‘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
‘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 made now and in the future. ‘Future decisions are made after the consequences of a basic decision become known. They are linked because the alternatives that will be available in the future depend on the choice made now. The essence of making smart linked decisions is planning ahead.’ (Hammond et. al, 2002) According to (Hammond et. al, 2002) there are six steps you must follow to analyze linked decisions; 1) Understand the basic decision problem
Here the elements of the ‘Eight keys to effective decision making’ must be address to give a greater perspective of the decision. Objectives should be decided upon, consequences must be understood and uncertainties should be clarified with the main ones highlighted. 2) Identify ways to reduce critical uncertainties
For each of the main uncertainties, there should be research around each respective area until relevant information is discovered which will reduce or resolve uncertainties and therefore improve your decision. 3) Identify future decisions linked to the basic decision Here future decisions must be recognised. The question needs to be asked, what decisions would naturally follow from each decision in the basic decision. E.g. if option A fails, then will I abandon the project or will I continue with option B?
4) Understand relationships in Linked Decisions
Perhaps the most effective way to do this is to construct a decision tree is to represent the links between choices and learned information in the sequence. The tree should the basic information surrounding the tree, any important information regarding the decision and future decisions that may affect the current decision. 5) Decide what to do in the basic decision
‘Roll back’ your decision tree whilst making decisions on what choices you make at certain points on the tree. Correspondingly, cancel out the alternative branches which you decide not to use. Then a decision must be made on which the best alternative or route to choose is based on your diagram and calculations. 6) Treat later decisions as new decision problems
Take advantage of new knowledge, a change in circumstances or the passage of time in order to enhance your understanding of a new decision problem or to improve your current situation. Psychological Traps
According to (Hammond et. al, 2002) the eight most common and serious errors which occur in decision making are as follows: 1. Working on the wrong problem
2. Failing to identify
3. Failing to develop a range of good, creative alternatives 4. Overlooking crucial consequences of your alternatives
5. Giving inadequate thought to tradeoffs
6. Disregarding uncertainty
7. Failing to account for your risk tolerance
8. Failing to plan ahead when decisions are linked over time
By familiarising yourself with the common psychological traps involved in decision making and the diverse form they take, people are in a better position to ensure decisions are dependable and consistent. The following are 3 examples of different types of traps: Psychological traps:| How?| How to reduce/avoid these traps?| The Anchoring Trap| The mind gives disproportionate weight to the first information it receives i.e. ‘anchors’ subsequent thoughts which influences future decisions in some way. E.G is the population of Ireland 5 million? What’s your best estimate of Ireland’s population? (Second question influenced by first)| 1) Be open- minded 2) View problem from different perspectives 3) Analyze the problem on your 4) Research around the area in relation to the decision.| The Status Quo Trap| When decision making is influenced towards the current situation (status quo), usually in a subconscious effort to defend our ego from failure. The status quo is the “safe and sound” alternative.| 1) Remember the objectives and examine how they would be served by the status quo 2) Identify other options and compare with status quo 3) Avoid exaggeration in the effort or cost involved in switching from status quo.| The Sunk Cost Trap| Based on past experience. Opinions foremost in our minds when making decisions and often lead us to make inappropriate decisions.| 1) Seek views of people who weren’t involved in earlier decisions 2) Acknowledge mistakes made in the past 3) Choose previously involved individuals to make new decisions.|
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.