Most of us think that success comes from working hard only on that one thing.
Parents push their kids early on to excel so their child can become the next Tiger Woods, armed with the 10,000 rule and the assumption that the more you specialise, the faster you arrive at excellence.
I’ve collected here particularly compelling ideas from the decision-making aspect that have really stuck with me from the book.
The different mindsets required in Kind vs. Wicked world
Humans often excel in decision-making because we build up experience in a domain that makes us confident that we understand how particular systems or contexts work.
This is particularly the case in kind learning environments, like chess or soccer, where the rules are always the same and you can count on the same patterns emerging over and over again.
In a kind learning environment, you can practice that same golf swing 10 000 times or learn all the sequences of chess moves while knowing that with practice, you get closer to perfection.
But what about our rapidly changing modern world where things are no longer predictable; a world where we are faced with rapidly changing operational contexts, and are disrupted by pandemics, technological innovation, and unprecedented political and extreme events?
In this wicked world, we face situations and contexts that are novel and where we are likely to lack the experience to know which decisions we should make and what their likely outcomes are.
In such a context, we need a different type of knowledge that is not necessarily domain specific:
“Knowledge increasingly needs not merely to be durable, but also flexible – both sticky and capable of broad application… for knowledge to be flexible, it should be learned under varied conditions, an approach called varied or mixed practice, or, to researchers, “interleaving” “ (p. 94).
This interleaving approach encourages analogical thinking and is increasingly the key asset that successful people and innovators harness:
“Whether chemists, physicists, or political scientists, the most successful problem solvers spend mental energy figuring out what type of problem they are facing before matching a strategy to it, rather than jumping in with memorised procedures” (p. 96)”.
They have a clear idea of the characteristics of the problem, its structure in particular, and they look across different sets of knowledge, contexts and experience to first compare their case with other structurally similar cases before deciding the course of action.
They learn about other domains and look for similar patterns across.
Surface vs. Deeper/Inside vs. Outside
This type of analogical thinking helps us to take something familiar and use it in new contexts.
Also called relational thinking, it helps you to see things that cannot be seen (e.g. you learn about electricity by thinking about how water flows) and how abstract ideas can be connected even in different knowledge contexts.
Analogies occur either at the surface or at a deeper level:
Surface analogies are based on insights from our experience where we draw on a memory from a similar situation to solve a problem.
Yet, novel and unfamiliar problems are not likely solvable via surface analogies but through spotting deeper structural similarities across cases from different domains.
This requires using abstractions to spot similar patterns and principles that hold true regardless of context.
Epstein also recommends that we need to be able to shift between the inside and the outside view: the inside view happens “when we make judgments based narrowly on the details of the particular project that are right in front of us” (p. 108).
Yet, the outside view actually helps us to look for
“deep structural similarities to the current problem in different ones. The outside view is deeply counterintuitive because it requires a decision maker to ignore unique surface features of the current project, on which they are the expert, and instead look outside for structurally similar analogies. It requires a mindset switch from narrow to broad” (p. 108).
This outside view is often immensely difficult because the more we know about unique details, the more confident we become and the more likely we are to stick with the options that are familiar.
For example, in a scientific study, researchers asked venture capitalists to rate their own current project and its success by comparing it with similar projects they were assessing at the time.
The venture capitalists could easily spot many faults with other projects, and were confident that these projects would not succeed; yet, when it came to their own projects that were similar but which they knew inside out, they ranked the probabilities of success very high.
This inside view often clouds our judgment and makes us to rely on surface pattern recognition and not take a broader view that looks for those deeper structural patterns.
Don’t fixate on one skill but instead broaden your mindset
What Epstein really emphasises throughout the book is that being a generalist (knowing a lot about many things and trying out many different kinds of hobbies) does not slow you down but actually supports superior performance.
Understanding and experiencing different types of practice and gaining a wider set of knowledge is more beneficial than strictly keeping your brain inside one domain.
The skills we learn this way are very useful in transferring ideas and experiences across domains, and even across different sports.
It is this diversity that sets us apart from those who only toil within strict boundaries of knowledge and experience.
The book is filled with countless examples where the great innovators don’t necessarily have years of experience in some area but who are generalists with a passion to understand the world.
They are simply curious creatures who wonder why things are as they are and are not afraid to try something new.
If anything else, this book is a call for us to remain curious, to learn as much as we can, and to develop those skills that allow us to excel in a range of areas.
Be, remain, become curious.