Tag: mentors

Genius time management – how do really successful people manage their time?

There are lots of books on time management, from the famous ‘Getting Things Done’ to less famous works like ‘How to Live on 24 hours a day’ or ‘How to get everything done and still have time to play’. These books may have value, as they represent the struggles and experiments of real people to get grips on their life. Still, it may also be worthwhile to look at people who achieve what time-managers strive to obtain, which is not so much cramming as much stuff as possible in one’s daily allotment of 24 hours, but a successful life.

If you ask people why they cannot achieve their goals, the likely answer is “because I don’t have enough time’. Or perhaps more worryingly, even many people without grand (or not so grand) goals seem to be suffering from chronic stress, which, even if it does not lead to burnout, likely leads to a lower life expectancy. Scientists in academia are no exception to the ‘rat race’ of modern life, they even likely work longer hours than the average person, somewhere in the neighbourhood of 55 to 61 hours a week.

Now, this may be logical; after all, prizes, grants and careers are typically awarded to scientists who produce quite a lot of work. And it stands to reason that if you work longer hours, you can produce more work. However, if you look to research that tried to predict the success of a number of scientists, there does not seem to be a relationship between numbers of hours worked in the week and scientific accomplishment; in fact, most top scientists described themselves as ‘lazy’. What is going on?

The first explanation, that top scientists have much better brains and therefore can work faster, does not seem to hold true; all professional scientists have IQs of 120 and above, there don’t seem to be IQ differences between Nobel laureates and random scientists (as the quoted Root-Bernstein study as well as other comparative research between top and average scientists suggests).

But if raw brain power is not the issue, what is? There seem to be three factors:

1. Top scientists use their time more efficiently. This seems at least for a part because of smarter research strategies, often gleaned from their mentors (which were usually also top scientists themselves). Top scientists often do riskier, or more original, or more important, or more ‘doable’ research; they seem to spend more time finding the right question and choosing the right approach, instead of just ‘experimenting and writing.’

2. Next to working in smarter ways, top scientists also work with more focus, enthusiasm, and likely speed. Let’s call this ‘energy‘. Top scientists tend to be quite good at managing their energy. This happens in a quite unexpected way:  they consider themselves ‘lazy’, by which it seems they mean that they only work when they feel like it, and generally don’t do things they do not like. If taken to excess, this has some disadvantages in social relationships (Einstein’s first marriage broke down because he was not a very supportive husband), but in general, being bold in doing things as much as possible only when you feel like them has some unexpected advantages. First of all, since top scientists generally do not overwork themselves (though exceptions exist) they continue finding their work joyful and interesting instead of just one more duty on the treadmill. Secondly, since they get joy out of their work itself, they can feel less attached to uncontrollable outcomes like tenure or Nobel prizes, which cause their colleagues stress and may also contribute to loss of the joy of science if the sought awards take too long coming. Thirdly, they also have fewer ‘energy leaks’ since they do fewer things that bore or frustrate them. Fourth, by doing enjoyable things even if those are not ‘scientific’, such as having hobbies, like playing the piano, or sailing, or painting, they regularly recharge energy.

3. Top scientists are willing and able to spend a greater proportion of their waking time to research. Whether by character, social skills, or ambitions, top scientists tend to focus more on doing research, and less on teaching, administrative tasks, or prestigious invitations. They find it easier to say ‘no’, also to themselves! Less time spent in meetings or editing journals equals more time spent on research. Of course, it is fortunate that there are academics who are dedicated to teaching or to administration, as those are possibly even more needed than ‘pure research-heads’. And some people simply love teaching or getting a high-status administrative position. Still, top scientists found it easier to focus on research, the Root-Bernstein paper reported that they much more rarely took up administrative tasks than average scientists, and if they did, they tried to drop them as quickly as possible. So next to a generally more productive research strategy (point 1), top scientists tend to have certain interests and priorities which differ from the average (less aiming for status and social contacts, more aiming for research) and are skilled enough to get away with it.

These factors led to the surprising interview results of Root-Bernstein that while average scientists wished they had more hours in their day, top scientists considered themselves to have plenty of time. They had fun, and they were paid for it!

If one would compare it to time management books, great scientists could be considered (in the ‘getting things done’-parlance) to drop almost everything, leading to very small ‘to-do’-lists. And since they mostly did what they enjoyed, problems with procrastination (like discussed in ‘How to get everything done and still have time to play’) also largely disappeared (largely, not entirely, the later Nobel prize winner Murray Gell-Mann had a huge writer’s block, not only as a student, but even when he was a famous, Nobel prize winning physicist, though that of course involved writing, not research).

 

The most interesting question may however be: how can we apply this knowledge to our own lives?

First, try to find effective strategies. The first obvious approach is try to befriend people who are successful in your field (or at least more successful than you) and talk with them, try find out how they approach problems or tasks. That may take care of the ‘effective strategy’-part. Of course, you can also experiment with approaches and see what works for you (as most self-help-book authors do), but finding a role model may save you lots of trial-and-error.

Secondly, try to enjoy your life more. Which for a part may depend on getting comfortable with wanting less, not being a person who wants a career and a relationship and a busy social life and lots of travel and a gloriously large and clean house and who knows what else (like kind of everything your friends have on Facebook). Of course, this is easier said than done. Not only is it scary (though for that it can help to know that other research kind of confirms Root-Bernstein’s finding: also outside science, happiness leads to success, so don’t fear too much that your success will be sacrificed on the altar of happiness), but it is also hard. It is not that easy to be happy. There are gratitude exercises, kindness exercises, but I guess the great scientists generally did not do such exercises but consciously or unconsciously maintained three principles: do what you like, do what you value, and let go of whether you achieve a certain goal or not.

The third item – spending more time on activities that are relevant to success in the direction you want to go- can also be complicated. If you like the other activities more than research, it seems legitimate to spend more time on them, though you should not complain then that scientific success eludes you. But do be honest with yourself: are you doing all those other activities for fear of being disliked or fired? Or do you do them because you burned yourself out on research by working too hard on projects that did not inspire you? In the first case, you may need to work on your skills, network, self-confidence or simply move to a less-demanding career. If the second, try to enjoy your research as per the second of three rules.

So be smart, be effective, and have fun too! And till next time!

Talent, desire, training, or tricks – what makes a top performer?

 

At the end of one of my recent posts I mentioned that aspiration to do better may be the characteristic distinguishing top performers and medium performers in many fields. However, while most people would likely agree that such differences in motivation may make a difference in regular jobs, there are also fields like professional sports, soloists in music, and academia, where competition is fierce and one has to be better than one’s peers to retain one’s job. Wouldn’t all those professionals be equally fiercely motivated? If that is the case, motivation would be a bad explanation for performance differences. Should we again try explain things by ‘talent’ or, if we look further, are there other factors we should take into account?

Most people, by definition, are not top performers in their jobs or careers. However, they generally do not have to be; as long as they are perceived by their employer or customer to deliver more value than they are paid, or customers or employers cannot very well judge the quality and quantity of their work, they can generally remain in their jobs and earn money for themselves and perhaps their family. So most people have no great need to improve in their job.

However, life is quite different if one is a professional sporter, artist, or untenured scientist. If you don’t perform very well compared to your competition (which tends to be considerable) you are soon out of clients, sponsors, funds, or a job. You really cannot slouch that much, every professional in these fields would have at least some motivation to perform well and pay attention to their performance. So it would be natural to think that if all performers are motivated if not very motivated, differences in performance in those fields cannot come from motivation, but must come from other factors, like talent.

Of course, talent may exist. In some fields, like the 100 m sprint, the dominance of black sprinters suggests some genetic talent that can give a small but crucial advantage over people who did not originate from the west of Africa. Sometimes genes play a role. The genetic advantage in this case may be small (0.15 s, or less than 2%), but in sports, very small differences count, as differences between best and worst professional sprinters may only be like 10%, which is noticeable, but is obviously much less than the reported factors of 2 to 10 differences observed for scientists, programmers and teachers.

So while talent may give explain some performance differences, one should also look at other factors. Quality and quantity of training, for example, and -indeed- differences in motivation.

The easiest factor to assess are differences in training. In general, top performance started training earlier in their field than less prominent performers. Mozart who started music lessons at age 2, and Tiger Woods, who even before that age was placed by his father in a children’s chair to watch dad Woods hit golf balls again and again. Michael Jackson and Andre Agassi similarly started (or rather were started) their training early, driven by dominant dads. It is hard to separate the effects here: brain plasticity is likely highest at young age, social support/pressure is enormous as the trainer is someone incredibly important to the trainee, the amount of time available for training is very large, and social recognition for the ‘prodigy’ will likely also enhance motivation. How early training starts, how much training one has received, and how much attention one pays to the training that is received simply because the trainer happens to be someone very important to you will all influence how much is learned. Definitely, differences in performance will at least for a part reflect differences in the amount of effective training, one can definitely explain differences even among professionals for a large part due to differences in training instead of immediately claiming differences in ‘talent’.

Another reason to believe in the importance of training, also in fields like science which seem to have much less fanatical dads drilling their offspring, is the phenomenon reported by the sociologist Harriet Zuckerman in her book “Scientific Elite“: over half of US Nobel prize winners had been  either PhD student or postdoc in the laboratory of another Nobel prize winner. Most of those who hadn’t, had worked as PhD student or postdoc of a scientist who was nominated for a Nobel prize (but did not get it), or had a supervisor who worked closely together with another (future) Nobel prize winner. In short, most extremely successful scientists worked closely in their ‘formative years’ with scientists who also were extremely good. And they indeed reported that their experience with those top scientists had been very important to them, not so much as for learning subject matter knowledge (like physics formulas) but ways of thinking and doing research.

Now, one could argue that learning might not have played a role at all here; the ‘mentors’ could have gotten their Nobel prize together with their mentee (like happened to physicist Gerard ‘t Hooft who shared his Nobel prize with his mentor Martinus Veldman), or the mentors used their social clout (Nobel prize winners can nominate candidates) to bring their favorite pupils to Stockholm too. Or only the most promising young scientists were selected by the mentors to join their labs; the young scientists would very likely received a Nobel prize on their own, their talents were simply recognized early.

The above factors may indeed have an influence, however, a closer look at the data suggests that education plays an important part too. The persons who supervised most future Nobel Laureates, Arnold Sommerfeld and Enrico Fermi, were neither the most famous scientists of their age (so they could not necessarily expect the best and brightest to flock to them), nor did they have the strongest networks they could use to ‘Nobelize’ their mentees; Sommerfeld never won a Nobel prize so could not nominate people himself, Fermi died relatively young. However, the striking similarity between the two mentors is that they cared a lot about mentoring their students. In Cropper’s book “Great Physicists“, Fermi was the only one described as wanting to become a professor because he loved teaching, and while he carefully selected his students, he was willing to spend infinite amounts of time and care on mentoring them. Sommerfeld was a supervisor who would have 1-to-1-discussions about their projects and developments in science in general for about 1 hour every other day with each of his PhD students, which is an enormous amount compared to the more typical half an hour a month that normal supervisors are willing to spare. Of course, Fermi and Sommerfeld were themselves also very good researchers. However, among the many great researchers in the 20th century they stood out not for being the best researchers but as those professors most dedicated to give promising young scientists a great education. And the record numbers of Nobel prizes for their pupils (7 for Sommerfeld, 6 for Fermi) seems to indicate that they were quite effective in that.

So even in science, training is important, and it is likely that top educators are in shorter supply than top potential talent is.

And the original premise of this blogpost, that in highly competitive fields all performers should be equally motivated? That would also seem to be untrue, in two aspects even: not only is the amount of motivation different between people (and likely in individuals over time), but people actually have multiple possible motivations, influencing their effectiveness in reaching goals.

For example, Daniel Pink (in his book ‘Drive’) cites research claiming that motivation to master one’s field is more correlated to the number of patents obtained than the desire for money is, even when controlled for effort. The article “Making It in Academic Psychology: Demographic and Personality Correlates of Attainment” indicates that both the quantity of motivation differs among professional academic psychologists (so motivation is unequal even among practitioners in a competitive field), and the types of motivation. Quantity of motivation is important: more motivated psychologists publish more. And kind of motivation is too: if psychologists were mainly motivated by the desire to outdo others, they published below-average work, if psychologists desired to master their field or simply liked to work hard, their work was above-average.

Talent may exist, but based on the above, training and motivation can move one up and down in any competitive hierarchy, which can at least make the difference between keeping one’s job and needing to find another career.

The above may sound nice and even somewhat convincing, but what can a practical scientist/artist/sportsperson do with that knowledge? Three conclusions stand out.

  1. It pays to find a good mentor/coach. Definitely, some weeks of effort, of networking, of asking more experienced people who they think are (beside themselves) make good mentors or coaches can pay off enormously. At least much more than those same four or such weeks simply spent ‘working hard’
  2. Try to keep your motivation high, for example by using the general strategies described in my previous posts on ‘passion growing‘ and motivation.
  3. You may also want to stress your personal growth and mastery instead of ‘beating others’. How to do that, I’m not sure yet, perhaps by praising and rewarding yourself when you have learned or improved something, instead of only congratulating yourself when you have ‘beaten’ another person. That being said, not all fields may be like academic psychology, and quite some top sporters became quite successful despite attaching great value to winning (like John McEnroe’s temper tantrums seemed to indicate).

In conclusion: while professionals in competitive fields may differ in talent, they also definitely differ in training and motivation; and while you may not reach the absolute top by only carefully handling your motivation and finding the best mentors you can possibly get, you can definitely achieve more (if not much more) that way.

So what is next for this blog? I’ve discussed the basics of training and of motivation, and while subjects like creativity, networking and marketing are also important for scientists, I’ll probably first check my archive to see which subjects may be most relevant to update and repost. And I’ll also add some book reviews, so you can know where to look or study further.

Till next time!