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Tech Leadership Spectrums — Recruiting

Tech Leadership Spectrums — Recruiting

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This is the first of a multi-part series that I will be writing about Technology Leadership Spectrums. The values of technology leaders fall on a spectrum much like the beliefs of politicians fall on the left or right of the political spectrum.

In this installment, I’ll talk about recruiting and its “low-bar” and “high-bar” ends of the spectrum. I’ll also dive deeper into hiring for professional experience vs. candidate characteristics and interviewing with empathy vs. apathy.

Recruiting

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On the Low-bar end of the spectrum, proponents think that the recruiting process is inherently flawed. So, they think, “Why bother with a long, drawn-out process?” Some Low-bar advocates may view new hires as expendable. They think, “If he doesn’t work out, we can just fire him and start again.” Low-bar proponents might also hire resources as contract-to-hire. This way an employer can use a try-before-you-buy model. Low-bar advocates might also think that recruiting analysis-paralysis can lead to hiring stagnation. Lastly, Low-bar supporters are often opposed to the high cost of comprehensive recruiting. This is especially true because the interview process often involves several highly-paid employees.

On the other end of the spectrum, picky and exclusive recruiters set a high bar for their candidates. Proponents on this end of the spectrum tout that while the costs of recruiting are high, they pale in comparison to the costs of making a bad hire. Just google “the cost of a bad hire” to find some astonishing figures for making a hiring mistake. Employers in this camp also believe that “the team you build is the company you build” (Vinod Khosla) and that hiring defines the company, its culture, and its future potential.

Maybe the best example of a high-bar recruiter was Google during its early days. The following excerpt from Work Rules! (p. 76) sums it up well:

As you might imagine, the [Google] hiring machine moved glacially. Being hired by Google could take six months or longer, and a candidate could endure fifteen or even twenty-five interviews before getting an offer… But in retrospect, this was the right trade-off at the time… It focused on avoiding false positives — the people who looked good in the interview process but actually would not perform well — because we would rather have missed hiring two great performers if it meant we would also avoid hiring a lousy one. A small company can’t afford to hire someone who turns out to be awful. Bad performers and political people have a toxic effect on an entire team and require substantial management time to coach or exit.

The current consensus seems to still be on the High-bar side. However, even Google has backed off considerably. A book about Google’s values states, “Our hiring process was simply too resource intensive, too time consuming, and too painful for candidates.” (Work Rules! p. 77)

Candidate Qualifications

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What do employers look for in candidates? What factors do employers use to determine if a candidate is worth hiring? One can categorize these factors into experience, personality traits, and cognitive ability. One can further distill the last two into candidate characteristics. Therefore, we can consider experience on one end of the qualifications spectrum and characteristics on the other end.

On the Experience end of the spectrum, proponents tout that the most important factor in evaluating candidates is professional experience. Not too long ago, it seemed that employers wanted three years of experience in a technology that was only one year old!

Now the pendulum seems to have swung the other way. Today’s employers seem to care much more about aptitude, creativity, and ambition than pure experience. (Not to get too philosophical, but the Honing theory posits that creativity draws upon associations among experiences. Therefore, more experience might lead to more creative possibilities.)

Although the following characteristics are also very important, they don’t seem to get the same focus as aptitude, creativity, and ambition. Maybe that’s because the following characteristics are hard to measure.

  • Intellectual curiosity

  • Love of solving problems

  • Teamwork

  • Independent

  • Work ethic

The book How Google Works emphasizes hiring learning animals, not specialists and explains:

In dynamic industries, conditions change frequently, so experience and ability to perform a particular role is not as important as the factors that define a “smart creative”: technical knowledge, business expertise, and creativity. When considering candidates for a role, favor the ones with a track record of learning new things over the ones with a track record in that particular role. The learners will successfully adapt to new roles, but role specialists will not.

A related book, called Work Rules! (p. 99), has a similar take:

By far the least important attribute we screen for is whether someone actually knows anything about the job they are taking on. Our reasoning and experience is that someone who has done the same task — successfully — for many years is likely to see a situation at Google and replicate the same solution that has worked for them. As the psychologist Abraham Maslow wrote: “I suppose it is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail.” The problem with this approach is that you lose the opportunity to create something new. In contrast, our experience is that curious people who are open to learning will figure out the right answers in almost all cases, and have a much greater chance of creating a truly novel solution. For technical roles, such as those in engineering or product management, we assess expertise in computer science quite extensively, but even there our bias is to hire people with a general (though expert-level) understanding of computer science rather than specialized knowledge of just one field. And to be fair, we have moved from a philosophy of hiring exclusively generalists to a more refined approach, where we look across our portfolio of talent and ensure we have the right balance of generalists and experts. One of the luxuries of scale is that you can build areas of deep specialization, but even in those pockets we monitor to make sure there is always an influx of fresh, nonexpert thinking.

Reid Hoffman, a member of the PayPal Mafia, also emphasizes the importance of hiring “learning animals”. In addition, Reid emphasizes the importance of ambition as he stated in the following interview:

What made PayPal so successful was Peter [Thiel] and Max [Levchin] were able to hire extremely talented folks with little experience but who were ambitious, as opposed to the classic wisdom of hiring people with 10–20 years of experience. PayPal got high quality people who were able to learn intensely and fast. This is a valuable thing to stack massively in a company. Peter and Max did this style of hiring for 98% of PayPal.

The other attributes were that it was an intense short run where eBay bought it, and there were a lot of young people who started to get some assets but were still very hungry.

This Week in Startups interview (min 57:25)

So how do interviewers assess aptitude, creativity, and ambition? Ambition seems much easier to measure than the other two because to some degree, interviewers can assess ambition by evaluating what a candidate has done outside of work (blogging, GitHub repository, etc.). Interviewers can also ask ambition-related questions like the following:

  • “Where do you plan to be in five years?”

  • “How do you expect to grow and learn in your next position?”

  • “What are the most interesting technology trends?”

The more difficult characteristics to measure are aptitude and creativity. The most common way of evaluating these characteristics is via whiteboard coding or take-home assignments (see the next post in this series).

Interviewing

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The biggest part of the recruiting process is interviewing, so it deserves its own focus. One can put the aspects of interviewing on many different spectrums. However, this section only deals with one aspect — empathetic vs. apathetic interviewers.

On the Empathetic end of the spectrum, proponents have respect for a candidate’s time and energy. They care about what the candidate thinks of the interview process and the potential employer.

On the other hand, apathetic interviewers test the limits of what a candidate is willing to endure to get the job. Sometimes the reasons are rooted in the High-bar selectivity mentioned in the Recruiting section. Other times the reasons stem from the interviewer’s ego. Interviewers sometimes try to validate their technical prowess by trying to trick or stump candidates.

The current consensus seems to be on the Apathetic side of the spectrum. The typical Silicon Valley interview process involves about eight hours of interviews. That’s usually about 7% of a candidate’s yearly vacation days (more if overnight travel is required or if a candidate only gets 2 weeks of vacation). Not only can that time commitment dissuade a candidate, but the inability to make an efficient, decisive decision can also be a warning sign that the potential employer suffers from bureaucracy, analysis-paralysis, or both.

In general, the harder the interview process, the shallower the talent pool. Apathetic interviewers run the risk of missing out on candidates that don’t have the time or the will to deal with an arduous process. This is particularly true for the largest talent pool, which includes candidates who are not currently looking for jobs. “Comfortably employed” engineers will likely avoid painful interviews even if it means sticking it out in a mediocre position.

For other philosophies related to technology leadership, please check out the parent post as well as the following posts:

Tech Leadership Spectrums — Assessment Tests

Tech Leadership Spectrums — Assessment Tests

Tech Leadership Spectrums

Tech Leadership Spectrums