Reward the second best, ignore the best

Archived Article • 18 June 2012 • Press release

New research published in PNAS, a leading interdisciplinary journal, suggests reasons why the richest should pay more tax; why rewarding the top performers leads to recurrent crises and scandals; and why we should resist the temptation to learn from and imitate the most successful.

Successful people don't like to have their success explained by luck, while audiences, too, seem unwilling to acknowledge the role of luck in determining success. As a result, the stories of the most successful attract the most media attention - described as 'extreme success' in this research report. These outliers are perceived to be the most skilful and so receive the highest rewards and get imitated.

However, new research by Dr Chengwei Liu, Assistant Professor of Strategy & Behavioural Science at Warwick Business School and Professor Jerker Denrell at Oxford Saïd Business School shows that the idea that the exceptional performers are the most skilled is flawed. The reason is that exceptional performance often occurs in exceptional circumstances. Top performers are often the luckiest people, who have benefitted from rich-get-richer dynamics that boost their initial fortune.

Consider a college drop-out who turns out to be the wealthiest person in the world. Yes, Bill Gates may be very talented, but his extreme success perhaps tells us more about how circumstances beyond his control created such an outlier. Stated differently, what is more exceptional in this case may not be Gates's talent, but the circumstances he happens to be in.

For example, Gates's upper class background enabled him to gain extra programming experience when less than 0.01% of his generation then had access to computers; his mother's social connection with IBM's chairman enabled him to gain a contract from the then leading PC company, generating a lock-in effect that was crucial for establishing the software empire. Of course, Gates's talent and effort play important roles in the extreme success of Microsoft. But that's not enough for creating such an outlier. Talent and effort are likely less important than the circumstances (e.g., network externalities generated by customers' demand for software compatibility boosted Gates's initial fortune enabled by his social background) in the sense that he could not have been so successful without the latter.

A rational learner should realise that it is more useful to draw lessons from the less exceptional performers, the second best, because their circumstances are likely to be less extreme, implying their performances are more informative and offer more evidence for skill.

Dr Chengwei Liu commented, "Humans, however, often rely on the heuristic of learning from the most successful. Our research found that even though observers were given clear feedback and incentives to be accurate in their judgement of performers, 58% of them still assumed the most successful were the most skilled when they are clearly not, mistaking luck for skill. This assumption is likely lead to disappointment - even if you can imitate everything Bill Gates did, you will not be able to replicate his initial fortune. This also implies that rewarding the highest performers can be detrimental or even dangerous because imitators are unlikely to achieve exceptional performance without luck unless they take excessive risk or cheat, which may partly explain the recurrent financial crises and scandals."

Implications of this research

The lucky few should understand and appreciate the role that luck played in their extreme success, and with that understanding comes an obligation to those that have not. The lucky few may be more skilful than others eventually, but the way they gain their superior skill can be due to strong rich-get-richer dynamics combined with the good fortune of being successful initially. This can justify a higher tax rate for the richest when their extreme fortune is accumulated in the fortunate fashion defined in this research.

This research also has important implications for learning and goal setting for individuals, organisations and society. Media and popular business books often advise on how to learn from the most successful with a goal of moving from 'good to great'. This research suggests that following such advice is likely to lead to frustrations and wasted resource, as it requires luck rather than talent to be exceptional. Instead, learning from the second best and setting the goal of moving from 'poor to good' may be more constructive not only for individual learners but also for business and society collectively.

Last but not least, rewarding the second best when it's clear that extreme performance cannot be achieved without luck, excessive risk-taking or cheating, may be a solution to avoid recurrent crises and scandals. But since a non-linear relationship between performance and reward is counterintuitive and may be perceived as unfair, policy-makers need to design 'nudges' to help people resist the temptation to reward or imitate the top performers.

This research is published in PNAS, one of the top three interdisciplinary journals along with Science and Nature. Proceedings of the National Academy of Sciences of the United States of America covers biological, physical, and social sciences. Its online publication, PNAS Online, receives around 21million hits per month.

The full research report on PNAS Online, titled 'Top performers are not the most impressive when extreme performance indicates unreliability' can be accessed here http://www.pnas.org/content/109/24/9331.abstract.

Further information

Publication details: 'Top performers are not the most impressive when extreme performance indicates unreliability', by Jerker Denrell and Chengwei Liu, edited by James G March, Stanford University, Stanford, CA, USA, and published in PNAS Online on June 12, 2012.

Extra
This research was reported on the BBC's World Service programme World Briefing on 20 June. It can be heard on the BBC's iPlayer until 24 June, thereafter on this Audioboo link.

See also: http://www.pnas.org/content/109/24/9331.abstract

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