at Google, I tried to hire one of the most productive programmers I know, who was promptly rejected by a recruiter for not being technical enough.
On the candidate side of hiring, I've experienced both being in demand and being almost unhireable. Because I did my undergrad at Wisconsin, which is one of the 25 schools that claims to be a top 10 cs/engineering school, I had recruiters beating down my door when I graduated. But that's silly -- that I attended Wisconsin wasn't anything about me; I just happened to grow up in the state of Wisconsin. If I grew up in Utah, I probably would have ended up going to school at Utah. When I've compared notes with folks who attended schools like Utah and Boise State, their education is basically the same as mine. Wisconsin's rank as an engineering school comes from having professors who do great research which is, at best, weakly correlated to effectiveness at actually teaching undergrads. Despite getting the same engineering education you could get at hundreds of other schools, I had a very easy time getting interviews and finding a great job.
I spent 7.5 years in that great job, at Centaur. Centaur has a pretty strong reputation among hardware companies in Austin who've been around for a while, and I had an easy time shopping for local jobs at hardware companies. But I don't know of any software folks who've heard of Centaur, and as a result I couldn't get an interview at most software companies. There were even a couple of cases where I had really strong internal referrals and the recruiters still didn't want to talk to me, which I found funny and my friends found frustrating.
When I could get interviews, they often went poorly. A typical rejection reason was something like “we process millions of transactions per day here and we really need someone with more relevant experience who can handle these things without ramping up”. And then Google took a chance on me and I was the second person on a project to get serious about deep learning performance, which was a 20%-time project until just before I joined. We built the fastest deep learning system in the world. From what I hear, they're now on the Nth generation of that project, but even the first generation thing we built had better per-rack performance and performance per dollar than any other production system out there for years (excluding follow-ons to that project, of course).
While I was at Google I had recruiters pinging me about job opportunities all the time. And now that I'm at boring old Microsoft, I don't get nearly as many recruiters reaching out to me. I've been considering looking for work2 and I wonder how trendy I'll be if I do. Experience in irrelevant tech? Check! Random experience? Check! Contractor? Well, no. But two out of three ain't bad.
My point here isn't anything about me. It's that here's this person3 who has wildly different levels of attractiveness to employers at various times, mostly due to superficial factors that don't have much to do with actual productivity. This is a really common story among people who end up at Google. If you hired them before they worked at Google, you might have gotten a great deal! But no one (except Google) was willing to take that chance. There's something to be said for paying more to get a known quantity, but a company like TrendCo that isn't willing to do that cripples its hiring pipeline by only going after people with trendy resumes, and if you wouldn't hire someone before they worked at Google and would after, the main thing you know is that the person is above average at whiteboard algorithms quizzes (or got lucky one day).
I don't mean to pick on startups like TrendCo in particular. Boring old companies have their version of what a trendy background is, too. A friend of mine who's desperate to hire can't do anything with some of the resumes I pass his way because his group isn't allowed to hire anyone without a degree. Another person I know is in a similar situation because his group has a bright-line rule that causes them to reject people who aren't already employed.
Not only are these decisions non-optimal for companies, they create a path dependence in employment outcomes that causes individual good (or bad) events to follow people around for decades. You can see similar effects in the literature on career earnings in a variety of fields4.
Thomas Ptacek has this great line about how “we interview people whose only prior work experience is "Line of Business .NET Developer", and they end up showing us how to write exploits for elliptic curve partial nonce bias attacks that involve Fourier transforms and BKZ lattice reduction steps that take 6 hours to run.” If you work at a company that doesn't reject people out of hand for not being trendy, you'll hear lots of stories like this. Some of the best people I've worked with went to schools you've never heard of and worked at companies you've never heard of until they ended up at Google. Some are still at companies you've never heard of.
If you read Zach Holman, you may recall that when he said that he was fired, someone responded with “If an employer has decided to fire you, then you've not only failed at your job, you've failed as a human being.” A lot of people treat employment status and credentials as measures of the inherent worth of individuals. But a large component of these markers of success, not to mention success itself, is luck.
I can understand why this happens. At an individual level, we're prone to the fundamental attribution error. At an organizational level, fast growing organizations burn a large fraction of their time on interviews, and the obvious way to cut down on time spent interviewing is to only interview people with "good" qualifications. Unfortunately, that's counterproductive when you're chasing after the same tiny pool of people as everyone else.
Here are the beginnings of some ideas. I'm open to better suggestions!
Billy Beane and Paul Depodesta took the Oakland A's, a baseball franchise with nowhere near the budget of top teams, and created what was arguably the best team in baseball by finding and “hiring” players who were statistically underrated for their price. The thing I find really amazing about this is that they publicly talked about doing this, and then Michael Lewis wrote a book, titled Moneyball, about them doing this. Despite the publicity, it took years for enough competitors to catch on enough that the A's strategy stopped giving them a very large edge.
You can see the exact same thing in software hiring. Thomas Ptacek has been talking about how they hired unusually effective people at Matasano for at least half a decade, maybe more. Google bigwigs regularly talk about the hiring data they have and what hasn't worked. I believe they talked about how focusing on top schools wasn't effective and didn't turn up employees that have better performance years ago, but that doesn't stop TrendCo from focusing hiring efforts on top schools.
You see a lot of talk about moneyball, but for some reason people are less excited about… trainingball? Practiceball? Whatever you want to call taking people who aren't “the best” and teaching them how to be “the best”.
This is another one where it's easy to see the impact through the lens of sports, because there is so much good performance data. Since it's basketball season, if we look at college basketball, for example, we can identify a handful of programs that regularly take unremarkable inputs and produce good outputs. And that's against a field of competitors where every team is expected to coach and train their players.
When it comes to tech companies, most of the competition isn't even trying. At the median large company, you get a couple days of “orientation”, which is mostly legal mumbo jumbo and paperwork, and the occasional “training”, which is usually a set of videos and a set of multiple-choice questions that are offered up for compliance reasons, not to teach anyone anything. And you'll be assigned a mentor who, more likely than not, won't provide any actual mentorship. Startups tend to be even worse! It's not hard to do better than that.
Considering how much money companies spend on hiring and retaining "the best", you'd expect them to spend at least a (non-zero) fraction on training. It's also quite strange that companies don't focus more or training and mentorship when trying to recruit. Specific things I've learned in specific roles have been tremendously valuable to me, but it's almost always either been a happy accident, or something I went out of my way to do. Most companies don't focus on this stuff. Sure, recruiters will tell you that "you'll learn so much more here than at Google, which will make you more valuable", implying that it's worth the $150k/yr pay cut, but if you ask them what, specifically, they do to make a better learning environment than Google, they never have a good answer.
I've worked at two companies that both have effectively infinite resources to spend on tooling. One of them, let's call them ToolCo, is really serious about tooling and invests heavily in tools. People describe tooling there with phrases like “magical”, “the best I've ever seen”, and “I can't believe this is even possible”. And I can see why. For example, if you want to build a project that's millions of lines of code, their build system will make that take somewhere between 5s and 20s (assuming you don't enable LTO or anything else that can't be parallelized)5. In the course of a regular day at work you'll use multiple tools that seem magical because they're so far ahead of what's available in the outside world.
The other company, let's call them ProdCo pays lip service to tooling, but doesn't really value it. People describing ProdCo tools use phrases like “world class bad software” and “I am 2x less productive than I've ever been anywhere else”, and “I can't believe this is even possible”. ProdCo has a paper on a new build system; their claimed numbers for speedup from parallelization/caching, onboarding time, and reliability, are at least two orders of magnitude worse than the equivalent at ToolCo. And, in my experience, the actual numbers are worse than the claims in the paper. In the course of a day of work at ProdCo, you'll use multiple tools that are multiple orders of magnitude worse than the equivalent at ToolCo in multiple dimensions. These kinds of things add up and can easily make a larger difference than “hiring only the best”.
Processes and culture also matter. I once worked on a team that didn't use version control or have a bug tracker. For every no-brainer item on the Joel test, there are teams out there that make the wrong choice.
Although I've only worked on one team that completely failed the Joel test (they scored a 1 out of 12), every team I've worked on has had glaring deficiencies that are technically trivial (but sometimes culturally difficult) to fix. When I was at Google, we had really bad communication problems between the two halves of our team that were in different locations. My fix was brain-dead simple: I started typing up meeting notes for all of our local meetings and discussions and taking questions from the remote team about things that surprised them in our notes. That's something anyone could have done, and it was a huge productivity improvement for the entire team. I've literally never found an environment where you can't massively improve productivity with something that trivial. Sometimes people don't agree (e.g., it took months to get the non-version-control-using-team to use version control), but that's a topic for another post.
Programmers are woefully underutilized at most companies. What's the point of hiring "the best" and then crippling them? You can get better results by hiring undistinguished folks and setting them up for success, and it's a lot cheaper.
When I started programming, I heard a lot about how programmers are down to earth, not like those elitist folks who have uniforms involving suits and ties. You can even wear t-shirts to work! But if you think programmers aren't elitist, try wearing a suit and tie to an interview sometime. You'll have to go above and beyond to prove that you're not a bad cultural fit. We like to think that we're different from all those industries that judge people based on appearance, but we do the same thing, only instead of saying that people are a bad fit because they don't wear ties, we say they're a bad fit because they do, and instead of saying people aren't smart enough because they don't have the right pedigree… wait, that's exactly the same.
See also: developer hiring and the market for lemons
Thanks to Kelley Eskridge, Laura Lindzey, John Hergenroeder, Kamal Marhubi, Julia Evans, Steven McCarthy, Lindsey Kuper, Leah Hanson, Darius Bacon, Pierre-Yves Baccou, Kyle Littler, Jorge Montero, and Mark Dominus for discussion/comments/corrections.
This estimate is conservative. The math only works out to 78 hours if you assume that you never incorrectly reject a trendy candidate and that you don't have to interview candidates that you “correctly” fail to find good candidates. If you add in the extra time for those, the number becomes a lot larger. And if you're TrendCo, and you won't give senior ICs $200k/yr, let alone new grads, you probably need to multiply that number by at least a factor of 10 to account for the reduced probability that someone who's in high demand is going to take a huge pay cut to work for you.
By the way, if you do some similar math you can see that the “no false positives” thing people talk about is bogus. The only way to reduce the risk of a false positive to zero is to not hire anyone. If you hire anyone, you're trading off the cost of firing a bad hire vs. the cost of spending engineering hours interviewing.[return]
Or Aphyr, one of the world's most respected distributed systems verification engineers, who failed to get responses to any of his job applications when he graduated from college less than a decade ago.[return]
I'm not going to do a literature review because there are just so many studies that link career earnings to external shocks, but I'll cite a result that I found to be interesting, Lisa Kahn's 2010 Labour Economics paper
There have been a lot of studies that show, for some particular negative shock (like a recession), graduating into the negative shock reduces lifetime earnings. But most of those studies show that, over time, the effect gets smaller. When Kahn looked at national unemployment as a proxy for the state of the economy, she found the same thing. But when Kahn looked at state level unemployment, she found that the effect actually compounded over time.
The overall evidence on what happens in the long run is equivocal. If you dig around, you'll find studies where earnings normalizes after “only” 15 years, causing a large but effectively one-off loss in earnings, and studies where the effect gets worse over time. The results are mostly technically not contradictory because they look at different causes of economic distress when people get their first job, and it's possible that the differences in results are because the different circumstances don't generalize. But the “good” result is that it takes 15 years for earnings to normalize after a single bad setback. Even a very optimistic reading of the literature reveals that external events can and do have very large effects on people's careers. And if you want an estimate of the bound on the "bad" case, check out, for example, the Guiso, Sapienza, and Zingales paper that claims to link the productivity of a city today to whether or not that city had a bishop in the year 1000.[return]