How Innovators Choose Their Next Career Move Take Notes

How Innovators Choose Their Next Career Move Take NotesHow Innovators Choose Their Next Career Move - Take Notes What do online financial services, commercial spacecraft, and mass-market electric cars all have in common? Other than being industries shaped by serial entrepreneur Elon Musk , not a whole lot.What prompted Musk to choose to veer from PayPal to SpaceX, to Tesla? For that matter, what makes anybody choose the next move in their career?Dashun Wang , an associate professor of management and organizations at the Kellogg School, wondered if such seemingly mercurial choices could be modeled scientifically. Musk, whom Wang considers his personal hero, may be an extreme case. But every serial entrepreneur, artist, or scientist- that is, anyone whose job involves discovery, experimentation, and deciding what to work on next- thrives on seeking out new challenges.And understanding how professional innovators move from project to project has implications beyond th e merely philosophical.If we know individually how ansicht people tend to change direction, then that determines collectively where things are going, Wang says.So how do innovative people choose their next career move? Is it really as random as it often seems?Wang, who is also a faculty member at the Northwestern Institute on Complex Systems , is used to tackling questions that might seem too ambiguous to yield to quantitative analysis. Were the unreasonable optimists, Wang says. We figured that theres got to be some pattern that we can document.Lets first understand how our interests change during the course of our careers- then we can debate about what the best strategy is for making those changes.Wang and his coauthors Tao Jia of Southwest University in China and Boleslaw K. Szymanski of Rensselaer Polytechnic Institute began by narrowing their investigation to one particular domain of innovators physicists.This scientific community uses a detailed set of numerical codes- the Phy sics and Astronomy Classification Scheme (PACS)- to define research topics, much like the Dewey Decimal System uses numbers to categorize the subject matter of library books. The researchers used these codes to analyze how the work of the approximately 10,000 physicists in the database changed from project to project.We realized that theres a remarkable amount of regularity in what we choose to do next in our careers, Wang says.Several trends emerged from their analysis. The first is that fruchtwein physicists research stayed relatively constrained within particular disciplines or domains.What this means is that most people- even innovators- dont change as much as they conceivably could, explains Wang, who holds a PhD in physics himself.When researchers did shift to a new project, it tended to be one that was very close to a previous project in terms of what Wang calls knowledge space.But which previous project? Somewhat unexpectedly, according to the data, the physicists most recen t projects exerted the most dominant influence on what project they chose next.According to Wang, the physicists decisions go against a common intuition about innovators decision-making. That idea posits that the more time is spent moving in one direction, the further one gets ahead of the competition, and the more incentive there is to choose new projects that align with that initial direction. If physicists were trying to maximize their hard-won knowledge about that topic, they would double down on projects in similar domains as their earliest efforts.So your fourth project should more likely be similar to your first project than your third, Wang says.Instead, he says, what we find in the data is the other way around. If you study something, the next topic you study is predominantly determined by what you studied last- not what you studied first.This recency effect likely applies even to apparent outliers like Musk. Take his latest venture a startup called Neuralink , specializin g in braincomputer interface technology with the goal of allowing human brains to keep up with artificial intelligence. It seems wholly unrelated to Musks prior successes with online payments, electric cars, and rocketry. However, one of Musks lesser-known projects- a nonprofit research company called OpenAI , focusing on artificial intelligence- does share clear similarities with Neuralink. Musks involvement in OpenAI began just two years before he launched Neuralink.Still, while Wangs model sheds new light on how innovators choose their next projects, it doesnt speak to how they should choose- both to move forward an entire field and their own careers.Lets first understand how our interests change during the course of our careers- then we can debate about what the best strategy is for making those changes, says Wang.Previously published in Kellogg Insight . Reprinted with permission of the Kellogg School of Management.