Understand overconfidence bias and how to avoid it.
Understand hindsight bias and how to avoid it.
Understand anchoring and how to avoid it.
Understand framing bias and how to avoid it.
Understand escalation of commitment and how to avoid it.
Avoiding Decision-Making Traps
No matter which model you use, it is important to know and avoid
the decision-making traps that exist. Daniel Kahnemann (another
Nobel Prize winner) and Amos Tversky spent decades studying how
people make decisions. They found that individuals are influenced
by overconfidence bias, hindsight bias, anchoring bias, framing
bias, and escalation of commitment.
Overconfidence
bias occurs when individuals overestimate their ability
to predict future events. Many people exhibit signs of
overconfidence. For example, 82% of the drivers surveyed feel they
are in the top 30% of safe drivers, 86% of students at the Harvard
Business School say they are better looking than their peers, and
doctors consistently overestimate their ability to detect problems
(Tilson, 1999). Much like friends that are 100% sure they can pick
the winners of this week’s football games despite evidence to the
contrary, these individuals are suffering from overconfidence bias.
Similarly, in 2008, the French bank Société Générale lost over $7
billion as a result of the rogue actions of a single trader. Jérôme
Kerviel, a junior trader in the bank, had extensive knowledge of
the bank’s control mechanisms and used this knowledge to beat the
system. Interestingly, he did not make any money from these
transactions himself, and his sole motive was to be successful. He
secretly started making risky moves while hiding the evidence. He
made a lot of profit for the company early on and became overly
confident in his abilities to make even more. In his defense, he
was merely able to say that he got “carried away” (The rogue
rebuttal, 2008). People who purchase lottery tickets as a way to
make money are probably suffering from overconfidence bias. It is
three times more likely for a person driving 10 miles to buy a
lottery ticket to be killed in a car accident than to win the
jackpot (Orkin, 1991). Further, research shows that overconfidence
leads to less successful negotiations (Neale & Bazerman, 1985).
To avoid this bias, take the time to stop and ask yourself if you
are being realistic in your judgments.
Hindsight
bias is the opposite of overconfidence bias, as it
occurs when looking backward in time and mistakes seem obvious
after they have already occurred. In other words, after a
surprising event occurred, many individuals are likely to think
that they already knew the event was going to happen. This bias may
occur because they are selectively reconstructing the events.
Hindsight bias tends to become a problem when judging someone
else’s decisions. For example, let’s say a company driver hears the
engine making unusual sounds before starting the morning routine.
Being familiar with this car in particular, the driver may conclude
that the probability of a serious problem is small and continues to
drive the car. During the day, the car malfunctions and stops miles
away from the office. It would be easy to criticize the decision to
continue to drive the car because in hindsight, the noises heard in
the morning would make us believe that the driver should have known
something was wrong and taken the car in for service. However, the
driver in question may have heard similar sounds before with no
consequences, so based on the information available at the time,
continuing with the regular routine may have been a reasonable
choice. Therefore, it is important for decision makers to remember
this bias before passing judgments on other people’s actions.
Anchoring refers to the tendency for
individuals to rely too heavily on a single piece of information.
Job seekers often fall into this trap by focusing on a desired
salary while ignoring other aspects of the job offer such as
additional benefits, fit with the job, and working environment.
Similarly, but more dramatically, lives were lost in the Great Bear
Wilderness Disaster when the coroner, within 5 minutes of arriving
at the accident scene, declared all five passengers of a small
plane dead, which halted the search effort for potential survivors.
The next day two survivors who had been declared dead walked out of
the forest. How could a mistake like this have been made? One
theory is that decision biases played a large role in this serious
error, and anchoring on the fact that the plane had been consumed
by flames led the coroner to call off the search for any possible
survivors (Becker, 2007).
Framing
bias is another concern for decision makers. Framing
bias refers to the tendency of decision makers to be influenced by
the way that a situation or problem is presented. For example, when
making a purchase, customers find it easier to let go of a discount
as opposed to accepting a surcharge, even though they both might
cost the person the same amount of money. Similarly, customers tend
to prefer a statement such as “85% lean beef” as opposed to “15%
fat” (Li, Sun & Wang, 2007). It is important to be aware of
this tendency, because depending on how a problem is presented to
us, we might choose an alternative that is disadvantageous simply
because of the way it is framed.
Escalation of
commitment occurs when individuals continue on a failing
course of action after information reveals it may be a poor path to
follow. It is sometimes called the “sunken costs fallacy,” because
continuation is often based on the idea that one has already
invested in the course of action. For example, imagine a person who
purchases a used car, which turns out to need something repaired
every few weeks. An effective way of dealing with this situation
might be to sell the car without incurring further losses, donate
the car, or use it until it falls apart. However, many people would
spend hours of their time and hundreds, even thousands of dollars
repairing the car in the hopes that they might recover their
initial investment. Thus, rather than cutting their losses, they
waste time and energy while trying to justify their purchase of the
car.
A classic example of escalation of commitment from the corporate
world is Motorola Inc.’s Iridium project. In the 1980s, phone
coverage around the world was weak. For example, it could take
hours of dealing with a chain of telephone operators in several
different countries to get a call through from Cleveland to
Calcutta. There was a real need within the business community to
improve phone access around the world. Motorola envisioned solving
this problem using 66 low-orbiting satellites, enabling users to
place a direct call to any location around the world. At the time
of idea development, the project was technologically advanced,
sophisticated, and made financial sense. Motorola spun off Iridium
as a separate company in 1991. It took researchers a total of 15
years to develop the product from idea to market release. However,
in the 1990s, the landscape for cell phone technology was
dramatically different from that in the 1980s, and the widespread
cell phone coverage around the world eliminated most of the
projected customer base for Iridium. Had they been paying attention
to these developments, the decision makers could have abandoned the
project at some point in the early 1990s. Instead, they released
the Iridium phone to the market in 1998. The phone cost $3,000, and
it was literally the size of a brick. Moreover, it was not possible
to use the phone in moving cars or inside buildings. Not
surprisingly, the launch was a failure, and Iridium filed for
bankruptcy in 1999 (Finkelstein & Sanford, 2000). In the end,
the company was purchased for $25 million by a group of investors
(whereas it cost the company $5 billion to develop its product),
scaled down its operations, and modified it for use by the
Department of Defense to connect soldiers in remote areas not
served by land lines or cell phones.
Why does escalation of commitment occur? There may be many
reasons, but two are particularly important. First, decision makers
may not want to admit that they were wrong. This may be because of
personal pride or being afraid of the consequences of such an
admission. Second, decision makers may incorrectly believe that
spending more time and energy might somehow help them recover their
losses. Effective decision makers avoid escalation of commitment by
distinguishing between when persistence may actually pay off versus
when it might mean escalation of commitment. To avoid escalation of
commitment, you might consider having strict turning back points.
For example, you might determine up front that you will not spend
more than $500 trying to repair the car and will sell it when you
reach that point. You might also consider assigning separate
decision makers for the initial buying and subsequent selling
decisions. Periodic evaluations of an initially sound decision to
see whether the decision still makes sense is also another way of
preventing escalation of commitment. This type of review becomes
particularly important in projects such as the Iridium phone, in
which the initial decision is not immediately implemented but
instead needs to go through a lengthy development process. In such
cases, it becomes important to periodically assess the soundness of
the initial decision in the face of changing market conditions.
Finally, creating an organizational climate in which individuals do
not fear admitting that their initial decision no longer makes
economic sense would go a long way in preventing escalation of
commitment, as it could lower the regret the decision maker may
experience (Wong & Kwong, 2007).
Figure \(\PageIndex{10}\): Motorola released the
Iridium phone to the market in 1998. The phone cost $3,000 and it
was literally the size of a brick.
Wikimedia Commons – public domain.
So far we have focused on how individuals make decisions and how
to avoid decision traps. Next we shift our focus to the group
level. There are many similarities as well as many differences
between individual and group decision making. There are many
factors that influence group dynamics and also affect the group
decision-making process. We will discuss some of them in the
following section.
Key Takeaways
Understanding decision-making traps can help you avoid and
manage them. Overconfidence bias can cause you to ignore obvious
information. Hindsight bias can similarly cause a person to
incorrectly believe in their ability to predict events. Anchoring
and framing biases show the importance of the way problems or
alternatives are presented in influencing one’s decision.
Escalation of commitment demonstrates how individuals’ desire to be
consistent or avoid admitting a mistake can cause them to continue
to invest in a decision that is no longer prudent.
Exercises
Describe a time when you fell into one of the decision-making
traps. How did you come to realize that you had made a poor
decision?
How can you avoid escalation of commitment?
Share an example of anchoring.
Which of the traps seems the most dangerous for decision makers
and why?
References
Becker, W. S. (2007). Missed opportunities: The Great Bear
Wilderness Disaster. Organizational
Dynamics, 36, 363–376.
Finkelstein, S., & Sanford, S. H. (2000, November). Learning
from corporate mistakes: The rise and fall of Iridium. Organizational Dynamics, 29(2), 138–148.
Li, S., Sun, Y., & Wang, Y. (2007). 50% off or buy one get
one free? Frame preference as a function of consumable nature in
dairy products. Journal of Social
Psychology, 147, 413–421.
Neale, M. A., & Bazerman, M. H. (1985). The effects of
framing and negotiator overconfidence on bargaining behaviors and
outcomes. Academy of Management Journal,
28, 34–49.
Orkin, M. (1991). Can you win? The real
odds for casino gambling, sports betting
and lotteries. New York: W. H. Freeman.
The rogue rebuttal. (2008, February 9). Economist, 386, 82.
Tilson, W. (1999, September 20). The perils of investor
overconfidence. Retrieved March 1, 2008, from
www.fool.com/BoringPort/1999/...Port990920.htm.
Wong, K. F. E., & Kwong, J. Y. Y. (2007). The role of
anticipated regret in escalation of commitment. Journal of Applied Psychology, 92, 545–554.