{"id":548,"date":"2021-04-13T20:37:34","date_gmt":"2021-04-14T00:37:34","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-peopleanalytics\/submission\/how-much-do-leaders-matter\/"},"modified":"2021-04-13T20:37:34","modified_gmt":"2021-04-14T00:37:34","slug":"how-much-do-leaders-matter","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-peopleanalytics\/submission\/how-much-do-leaders-matter\/","title":{"rendered":"How much do leaders matter?"},"content":{"rendered":"

How much do CEOs matter? According to a paper co-authored by HBS\u2019 former dean Nithin Nohria[1]<\/a> in 2010 estimates that CEOs explain 14% of a company\u2019s profitability. According to another study of Stanford\u2019s Rock Center for Corporate Governance[2]<\/a>, CEOs attribute 30% of a firm\u2019s performance to themselves, while directors are even more generous, and attribute them 40% of the results. These results certainly explain why CEOs are paid generously but are they that relevant?<\/p>\n

In a paper released in 2019 by Christopher Berry and Anthony Fowler[3]<\/a>, they explore the answer to how much do coaches matter. <\/em>They use a novel technique called RIFLE –randomization inference for leader effects\u2014to calculate the effectiveness of leaders in general. In simple terms, RIFLE is a regression with a dummy for each leader \u2013coaches in their paper. To control for serial correlation and real coach effects, they randomly permuted each coach\u2019s tenure as a block. Then they artificially created a dataset where the data has the same features as the real one, except that the coaches do not align with the outcomes that they actually got. Then if the real dataset consistently shows a larger coach effect than the artificial one, they can conclude that there is a positive or negative coach effect.<\/p>\n

Berry and Fowler found that coaches explain 20-30% of the team\u2019s performance \u201314 wins per season in the NBA if you go from a coach that is two standard deviations below the mean to one that is two standard deviations above the mean.<\/p>\n

When using the same approach to understand the impact that CEOs have, the answer that they found is\u2026 almost no effect. The same applies to political leaders in democracies, whereas not so much in autocracies. What does this mean? probably that the more complex the environment and the larger and more diverse the stakeholder base is, the less power the leader has. The \u201cgame\u201d for these leaders is certainly more complex as well, making it a balancing act.<\/p>\n

We are left with a wide range of potential leader impact on their organization\u2019s performance: from 0% to 40%. What are the lessons that we can derive from this?<\/p>\n

First, that it is still important to have well-prepared business and political leaders, but it is humbling \u2013and common-sense– to acknowledge that one leader cannot radically change the direction and performance of a complex organization or territory. And second, to bring it back home with people analytics, it is critical to understand that people are much more powerful than what a model can predict. We, humans, are capable to achieve the most impressive feats, ones that have never done or even imagined before. Algorithms might underestimate individuals, but we need to remain human-centric rather than machine-centric and use data and analytics to complement our skills and ability to create and make things happen.<\/p>\n

 <\/p>\n

[1]<\/a> Wasserman, Anand, Nohria (2010)<\/p>\n

[2]<\/a> CEOs and Directors on Pay, 2016 Survey on CEO Compensation<\/p>\n

[3]<\/a> Berry, C.R., & Fowler, A. (2019). How Much Do Coaches Matter?<\/p>\n","protected":false},"excerpt":{"rendered":"

How much do leaders matter? 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