Tutorspree

The Failure of Passive Recruiting: Recruiters

This is an actual conversation I had with a recruiter:

Phone rings and I pick it up

Him: Hi, is Paul there?
Aaron: May I ask who is calling?
Him: I have a technical question.
Aaron: Ok, what is it?
Him: Are you technical?
Aaron: Yes. Who is this?
Him: Who are you?
Aaron: Are you a recruiter?
Him: Yes and…
Aaron: Great, send us your resumes, if we like what you send over, we’ll let you know if we want to meet with the candidates, other than that, have a good day.

That’s the first of several times the same recruiter, or someone from his office called with the same lame attempt to…build a relationship?

There are a lot of recruiters who have realized that technology (broadly construed) is hot right now. They’ve further realized that there are a relatively large number of companies looking to spend raised capital on a technical talent pool that is too small to meet demand. In the minds of most recruiters, that means that all they need to do is throw engineers at companies in the hopes that one or two will stick and they’ll get their commission.

The truth is that that model does work in certain situations. Recruiting shops exist for a logical reason - companies often need to fill roles and can’t figure out how to do it. Enter recruiter who understands the role well, where to find candidates, and how to properly match them up. What the recruiters don’t understand, however is…anything about the way a startup works, what it needs, and how to procure those people.

The roles that we fill at this stage are highly specialized and generally call for nearly contradictory attributes in candidates. You need incredible good engineers who are not already in golden handcuffs, are crazy enough to join a risky early stage company, do not want to found their own company right now, want to work at all hours, and are aligned with the culture you are trying to build.

In order to understand how all those pieces properly fit together, the recruiter would have to spend a material amount of time with your company - getting a proper feel for your culture, your working style, etc. Then, the recruiter would have to do a similar thing with the candidates - actually getting to know them as people rather than just resumes. More than that, the recruiter would have to find a way to become totally trusted by both sides in order to get the real answers and be able to make good matches.

Those requirements on the recruiter are significantly different than they are when working with larger companies who a) have more easily discernible cultures b) have higher tolerance for error in hiring and c) are simply more familiar.

Now take a look at the economics of recruiting (with a number of simplifying assumptions) - recruiters rely on the fact that they get a ~25% first year salary placement fee for each candidate. With early stage startups eschewing high salaries in favor of equity, that placement fee isn’t huge (relative to more established companies). If one out of every 100 candidates delivered is actually a good fit (generous assumption), then the recruiter would need to spend enough time with maybe 5x that number to send you the 100. If you figure that the recruiter needs a minimum of 3 hours to get a deep enough sense of the candidates “matchiness,” the system begins to look incredibly inefficient. And it is, especially relative to larger companies that will accept more candidates more rapidly.

Hypothetically, this sort of effort makes sense if the startup gets huge and if the recruiter can build a relationship that leads to a lot of hires down the road. Those are bad odds. More than that, it’s a bad way to spend time and money. As a result, the good recruiters focus on what they’re good at, on the accounts that come with retainers and huge success fees. Those relationships are with big companies, not startups. And so startups are left with firms throwing darts in the hope that a small amount of effort will lead to one or two hits.

What that means for a startup founder is that recruiters are, by and large, a waste of your time. Yes, there are a few good ones out there who will put in the effort and select good candidates, especially if you are as strict with them as Paulie (more on that later). However, your interests are, for the most part, fundamentally misaligned with theirs. Which means, end of the day, that recruiters, despite what they might say, are not a source of hires. You cannot let someone else passively search for your employees.

At least, this is some of what we’ve learned from working with recruiters thus far at Tutorspree.

Killing your startup while looking smart: Half Measure Syndrome

Aaron is a cofounder of Tutorpsree, and a tutor. He writes about what we’ve learned and how it influences what we do. This post originally ran in TechCrunch.

In the wide world of startups, we mostly like to think of ourselves as go-getters, ass kickers, “in all the way” sorts. We also like to think of ourselves as tinkerers, rapid iterators who test unceasingly. But the combination of those two traits can lead to one of the most dangerous cycles in startup - half measure syndrome (HMS).

Interestingly, HMS starts off as something very intelligent - the team does not want to commit to a single strategy until it can prove that that strategy will create the hockeystick. When controlled and focused, that impulse is an excellent driver of evolution, but when not properly grounded in the reality of where you are, it becomes quite dangerous.

Steve Blank (arguably the inventor of the rapid iteration philosophy as applied to launching a startup) did an incredible job illustrating the dangers of HMS in a post he wrote about a former student who, despite having achieved product market fit, refused to commit his full resources on the found solution - preferring to continue iterating in the belief that something bigger was hopefully around the corner. Looking at his bank account and fearing the prospect of it dwindling to zero, he became locked in a potential death spiral - continually pitching halfsies that did not go anywhere, more desperate each time, rather than committing to the seemingly proven if not 100% certain results already seen.

That mental state makes a lot of sense to me. It is, to a large degree, driven by fear of failure - and not just of your idea. As we build companies, we continually create buy-in from stakeholders - be they friends, family, colleagues, investors, or admirers. That faith in our ability to succeed is, at surface, driven by the particular success of a product. To risk the failure of that product, without the potential recourse of “but we haven’t tried everything” is terrifying. At it’s heart, it would mean that, fundamentally, you, as a founder, fell short of a goal that others thought you were capable of achieving. HMS allows a founder to continually list things that have not been tried in total, to believe in the savior lodged around the corner which they’ll get to before they run out of time. Paradoxically, that faith means that you will likely never uncover that secret - if it does exist (and very rarely is there a single silver bullet for any company). Committing halfway fundamentally means that you will not fully understand any piece of that halfsies strategy. It means that, should the strategy fail, you will not fully understand the reason for it. While, in some instances, that may mean you avoid a number of bad roads, it will also mean that your ability to identify the right road will be materially decreased.

Then how, really, can you identify whether or not you are pursuing verifiable tests, or are simply caught by HMS? Fundamentally, I believe the answer is in how you approach testing, in the type of framework you build around it. Tests are not half measures when they are designed to prove individual pieces of an overall hypotheses (can I get to 500 tutors in NYC?). Keeping a conscious eye of what the point of a test or iteration is, not just to itself, but to your overall plan and mission (how building a certain number of tutors in a given area influences student activity and community creation, rather than just the number of tutors) removes the halfsies quality of a test. Rather than continually shifting a business strategy to reflect the results of a single test, aggregating data across a set of them, and altering your strategy accordingly creates consistent momentum for your company where the success or failure are equally useful.

Within that framework, there need to be set decision points - moments where you predetermine that, based on given sets of data, you will make a decision. This is, in truth, the most important aspect of not falling to HMS. Create whatever forcing function you need around those decision points - whether a giant whiteboard, a commitment to your cofounders or employees, or an agreement with your investors or board. At each stage, map out what your confidence interval is/will be. Know whether or not you need complete data on any single iteration to make a decision, or if the aggregate will suffice. And when that decision comes, make the hard choices necessary. Get advice on those decisions if you can, but make the decision. Don’t push it off because, now that it is here, it is scary - that’s what HMS does. Take the most objective POV you can, and go. Because, fundamentally, your most dangerous enemy at a startup is time, not any single decision. Every minute you spend not deciding is a minute you’re not learning and not evolving. It may feel like being intelligently deliberate, but it might very well behalf measure syndrome.