Neglect of Probability

When we've made a decision that has led to serious trouble, it's possible that a cognitive bias known as neglect of probability might have played a role. This cognitive bias can affect decision making by causing us to choose among options based solely on the values of the respective "best outcomes," respectively, of those options. Using this criterion leads to trouble when the outcomes of the options are uncertain, because it ignores the probabilities of actually achieving those outcomes.

Stated a Neglect of Probability causes us
to choose among options based
solely on the values of their
respective "best outcomes,"
ignoring the likelihood of those
outcomes actually coming aboutbit more precisely, a rational decision would be based on considering both the value of an option's potential outcome and the probability of actually generating that outcome. Instead, when we're under the spell of Neglect of Probability, we tend to assess the goodness of an option by focusing solely (or excessively) on the value of its best outcome, while ignoring the probability of achieving that outcome.

An illustration might clarify this effect further.

The IT department at Dewey, Cheatham and Howe, LLP, (a fictitious global law firm), is upgrading the operating systems of DCH's fleet of personal computers from PC-OS 11 to PC-OS 12 (a fictitious operating system). The task would be relatively straightforward were it not for the enormous number of commercial and custom applications running on those computers. DCH's experts expect that the change from PC-OS 11 to PC-OS 12 will render many of those applications unusable. Among the 18,000 total applications, most are expected to operate correctly, but many will not. The full list of questionable applications is unknown.

Testing all 18,000 applications is an impractically large effort. But by working with the vendors of the commercial applications, and by collaborating with IT departments in other law firms, DCH has reduced the number of applications whose status is unknown to a mere 1,500. That number is less daunting, but it's still impossibly large.

IT has therefore decided to let users of each of the questionable applications perform the testing and certification, in three stages. In Phase I an application expert checks that the app operates in PC-OS 12. If it does, then in Phase II for that app, 10% of the app's users are authorized to use the app for up to 30 days. If they report no problems, then the app is cleared for Phase III, general use. If the Phase II users do report problems, usage of that app is suspended and IT works with the vendor or internal author to resolve the issue. When the issue is resolved, the app is returned to Phase II for another 30 days and the procedure repeats until the app is cleared.

In this way, IT can reduce the number of apps that need more thorough testing. And when an app functions properly, the cost of determining that it does so is very low. These cost-control features are very attractive to IT decision makers.

But there's a problem with this approach. In the 30 days during which Phase II users operate untested apps, those untested apps might corrupt existing data or documents, without the knowledge of the users of the apps. Based on prior experience with PC-OS 10, this corruption is almost certain to occur in many apps. Therefore, the probability of a successful outcome for IT's intended three-phase approach is very low. But the decision makers in IT who conceived of this plan are neglecting the probability of that good outcome. They're attracted by the low cost of the best outcome, and that has caused them to ignore the fact that some applications — IT knows not which ones — will almost certainly cause data corruption. In this example, IT's approach might have a very good outcome, but the probability of that outcome is small.

Neglect of Probability is most likely to play a role in decision making when the decision-making scenario involves choosing among a set of options, some of which have outcomes very much more attractive than others. In these decision-making scenarios, Neglect of Probability tends to cause the decision makers to choose options with too little regard for — or without regard for — the probabilities of success of the various options.

And even when decision makers do consider probabilities, the risk of a poor decision remains unacceptably high for some kinds of mission-critical decisions. Decision makers might in some cases estimate probabilities in a biased way that tends to favor the options with the outcomes they find most appealing. There are indeed many ways to mess things up.  Top    Next Issue

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More articles on Cognitive Biases at Work:

Effects of Shared Information Bias: I

Shared information bias is the tendency for group discussions to emphasize what everyone already knows. It's widely believed to lead to bad decisions. But it can do much more damage than that.

Seven Planning Pitfalls: III

We usually attribute departures from plan to poor execution, or to "poor planning." But one cause of plan ineffectiveness is the way we think when we set about devising plans. Three cognitive biases that can play roles are the so-called Magical Number 7, the Ambiguity Effect, and the Planning Fallacy.

The Risk of Astonishing Success

When we experience success, we're more likely to develop overconfidence. And when the success is so extreme as to induce astonishment, we become even more vulnerable to overconfidence. It's a real risk of success that must be managed.

Lessons Not Learned: II

The planning fallacy is a cognitive bias that causes us to underestimate the cost and effort involved in projects large and small. Efforts to limit its effects are more effective when they're guided by interactions with other cognitive biases.

The Risk Planning Fallacy

The planning fallacy is a cognitive bias that causes underestimates of cost, time required, and risks for projects. Analogously, I propose a risk planning fallacy that causes underestimates of probabilities and impacts of risk events.

See also Cognitive Biases at Work for more related articles.

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