ABSTRACT: Who is most likely to discover a breakthrough? Why are some scientists more successful than others at discovering them? By using extant theories of breakthrough emergence to predict a groundbreaking discovery in biology, RNA interference, I show that the explanatory power of combining all current theories are weak because they sample on rare successes rather than the multiple instances of failure in the discovery process. Instead, I focus on understanding these failures by interviewing scientists with high potential of discovering breakthroughs in a case historical analysis. My findings suggest that the seminal discovery was missed several times not only due to difficulties in solving a particular problem but also due to failures to identify breakthrough opportunities. I propose a cognitive framework with institutional underpinnings at the basis of these failures. In the problem identification stage, framing barriers from pursuing normal science and existing boundary barriers between communities of scientists contribute to difficulties in identifying the breakthrough opportunity by misrepresenting the magnitude of the problem. In the problem-solving stage, scientists are constrained by paradigmatic pressures to avoid being wrong, and coupled with boundary barriers similar anti-dogmatic observations stay isolated and unsubstantiated, thus diminishing confidence to identify a new revolutionary paradigm.
BIO: Sen Chai is a post-doctoral fellow at Harvard University and the National Bureau of Economic Research (NBER), and recently obtained her doctorate from the Technology and Operations Management (TOM) unit at Harvard Business School. Her research interests are the emergence, diffusion and commercialization of creative breakthroughs. Her current project focuses on understanding where scientific breakthroughs come from and which scientists are more likely to discover them using a hybrid methodology. In the context of innovation policy, she is also studying innovative performance and productivity effects of academic-industry collaboration funding, as well as understanding which managerial and structural factors of these grants make them more successful. Prior to Harvard, Sen worked in the San Francisco and Seattle offices of Deloitte Consulting LLP as a consultant helping clients optimize their business processes. She received a B.Eng. in Electrical Engineering from McGill University and a M.S. in Management Science and Engineering from Stanford University. She has also passed all three levels of the CFA curriculum. Sen grew up in Beijing, Paris, New York City and Montreal, and is fluent in Mandarin Chinese and French. She enjoys traveling, sailing, and skiing during her free time.