> The idea that Google has internal research indicating this wouldn't be surprising to me.
The problem with internal research on these matters is the nearly total lack of negative examples. Depending on the quality of the pre-on-site screening the quality of candidates at that point might be so high that random selection might be just as good.
A negative example would be someone who scored good within the interview process, but then performs bad on the job (bad performance rating).
Such examples get discussed internally by the hiring committee (senior people doing the last hiring decision for every candidate).
I think the biggest issue with the current approach among faang interviews is that a lot of really good people get filtered out (false negative) - but faang get so many applications that they are ok with this.
And yet, googles previous public comments on the topic are somewhat the reverse - all their interview question except for questions on previous work/experiences were not correlated with "success".
Scare quotes used because knowing how to define success is an even more hairy question that we (industry, humans) dont have a good grasp on either. So any criteria you use might be wrong or a subset of the right (where "wrong" means you would change your conclusion if you saw the bigger picture, which none of us can.)
The problem with internal research on these matters is the nearly total lack of negative examples. Depending on the quality of the pre-on-site screening the quality of candidates at that point might be so high that random selection might be just as good.