What makes a successful scientist?
In the 1950’s, Bernice T. Eiduson started to wonder why some scientists had a greater impact than others. Some scientists produce insight after insight, racking up papers and prizes. Whilst others just plod along and never account for much.
What makes some scientists more innovative than others?
To find out, she picked a group of academics and followed their careers over 20 years. During that time she carried out interviews, ran psychometric tests and recorded their work. All the time trying to figure out what made some more successful than others.
How do you define success?
It is hard to say that one person is more successful than another; beauty is, after all, in the eye of the beholder. Fortunately in the academic world it is easy to measure. Academics write papers. Every time they discover something new they publish it. Their peers then decide if the science was good or not by building on it. The more citations a paper gets the more relevant and insightful it is.
So it is easy to define success. Simply count the number of papers published and the number of citations they received.
The more citations a scientist gets, the more successful he is.
So what makes a scientist innovative?
Unfortunately Bernice Eiduson died before the end of her study, but some of her colleagues (Root-Bernstein et al.) picked up the mantle and sifted through the evidence.
There were several factors that didn’t make much difference:
- Age
- Health
- Childhood hobbies
- Athletic ability
Non of these were correlated with impact. The team also looked at over 50 cognitive, emotional and motivational variables. Nothing was significant.
The magic ingredients
Eventually the team highlighted two indicators that predicted how much impact a scientist would have:
Indicator one
The first was whether the scientist publish a series of high impact papers early in their career. If they published 5 or more such papers before they were 45 then they were likely to publish more.
I’m afraid this insight falls into the “no shit Sherlock” camp. Perhaps I am being a little harsh in my criticism.
Indicator two
The second insight was far more revealing. The pie charts below show how the subjects that the scientists studied changed over their careers:
Each colour represents a change of topic.
- The pink segment is the first topic a scientist wrote about (say Chemistry)
- The blue segment is the second topic they wrote about (perhaps BioChemistry)
- The third topic is in green and on it goes
The last black segment represents papers that weren’t research based; reviews for example.
The pie charts of the low impact scientists are nice and neat. They published papers on their specialism and maybe one or two related topics. They were experts in their fields.
The high impact scientists moved from one subject to another. They had a much more confused approach.
The pie charts don’t do justice to how messy the careers of these guys were. The charts below show how the topics some of the scientists wrote about varied over time.
Each horizontal line represents the sequential order of the first 100 papers published by each scientist. Every time the scientist wrote about a different topic the colour changes. If the line doesn’t reach 100 then unfortunately the scientist died during the corse of the study. Or they simply ran out of things to say.
The more varied the experience of the scientist and the further reaching their interests, the more creative they were. The ability to pull together threads of logic and reasoning from different subjects was far more powerful than developing a deep specialist understanding of a single topic.
Innovation in business
If you insist that new recruits to your organisation have 10 years industry experience, with a clearly defined career path and ask your head hunters look for them at industry specific conferences, you are unlikely to have an organisation that ever tries anything new.
This is fine and sensible if you run nuclear power-plants for a living. Experimentation is sometimes best avoided.
If, however, you want innovation and new ideas; then mix it up a little. Hire people from different sectors and industries. Ask people to take on roles outside their comfort zone and give them the time to pursue their own interests within work.
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Hello James
The big assumption that you are making is that the folks that lead/run big companies want innovation. I find myself in disagreement with this assumption.
I am clear that these folks want the FRUITS of innovation: the product, the publicity, the revenues, the profits, the bigger remuneration package…
Yet getting to this outcome is not pain free. Innovation requires experimentation. Innovation involves failure. The process of innovation takes time and tends to be costly. Most importantly the experimentation involved in innovation can be disruptive to the business. Or just to the status / authority of the elite.
So I say that most Tops are allergic to the process of innovation. So they prefer to show up as leader by talking about innovation but not taking any risks. If risks are taken then they are likely to be in the realm of the product and left to the R&D dept – you know those odd folk in their own building on the periphery of the business.
Yes Maz, Tops are good at not taking any risks