Comment by fsk
11 years ago
This has got to be the biggest hiring fallacy I've ever heard. "It's better to reject a good candidate than hire a bad candidate."
That's completely false, and anyone who says that is completely ignorant of Bayesian logic.
Here are some simple numbers.
Suppose that a "good" candidate is a 1-in-100 find. Suppose that a "bad" candidate has a 1% chance of tricking you into hiring them anyway.
Every time you pass on a "good" candidate, that is greater opportunity for a "bad" candidate to trick you into hiring them!
Counterintuitively, if you pass on too many of the "good" candidates, in your overzealousness to reject bad candidates, you're actually INCREASING THE ODDS OF A BAD HIRE.
This is management porn. "It's better to reject a good candidate than hire a bad candidate." It makes the manager feel good. "Wow! That candidate seemed smart, but I rejected him anyway! I'm such a great leader! I make the tough decisions!"
tl;dr summary
Because "good" candidates are rare, every time you pass on a good candidate that increases your odds of making a bad hire! This is simple Bayesian reasoning!
Those are simple numbers, but they don't get at the real issue. People say that because 1 bad hire can have negative effects on the whole team, causing others to get less done and leave. Missing a good hire doesn't poison your team.
But 1 bad hire is easily correctable - you fire the person. You won't know that you missed on the good hires.
I personally have worked with several awesome people that have interviewed with Google, and none of them got hired. They all said the interview process was flat out insulting.
Interestingly enough, most of them ended up at Facebook.
>>But 1 bad hire is easily correctable - you fire the person.
Not sure if you have ever been a manager, because firing someone is NEVER easy. It hurts everyone emotionally. The person getting fired feels awful. The person doing the firing feels awful (unless they are a real sociopath). And team morale tends to take a big hit.
Here is my stance: if you hire someone who isn't a good fit, unless they actively deceived you, it is your god damn job to find a way to make it work. As a principle you should treat people with respect and dignity, and not as easily disposable and replaceable cogs.
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The good and bad the op is talking about is different. If the attitude is not the best, you don't hire anyway.
If the candidate cannot invert a binary tree and gets mostly there, and has demonstrable real world software, it's a different thing.
> invert a binary tree
What does that even mean? Swap left-right child nodes? Write it linearly (n-th children at 2n and 2n+1) and reverse it as if it was a string? OP later described it as "to min-max the tree, ascending to descending." confusing me further.
>People say that because 1 bad hire can have negative effects on the whole team, causing others to get less done and leave. Missing a good hire doesn't poison your team.
That doesn't disprove what he said. In fact it strengthens it and makes missing a good hire even worse, because, as he said missing good hires -> MORE change of bad hires (that can "poison your team").
In other words, it's not a choice: "I'm better of rejecting a good hire than getting a bad one, because a bad one could poison the team".
By rejecting good ones, who're actually getting MORE bad ones. So it should be corrected to:
"I'm better of NOT rejecting good hires, or else I'll get more bad hires and poison my team".
This is akin to banning food because people might get a stomach ache, and this is bad for the team.
> Counterintuitively, if you pass on too many of the "good" candidates, in your overzealousness to reject bad candidates, you're actually INCREASING THE ODDS OF A BAD HIRE.
Yes, but what hiring managers are doing isn't passing over candidates that they know are good, they're passing over candidates that they're not very sure about.
> Because "good" candidates are rare, every time you pass on a good candidate that increases your odds of making a bad hire! This is simple Bayesian reasoning!
Similarly, of course this is true, but again hiring managers aren't passing up candidates that they know to be good, they're passing up on candidates that they're not sure about, whom the acknowledge could be good.
Under certain conditions, every time you pass on a candidate you're not sure about, you decrease your chance of making a bad hire. The conditions are that increasing hiring standards must weed out more bad candidates than good candidates.
Let's work with your model. Suppose 1% of candidates coming for an interview are good and 99% are bad.
Hiring strategy A manages to hire all good candidates it interviews, and 1% of the bad candidates it interviews. End result: for every 100 people you interview, you get 1 good candidate and 1 bad candidate.
Hiring strategy B is more conservative and hires 50% of all good candidates it interviews, and 0.1% of the bad candidates it interviews. End result: for every 100 people you interview, you get 0.5 good candidates and 0.1 bad candidates.
The claim is something like, the team produced by strategy B is better than the team produced by strategy A, even though team B has less good candidates than team B.
The slogan represents the opposite. You hire only 10% of the good candidates but the odds of hiring a bad candidate are cut to only 0.5%.
I agree with you that if hiring strategy B led to hiring 10% of the good candidates and cut the odds of hiring the bad candidate to 0.5%, compared to 100% and 1% for hiring strategy A, then strategy B is worse than strategy A. However
1) This means that by raising your hiring bar (adopting B instead of A), you eliminate more good candidates than bad candidates. You now have to prove this empirical claim. 2) All I wanted to say was that the statements you made like "every time you pass on a good candidate that increases your odds of making a bad hire!" is only true under certain conditions (namely that raising hiring standards eliminates more good candidates than bad candidates), and it's not "simple bayesian reasoning".
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This is not about numbers.
A bad hire can easily cause more friction than if nobody was hired at all. Net effect for the business is negative. You're also probably severely overestimating the likelihood of a bad hire going through.
Bad hires can be fired. Bad rejections poison the well for hiring the good candidates who never apply because of hearing about all the bad rejections.
Bad hires can be fired.
But the cost and other effects of doing so vary significantly depending on where you are. Most of the US may have at-will employment, but much of the rest of the world does not.
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You can fire a bad hire. You can't hire someone you already rejected because a few weeks later they already have a job.
Easier said than done.
We had a really bad hire about 2 years ago. So bad it caused us to review our entire hiring process to understand how he got in. It took almost a year before he was fired (and he was a contractor so it should have been easier). In that time, he used up untold resources while we tried to find work he could actually do, people helping him "just in case he just needed a helping hand" and so on. Finally after wasting other people's time for 9 months, a manager made the decision to get him out.
A year later I got an email from him asking for a recommendation. Nothing ventured, nothing gained I guess.
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Doesn't understand bayesian logic! Doesn't understand risk management!
Idiot: We don't want to make any bad hires! Therefore, we reject a lot of good candidates!
FSK: If you pass on many good candidates, and you have a small chance of hiring any given bad candidate, then each good candidate you reject actually INCREASES your odds of making a bad hire.
Idiot: We made a bad hire once! Never again! Now we reject lots of good candidates to avoid that repeat disaster!
FSK: But, if you want to minimize your bad hire rate, you also have to minimize the number of good candidates you reject.
Idiot: NO! NO! NO! The way you make sure you hire no bad candidates is to be so strict that you reject lots of good ones! That's what everyone told me so it must be right!
In one ear and out the other. Why do people who don't understand statistics get to be managers? If you don't understand this statistics argument I made, you're unqualified to work in any sort of technical area.
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Not really. The population is large enough that you're treating each potential hire as a random variable. Given the amount of possible good new hires the effect of passing on one actual good hire has negligible effect on the next potential hire.
The theory behind the "raise the bar" argument is that obviously good hires are easy to spot (this is the part most people reasonably take issue with), so people who do not pass that bar of "obviously good" aren't worth taking a risk on. The conclusion is statistically reasonable if you accept the premise (which, again, you probably shouldn't).
> The population is large enough that you're treating each potential hire as a random variable.
This is only true for new grads. The population of engineers with ten years of appropriate corporate experience (that match the technology survivor bias) and at the ~12 locations google can use is tiny.
When I look at my old corporation, only 3 people (of 500+ I would be aware of) were hired by google. One of them is genuinely great, but I doubt he passed the current process as a blind hire. The other two I wouldn't want to work with, but I bet they passed this process precisely because the right kind of focus. (I.e. everything people around them didn't know was their priority and since we normally focus on what's important to completing our project, none of that was so important..)
I was very interested in google when I was under the impression that (without experiencing menlo park on a daily basis,) I could either walk away with over $500k (gross) in 2- years, enjoy working there for 5 years, and/or work with the best >experienced< engineers in our field. When glassdoor and my own linkedin network revealed my best perspective into their setup, blind applying to them is now just a good filter to test my new age employability skills. So, now they've built themselves a new problem of true positive false positives who are just along for the ride.
The hiring market is already NP Hard for both sides when you are genuinely trying to get a good enough fit for yourself rather than the best deal on the market. If you try to misuse the other side they will see less ethical constraints in using the resources you'll have to put in.
How many developers genuinely want a job they can't do that they will have to be awkwardly fired from in six months and explain at every future interview?
The difficult thing with hiring bad candidates vs not hiring bad candidates is that you get to experience the bad hire every single day, so it is quite apparent that you made a mistake. With not hiring a good candidate, you don't really know what you were missing. You may just assume that the best applicant you reject is no better than your average employee. But there is a chance that that person would bring something to the table so unexpected that you can't even imagine the world that would have been had you hired them.
Obligatory reference to tptacek's post at http://sockpuppet.org/blog/2015/03/06/the-hiring-post/ -- see the end of chapter 2 for an amazing example
Apparently you hadn't been recruiting anyone in Europe. Once you've hired a bad candidate, it is very hard to get rid of it (borderline impossible in Scandinavia, for example).
You're conclusion rests on the numbers you start with, those aren't a given.
I understand your point, and I'm not trying to be a troll.
Humans are more complex than that. I don't think you can assume that candidates will perform the same all the time. Sometimes an excellent candidate can perform badly for multiple reasons (e.g. nervousness, poor preparation, bad interviewer, personal problems, etc).
It seems to me, that rejecting a good candidate, and have him/her interview again after some time, if that candidate was a 'good-hire', then it would increase the chance of hiring him/her, since it is most likely they will prepare better, and know what to expect.
Why would anyone who has a job waste a vacation day to interview at a place that previously rejected him?
If your flawed process rejected a good candidate the first time around, what makes you think the same flawed process won't reject them a second time?
And why don't they count the cost of good candidates who simply drop out of their hiring pool entirely, because they can't be arsed to bone up on the easily gamed idiotic hiring process?
I'd never even apply to Google based on the stories I've heard, and I'm sure there are plenty of others in the same position who are even better at what they do than I am. There are just so many stories out there of how crappy the hiring process is that everyone who's any good must have heard about it. Some significant fraction will have said, "Yep, not for me."
I've heard that it's not uncommon to have to interview twice before getting in to Google.
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