multi-billion marketcap company in the SP500 and this particular person was promoted two levels to managing vice president in 1.5 years.
Basically, like some other people have already said, companies are inherently political - they do not want data-driven decisions they want their decisions to be data-validated. If their view of reality aligns with the data that is all the better, but if it doesn't, their alignment takes priority. Moving up as a DS then involves delivering "evidence" that fits whatever narrative your boss and senior management want. Sometimes that evidence will be rock solid, other times there is no evidence. That's why I suspect in the beginning they loved hiring STEM PhDs from "elite" universities. If your degree is from Harvard Astronomy Dept, people will borrow your credentials to further their agenda - because you got a golden halo.
TLDR: science is not gospel, it's just a method of thinking to deduce natural laws, if you keep digging you can find your initial assumptions proven wrong, sometimes completely wrong, - in business and politics if you dig too hard, you start finding things that nobody wants to hear.
Regarding your point about owning profit and loss that is very true as well. In my second job I was in a center of excellence team and it was extremely hard to get any traction because we didn't own any sources of revenue so we were a cost center like HR or Accounting. Teams that owned LOBs want to hire their own analytics rather then "outsource" to a COE team as a way to retain control and expand their own power base.
Would I ever do it again? Who knows, maybe, I still believe it's possible to do good scientific work outside of academia (not to say good science always gets done in academia either). I am living off investments and savings right now and working on hobby projects that may or may not pan out. People always take less than ideal jobs for want of reality.
I think there is real value in scientific analysis in business but it's closer to operations research where you solve complex optimization problems that are directly pertinent to the core business (like traffic routing or container packing) than in busting out the latest DNN techniques.