I don't believe anyone is losing >1% productivity from these measures (at FANG employers).

When Apple switched to their own silicon, I was maintaining the build systems at a scaleup.

After I saw the announcement, I immediately knew I needed to try out our workflows on the new architecture. There was just no way that we wouldn't have x86_64 as an implicit dependency all throughout our stack. I raised the issue with my manager and the corporate IT team. They acknowledged the concern but claimed they had enough of a stockpile of new Intel machines that there was no urgency and engineers wouldn't start to see the Apple Silicon machines for at least another 6-12 months.

Eventually I do get allocated a machine for testing. I start working through all the breakages but there's a lot going on at the time and it's not my biggest priority. After all, corporate IT said these wouldn't be allocated to engineers for several more months, right? Less than a week later, my team gets a ticket from a new-starter who has just joined and was allocated an M1 and of course nothing works. Turns out we grew a bit faster than anticipated and that stockpile didn't last as long as planned.

It took a few months before we were able to fix most of the issues. In that time we ended up having to scavenge under-specced machines form people in non-technical roles. The amount of completely avoidable productivity wasted from people swapping machines would have easily reached into the person-years. And of course myself and my team took the blame for not preparing ahead of time.

Budgets and expenditure are visible and easy to measure. Productivity losses due to poor budgetry decisions, however, are invisible and extremely difficult to measure.

Actually, just time spent compiling, or waiting for other builds to finish makes investing in the top level macbook pro worth it every 3 years. I think the calculation assumed something like 1-2% of my time was spent compiling, and I cost like $100k per year.