To crack the code on true potential, data scientists on Google’s world-famous People Analytics team launched an initiative with the not so secret code name Project Aristotle. Here was their initial mission: Build the perfect team. On the surface, the task might seem straightforward. If you were going to build a dream team, you’d simply fill it with the highest performing individuals, right?
So what specific qualities would you look for? High IQ? Fluency in several languages? Project Aristotle was using the greatest algorithm technology to find out. By analyzing incredible amounts of data—including tens of thousands of responses across 180 teams—they sought to create the profile that would make for the perfect performer in the workplace. The conclusion was astonishing and challenged everything you might think you know about potential.
They found there is no such thing as a perfect performer. When it comes to potential, individual traits and aptitudes are poor predictors of success on a team.
It isn’t about how smart you are, how many degrees you have, what grades you received, how creative you are or what your personality is like. Google confirmed using the best technology available that those are the wrong variables to be measuring when trying to calculate success and potential.
Why? Because they’re individual attributes. If those individual attributes don’t predict success, what does? The answer is clear: It is all about the ecosystem around you. Project Aristotle found that if the individuals on the team had 1) High “social sensitivity”—that is, a strong awareness of the importance of social connections, and 2) If the team had cultivated an environment where each person spoke equally and everyone felt safe sharing their ideas, the team hit their highest levels of performance over and over.
In other words, success on a team isn’t about survival of the fittest—it’s about survival of the best fit.
For decades, we’ve been measuring intelligence at the individual level, just as we have been measuring creativity, engagement and grit. But it turns out we were failing to measure something with far greater impact.
Photo by Pascal Swier on Unsplash
