The Case for Range
How multidisciplinary learning can give you an unfair advantage
Hello good friends,
Firstly, I’d like to warmly welcome all new subscribers who have joined in the last couple of weeks. If you came in expecting to learn new ideas and insights while giggling a good deal through the process, you’ve made the right choice.
Since the world is going nuts watching the football World Cup right now, I want to start with a fascinating observation on the team that won the trophy 8 years ago. Die-hard fans and expert Googlers will instantly know that I’m referring to the Germans.
Seeing such a group of hyper-talented folks, we believe that they must have spent millions of hours practicing their craft, without which they’d not have reached the top. Malcolm Gladwell even popularised this line of thinking with his famous 10,000-hour rule.
It’s a widely believed idea that to get better or achieve success, repetition is the key. You HAVE to do the same thing over and over again till you suddenly become an expert.
In the world of sporting, this is taken even further. If you don’t begin net practice in the womb, you’re gone. If by the age of 2 you can’t play the perfect cover drive, forget about making it to the national cricket team. To be the next Sachin, you have to start 8 hours of daily practice before being born.
But you know what a team of scientists discovered about the winning German team?
They found that most of them were late specialists- they didn’t begin to put that kind of time into football early on and began playing at the league level only in their early 20s! This totally flies in the face of conventional theories. Even Roger Federer, one of the GOATs of tennis, was also in this category of dabblers.
What’s more interesting is that these folks sampled a variety of sports and tried many things out before settling on one particular sport- which they’d then go on to specialize in, and ultimately dominate.
Early sampling and diversity proved to be key, and many athletes are known to have dabbled with multiple sports before focussing deeply on a particular one. But this underscores a larger point that researchers have begun to identify.
It is the idea that in today’s world, learning from multiple disciplines offers very high value as compared to narrowly focusing and mastering one tiny area. To understand that better, we need to discuss 2 types of learning environments and what they tell us about the alpha generated by prioritizing width.
Kind and Wicked Environments
Don’t get petrified by the jargon. It’s really simple, and you’ve already experienced both of these environments.
Consider the game of chess. It has rules, which all of us can learn. Those rules aren’t ambiguous and don’t change over the course of a game, a tournament, or even the life of a grandmaster. There are techniques that one can learn, and repetition and practice improves a player’s skill level over time.
That’s a kind learning environment, where the rules are set, feedback is immediate, and similar challenges occur repeatedly over time.
Now consider managing people. Or understanding the mind of a girlfriend. The rules are constantly changing. In fact, there are no rules. Feedback is often vague (“You don’t understand me!!!”), delayed (where you get blasted for something you did 2 years ago) and doesn’t follow the same patterns over time. You may think she’ll be happy if you give her a surprise visit but that might just trigger a war. Using past data does NOT always help in solving problems.
That’s a wicked learning environment. And come to think of it, wicked environments are becoming increasingly common in the modern world. Predicting how markets will move in response to big events, how people will embrace new technology, or how the workforce will react to a new economic policy- there are no clear answers to these questions based on pre-set rules.
Moreover, machines are increasingly dominating all narrow domains. They’re better than us at playing chess, forecasting seasonal demand in retail, and the millions of things that require kind learning environments (which can enable the usage of algorithms) to deliver the goods.
But humans are still good at big-picture thinking- an area that the machines haven’t conquered (yet). And the greatest returns are conferred to those who can integrate broadly, picking up concepts from diverse fields and drawing analogies to arrive at clever ideas and innovations.
Take the example of Claude Shannon, the founding father of information theory. He was able to combine ideas from call routing technology with Boole's binary system for information transmission to give birth to this totally new field that would revolutionize telecommunications. When asked about what enabled the breakthrough, he made a beautiful statement: "It's just that nobody was familiar with both fields at the same time".
That’s what width offers. The ability to combine, the skill to analogize. Researchers who observed teams of scientists collaborating on problems to arrive at breakthrough solutions noted that the teams that got ahead were able to draw and use many more analogies for their ideas and explanations.
And that’s exactly the skill we need to thrive in a world where the rules keep changing, the nature of jobs keeps evolving and new trends constantly kill old ones. The ones who are able to operate despite the ambiguity are the ones who will flourish.
But there’s another reason to embrace wide learning, and it’s rather alarming.
“Experts” often become victims of their own expertise, failing to come up with novel solutions to problems and sticking rigidly to the things they know have always worked. That’s why you see industries getting disrupted all the time- the old hats just can’t drop the rules and tools that made them successful.
When experienced accountants were asked in a study to use a new tax law for deductions that replaced a previous one, they did worse than novices. When the rules of the card game ‘Bridge’ were changed, experts did much worse than regular joes. We really have a tough time if we only know how to perform when the rules are fixed!
So what is the solution? How can we let our ‘expertise’ not be our enemy and learn to operate skillfully as the world produces more and more wicked environments?
By learning widely and opting for range. By focusing on disciplines beyond our own field of work. By cultivating many ‘avocations’ beyond our vocation- a known recipe behind the success of many a Nobel laureate.
That’s exactly why you should be using sources of learning like this newsletter, and that’s also a big reason why I try to mix things up all the time, ranging from history and philosophy to organization building and technology. I purposely try to read from as many fields and diverse sources as possible, because you often end up drawing parallels and taking inspiration from things beyond the narrow confines within which you operate.
More than anything, the joys of cultivating width and range are unparalleled. Beyond the benefits that can accrue over the span of your career, the pure joy of learning things that you had no clue about and getting your mind blown on a regular basis is a worthy end in itself.
If you are convinced with this thesis and want to dive deeper, there are 2 things you can do. Firstly, read this amazing book called ‘Range’ by David Epstein that inspired today’s article. Secondly, to keep your learning wide, get onto the email list.