Serial Innovators and Betting on the Future

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Betting on serial innovators is a widespread phenomenon. Who would you trust more with your money? Someone with a proven track record or someone with little proof of past success? Many entrepreneurs and innovators who get it right the first time succeed the second time as well. However, correlation between past success and likelihood of continued success in the future isn't always as straightforward as it might sound.

We celebrate innovators, and we look up to them. They are literal heroes in our eyes because they dared to challenge conventional ways of seeing the world and came up with radically new ideas that completely changed mainstream thinking. We admire serial innovators even more. They achieved this feat not just once but multiple times. We have great respect for people like Edison, Tesla, Leonardo Da Vinci, Richard Branson. Their contribution to the human race is indisputable.

However, a question has been bothering me for some time. Is it more likely for a serial entrepreneur or innovator to succeed the next time? Do serial innovators have a greater chance of success? Or is it just chance?

There are many examples of people who transformed an industry multiple times. But there are also plenty of examples of people who, following on from an initial success, held on to their ideas for too long and failed to re-examine them. History is full of examples of innovators who fall flat on their faces after multiple success stories.

The issue at stake here is whether past successes increase the likelihood of future success. And the answer seems to be: it depends. Let’s investigate a little further.

Serial innovators typically come at problems from a position that is outside of mainstream thinking. We can observe this in various domains of human life, including in business, science, and the arts. These innovators are correspondingly less likely to be familiar with the mainstream tools, processes and thinking patterns employed by their contemporaries. 

Because they are not trapped within conventional ways of seeing the world, they are much more likely when faced with a problem to come up with unique solutions. Let’s look at a few examples to illustrate the point.


  • Franz List failed the admission exam to the Paris Conservatory (Conservatoire National Supérieur de Musique et de Danse de Paris).
  • Impressionist painters didn’t have the chance to present their paintings in the Saloon, the world’s most significant exhibition at the time.
  •     Many music theorists argue that if you are a jazz pianist, it is still possible to learn how to play classical piano. But suppose you have spent decades undergoing rigorous classical music training. In that case, the chances are meagre that you can ever become a good jazz musician because the basis of jazz music is improvisation, the exact opposite to interpreting given notes on a piece of sheet music.


  • According to legend, Einstein was a poor student who failed in math.
  •     Charles Darwin dropped out of medical school after just two years of study.

ENTREPRENEURSHIP (immigrants and college dropouts are transforming the tech world)

  • Google co-founder Sergey Brin was born in Russia.
  • Microsoft CEO, Satya Nadella, is Indian.
  • Google’s CEO, Sundar Pichai, is Indian.
  • Google’s CFO, Ruth Porat, is British.
  • Elon Musk, of Tesla and SpaceX fame, is South African.
  • Aerospace entrepreneur turned astronaut Anousheh Ansari is Iranian.
  • Intel co-founder Andy Grove was born in Hungary.
  • NVIDIA co-founder Jen-Hsun Huang was born in Taiwan.
  • Venture capitalist Peter Thiel was born in Germany.
  •     Steve Jobs’ father immigrated from Syria.

(Taken from David Epstein, Why Generalists Triumph in a Specialized World)

There is, however, a caveat there. After coming up with a completely innovative idea that revolutionises their field, great innovators often become “too familiar” with their theories. Sometimes people who create something extraordinary fail to persevere in continuing to re-examine the world from new perspectives.

  • Einstein reframed Newtonian physics from the new perspective of relativity. Later, however, he refused to rethink his theory, even in light of contradictory evidence. He famously said: “God does not play dice with the universe”, thus completely disregarding the revolution that was happening in quantum physics.
  • Kodak reinvented the photography industry twice. In the late 1800s, people used chemicals on glass plates to capture images. George Eastman came up with a much more convenient solution for taking pictures. He invented paper film and founded Eastman Kodak in 1892. His new invention became an instant success; his company couldn’t keep up with demand for more than a decade. In the early 1900s, Kodak reinvented itself by shifting focus to colour photography. However, after revolutionising an industry twice, it failed to make the shift the third time. Kodak invented digital photography and made the first digital camera in the 1970s. However, it used the newly developed digital technology to improve its existing, film-based technology, thus completely missing the digital revolution and resulting in the wiping out of its remaining business.
  •     IBM made mainframe computers a success story. Yet, after dominating the computer industry for decades, they failed to recognise the market potential of the personal computer in the 1980s.

The danger might be formulated something like this: becoming too familiar with a particular way of thinking makes it harder to reimagine the world a second or third time. Shifting paradigms represent one of the greatest challenges faced by any well-established expert. Coming up with something entirely new, making it mainstream and then disregarding that very same idea to come up with something even more profoundly unique is perhaps one of the most admirable things a human being is capable of. It has been accomplished by just a handful of thinkers in history.

The more common scenario is that people, like protective guards, hold on to their ideas for too long, even in light of contradictory evidence. People become so deeply ingrained in their own way of thinking that they fail to re-examine their theories, even when clearly superior new methods render old ways of thinking obsolete. As Nobel Prize–winning physicist Max Planck explained: “A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it (…).” He also noted: “Science progresses one funeral at a time.”



Outlined below are a few possible explanations. The list is not exhaustive.

Randomness bias

We tend to see order, even where there is nothing but randomness. Nassim Nicolas Taleb has famously argued that as humans, we cannot understand the nature of randomness. We see patterns, structures, rules and order in completely random situations. According to Taleb, an outstanding achievement isn’t always the result of excellent skills and abilities. From the outside, it can look like a person is repeatedly changing the world. But in reality, his or her success can be attributed to numerous factors that we fail even to consider. People are terrible at distinguishing blind luck from personal competency as factors determining successful outcomes.


“Hot-hand” fallacy

If you flip a coin 100 times, getting 50 heads in a row and then 50 tails is possible. Statistically, there is an equal chance of this outcome as of any other combination of heads and tails. Yet, after seeing a coin flip to heads 49 times in a row, people are convinced that the next coin flip will be the same. In basketball, they call this tendency the “hot-hand fallacy”. We tend to believe that a successful streak is likely to lead to further success. For example, if a basketball player has made three consecutive shots, we might believe he has a greater chance of making the fourth shot as well. But in reality, there is an equal chance of a different outcome.


We see past events as a good indicator of future events

Consider the “Turkey-problem” or the “Problem of Inductive Knowledge” presented by philosopher Bertrand Russell and popularised by Nassim Taleb. “Consider a turkey that is fed every day. Every single feeding will firm up the bird’s belief that it is the general rule of life to be fed every day by friendly members of the human race “looking out for its best interests,” as a politician would say. On the afternoon of the Wednesday before Thanksgiving, something unexpected will happen to the turkey. It will incur a revision of belief.” If that turkey could talk, he would probably warn us that past events are not always good indicators of future events.


Recallability trap

Our memory is significantly shaped by events that have left a strong impression on us. As decision expert Howard Raiffa and his colleagues write, “We all, for example, exaggerate the probability of rare but catastrophic occurrences such as plane crashes because they get disproportionate attention in the media.”

We tend to remember much better, for longer and more vividly events that are easier to recall. If someone has had a stunning record of success, it can cloud our perception of the situation as a whole. We fail to recognise the hundreds of others who tried the same thing, went through similar difficulties and whose endeavours ended in failure.

Someone succeeding against the odds on multiple occasions is pretty unusual. In judging their likelihood of success on subsequent occasions, we inevitably consider the odds in light of these past successes.


Halo effect

The appearance of success can be contagious. Our impression of a person formed through gauging the success of their actions in one area can influence our opinion of that person’s abilities in other areas as well. This phenomenon is known as the halo effect.

We often mistake the message with the messenger. We fail to critically examine the ideas of someone who has already proven him- or herself successful. The reality of present circumstances, however, isn’t necessarily influenced by previous outcomes. There are many cautionary examples of people who wandered outside their circle of competence, tried their hand in an area they were unfamiliar with, and failed. Believing too firmly in their abilities to make things happen, they didn’t bother to examine the new rules governing new situations. They played the old game in a new field, one where outcomes were determined based on entirely different sets of rules.



There are, however, various reliable techniques that can be employed to better predict the likelihood of success in any given innovative venture.


1. Assess the likelihood of someone having developed actual expertise.

There are certain cases when, through repeated experience, a person can develop expertise. However, there are also situations when experience does not lead to learning. As Daniel Kahneman explains, the development of expertise requires an environment with specific conditions. Your world needs to be regular, relatively stable, with clear rules that you can master. You also need immediate feedback, so you can see the consequences of your actions and learn from them. You also, furthermore, need time to master the rules. When operating under these circumstances, you may, over time, develop expertise in an area.

However, there are certain environments where experience does not lead to learning. Psychologist Robin Hogarth calls these situations “wicked” learning environments. In these cases, the rules of the game are often unclear or incomplete, or the environment is unstable. There may or may not be repetitive patterns, and these patterns may not be obviously observable. Feedback is often delayed, inaccurate or both. In these cases, past success is not a great indicator of future success.


2. Use critical thinking to examine what could go wrong.

We tend to predictably and systematically underestimate the likelihood of catastrophic failure. We also tend to see order where is nothing but randomness.

We need to be especially aware of the pitfalls and negative consequences of our actions. Successful strategists tend to focus obsessively on things that can go wrong. They don’t just prepare for success; they prepare for failure as well. They critically examine every single possibility where decisions might go wrong.


3. Consider the broad picture.

Don’t just focus on individual details and success stories. Try to examine the situation from as many different perspectives as possible.

Philip E. Tetlock, one of the greatest experts in prediction science, has shown how to increase the accuracy of our predictions. The most successful forecasters, he writes, are those able to see a problem from many different perspectives. They accept ambiguity. They can integrate contradictory world views into a single theory. They have a broad range of knowledge, derived from many different fields. And they keep an open mind to the possibility of changing their initial assumptions in light of new evidence.


4. Finally, and perhaps most importantly: Focus on the process.

Many of the most successful serial innovators had a process. It might be possible to get it right once or twice without one. But in the long run, if someone doesn’t have a process, their endeavours are likely to fall foul of blind luck and randomness.

A good process makes innovation more predictable, understandable and manageable. It can minimise uncertainty, though it cannot guarantee success. The factor of uncertainty is always present when we make a decision. However, using a solid and proven process can greatly enhance the chances of getting innovation right.




On serial innovators

  • Griffin, Abbie, et al. Serial Innovators: How Individuals Create and Deliver Breakthrough Innovations in Mature Firms. United States, Stanford University Press, 2012.

List of immigrants entrepreneurs

  • Epstein, David. Range: Why Generalists Triumph in a Specialized World. United States, Penguin Publishing Group, 2019.

The story of Kodak

  • Barabba, Vincent P. Surviving Transformation: Lessons from GM’s Surprising Turnaround. United Kingdom, Oxford University Press, 2004.


  • Christensen, Clayton M. The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. United States, Harvard Business Review Press, 2013.

Science progresses one funeral at a time.”

  •     Planck, Max. Scientific Autobiography: And Other Papers. United States, Philosophical Library/Open Road, 2014.

Randomness bias

  •     Taleb, Nassim Nicholas. Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets. United Kingdom, Penguin Adult, 2007.

“Hot-hand” fallacy

  •     Tversky, A, Gilovich, T. & Vallone, R. (1985). The hot hand in basketball: On the misperception of random sequences. Cognitive Psychology, 17(3), 295-314.
  • (2016, January 21). Law of small numbers. Psychology. Retrieved August 12, 2020, from
  •     Johnson, J., Tellis, G. J., & Macinnis, D. J. (2005). Losers, winners, and biased trades. Journal of Consumer Research, 32(2), 324-329.
  •     Castel, A. D., Rossi, A. D., & McGillivray, S. (2012). Beliefs about the “hot hand” in basketball across the adult life span. Psychology and Aging, 27(3), 601-605.
  • Ayton, P., & Fischer, I. (2004). The hot hand fallacy and the gambler’s fallacy: Two faces of subjective randomness? Memory & Cognition, 32(8), 1369-1378. Link here

The “Turkey-problem”

  • Russell, Bertrand. The Basic Writings of Bertrand Russell, 1903-1959. United Kingdom, Routledge, 1992.
  • Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. United Kingdom, Penguin Books Limited, 2008.

Recallability trap

Halo effect

  • Murphy, Kevin R.; Jako, Robert A.; Anhalt, Rebecca L. (April 1993). “Nature and consequences of halo error: A critical analysis”. Journal of Applied Psychology. 78 (2): 218–225.
  • Palmer, Carl L.; Peterson, Rolfe D. (March 2016). “Halo Effects and the Attractiveness Premium in Perceptions of Political Expertise”. American Politics Research. 44 (2): 353–382.

Expert intuition

  • Kahneman, Daniel. Thinking, Fast and Slow. United Kingdom, Farrar, Straus and Giroux, 2012.
  •     Hogarth, Robin M. Educating Intuition. Chicago, University of Chicago Press, 2001.

Prediction science

  • Gardner, Dan, and Tetlock, Philip. Superforecasting: The Art and Science of Prediction. United Kingdom, Random House, 2015.


On the importance of a decision-making process

  • Winter, Hannah, et al. Decision Quality: Value Creation from Better Business Decisions. Germany, Wiley, 2016.