Samuel Goldwyn recast Thomas Jefferson’s earlier observation: “I am a great believer in luck, and I find the harder I work, the more I have of it.”
Michael Mauboussin, of Columbia University, and previously Chief Investment Strategist at Legg Mason Capital Management Inc. investigated this relationship between effort and luck in his book, The Success Equation.
Mauboussin, an innovator in behavioral finance, adopted Harvard biologist Stephen Jay Gould’s “paradox of skill” to analyze the interaction of effort, skills, and luck, and best strategies to optimize outcomes in investing, sports, and career performance.
He posits that as skill improves in activities where outcomes are affected by skill and luck, the standard deviation of skills narrows.
In this case, luck becomes more important in determining outcomes:
“Whenever you see an outlier in sports, it is always a combination of really good skill and really good luck… (Often) they are about one and a half or two standard deviations away from the average…not all skilled players have (winning) streaks, but all (winning) streaks are held by skillful players.”
For example, as investors become more sophisticated and have access to advanced computational tools, as athletes benefit from targeted training and development regimens, and as students are groomed for admission to top universities, differences among these skilled performers decreases.
Chance influences can determine outcomes.
Mauboussin says that luck has several elements:
- Affects an individual or organization,
- May be evaluated as “good” or “bad”
- Another outcome could have occurred
- The outcome is uncontrollable, but is comprised of several elements
To increase luck, he advises assessing each contender’s strength in the situation and finding “…something completely different to get you on the right side of the tail of the skill distribution,” such as employing an unusual or unexpected tactic.
The stronger player has positive asymmetric resources, so the effective strategy is to simplify the game.
In contrast the underdog should seek to complicate the game, such as through disruptive innovation, a flank strategy or a guerilla tactic.
Because most people have a bias toward optimism and overestimate personal capabilities, it may be difficult to assess oneself as an “underdog” in a performance situation.
Nobel Prize winner Daniel Kahneman and Amos Tversky explained that individuals who adopt an inside view gather substantial information, combine it with their own inputs, then project into the future without considering “distributional information” about a wide variety of previous instances.
This approach risks developing an idiosyncratic, overconfident perspective by underestimating costs, completion times, and risks of planned actions, while overestimating benefits.
In contrast, people who adopt the outside view consider the problem as an instance of a larger reference class and consider the entire distribution of outcomes when this type of situation occurred previously.
This approach can reduce overconfidence.
However, this approach could discourage entrepreneurs, who will realize that a small percentage actually succeeds.
In addition, besides the bias toward overconfidence, people tend to “under-sample” instances of failure when a previously successful approach is applied in a new situation and doesn’t succeed.
Sabermetricians like Nate Silver, posit that worthwhile statistics provide:
- Persistence or correlation from one period to the next, a strong indicator of high skill
- Predictive value or high correlation with the target objective
The Oakland As baseball team uncovered these principles in determining that a superior measure of athletic performance in this sport is on-base percentage rather than the traditional measure, batting average.
In this case, on-base percentage has a higher correlation from one season to the next and a higher correlation with run production than batting average, fulfilling both criteria.
Daniel Kahneman also suggested that skill, expertise, and intuition render more uniform results in a predictable environment.
However, many organizational environments are unstable and non-linear, rendering experts less accurate because they cannot employ an effective predictive model.
Collective judgments through “the wisdom of crowds” may mitigate the challenges of unstable contexts because they provide more data points.
Mauboussin advocated considering the continuum of stability vs instability in which the issue is situated to determine strategy and to beware of applying simple heuristics that are vulnerable to bias, and social or situational influences.
He suggested the guideline “think twice” to prepare, detect and correct for common mental traps, including:
- The Inside-only View
- Tunnel Vision
- Situational Power
- Overvaluing Expert Knowledge
-*How do you optimize your performance when chance elements can affect your outcomes?
- It’s Mostly Random, So Just Do Something
- Biases in Unconscious Automatic Mental Processing, and “Work-Arounds”
- Reduce Evaluator Bias: Showcase Best Features in Any Offer
- Useful Fiction: Optimism Bias of Positive Illusions
- Consider All Your Options at Once, Be Happier with Choices: Minimize “Quest for the Best” Bias
- Hypothetical Questions May Lead to Bias
- Detect and Mitigate Decision Biases
- Human Decision Biases Modeled with Automatons
- Overcoming Decision Bias: Allure of “Availability Heuristic”, “Primacy Effect”
- Creating Productive Thought Patterns through “Thought Self-Leadership”
Blog: – Kathryn Welds | Curated Research and Commentary
LinkedIn Open Group Psychology in Human Resources (Organisational Psychology)
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