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.