How often do we stress about the unfavorable outcomes of our decisions. It makes us feel we should have known better.
However, it turns out that we’re often wrong in judging our decisions after the fact. In their 1988 paper, Outcome bias in decision evaluation, Baron and Hershey refer to Ward Edwards:
“A good decision cannot guarantee a good outcome. All real decisions are made under uncertainty. A decision is therefore a bet, and evaluating it as good or not must depend on the stakes and the odds, not on the outcome.” – Ward Edwards
The authors emphasize that the distinction between a good decision and a good outcome is a basic one to all decision analysts, but is not very well understood outside the decision-analysis profession.
The Outcome Bias
In his comprehensive volume on human decision making, Thinking and Deciding, Jonathan Baron gives a more gentle introduction to the outcome bias:
A good decision is one that makes effective use of the information available to the decision maker at the time the decision is made. A good outcome is one that the decision maker likes. Such an outcome can result from a good decision, but it can also result from good fortune, following a bad decision. Of course, the whole point of good thinking is to increase the probability of good outcomes (and true conclusions), but many other factors affect outcomes aside from good thinking. Some of these have to do with good thinking on earlier occasions. Others have to do with luck — factors beyond the person’s control.
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If we want to promote good decision making, we should ensure that people do the best they can with what is knowable. We cannot insist on clairvoyance. Prudently made investment decisions can lead to surprising losses. A decision to perform surgery could have been a rational one, even if the patient is the one in a thousand who dies on the operating table from that operation.
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People do tend to judge decisions by their outcomes even when they know everything that the decision maker knew, as though decision makers were held responsible for their luck.
The real danger of falling for the outcome bias, as Baron notes, is that it can cause us to hold people responsible for events they could not control.
In her HBR article What We Miss When We Judge a Decision by the Outcome, Francesca Gino, a professor at Harvard Business School, outlines the effects of outcome bias in today’s business world:
When people are judging the quality of leaders’ decisions, they tend to focus much more on outcomes than intentions. For example, they judge hiring decisions not on the basis of whether the decision was made thoughtfully or fairly but on whether the new employee performs well. They judge the quality of a product decision on whether the product was well received in the market, rather than the quality of the process that led to the decision in the first place.
[…] The outcome bias is costly to organizations. It causes employees and leaders to be blamed for negative outcomes even when they had good intentions and used a thoughtful decision-making process, considering all the information that should be taken into account.
What to Do About It?
A solution – take into account the decision-making process and make an effort to eliminate knowledge of the outcome in decision-analysis process. As Gino concludes:
Requiring individuals to make judgments about people’s decision-making process before the outcomes have been achieved is an effective strategy to reduce the outcome bias in contexts in which scenarios or decisions are evaluated simultaneously rather than one after the other.
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It is easy to celebrate or lament a particular decision or action based on how it turns out. But it is important to remember that the process that led to the outcome, including the decision maker’s initial intentions, deserve to be taken into account in evaluating the results.