Hrtech Interview with CEO and Founder, pymetrics – Frida Polli

Frida Polli CEO and Founder, pymetrics talks about the talent matching technology and gamification for better talent assessment in the hrtech arena.

1. Tell us about your role at pymetrics?
I am the founder and CEO of pymetrics, a talent matching platform that makes workforce decisions more efficient, accurate, and fair. We have uniquely combined behavioral science and AI to help companies like BCG, Kraft Heinz, and McDonald’s match external and internal talent with their ideal jobs in the most predictive and bias-free way. pymetrics has raised $60M in funding from investors including Khosla Ventures, General Atlantic, Workday and Salesforce Ventures. As CEO of pymetrics, I lead the business and spend my time building the company’s overarching strategy and product development, spearheading our thought leadership efforts, and more recently I have been working with my team to lobby across various states for the implementation of more rigorous AI auditing. We have joined coalitions in New York City and California that aim to provide greater transparency and fairness to hiring assessments, often built using AI, that help employers evaluate job candidates.

2. Can you tell us about your journey into this market?
After a decade working as an academic neuroscientist at Harvard and MIT, I got a fellowship for an MBA at Harvard where I had a front-row seat to the recruiting process. I was shocked to see recruiting had not changed meaningfully since I graduated from college. My classmates were prepping for 6 months to land their “perfect” internship or job, only to hate it 3 days in. I was experiencing the problem too. My 30-page-plus academic resume said nothing of what I could do in the business world, let alone that I could be a tech entrepreneur. I was a 38-year-old single mom who didn’t fit the 20-something, male entrepreneur mold. There had to be a better solution.

Platforms like Spotify and Netflix take in information about you and give personalized recommendations that seem to know you better than you know yourself. Their movie and song recommendations are not based on their descriptions. Instead, they analyze movies deeply based on traits and then match you with suggestions based on what you like in movies.

Where was the equivalent for jobs? pymetrics set out to solve this problem, harnessing the power of ethical AI to match people to the jobs where they are most likely to succeed in the long run. pymetrics came out of a strong desire to both help people like myself, because I was a career switcher, but also to help all the students I was surrounded by who were trying to figure out what to do next in life. Knowing that Harvard students, an overserved population when it comes to job opportunities, were struggling made me confident that job matching was a problem for many people. pymetrics came to be in order to provide both job seekers and companies a better matchmaking process based on people’s potential and inherent behavioral traits.

3. How is digitization empowering the talent matching processes?
I saw many technology platforms out there using machine learning at scale to solve everything from movies to music, but was shocked that nothing like this existed for career search despite how critical employment is.

Today, pymetrics is redefining efficiency and fairness in HR by doing things differently and challenging the status quo of talent matching. We help companies measure and evaluate people using new data points, focusing on potential over pedigree. Traditional hiring tools, such as resume reviews, personality tests and traditional cognitive tests are highly outdated, inaccurate, and manual processes. Whether it’s by using pymetrics or another technology provider, companies must widen the funnel of individuals they can evaluate and and rely on more predictive data sources.

Digitization of this process allows us to assess the entire pipeline of candidates rather than forcing time-constrained humans to implement biased processes to shrink the pipeline from the start.

This leads to meaningful improvements across a range of key areas including efficiency, performance, diversity outcomes, and the overall predictiveness of matching talent to jobs. Technologies like ours have helped many clients realize meaningful time and cost savings, while also making better quality hires that stick around and out-perform their peers.

In addition to such time-savings and predictiveness, while it is impossible to correct human bias, it is possible to identify and correct the bias in AI. AI must be designed to be audited and the bias found in it to be removed. An AI audit should function not unlike the safety tests of a new car before someone drives it. If standards are not satisfactorily met, the defective technology can actually be corrected before it is allowed into production.

4. What is the significance of gamification for talent assessment?
pymetrics uses 12 exercises (also referred to as assessments or games) that gather behavioral measurements explained by nine cognitive, emotional, and social constructs we call factors (i.e., Learning, Attention, Effort, Decision Making, Risk Tolerance, Focus, Fairness, Emotion, Generosity). Models based on the soft skills behavioral data (collected through the exercises) of a company’s successful incumbents in a particular role can be used to evaluate applicant fit for the role. Job seekers can play the games and receive feedback on roles they are suited for.

pymetrics did not create these exercises – they all come from highly regarded peer-reviewed research. pymetrics simply put them online and gamified them. Because they capture “objective” behavioral responses, the measurements are free from confounds found in more traditional self-report assessments.

The fact that it is not obvious to candidates what the games are measuring, makes it difficult for them to try to artificially adjust their responses in accordance with what they think the hiring manager is looking for– which is frequently done on resumes and other forms of assessments. This is known as “social desirability” or “impression management” and has been shown to reduce the validity of an assessment. The gamification of our assessment supports the mitigation of this risk because we are measuring actual behaviours and not someone’s impression of themselves, so biases around self-perceptions are removed. Finally, gamification is fun! We have received overwhelmingly positive feedback from candidates over the years that they appreciated our more engaging, creative way of capturing data, further reflected by our stellar completion rates and candidate satisfaction ratings.

5. How does the redirection aspect of pymetrics work?
Redirection helps rejected candidates find their better fit, either at the company they already applied to, or within the broader pymetrics network of open roles. Through redirection, recruiters and clients are able to maximize candidate yield by 1) assessing candidate fit against all roles at the company, following rejection from one position, 2) maximizing the yield on sourcing investments, as rejected candidates may be a great fit elsewhere within the organization, and 3) gain access to highest fit candidates via the marketplace if redirecting both internally and externally.

From the candidates’ perspective, they are able to receive suggestions for best fit roles elsewhere in the organization to which they applied, and for similar roles at other companies– essentially turning rejection into a brand new potential job opportunity. The self-learning component of redirection also allows candidates to learn about their recommended careers, based on their unique characteristics after completing the pymetrics games.

6. How can dynamic and interactive insights future proof the workforce?
As we look to the future, talent leaders are faced with a number of challenging questions about their people and their workforces: What makes employees unique and how do they compare with industry benchmarks? How can we give employees a way to better understand themselves and how to best apply their inherent behavioral characteristics at work? Are employees digitally ready, do they possess the attributes needed to be agile, and how can we best work together as a team?

Historically, it has been difficult or even impossible to answer these questions even though “only enterprises equipped with talent data and insights will meet the fast-paced demands of digital business and the next-generation workforce.” (source: Gartner). pymetrics built our Workforce Insights product to help talent leaders answer these critical questions and future-proof their workforces, powered by a unique dataset and interactive dashboard. This solution is easy to use, quick to get started, and engaging for both talent leaders and employees.

As soon as just five employees have played the pymetrics games, a company’s Insights dashboard comes to life. The product provides a high-level overview of the DNA of a workforce including an understanding of the soft skills that make teams, roles, or regions similar or different. Being able to do so enables companies to lift and shift talent into roles where they are most likely to succeed, and also helps bring to light gaps in an organization’s digital readiness, which can strategically inform future L&D strategy.

7. What book are you currently reading?
I am currently reading The Ethical Algorithm: The Science of Socially Aware Algorithm Design by Professors Michael Kearns and Aaron Roth. This book explains how everyday technology can and should be designed to be more “socially aware”, as determined by the conscious and unconscious biases that their designers have imbued them with.

Technology is often perceived as a welcome addition to our day-to-day lives, helping us be more efficient, more intelligent, and make more informed decisions.

However, certain algorithms undoubtedly have the potential to violate basic human rights, such as amplifying racial and ethnic biases or leaking personal information. Therefore, we must take it upon ourselves to embed human principles into machine code, whilst still fostering innovation and exploration — a very difficult line to toe, as you might imagine.

It may or may not come as a surprise that what I am reading in my “free” time is directly related to pymetrics — this book has certainly inspired how we at pymetrics are developing ethical AI to be deployed in the workplace as part of hiring, internal mobility, and redeployment processes. This book has shed immense light on the issues my team and I are tackling every day, and I highly encourage you to give it a read if you are interested in better grasping the perils of biased algorithms and the steps being taken to combat them.

8. We have heard that you have a very joyful work culture, we won’t mind having a look at some of the pictures?
While difficult to capture team memories now that we have been working from home for most of the year, here are some photos from years past that I hold near and dear to my heart:

9. Can you give us a glance of the applications you use on your phone?One of my most used apps right now is the 5 Minute Journal (link to the app store here), a self-proclaimed “toothbrush for your mind”. The app is built on proven principles of positive psychology. I enjoy it because it allows me to easily capture photos, receive daily inspirational quotes and weekly challenges, and of course enter my thoughts in a virtual journal that I can easily look back on in the future. I love being able to track my personal progress and reflect on memories and thoughts all in one place. While it can sometimes be tough to bring myself to start writing, I am always satisfied when I do.

Frida Polli CEO and Founder, Pymetrics

Frida Polli PhD is an award-winning Harvard and MIT trained neuroscientist turned AI-startup founder and CEO. She is the CEO of pymetrics, a talent matching platform that uses behavioral science and AI to help companies like Postmates, Kraft Heinz, and PwC to match external and internal talent with their ideal jobs in the most predictive and bias-free way. While an academic, Frida was a NARSAD Young Investigator, an NIH fellow, an MIT 100K winner, and a Life Science Fellow at Harvard Business School (where she earned an MBA). She has been featured on CNN, CNBC, the Wall Street Journal, the New York Times, Fast Company, and Inc, and she regularly contributes to Forbes.


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