Yes, I speak from bitter experience.
When I was at IBM, post acquisition, they were trying to move a company into open space from their existing offices and the former CEO presented them with incontrovertible evidence of work productivity vs offices vs cubes vs openspace vs individuals. To explain that to maximize work done per unit time they needed a mix of offices and open space, just open space would harm the productivity of the team. The VP on the line kept falling back to "but everyone else has to do this" and "you aren't seeing the big picture" kinds of arguments. It was really sad.
The truth is that "office space", which is to say the number of square feet (or meters) of office space you need per employee is a "cost." And that cost is computable, whereas the cost of less productivity, or inability to attract the best talent, are not. And when you run your company with accountants they go for the "known savings" over the "potential gains" every, single, time. You can put more employees in a building that is "open plan" than you can in one with cubicles, and much more than in a building with offices. So the accounts force this on the company and senior leadership doesn't have the stones to contradict them.
Until it becomes quantifiable, cost does not exist for some people.
Numeric metrics are certainly not the only way to bolster an argument but I'd be curious to hear more about the type of evidence the CEO used to make their case.
Basically this guy was really (and I mean really) analytical about characterizing as many things as possible to understand whether or not they had impact on the overall ability of his company to produce quality products and support.
What struck me though was IBM was completely unwilling to engage on the facts. And that is largely because IBM is run by their finance group.
And the CEO here wasn't trying to tell IBM that every facility should be run that way, just that they felt justified in demanding that their facility be run that way.
Anyway, IBM couldn't (or wouldn't which is expressed externally in the same way) see it and proceeded with their plan. The entire time I was there helping to integrate our startup (Blekko) I saw IBM make stupid choices like this again and again.
I see this pattern as the biggest contributing factor to IBM never getting out of the starting gate with machine learning as a product enhancer. Trapped in their own complexes and being unable to step outside of them in a controlled way left them unable to execute against what could have been a really good strategy for them.
It was the same at the Santa Clara Sun campus even after the Oracle acquisition (referred to by some as “Snoracle”). Mostly offices and some cubicles here and there.
Tell me the incentives and I can tell you the outcome.
VR makes more sense in the office now.