Decision-making consumes a tremendous amount of cognitive energy. Over the course of a day, hundreds of minor decisions can lead to mental fatigue. Most workers use a number of decision-making short-cuts to minimize the amount of cognitive energy they expand throughout the day.

These shortcuts (or heuristics, as my capstone instructor in business school referred to them) are a double-edged sword for workers. They may leave employees with more mental energy to make important decisions, but they can also lead to poor decisions if used improperly.

As a manager, you are accountable for the quality of the decisions of everyone on your team. It is important to educate them about the benefits and fallacies of the most common decision-making heuristics.

Problems with the Most Common Decision-Making Heuristic

All employees have different decision-making styles, which can lead to different challenges. Before managers can educate their subordinates about these issues, they must be aware of them themselves. Here is an overview of some of the most common decision-making pitfalls.

Paralysis by Analysis

Many managers encourage their subordinates to perform an extensive due diligence before making decisions. While a highly analytical approach may seem beneficial, it can lead to a symptom known as paralysis by analysis.

My capstone program’s curriculum focused on this topic, which was covered in Henry Mintzberg and Frances Westley’s 2001 article: Decision Making: It's Not What You Think in Sloan Management Review.

The authors point out that this struggle is most common with complex problems where obvious solutions are not evident. In these cases, the best approach is to improvise and find a solution with trial and error.

“What happens when you don’t see it and can’t think it up? Just do it. That is how pragmatic people function when stymied: They get on with it, believing that if they do “something,” the necessary thinking could follow. It’s experimentation — trying something so that you can learn. That means doing various things, finding out which among them works, making sense of that and repeating the successful behaviors while discarding the rest. Successful people know that when they are stuck, they must experiment. Thinking may drive doing, but doing just as surely drives thinking. We don’t just think in order to act, we act in order to think.”

Managers must identify this challenge with employees that have a tendency to overcomplicate problems. This is most common with highly analytical workers with little tolerance for uncertainty.

Managers are unlikely to convince these employees that knowledge is unnecessary for decision-making. Rather than reconditioning them to disregard the importance of data, they should be encouraged to view taking action as a fact-finding exercise to make more informed decisions down the road.

Affect Heuristics

Affect heuristics are applied when workers make decisions based on emotion. They come into play most often when they want to make decisions quickly and efficiently.

This is one of the most common heuristics and offers the fewest upsides, because they rarely have a rational basis. The only way to overcome it is to point out the costs of decisions made with a primarily emotional basis and encourage workers to avoid those problems by seeking more data whenever possible.

Another solution is to develop a standardized approach to problem solving. According to Workfront’s How Email, Meetings & Automation Are Shaping The Future Of Work: 2017-2018 State Of Enterprise Work Report, 30% of workers state that lack of a standard workflow process is one of their biggest challenges. This leads to situations where they are more likely to make decisions based on emotional criteria rather than hard data.

Recognition Heuristics

People have a tendency to find patterns in data. Sometimes those patterns are subconsciously detected based on previous experience, which can simplify the decision-making process. In other instances, they may lead to poorly drawn conclusions.

Recognition heuristics are most problematic when the worker is encountering problems they have little prior experience with. The patterns they “observe” may be formed from experiences with unrelated problem-solving challenges, which may have little correlation with the problem at hand.

Dan Goldstein and Gerd Gigerenzer were the first researchers to tackle the problems caused by recognition heuristics in their 2012 white paper: Models of Ecological Rationality: The Recognition Heuristic. The authors emphasized the need to dig deeper to find more meaningful insights, rather than relying on poorly researched assumptions.

“Whereas these models are precisely formulated but nontransparent, there also exist imprecisely formulated and nontransparent models of heuristics, such as “representativeness,” “availability,” and other one-word explanations. Transparent fast and frugal heuristics use no (or only a few) free parameters, allow one to make quantifiable and testable predictions, and avoid possible misunderstanding (or mystification) of the processes involved, even if they do sacrifice some of the allure of the unknown.”

This heuristic may have merit with some applications, but should be discouraged in others. Managers must encourage workers to understand the nuances with different problems and consider their own level of experience, so they can see when the representation heuristic should be applied.