For almost two centuries, Spain has hosted an enormously popular Christmas lottery. Based on the payout, it is the biggest lottery in the world and nearly all Spaniards play. In the mid-1970s, a man sought a ticket that ended in 48. He found a ticket, bought it, and won the lottery. When asked why he was so intent on finding that number, he replied, “I dreamed of the number seven for seven nights. And seven times seven is 48.”

The outcomes for many activities in life — including sports, business, and investing — combine skill and luck. Most of us understand and accept this statement, but there are two good reasons why few of us understand the relative contributions of each. The first reason is psychological. When we enjoy a good outcome due to luck, we are naturally inclined to chalk up our success to skill. Similarly, if we suffer an adverse outcome because of poor skill, we blame our bad luck. I recall an acquaintance who won big one Saturday night playing slot machines. The next week he solicited friends to build his bankroll, convinced he had devised a winning formula. Needless to say, Lady Fortuna stopped smiling and he returned his gains, along with the money of his credulous sponsors, to the house. We have psychological defense mechanisms that blur our view of the relative role of skill and luck.

The second reason has to do with how we measure performance. We have a strong tendency to dwell on outcomes without considering the role of process. Take baseball hitting statistics as an example. Some measures, including strikeout ratio, reveal a great deal about the hitter’s skill, while batting average, a more popular measure, includes a great deal of randomness. We need to find performance measures that reflect skill, or elements of the outcome that we can control.

Businesspeople who want to incorporate the roles of skill and luck into their decision making must take some concrete steps. The first is to define the terms. We will define skill as “the ability to use one’s knowledge effectively and readily in execution or performance” and luck as “events or circumstances that operate for or against an individual.” Think of skill as a process.

Next, we need to understand where an activity falls on a continuum from pure skill/no luck on one extreme to no skill/pure luck on the other. For instance, running races are nearly all skill — the fastest runner wins — and roulette wheels are all luck. Everything else is somewhere between the extremities. Quantifying where your activity sits is enormously useful in assessing past outcomes and for making decisions about the future.

Here are some specific ways that understanding the role of skill and luck can be useful for business leaders:

Always compare results with a null model that reflects luck. Whether outcomes are good or bad, the question is always: What should we have expected from chance alone? This idea is central to assessing the validity of the hot-hand in sports. For example, believers assert that a streak of successful shots in basketball occurs because a player who has made her most recent shot is more likely to make her next shot (she has a hot hand). Yet, streaks are not uncommon and are completely consistent with chance. So the issue is not how many shots our player made in a row, it is how many she made compared to what we should expect due to chance alone. When that standard is applied to the empirical data, the hot hand melts away. The same principle applies in business. Always ask what you would expect by chance.

Whether outcomes are good or bad, the question is always: What should we have expected from chance alone? This idea is central to assessing the validity of the hot-hand in sports. For example, believers assert that a streak of successful shots in basketball occurs because a player who has made her most recent shot is more likely to make her next shot (she has a hot hand). Yet, streaks are not uncommon and are completely consistent with chance. So the issue is not how many shots our player made in a row, it is how many she made compared to what we should expect due to chance alone. When that standard is applied to the empirical data, the hot hand melts away. The same principle applies in business. Always ask what you would expect by chance. Reversion to the mean. Any system that combines skill and luck will revert to the mean over time. This means that an extreme outcome, good or bad, will be followed by an outcome that has an expected value closer to the mean. Take, for instance, a group of companies that currently have high returns on invested capital (ROIC). If you follow that group over time, you would see their ROICs revert back toward the cost of capital. As important, the rate of reversion to the mean is a function of the relative contribution of luck. Business people are ensnared by reversion to the mean because they don’t acknowledge it, fail to understand what it means, or don’t act on it.

Any system that combines skill and luck will revert to the mean over time. This means that an extreme outcome, good or bad, will be followed by an outcome that has an expected value closer to the mean. Take, for instance, a group of companies that currently have high returns on invested capital (ROIC). If you follow that group over time, you would see their ROICs revert back toward the cost of capital. As important, the rate of reversion to the mean is a function of the relative contribution of luck. Business people are ensnared by reversion to the mean because they don’t acknowledge it, fail to understand what it means, or don’t act on it. Paying for randomness. Ideally, a compensation program pays an individual for his or her skillful contribution toward achieving a desirable objective. In reality, many compensation programs pay for randomness. One prominent example is the use of employee stock options (ESOs). While ESOs seek to align the interests of managers and shareholders, a worthy goal, in reality they largely end up remunerating for randomness. Consider the 1990s, when stock prices soared to lofty levels. Executives with ESOs made substantial sums, even if their relative performance was poor. Likewise, executives who led their companies in the 2000s did poorly with their ESOs. In determining the ultimate amount of pay, the vagaries of the market overwhelmed the performance of the executives. Compensation programs need to be modified so as to strip out as much randomness as possible.

Ideally, a compensation program pays an individual for his or her skillful contribution toward achieving a desirable objective. In reality, many compensation programs pay for randomness. One prominent example is the use of employee stock options (ESOs). While ESOs seek to align the interests of managers and shareholders, a worthy goal, in reality they largely end up remunerating for randomness. Consider the 1990s, when stock prices soared to lofty levels. Executives with ESOs made substantial sums, even if their relative performance was poor. Likewise, executives who led their companies in the 2000s did poorly with their ESOs. In determining the ultimate amount of pay, the vagaries of the market overwhelmed the performance of the executives. Compensation programs need to be modified so as to strip out as much randomness as possible. Hiring stars. Some companies seek to enhance their performance by hiring stars from other organizations. This practice has a number of challenges. First, a good deal of performance is context dependent; an individual can thrive in one setting but struggle in another. Second, stars tend to be, in part, beneficiaries of luck. A .300 hitter in baseball, for example, will go through periods of hitting .400-plus or sub-.200. Players who go on the market after a period of above-average results will be evaluated, and paid, based in part on luck. Research shows that stars rarely deliver good value for their new organizations.

A decade ago, Nassim Taleb raised awareness about the role of luck through his best-selling book, Fooled by Randomness. It is now time to take the next step by quantifying the relative contributions of skill and luck and tailoring business practices to focus on the contribution of skill.

Michael J. Mauboussin is chief investment strategist at Legg Mason Capital Management and an adjunct professor at Columbia Business School. You can read more about his thoughts on skill and luck here.