So here’s a counter perspective: there is no good way to interview, there are just less bad ways, which depends on your company.
The worst filter is choosing at random. If I shuffle a stack of resumes and throw half in the trash, I have eliminated the unlucky candidates. I have certainly rejected a good number of skilled and highly qualified candidates. Regardless the filter did its job, I have fewer applications to review.
If I give candidates whiteboard problems, I filtered out thoughtful people who don’t perform well under pressure. If I look at interviewees github submission and blog posts I have filtered out intelligent people with a dearth of free time. If I combine the two filters with an OR relationship, I now let more people through and have a filter that is less effective at narrowing down candidates.
All filters filter out good candidates. Anyone who finds a way to find exactly the right candidates from a filter in a way that isn’t bespoke and is scalable is going to be very successful.
There are enough lemons on the job market that this barely even bears examination. Anyone who's ever looked at a pile of incoming resumes can see at a glance that selecting at random from them is going to get a viable employee with vanishingly small probability. Anyone's who's tried to interview from even a selected pool of those can assume that the actual pool of candidates is overall even worse than it looks on paper.
Actual hiring results look a lot in abstract like dartboarding after trying to filter out the obviously unfit applicants, and while people can reasonably disagree on how hard to filter, not at all seems like a good way to put yourself out of business.
The thing is, it's not "random". I have a good reason for my filter - it represents attention to detail. And yes, it will exclude the occasional good candidate, but it will exclude far more bad candidates.
If I have 100 resumes for two roles, and I can, through heuristics, knock it down to five, then I'm starting with enough "good" resumes to stand at least a chance of filling the two roles. Mind you, we're now about a day's worth of work for a manager, and five interrupted afternoons for the senior/lead engineers doing the interviews.
On top of that, the good candidates are going to have other companies competing for them. If my response is "Well, we like this candidate, but let's spend two weeks interviewing another twenty people, just to be sure", my odds of missing the good candidate are pretty high.
Filters should be created and maintained based on their efficacy, not on how easily they can be applied.
Yes, it's impossible to interview every applicant, but a company focused on minimizing time spent and resources used instead of maximizing recruitment of employees who can create the most value is doing it wrong.
The purpose of a hiring filter is to reduce the false positives. Your discovery of false negatives doesn't say much about the filter quality in this respect.
If you could take random samples from the group of people who would apply to Haskell jobs and from people who would apply to Java jobs and come up with a measure of motivation/willingness-to-learn, I believe there would be some statistically significant things to say. Samples from two mainstream (and in my opinion, trashy) languages like C++ and VB might be harder to differentiate.
As a side note, I've noticed that companies that can afford a large amount of false negatives tend to have horrible interviewing practices. Google is in the top two of the worst interviewing experiences I've ever had. When everybody salivates over your company, you can afford use a quick and dirty filter that hones in on any one arbitrary characteristic. As a matter of fact, one could possibly argue that these lazy filters do better than more accurate filters in the same way that Google argues that more data is better than superior AI. It's stupid for people to look to companies like these for exemplary models of interviewing.
just because you hire anyone who applies doesn't mean just anyone will apply. people don't actually want to get a job they have no idea how to do. applicants will filter themselves. the question is how much better is a company's filtering process, really, than the applicants' self-filtering? would be embarrassing if it were no better, or even worse.
Those aren't the filters being used, not when there are hundreds of applications for a role.
You could be the platonic ideal candidate yet be screened out in the 0th round because you didn't go to a fancy school or you're missing one keyword from an irrelevant list.
Getting past the resume screening to a recruiter call is always worth it. Always.
But you are assuming your filtering mechanism, in a short window of interviewing, si actually any better than the people that have worked with that person for many months, if not years! Haven't you ever recommended someone, just to see them not get hired for reasons that don't seem realistic? I have, it happens all the time. Companies are often selective, in the same way that asking a candidate to roll a D20 and only hiring them if they roll a 3 is selective.
If 4 people that work together and I want to hire happen to bring in a 5th person that did worse in my interviews, I don't worry about their judgement: I wonder about my interview process!
This. Why have an interview filter that isn't based on what you actually need to hire? (And then, probably, complain that you can't find enough good candidates...)
Yes, not filtering is good, interviewing is good, hiring qualified candidates is good, not insulting senior candidates is good, blind filtering is bad.
Depends for many people there is not a shortage of jobs to apply for, so coding a path through a maze which is just regurgitation rote memorised algos is a filter for us.
I do agree about a daylong set of interviews with 4 or 5 people that's also a filter id use.
> what's a better way, subject to real limitations of time and resources?
Selecting at random from the applicant pool.
Any reasonably selective filter function that becomes sufficiently part of HR conventional wisdom will render the fraction of applicants who both pass it, and are capable of getting and keeping a job, unavailable in the market. The residue is people who either fail the function or pass the function and are sub-par employees. Because the feedback loop on the effectiveness of hiring practices is sufficiently attenuated, the utility of the filter going negative will not be noticed.
Treat easy, popular ways of identifying top talent like stock tips: even if they were true in the past, by the time you hear about it, it's not a good idea anymore.
Then that company has an incredibly broken interview process and is going to miss out on quality talent. And if that is a filtering tactic it's probably a shitty company to work for.
The sad part about this is that the filtering doesn't prevent getting sub standard candidates through the door. For example, I've been rejected by the Google interview process...but then shortly afterwords went to I/O expecting to find loads of insanely smart people working at their sand boxes and office hours that could run circles around my abilities and teach me things. There are some that know their stuff, but a lot who's apparent knowledge etc. was very under-whelming to the point of me knowing more than they did about the subject. Over time I've come to realize that part of the hiring process at these companies is political and that the filtering is still not preventing bad candidates from making it inside the company.
In a completely random spread is should be able to discard 90% of the applications without even looking at them. That's you dart-board approach.
In order to improve the odds though one can apply some reasonable filter. Any filter that does a better job of improving the dart board odds is, by definition, better than a dart board.
Now different jobs benefit from different filters. If I'm applying to do a job that takes a high-functioning brain, then it makes sense to apply a filter that already clasifying people based on mental ability.
It's important to understand that the goal is not to find the best 20 people. The goal is not to even find the best person. (because after some level the notion of "best" is highly subjective.) the goal of a recruiter is to find someone who is capable, and is good at the job.
The goal of you, the person trying to get hired, is to get past the filters. You may think you're the "best" person for the job ( but how would you know without yourself interviewing the other 199?)
Some filters, like a college degree, are hard to overcome. Because I can completely ignore you and still succeed in my task of hiring someone. To be honest what -you- think of my filter(s) is irrelevant. I'm not out to find every quality candidate - just fining 1 is sufficient.
If you find you are being negatively affected by hiring filters then you need to be creative about overcoming that.
Very often the interview is a mechanism to complete a pre-defined checklist. Not only does it lead to false positives but, for the worse, false negatives.
There are platforms that claim to filter candidates, but it's tough to vouch for the effectiveness. Interviewing is hard.
Either end of the hiring channel is extremely noisy, recruiters work by spamming and candidates get seen by spamming. In my anecdotal experience, maybe 1 in 10 of any given job listing or applicant is worth pursuing.
These questions are a less bad way of filtering people out than others. They're not the only filters used, and others have different tradeoffs. Sometimes if you're hitting these questions it's because the other filters have already excluded you.
The worst filter is choosing at random. If I shuffle a stack of resumes and throw half in the trash, I have eliminated the unlucky candidates. I have certainly rejected a good number of skilled and highly qualified candidates. Regardless the filter did its job, I have fewer applications to review.
If I give candidates whiteboard problems, I filtered out thoughtful people who don’t perform well under pressure. If I look at interviewees github submission and blog posts I have filtered out intelligent people with a dearth of free time. If I combine the two filters with an OR relationship, I now let more people through and have a filter that is less effective at narrowing down candidates.
All filters filter out good candidates. Anyone who finds a way to find exactly the right candidates from a filter in a way that isn’t bespoke and is scalable is going to be very successful.
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