Pitfalls of Decision Making

Topics: Decision making, Decision theory, Risk Pages: 5 (1590 words) Published: February 23, 2013
Pitfalls and Limitations of Decision Making
Heuristics and Biases:
‘People rely on a limited number of heuristic principles which reduce the complex tasks of assessing probabilities and predicting values to simpler judgmental operations.’ (Kahneman et. al, 1974) Heuristics are cognitive shortcuts or ‘rules of thumb’ used to simplify the decision making process. Heuristics result in good decisions and their main asset is that they save time. Most of the heuristics are used by people with specific cognitive styles of problem solving. However, heuristics can cause biases and systematic errors when they fail. Whilst making decisions, people are typically unaware of the heuristics and biases and when or in what instances they should be used. There are many biases in the use of heuristics but some of the most common include; 1) Availability

2) Adjustment and Anchoring
3) Representativeness
4) Motivational

1) Availability
‘There are situations in which people assess the frequency of a class or the probability of an event by the ease with which instances or occurrences can be brought to mind’ (Kahneman et. al, 1974) Availability can be described as the inability to accurately assess the probability of a particular event happening. The most common factor here is experience. Assessments based on past experience may not be representative e.g. one may evaluate the probability of a new local fish shop in the Letterkenny area, failing, by imagining the various problems in may encounter. The structured review and analysis of objective data can reduce availability bias. 2) Adjustment and Anchoring

‘In many situations, people make estimates by starting from an initial value that is adjusted to yield the final answer’ (Kahneman et. al, 1974) The majority of subjectively derived probability distributions are too narrow and fail to estimate the true variance of the event and perhaps the best way to overcome this is to assess a set of values, rather than just the mean. (I.e. anchoring) 3) Representativeness

This is the process by which an attempt to establish the probability that a person or object belongs to a particular group or class, based on the degree to which the characteristics of that person/object fits into the stereotypical perception of members of that group or class. In the answering of these questions, people generally focus on the similarities with the respective person/object versus the stereotypical perception. The closer the similarity between the two, then there is a high probability that the respective person/object belongs to a particular class. An example from (Kahneman, 1974) shows how representativeness may take place; Q: How do people assess the probability that Steve is engaged in a particular occupation from a list of possibilities (e.g. farmer, salesman, airline pilot, librarian or physician)? ‘Steve is a very shy and withdrawn, invariably helpful, but with little interest in people, or in the world of reality. A meek and tidy soul, he has a need for order and structure, and a passion for detail’. A: In the representativeness heuristic, the probability that Steve is a Librarian, for example, is assessed by the degree to which he is representative of, or similar to, the stereotype of a librarian. Motivational

This is the case when probability estimates are often influenced by incentives and therefore, the estimates do not accurately reflect people’s true beliefs. These incentives can be real or perceived.

Linked Decisions and there complexity
Linked decisions are decisions made today which creates new decisions to be made in the future. There are no time limits on linked decisions and they can be minutes, months, years even decades ahead. In terms of making linked decisions, to choose the correct choice now, you must think and analyze about decisions in the future. Therefore future planning is a massive element, as well as understanding the relationship between the decisions...

Bibliography: Kahneman, D. And Tversky, A. (1974) Judgement under Uncertainty: Heuristics and Biases. Science, Vol.185, No. 4157, p1124-1131.
Hammond, J., Keeney, R., & Raiffa, H. (2002). Smart Choices – Chapter 9.
Hammond, J., Keeney, R., & Raiffa, H. (2002). Smart Choices – Chapter 10
Originally after meeting with the group, I was assigned the part of completing the ‘group decision making’ area of the project in correlation with Shane. But, after researching and investigating that area we found that perhaps that part was more suited to one individual and so when the group met again, it was decided that I would look at the ‘pitfalls of decision making’. After some research, I discovered it was an area with a lot of information and decided I would try an incorporate what I felt was the most important pitfalls, rather than focusing on only one area. Firstly, I looked at the area of heuristics and biases. Using the class notes I touched on the various main types of biases involved in decision making. I tried to back up my points with quotes from the Kahneman’s and Tversky’s handout on ‘Judgement under Uncertainty, which was part of the compulsory reading surrounding topic 1. I then touched on Linked Decisions and tried to stress the complexity of them. I felt it was important to make note of the 6 steps in analyzing linked decisions; I got a lot of information to try back up my points again through the ‘Smart Choices’ Handout. Finally I talked about psychological traps, how they happen and what are the best ways in which to address them.
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