- I was a mid 30s, female, single mom,
didn't look like the prototype of the tech entrepreneur
by any stretch of the imagination,
yet I was super passionate about the field.
If I had listened or looked at
the world of tech entrepreneurship
and made my determination that way,
I would've never ventured into the field.
(angsty rock music)
- [Narrator] Pymetrics was founded
by Harvard and MIT-trained neuroscientist
Frida Polli in 2011.
Pymetrics developed neuroscience-based assessment
and prediction technology
to transform the way that companies hire.
(playful music)
- The way people are matched to jobs,
whether it's from an external recruitment process
or within the company, it is very analog
and that leads to four major problems.
One is it's hugely inefficient.
There are 250 applying for any one open role.
Secondly, it's very ineffective,
so 50% of first-year hires fail.
That's a massive, massive failure rate.
Three is it's very lacking in diversity.
And then last, but not least,
the candidate experience is terrible.
Your application was often never even acknowledged
that it had been received.
The resume black hole, as I like to say, is a thing.
It exists.
If you look at the workforce today,
it's full of all types of bias,
gender bias, ethnic bias, socio-economic bias, age bias,
and we as humans are incapable of having our biases
removed from us.
It is physically impossibly.
- As technology develops in the employment space,
what we see are lots of opportunities
for us to improve processes and increase efficiency.
What that means is we can automate decisions
and so what Pymetrics does
is intentionally audit these algorithms
to ensure that we're not inherently bringing in
the unconscious biases that the human selection process has.
- Pymetrics works very much like Netflix did
to transform what used to be a Blockbuster economy
to a Netflix economy.
It opened up the options to millions,
tens of millions, hundreds of millions.
So that's part of what we do is we allow a company
to evaluate many, many more candidates
than they ever would've in the past.
(upbeat electronic music)
The beauty of this technology
is that it is giving a person a fit
to many, many different roles
that they may be being evaluated for
and it's allowing a company to really evaluate all people
that are applying to it,
as well as doing it for multiple different roles.
As a candidate, you go to their website,
you say this is the job I'm looking to apply for,
you start an application process,
you fill in all your basic data,
and then at that point, you will be sent a link
saying hey, please go do the Pymetrics game.
- Underlying the games are longstanding,
well-developed neuroscience activities.
So these are the same sorts of exercises
that academics and very well known universities
have been using for decades
to understand difference between groups and individuals
on traits like attention, inhibition, risk, and emotion.
And so given that we wanted to rely on something
that we know is sound and based in solid science,
we adapted some of those neuroscience exercises
that we see in the literature
for our use in the employment space.
- Pymetrics knows absolutely nothing
about your demographic background.
We don't know your name.
We don't know your age.
We don't know your gender.
We don't know your ethnicity.
We know nothing about you
and that's exactly the way we want to keep it.
(chuckling) It's like don't tell us anything about yourself,
except for your cognitive, social, and emotional traits,
and that's the only information we are gonna use
to make that matching.
So if I apply to a company that's using Pymetrics,
I don't just get evaluated for the role I've applied to,
I do get that, but I also get evaluated for any role
that I may not have thought of applying to
that's also being powered by the Pymetrics platform,
so that's a huge value to me.
If I choose to come out of that application process
or the company decides not to hire me, I can then be put
into a much, much broader pool of evaluation
for roles across all of the Pymetrics companies.
(uplifting music)
Right now, I feel like we're kinda at the starting point
of a new age of HR,
really being engaged with analytics and AI
and machine learning and big data
and all of those labels that people throw around
in a way that really is unprecedented.
We work with about a 100 different companies at this point,
ranging from giant companies like Unilever and Accenture
that are taking hundreds of thousands of employees
and really radically transforming their experience
to fast-growth startups.
- What we're seeing with some of our clients
are numbers such as 15-20% increases
in under-represented minorities.
We're seeing 100% increases
in individuals hired over the age of 30 and 40.
Specifically with clients who have a very young workforce,
what that means
is that people who traditionally would've been discouraged
from applying for a particular role,
or even just screened out by a human screener,
would have had that opportunity opened to them.
- The self-discovery process for the applicant is huge.
Think of me.
I was a mid 30s, female, single mom,
didn't look like the prototype of the tech entrepreneur
by any stretch of the imagination,
yet I was super passionate about the field.
If I had listened or looked at
the world of tech entrepreneurship
and made my determination that way,
I would've never ventured into the field.
And that's what we do for people.
We give them the confidence,
we give them the data point that they need
to say I would be a good fit for this role,
I'm gonna go ahead and apply to this,
even if I don't see people that necessarily look like me
that are predominant in the field.
If everyone used Pymetrics today
or some technology that functioned like Pymetrics,
the workplace would be a more accurate and fair place.
We would have people that were happier at their jobs,
better suited for their jobs,
staying longer, performing better, and so on.