This assumes you can identify bad workers (for some metric of bad which may or may not be ethical or sensible)
This assumes you can identify bad workers (for some metric of bad which may or may not be ethical or sensible)
This not only assumes that you can identify bad workers, but that you can also identify some percent of "good workers that other companies identified as bad workers".
Shameless profit taking by executives and shareholders seems a lot more likely. Google and Microsoft providing PR cover for smaller companies to do it under the radar.
Good: P(good)=p Bad: P(bad)=(1-p)
Have a bad employee detector
P(detected as bad|bad)=q1
P(detected as good|bad)=1-q1
P(detected as good|good)=q2
P(detected as bad|good)=1-q2
Fraction of employees detected as good:
pq2+(1-p)(1-q1)
Fraction of employees detected as bad (and therefore fired)
p(1-q2)+(1-p)q1
Suppose you pay a discount on ability to hire new good employees as d (so probability to hire a new good employee is dp instead of p)
So you benefit as long as
p(1-q2)/((1-p)q1)<dp/(1-dp)
Or
(1-q2)/q1 < d (1-p)/(1-dp)
Plugging in p=.8, d=.5, q1=q2=q (knowing good and bad is equally hard)
(1-q)/q < .167
Break even is then
q = 1/1.167=.857
So if you start with 80/20 distribution and after a while improve your discrimination to 86/14 then firing benefits you even if you are hiring from a 40/60 pool.