The first reason, the social network, is probably the most prevalent and the hardest to track. It’s very difficult to measure the instances of applicants who did not even get the opportunity to enter the hiring funnel. Most technology companies hire primarily by employee referral; current employees are compensated when their employer hires people they recommend. By using these networks, the same schools, backgrounds, and former employers are represented. Many candidates coming from different networks, schools, and backgrounds are generally unaware of this dynamic, and expend a lot of time and energy dropping applications into a vacuum, never to be considered.

The second reason, risk profile and compensation, refers to cultural reasons regarding how diverse applications tend to treat risk. Candidates from these groups may get through the process of interviewing and want to work at the startup, but they don’t understand the equity opportunities or prefer the cash liquidity over the potential upside of having equity in a growing company. Many recently graduated Latino and African-American students have significant student loan debt and financial responsibilities to support their families—how can they choose a lower salary option and risky equity packages, when liquidity might actually be very important to this candidate? Although liquidity is not the primary motivation of every diverse candidate, it is simply an example.

The third reason, “X candidate is not
a culture fit,” refers to the most blatant
bias seen in tech recruiting, yet under
the guise of an objective business rea-
son. This statement represents a series
of concerns and biases, masqueraded
behind a very simple, harmless sound-
ing statement. While fit with a compa-
ny’s culture, especially at a startup is
important, the specifics need careful
examination. For some candidates, it
may mean they don’t fulfill the physi-
cal characteristics (not a white, male
hacker) recruiters expect for some-
one doing this role. For others, it may
mean the candidate does not seem to
like drinking as much as the average
member of the company. The recruit-
ing team, which is trained to pattern
recognize in a highly generalizable
fashion, looks at a particular role and
tries to find candidates who match the
qualifications and skills of the first few
candidates doing that same role. How-
ever, the fact that the model is being
based on a 25 year old, white, male who
dropped out of Carnegie Mellon to join
Y-Combinator before getting acquired
by this hot startup makes this profile
very hard to replicate. Are these char-
acteristics really good heuristics for
hiring success?

OPPORTUNITIES FOR IMPROVEMENT There are some interventions employers can take to ameliorate these issues, though.

˲ Anonymize resumes and remove university affiliation.

˲ Prime candidates.

˲ Reconfigure employee referral benefits.

˲ Set an explicit diversity hiring goal.

The first opportunity, anonymizing resumes, is designed to help an organization better understand how its hiring has been biased, and in response, to have an honest conversation about the validity of these hiring proxies. The resume study mentioned previously showed the mere existence of an African-American or Latino name on a resume, all other factors being equal, is of great disadvantage to an applicant.

We are proposing you isolate a particu-
lar team or function and run a pilot,
stripping a subset of new resumes of
name and school attended, before re-
viewing the candidate. Now codify the
results and compare it to your control,
which was not anonymized. Did you
offer more phone screens to diverse
candidates? Interview some of these
candidates and confront some of your
organization’s assumptions about the
correlation between college attended
and competency.

The typical proxies of success, like school attended or GPA, have been found by organizations like Google to not be predictive of employee success. Similarly, The College Board has recently overhauled the SAT because, among many failings, there was a direct relationship between increasing family income and increasing scores. Many technology companies currently use these and other similarly unpredictive factors as proxies for future success at their organization. Laszlo Bock of Google proposes shifting interview techniques toward expressed general cognitive ability and creative problem solving of real-workplace situations [ 2].

The second intervention we propose is priming candidates once they make it through the initial screening process. Many diverse candidates come from backgrounds where strategies for getting jobs at technology companies are not understood—often nobody in their peer group has ever pursued a career in the technology sector. Making sure candidates are primed with information about the style, length, tone, and general content of the interview tasks can be immensely helpful in making sure they are comfortable and not completely surprised by the interview.

A fascinating study confirms the importance of priming college freshmen [ 3]. A video that depicted common anxiety-inducing experiences (for instance difficulty finding study groups, or concerns that everyone else is smarter) dramatically assuaged these issues. The video promoted social belonging by demonstrating these experiences are common and not a sign of an individual’s weakness, and had a lasting impact. In fact, the African-American students who viewed the video had significantly higher GPAs and graduation rates than their counterparts who had not.

In addition to priming a candidate

Economies cannot
remain, or become,
competitive without
finding all available
talent, nurturing
it and providing
opportunities
for budding
entrepreneurs,
investors and
employees from
every corner.