In 1928 a fungus contaminated a petri dish
and killed some of the bacteria living in it.
Famously, Alexander Fleming investigated
the phenomenon and discovered penicillin:
an accidental and lucky discovery!
Many scientific careers are made up of
serendipitous successes and failures.
But it isn’t all luck.
A scientist’s productivity and ability matter too.
So is it possible to predict
who will make an exceptional discovery, and when?
Is a scientific career predictable?
To answer these questions, an international team
studied the research publications
of many scientists from different disciplines.
Take, for example, Richard Feynman,
who was awarded the Nobel Prize in Physics
for his work on quantum electrodynamics.
In his career, Feynman published 32 works
in Physical Review Journals.
Scientists measure the impact of a discovery
by looking at citations:
that is, how many other scientists around the world
mention the discovery in their work.
Let’s look at the number of citations
that Feynman’s works received
in the first 10 years after publication.
His highest impact paper,
“Theory of the Fermi Interaction”,
furthered our understanding
of the particle physics behind radioactive decay,
and received 330 citations.
You can see that he published
two more highly cited papers in his career.
In this way, the team reconstructed the careers
of more than 20,000 scientists
from disciplines including neuroscience, ecology,
physics, chemistry and economics.
All these careers look different,
with valleys and peaks of impact.
To identify outstanding discoveries,
the team focused on the highest impact publication
by each scientist shown here by the red dots.
The data showed that scientists
tend to make major discoveries when they are young.
This finding matches previous research on creativity.
For example, the first line here
represents a career of 23 years.
This scientist published his ‘breakout’ paper in year 5.
The second line represents a 14-year career,
with the highest impact work published in the first year!
But when the team examined
the reason behind early creative success,
they stumbled across something that surprised them.
Scientists are simply more productive
when they are young – giving them a higher chance
of producing that big hit in their early years.
If we ignore the timing
and only look at the position of the highest impact paper
in the sequence of a scientist’s publications,
we see that the highest impact paper can be,
with the same probability,
anywhere in the sequence of papers published.
It could be the first publication,
it could appear mid-career
or it could be a scientist’s last work.
In other words, impact is randomly distributed
within a scientist’s body of work,
regardless of discipline;
a result the team named the “random impact rule”.
But scientific careers are not entirely random.
A scientist’s ability matters too.
So the team developed a model to untangle
the effects of luck, productivity and ability.
They came up with this equation:
C is the impact of an individual publication.
P is luck,
while Q captures a scientist’s ability to take an idea
and convert it into a high impact discovery.
Each scientist has a unique Q value,
which can be high, like the scientist on the left,
or low like the one on the right.
Luck, or P, fluctuates throughout a scientist’s career.
Unsurprisingly, great discoveries seem to be the result
of both luck and ability, or Q.
As Pasteur said, ‘fortune favours the prepared mind’.
We might expect Q to increase
over the course of a career
as a scientist becomes more experienced.
But it doesn’t.
An individual’s Q value seems to stay constant.
This could make Q a more meaningful measure
than currently-used metrics
such as total number of citations or the H-index,
which do increase over time.
Nevertheless, there are lots of questions:
what exactly is Q?
Could we train scientists to have high Q?
And should we use it to make decisions
about funding or an individual scientist’s career?
There’s plenty to discuss.
But take heart;
with a bit of luck,
your next project could be your most successful one!
