At my former job at a FAANG, I did the math on allocating developers machines with 16GB vs 64GB based on actual job tasks with estimates of how much thumb twiddling waiting time that this would save and then multiplied that out by the cost of the developer's time. The cost benefit showed a reasonable ROI that was realized in Weeks for Senior dev salaries (months for juniors). Based on this, I strongly believe that if…
No doubt the math checks out, but I wonder if developer productivity can be quantified that easily. I believe there's a lot of research pointing to people having a somewhat fixed amount of cognitive capacity available per day, and that aligns well with my personal experience. A lot of times, waiting for the computer to finish feels like a micro-break that saves up energy for my next deep thought process.
Configuring devices more generously often lets you get some extra life out of it for people who don’t care about performance. If the beancounters make the choice, you’ll buy last years hardware at a discount and get jammed up when there’s a Windows or application update. Saving money costs money because of the faster refresh cycle.
My standard for sizing this in huge orgs is: count how many distinct applications launch per day. If it’s greater than 5-7, go big. If it’s less, cost optimize with a cheaper config or get the function on RDS.