Success is a product of the interplay between luck and skill. But we often confuse the two, or are uncertain about which one is which. For better results we need to be able to distinguish one from the other, ahead of time.
“There's a quick and easy way to test whether an activity involves skill,” says Michael Mauboussin, “ask whether you can lose on purpose.”
- Skill is the ability to fire knowledge readily in performance and execution. We know how to do something, and when the moment comes, we can do it.
- Luck has three specific features — it works for an individual and/or organization, it can be good or bad, and it's reasonable to expect something else could have happened.
In The Success Equation, Mauboussin says that when skill is predominant in a field, the best course of action is to engage in deliberate practice with feedback and coaching; while when luck is predominant, he advises not to worry over results, because we have little or no control over them. Instead we should just focus on getting our process right to succeed long term.
Even when we understand the definitions of luck and skill, we have a hard time attributing things that happen primarily because of luck to it. We're engineered to think it was us, that skill was responsible.
Our nature throws a wrench in our ability to distinguish luck from skill. The problem is that we naturally embrace stories and shy away from statistics. He says:
“While most of us are comfortable acknowledging that luck plays a role in what we do, we have difficulty assessing its role after the fact. Once something has occurred and we can put together a story to explain it, it starts to seem like the outcome was predestined.
Statistics don't appeal to our need to understand cause and effect, which is why they are so frequently ignored or misinterpreted.
Stories, on the other hand, are a rich means to communicate precisely because they emphasize cause and effect.”
This is partly due to our brain. In the left brain hemisphere we have an area called “interpreter” that constantly looks to make sense of what happened in the background. It assimilates everything we perceive and interprets that input to form a cause-and-effect narrative within our sphere of self-image and beliefs.
It doesn't know about luck, so it gravitates towards likely explanations and misleads our logical side. It doesn't help that we have a natural ability to act with confidence based on scant information.
Hindsight bias, which tells us that what happened is the only thing that could have happened keeps us locked into our story. So we lose track of other potential explanations or possibilities. Which is why we're not very good at sorting skill from luck.
Another reason makes the distinction hard.
Skill and luck are not fast categories, but are on a continuum, says Mauboussin.
For example, chess takes skill to play well and win, and gambling takes luck on the other end of the spectrum. For the rest of things that happen in life, we are caught between the two extremes. How we make decisions and predictions both depend on where we are on that continuum.
When we analyze sports, we find that some have a higher luck component, like hockey or the NFL due to shorter seasons, and others rely on higher skills, like basketball. Baseball is somewhere in the middle, with 162 games in a season.
Interestingly enough, investing is far on the luck side. It's counter intuitive because people are very skilled. But everyone else is also very skilled. So the variance or difference between results narrows considerably.
The idea Mauboussin introduces is that in a new market or sport, participants have big differences in ability. Which creates opportunity for the most skilled participants who sometimes have extraordinary success. For example, the .400 hitters in the earlier days of baseball.
However, in a mature market like investing, more skilled people have joined the ranks, and the existing participants have improved their abilities. Which elevates the overall skill but makes the difference in skill almost disappear. So the remaining variation is mostly due to luck.
We can have more success with less skill if we're an early entrant in a market. So our best chance of success is to do something few others are doing, changing the game, rather than trying to beat the established players at their own game. This is where we talk about unfair advantage.
Where we are on this continuum of skill-luck has enormous implications for decision making and predictions.
A few concepts in The Success Equation are worth highlighting for a greater understanding of how difficult it can be to tell luck from skill:
The paradox of skill — In fields where skill is more important to the outcome, luck's role in determining the ultimate outcome increases. While in fields where luck plays a larger role in the outcome, skill is also very important but difficult to ascertain without a large enough sample set.
IQ vs. RQ — Intelligence Quotient (IQ) is an overused talent measure for success because we associate the Rationality Quotient (RQ) more closely with decision making. Many people hide behind “good work product,” an IQ outcome, rather than evaluating “good decision making,” which is more about RQ. RQ involves adaptive behavioral acts, judicious decision making, efficient behavioral regulation, goal prioritization, the ability to be reflective, and proper calibration of evidence.
The Matthew Effect — is the idea that the most successful individuals tend to grow more successful while the poor grow poorer due to the endowment effect of early success, which may be due to good luck and not just skill.
Favorites should simplify the game — if we have superior resources, we should try to concentrate our battles in fewer fields than if we are the underdog. Various studies show that increasing complexity increases the role of luck and gives the underdog an advantage in competition while diluting the advantage of the stronger player.
Fluid vs. crystallized mind — research shows that our fluid mind, the part of our brain useful for creative decisions when facing problem sets we have not seen, decreases with age at an accelerating rate. The crystallized mind, our ability to develop mental models for “problems we have seen before,” tends to increase well into old age. This is also true of organizations. Statistical analysis offers clear evidence that corporate performance follows a predictable life cycle, falling prey to organizational rigidity with age.
Clutch performance — streaks have some empirical support but this topic hasn't been as well studied from a behavioral perspective as it has been from an observational standpoint.
We can outperform based on skill, it's statistically supported by data. But we still need luck to turn high skill into success. In fields where luck still plays a dominant role, we must understand what it means to be the best:
- high IQ
- elevated RQ with a strong system 1 for pattern recognition and a non-lazy system 2 for logical processing (based on Daniel Kahneman and Amos Tversky's research; see Thinking Fast and Slow)
- fluid mind that allows us to think creatively about opportunities using unique, differentiated framing
- well-tuned crystallized mind that correctly identify patterns and uses well-developed mental models to make decisions with the information
- clutch instincts to make difficult decisions even under pressure when presented with new, adverse, or fortuitous information
Recognizing where an activity lies on the luck-skill continuum can shape strategy, help us hone skills and deal with uncertainty, and improve performance in numerous ways that are relevant to business. We should:
- consider the sample size — if an activity is falls mainly under the control of luck, a small sample will not do
- understand history — helps more in skill-based activities than in luck-based activities
- categorize events — if they have simple/complex payoff and narrow/extreme outcome
It's also important to recognize whether the process is dynamic or not and to understand how reversion to the mean works.
When an activity is a mix of luck and skill, less extreme performances tend to follow extreme ones, good or bad. They tend to revert to the mean. If we praise someone for good performance, which then declines or if we tell someone about bad performance, which then improves, we might conclude it was because our intervention was counterproductive in one instance and beneficial in the other. But that would be wrong.
Mauboussin also points out how incentives reward factors that are generally luck-based and have little to do with an organization's real success. For example, stock options can reward poor performers when overall market prices rise and punish good performers when overall market prices drop.
Checklists are a simple way to prevent errors we can avoid. “Checklist routines avoid a lot of errors,” says Charlie Munger in his famous Commencement Speech at USC Law in May 2007. “You should have all this elementary wisdom and then you should go through a mental checklist in order to use it.”
Feedback is an essential part of improving performance. In a dynamic system, feedback helps us continue to adjust our aim to keep getting things less wrong. In dealing with our automatic system 1 in decision making we can work on:
- analyzing how to do things properly
- appreciating the psychology of the effort
- understanding the influence of the social system where we work
If we want to improve performance we must be aware of our automatic pilot and create habits that help us get out of our own way in decision making. Discipline is our ally.
The idea is not to have equal parts luck and skill, but to balance luck with skill and vice versa based on the situation and what it warrants.