Lately, we have experienced this.
As a Talent Acquisition, I have experienced the pressure of balancing the two.
A fast process is excellent, but it isn't very sensible if the quality of candidates being brought on board isn't up to par.
On the other hand, a perfect process may take too much time and leave us missing out on top talent.
We actually gave a masterclass on "How To Be An Amazing Interviewer In Tech". I can finally link it on a relevant question, woohoo!
How to hire quality engineers in a short time?
So... you can't really. I have a couple thoughts here, but these are all much easier said than done.
A fast process is excellent, but it isn't very sensible if the quality of candidates being brought on board isn't up to par.
On the other hand, a perfect process may take too much time and leave us missing out on top talent.
I feel like this is actually a big reason why Big Tech interviews are so data structures and algorithms (DSA) heavy. These interview processes are quite easy to spin up as they're very formulaic, and this allows Big Tech to process tons of candidates really quickly. In general, if the interviewer is doing a good job gathering signal as we talked about in the masterclass, those who pass will be solid engineers.
The problem with DSA interviews is that they're quite soulless and will lead to a ton of false negatives. There are so many great software engineers that don't want to spend 100+ hours studying how to invert a binary tree.
So if you have massive candidate volume and want to process them efficiently without letting in false positives (i.e. they pass the interview but actually suck), you could just spin up a standard Big Tech DSA interview. The downside is that, well, pretty much everyone hates DSA.