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Heuristics and Biases in Decision Making Owen Darbishire 10 th July 2008

Heuristics and Biases in Decision Making Owen Darbishire 10 th July 2008. Objectives. To understand how people make decisions To recognise common heuristics and biases in decision making To reflect upon the consequences of those for organisations

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Heuristics and Biases in Decision Making Owen Darbishire 10 th July 2008

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  1. Heuristics and Biases in Decision MakingOwen Darbishire10th July 2008

  2. Objectives • To understand how people make decisions • To recognise common heuristics and biases in decision making • To reflect upon the consequences of those for organisations • To recognise the limitations of considering individuals devoid of social context

  3. Table Sizes and Shapes

  4. Action and Belief in Decision Analysis Rational Models • logical analysis of decision task and use of deductive methods to derive behaviour or rational actors e.g. expected utility theory Descriptive • empirical, often psychological, seeking general principles to explain observed preferences e.g. identification of heuristics and biases

  5. Concept devised to address growing evidence of non-rationality in decision making; used in two rather different senses: 1. Rationality limited by processing and informational requirements - sets of decisions involve such complexity that rationality affected 2. Rationality systematically impaired by cognitive factors which cause patterned deviations from optimum Bounded Rationality [Simon 1957]

  6. Auction Rules • Only bid if you want to, it’s real money • Bids start at £1 and rise by 20p each bid • The highest bidder pays the amount they bid, and they win the £10 • The second highest bidder also pays the amount they bid, but they don’t win the £10 Small Print: If anyone breaks Rule 2, they will be fined £10.

  7. Commitment “If at first you don’t succeed, try, try again. Then quit. No use being a damn fool about it.” W.C. Fields • As resources (time, money etc.) are invested, the tendency to become committed grows. • Resources are then allocated to justify previous commitments, especially if a justification can be found for initial failure (e.g. economic downturn). • The danger is non-rational escalation

  8. Escalation of Commitment • Examples: • Investments for ‘winner take all’ markets • Pharmaceutical industries, software etc.. • Marketing races, such as airmiles • Arms races and wars • Strikes • Employee Performance Evaluation • Subjective performance appraisal ratings • Promotion decisions • NBA - draft choice and playing time • Loans for commercial investments

  9. Escalation of Commitment Errors in gathering &processing informationImpression management Competitive irrationality Commitment to initial decision Escalation ofcommitment

  10. Penny Auction • The container has a large number of 1p pieces within it. • There will be one round of simultaneous bids only • The winner will be given larger denominations notes and coins to avoid you having to have all those 1p pieces.

  11. Over-Bid Frequency Quantity Bid Estimate = Actual Value

  12. Winning Auction • Rational Bidding Distinguishes (a) expected value of object for sale on prior information available (b) the expected value conditioned on winning the auction • Errors (i) overconfidence in own estimate (ii) ignoring cognition of others (iii) irrational escalation to win auction

  13. Winner’s Curse • The more uncertain the value, the more likely it is overpaid for • Learning is difficult: • outcomes delayed • variability in environment degrades reliability of feedback • the most important decisions are unique • Mergers • Bidding for competitive contracts • 3G Mobile Licence Auctions

  14. 3G Mobile Licence Auctions Estimated Price - £1.5-£2.0 billion Actual Price – £22.47 billion (Cost of licence excludes cost of roll out) “Winners” – TIW, Vodafone, One2One, Orange, BT Cellnet “Losers” – WorldCom, Telefonica, NTL (backed by France Telecom) “If properly designed - and my team deserves credit for not screwing up the design - auctions are simply a way of finding the market price… . If chairmen paid too much for their licences, they have nobody to blame but themselves ” – Ken Binmore “A ruthless, poker-playing economist” – Newsweek

  15. Anchoring • People adjust rather than create when making decisions • Adjustment requires an anchor • Example: estimate the value of the following numbers • 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 = 512 • 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 = 2250 • Sources of anchor include: • first source of information; stereotype; advertised price; behavioural signals; initial position in negotiation

  16. Number Selection • Three numbers you will be given conform to a simple rule. This rule is concerned with the relation between any three numbers and not with their absolute magnitude (i.e. it is not a rule like all numbers above 50). • Your aim is to discover the rule by thinking of sets of three numbers. On doing this you will be told whether the numbers conform to the rule or not. • Try to discover the rule by citing the minimum sets of numbers. • When you are highly confident of the rule, write it down.

  17. Confirmation Bias & Perception • Selectively perceive what they expect / hope to see • Heuristic of positive test strategy • Mynatt, Doherty & Tweney (1977) found 70% of subjects used confirmation strategy even when instructed to disconfirm • Cognitive Dissonance • people reduce or avoid psychological inconsistencies • self perception theory indicates that people discover their own attitudes & emotions by watching themselves behave in various situation.

  18. NASA engineers asked to examine whether problems with o-rings on space shuttle were related to take-off temperature Challenger Space Shuttle NASA engineers asked to examine whether problems with o-rings on space shuttle were related to take-off temperature STS 51-C Graph of temperature and o-ring performance for flights where problems occurred (drawn before Challenger) 3 61A 2 # Incidents 41D 41B 41C 1 61C STS-2 0 50 55 60 65 70 75 Temp oF

  19. Confidence Confidence Estimation Exercise - 90% accuracy

  20. Question 1 How long, in days, is the gestation (pregnancy) period of an Asian elephant Question 2 How deep, in either feet or meters, is the deepest known point in the ocean ?

  21. Question 3 The figure below provides the dollar share price chart for a particular security over a forty-eight month period. What is your prediction for the dollar share price six months beyond this forty-eight month period?

  22. Question 4The figure below provides the dollar share price chart for a particular security over a forty-eight month period. What is your prediction for the dollar share price six months beyond this forty-eight month period?

  23. Question 5The figure below describes the dollar change in share price for a particular security over a forty-eight month period. What is your prediction for the average change in the share price, per month, for the six months beyond this forty-eight month period?

  24. Confidence • There is only weak relationship between confidence and accuracy: • Fischoff, Slovis & Lichtenstein (1977) found where people put odds of being correct at 100:1 they were accurate 73% of the time • Average confidence levels don’t appear to exceed accuracy by more than 10-20 percent, so usually not catastrophic results • Strategies for overconfidence • consider why you might be wrong • list alternatives • generate opposing reasons (not just reasons)

  25. Overconfidence Source: Plous 1993

  26. Retrievability & Availability Bias Decision makers 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 • Availability of information • Imagination of event • Vivid information given (versus pallid or statistical data)

  27. Our firm is in trouble – we are cutting jobs. HR director presents 2 plans: Program A Save 1 in 3 plants and 2000 jobs Program B 1/3 probability of saving 3 plants & 6000 jobs 2/3 probability of saving nothing

  28. Our firm is in trouble – we are cutting jobs. Operations director presents 2 plans: Program C Will lead to the loss of 2 of the 3 plants and 4000 jobs Program D 2/3 probability of losing all plants and 6000 jobs 1/3 probability of losing nothing

  29. Framing The manner in which issues or questions are phrased has a significant impact on answers and preferences. Gains versus Losses • risks about gains and losses are perceived differently • people are risk averse when gains are at stake • people are risk seeking in face of losses • If people do not adjust their reference point as they lose, they may take risks that they would ordinarily find unacceptable.

  30. Representativeness • Refers to judgements based on stereotypes • “Law of Small Numbers” (Kahneman & Tversky 1971) • e.g “bad” or “good” stocks (Shefrin 2000) • Causes individuals to fail to appreciate the role of sample size in assessing reliability of information, and an ignoring of regression to the mean • Gambler’s Fallacy: reversal of chance is due • e.g. 5 heads in toss of a coin. What next?

  31. Does Leadership Matter? The Attribution of Success Grint 2000

  32. Fundamental Attribution Error The tendency to over-emphasis dispositional or personality explanations, and to place too little emphasis on the situation, environment or chance • Longing for saviour, search for scapegoat • Observers & leaders suffer this heuristic • Power and prestige exacerbates the effect • Good leaders in bad units beware!! • Cultural differences in attribution

  33. How Much Does Leadership Matter? • Direct Leadership • Effect of immediate supervisor on organisational climate (Hogan et al 1994) • Small groups such as NBA (Smith et al 1984); Baseball (Kahn 1993) • Indirect leadership • Autos (Lieberman et al 1990) • CEO hubris and price paid for acquisition (Hayward and Hambrick 1997) • Reality of organisational power and environmental constraints • Overall – effect in larger organisations greatly overstated • Problem exacerbated by search for charismatic CEO (Khurana 2002; Collins 2001, 2005; Maccoby 2002)

  34. Distribution of Gifts • £100 is to be split between two strangers: • X gets to decide the division • Y gets to accept or reject that division • No negotiations occur – the money is divided as X determined or rejected completely

  35. Equity and Fairness • People continually make comparisons with others and this has a significant effect on such issues as pay systems • Fairness is a fundamental principle of societies, even if the precise ‘divisions’ show variation. Two forms of fairness matter: • Distributive Justice • Are rewards distributed ‘fairly’ given differences in skills, experience, effort and performance? • Procedural Justice • Is the method of determining the distribution of rewards ‘fair’ and ‘equitable’?

  36. Categories of Cognitive Bias • Influences on information gathering • Retrievability & availability, confirmation bias • Influences on information processing • Loss aversion, over confidence, framing, anchoring, representativeness • Influences on decision making • Groupthink, herding, social norms, impression management, competitive pressures, endowment effects • Influences on reactions to decision making • illusions of control, escalating commitment, hindsight bias, fundamental attribution error

  37. Examples of how to deal with biases • Reframe questions/issues in neutral terms • Initially form a view independently to avoid anchoring • View problems from different perspectives to uncover your implicit assumptions • Seek information/opinions from various sources to widen frame of reference • Seek out people most likely to challenge your assumptions • Avoid using leading questions when asking for opinions • Apply equal rigour to analysing all sources of evidence Always be alert to possibility of others peoples’ biases and try to identify their implicit assumptions

  38. What is missing? • Focus has been on heuristics and biases • We are missing context: • Personality • Social Interaction • Groups • Culture • Power & Politics • Organisational Structure

  39. Risks with Group Cultures • Group Think …the deterioration of mental efficiency, reality testing, and moral judgement that results from in-group processes (Janis 1982) • Group Polarisation • Abilene Paradox

  40. Pick a Number Choose a number between 1 and 100 The winner is the guess closest to two-thirds of the average entry.

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