Move over, MBTI — upcoming new startup Pymetrics seeks to revolutionize the world of self-assessment tools based on neuroscience research instead of behavioral psychology. We speak with Pymetrics co-founder and CEO Frida Polli, PhD, to learn more about the company.
Wharton Journal: Tell us the story behind Pymetrics. How does an MBA graduate end up launching a startup in the neuroscience research space?
Frida Polli: I have a sordid pre-MBA past. I spent a decade in… a research lab! My co-founder, Julie Yoo, and I met as postdoctoral fellows at MIT. We both have PhDs in neuroscience. For close to a decade, we worked in neuroscience labs scanning people’s brains. We loved assessing and understanding people better, but we wanted to do something more dynamic and applied with our research. So I went to Harvard for an MBA, and during my second year, we came up with the idea for Pymetrics: a neuroscience-based people-recommendation engine.
WJ: A handful of self-assessment tools today use behavioral questions to ultimately predict one’s career fit. How is Pymetrics’ approach superior in its predictive capability?
FP: In two ways. First, you don’t answer any questions about yourself. Instead, you play short games on the computer. These games are based on the last fifteen years of neuroscience research and tell us about your cognitive and emotional traits. These games are more accurate than questions because people don’t know what each game is assessing, and even if they did, it would be very difficult to change their performance. Second, we use recommendation engine technology to predict industry and function fit. Recommendation engine technology underpins some of the most powerful technology on the web (e.g., Google, Netflix) and we apply it to career fit prediction. If you want more detail, check out: www.pymetrics.com.
WJ: It’s interesting that beyond just providing industry fit results, Pymetrics goes a step further and even tells you which specific companies (say Bain vs. McKinsey) you would best belong in. What kind of profiling do you do on these specific companies to get to this additional layer of detail?
FP: We build all of our profiles on MBAs that have worked at those companies and meet certain metrics of success. We can be that specific because our recommendation engine modeling is very sensitive. The reason we give that level of detail is because we want our product to be as helpful to MBAs as possible. As a first-year MBA, I personally struggled with “what do I want to do”? I signed up for every club on campus, went to millions of company presentations, and ran around like a chicken with my head cut off. Part of the inspiration for Pymetrics was to match students not just to generic professions (e.g., accounting) but instead to give them really detailed matches. We are continually working to improve on that aspect of our product.
WJ: What’s next for Pymetrics? Any new features or collaborations you’re particularly excited about?
First, after starting at HBS this spring, we are launching at 8 other business schools – Wharton, Columbia, Stern, Sloan, Tuck, Stanford, Kellogg and Haas. Official launch date across the 8 schools is October 15th although the instrument is live now. We will be tracking this launch at www.businessschoolchallenge.com. On the site, we will have results across and within schools (e.g., by cohorts). Campus liaisons at each school that have been working hard to get the word out (Wharton liaison: Mary Winograd WG ‘13). We are excited to see how students respond and what additional feature requests we will get.
FP: Also, our product is greatly improved! When we started at HBS, it took a month (yes, a month) to get results! It’s amazing anyone took it. Now we offer immediate results on a variety of different measures. Also, we now we offer 19 fit scores across a variety of industries, functions and companies. So compared to our initial product, it is vastly improved. As LinkedIn founder Reid Hoffman said, if you’re not embarrassed by your first product, you waited too long to launch.
WJ: MBAs often get stereotyped as being “startup-unfriendly”. What advice would you give aspiring Wharton MBA entrepreneurs?
FP: Be excited and passionate about your startup idea and the startup world.