The behavioral economists are making the case for standardized checklists, algorithms and simple rules to reduce complexity. Many studies (including those offered by Goldberg) have shown that judgements made by human decision-makers are inferior when compared to judgements based on relatively simple formulae, statistics and checklists. Simplicity beats complexity when assessing and making decisions about the success of complex scenarios such as mergers and acquisitions. Even when smart people are given the result provided by formulae, they tend to overrule this analysis. These smart people (and experts) ignore it because they feel that they have more knowledge and information than that which is produced by the formulae. Kahneman notes that “they are most often wrong”.
Standardized approaches, simple algorithms and checklists can be very powerful tools. Atul Gawande, (2013), a general surgeon in Boston and assistant professor at Harvard Medical School, defines the power of checklists in this way:
We (humans) have accumulated stupendous know-how. We have put it in the hands of some of the most highly skilled and hardworking people in our society. And with it they have accomplished extraordinary things. Nonetheless, that know-how is often unmanageable. Avoidable failures are common and persistent, not to mention demoralizing and frustrating across many fields – from finance, business to government.
He goes not suggest why the checklists work:
. . . the reason is increasingly evident: the volume and complexity of what we know has exceeded our individual ability to deliver its benefits correctly, safely and reliably. Knowledge has both saved us and burdened us” … but there is such a strategy (to solve this problem) – though it is almost ridiculous in its simplicity, maybe even crazy to those who have spent years carefully developing ever more advanced skills and technologies (and indeed is resisted in many companies for this reason). It is a checklist!
Kahneman puts forward his own personal story regarding the quality of his judgment and predictive capabilities (or lack of) when serving as a young military psychologist in Israel. He was charged with assessing the leadership capabilities of aspiring officers. Kahneman admits that he was initially dismal at this task. He also highlights examples of poor capabilities of highly trained counselors predicting the success levels of college freshmen based on several aptitude tests and other extensive data. Kahneman compares these results with the predictive accuracy to be found in the use of a simple statistical algorithm that makes us of a fraction of the information available. The algorithm was a far more successful predictor than were the trained counselors.
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