3 Mechanisms That Bias Our Decision-Making: Representativeness Bias

Every single person has a mental model.

When assessing the likelihood of an event, the individual bases the event’s probability upon its similarity to that model.

This is called representativeness bias.

Last week, we talked about availability bias, one of the three mechanisms that bias our decision-making.

Availability bias involves one’s perception of an event’s frequency based upon its vividness and frequency in the forefront of one’s mind.

Now, let’s take a look at how this second mechanism – representativeness bias – distorts judgment and decision-making.

Marriage & Divorce

One example of representativeness bias involves marriage.

Many people’s mental model of marriage is that of a lifelong partnership. Not often does a couple enter into a marriage with a view of divorce.

Due to their mental model of eternal love, only around 5 percent of couples in the U.S. sign a prenup, despite around 50 percent of marriages ending in divorce, according to research by Harvard Law.

Somehow, most don’t consider they’ll be part of the statistic and, so, don’t plan for it.

In this way, the power of representativeness bias is stronger than the logic of probability.

Representativeness Bias in Business Decisions

Culture, of course, influences our mental models, and so representativeness biases are grounded in culture.

Let’s look at another example of how a business decision revealed representativeness bias, likely to the detriment of the business.

The global insurance company, Allianz, had built business in eleven African countries. Although profitable, the business was small and, in March 2014, Allianz reviewed their strategy on the continent.

They narrowed their way forward down to two roads: 1) apply aggressive growth through acquisition, or 2) wholly sell off the business.

The board of Allianz was presented with a growth strategy. They rejected it.

Their view was that Africa’s corruption was too extensive and might put the insurance company at reputational risk.

However, Allianz continued to do business throughout Eastern Europe.

According to the Transparency International list – an index of worldwide national corruption – several countries in Eastern Europe, in which the insurance group remained, rated equally corrupt as their African counterparts.

The West’s mental model of Africa considers the entire continent as one monolith of extreme corruption, thereby biasing judgment in lieu of logical probability.

In dismissing growth based on representativeness bias, the company may have lost out on a successful business venture and the profitability that accompanied it.

Tune in next week for anchoring bias.

3 Mechanisms That Bias Our Decision-Making: Availability Bias

Managers apply simple models to help make decisions. Personal experience and culture help form these models.

Our cultural environment largely influences the rationale of our decision-making processes.

Daily decisions don’t require extensive analysis; rather, progress is made more efficient using prior experience and rule of thumb.

But it’s important to note that when we lean heavily into “rule of thumb” and prior experience, we unconsciously rely on bias.

As identified by research, three mechanisms affect this decision-making bias:

  • Availability
  • Representativeness
  • Anchoring

We’ll outline each across the next few blog posts, starting today with availability.

First, a question…

Which of the following do you think kills more people worldwide each year?

  1. Vehicular accidents
  2. Lung cancer
  3. Cape buffalo

If you answered “a) Vehicular accidents,” you’re a product of availability bias.

Availability bias involves making a judgment based upon the frequency of an event in the forefront of one’s mind rather than the event’s real-life probability.

Emotional or easily imaginable events – like vehicular accidents – are recalled more readily than a vague, obscure, or uninteresting incident.

This makes such events seem more prevalent and probable than they actually are.

And the answer…

An experiment was done in the U.S. with just such a question, where participants were asked whether more worldwide deaths were caused by lung cancer or car accidents annually.

Most answered that car accidents resulted in a higher fatality rate. The reality is that lung cancer kills nearly twice as many each year.

On average, over 2 million die each year from lung cancer, according to the World Health Organization, while the CDC states that around 1.35 million are killed on roadways across the globe annually.

The reason there is such a lopsided perception on each event’s probability is partially related to media culture, in which vehicular deaths are much more widely covered than those caused by lung cancer.

Humans really do have a selective memory: we remember more frequently and distinctly situations with a vivid narrative.

This skews the perception of each event’s frequency.

Other aspects that contribute to an individual’s availability bias include personal experience. If the individual knew of someone or multiple people, for instance, who had died from either lung cancer or a vehicular accident, this information might also bias their judgment.

Now, consider if you asked the same question of a Kenyan participant. In Africa, 200 people die each year from Cape buffalo, and such fatal incidents are likely heavily covered by the media.

Overall, a Kenyan participant might have a higher estimate than their U.S. counterpart regarding the global fatality rate caused by Cape buffalo.

In this way, cultural differences impact our availability bias and, in turn, our perception and judgment when it comes to decision-making.

On deck next week: representativeness.