Sunday 25 September 2016

Psychological Bias In Decision Making

What is Psychological Bias?

Psychologists Daniel Kahneman, Paul Slovic, and Amos Tversky introduced the concept of psychological bias in the early 1970s. They published their findings in their 1982 book, "Judgment Under Uncertainty." They explained that psychological bias - also known as cognitive bias – is the tendency to make decisions or take action in an illogical way. For example, you might subconsciously make selective use of data, or you might feel pressured to make a decision by powerful colleagues.

Psychological bias is the opposite of common sense and clear, measured judgment. It can lead to missed opportunities and poor decision making. Dealing with cognitive errors is increasingly becoming a central concern for developing leaders and managers. Our friends at Mind Tools have kindly given us permission to reproduce an extract from an article on cognitive errors and ways to deal with them. For each of the errors, read the definition and the example and before you read the section on ‘how to avoid’ the error, ask yourself how you would avoid the error and compare your response with the advice given.

1. Confirmation bias

Confirmation bias happens when you look for information that supports your existing beliefs, and reject data that go against what you believe. This can lead you to make biased decisions, because you don’t factor in all of the relevant information.
A 2013 study found that confirmation bias can affect the way that people view statistics. Its authors report that people have a tendency to infer information from statistics that supports their existing beliefs, even when the data support an opposing view. That makes confirmation bias a potentially serious problem to overcome when you need to make a statistics-based decision.

How to avoid confirmation bias? Look for ways to challenge what you think you see. Seek out information from a range of sources, and use an approach such as theSix Thinking Hats technique to consider situations from multiple perspectives. Alternatively, discuss your thoughts with others. Surround yourself with a diverse group of people, and don’t be afraid to listen to dissenting views. You can also seek out people and information that challenge your opinions, or assign someone on your team to play ‘devil’s advocate’ for major decisions.

2. Anchoring

This bias is the tendency to jump to conclusions - that is, to base your final judgement on information gained early on in the decision-making process. Think of this as a ‘first impression’ bias. Once you form an initial picture of a situation, it’s hard to see other possibilities.

How to avoid anchoring? Anchoring may happen if you feel under pressure to make a quick decision, or if you have a general tendency to act hastily. So, to avoid it, reflect on your decision-making history, and think about whether you’ve rushed to judgement in the past. Then, take time to make decisions slowly, and be ready to ask for longer if you feel under pressure to make a quick decision. (If someone is pressing aggressively for a decision, this can be a sign that the thing they’re pushing for is against your best interests.)

3. Overconfidence bias

This happens when you place too much faith in your own knowledge and opinions. You may also believe that your contribution to a decision is more valuable than it actually is. You might combine this bias with anchoring, meaning that you act on hunches, because you have an unrealistic view of your own decision-making ability. Researchers found that entrepreneurs are more likely to display the overconfidence bias than the general population. They can fail to spot the limits to their knowledge, so they perceive less risk. Some succeed in their ventures, but many do not.

How to avoid overconfidence bias? Consider the following questions:

  • What sources of information do you tend to rely on when you make decisions? Are these fact-based, or do you rely on hunches?
  • Who else is involved in gathering information?
  • Has information been gathered systematically?

If you suspect that you might be depending on potentially unreliable information, think about what you can do to gather comprehensive, objective data.

4. Gambler’s fallacy

With the gambler’s fallacy, you expect past events to influence the future. A classic example is a coin toss. If you toss a coin and get heads seven times consecutively, you might assume that there’s a higher chance that you’ll toss tails the eighth time. Often, the longer the run, the stronger your belief can be that things will change the next time. However, in this example, the odds are always 50/50. The gambler’s fallacy can be dangerous in a business environment. For instance, imagine that you’re an investment analyst in a highly volatile market. Your four previous investments did well, and you plan to make a new, much larger one, because you see a pattern of success. In fact, outcomes are highly uncertain. The number of successes that you’ve had previously has only a small bearing on the future.

How to avoid gambler’s fallacy? A 2008 study reported that gambler’s fallacy was less likely to happen when decision makers avoided looking at information chronologically. So, to avoid gambler’s fallacy, make sure that you look at trends from a number of angles. Drill deep into data using tools such asSituational Appreciation. If you notice patterns in behaviour or product success – for example, if several projects fail unexpectedly – look for trends in your environment, such as changed customer preferences or wider economic circumstances. Tools such as PEST Analysis can help here.

5. Fundamental attribution error

This is the tendency to blame others when things go wrong, instead of looking objectively at the situation. In particular, you may blame or judge someone based on a stereotype or a perceived personality flaw. For example, if you’re in a car accident, and the other driver is at fault, you’re more likely to assume that he or she is a bad driver than you are to consider whether bad weather played a role. Fundamental attribution error is the opposite of actor-observed bias, in that you tend to place blame on external events. For example, if you have a car accident that’s your fault, you’re more likely to blame the brakes or the wet road than your reaction time.

How to avoid fundamental attribution error? It’s essential to look at situations, and the people involved in them, non-judgmentally. Use empathy and (if appropriate)cultural intelligence, to understand why people behave in the ways that they do. Also, build emotional intelligence, so that you can reflect accurately on your own behaviour.

Source: MindTools (www.mindtools.com)

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