1. A bat and a ball cost $1.10 in total. The bat cost a dollar more than the ball. How much did the ball cost?

2. What We Attend to Influences Our Assessment of Probability

3. A Good Man Gone Bad? Page 3

4. The Ford Pinto: 1971-1980 Lee Iacocca: build me a car “under 2000 pounds and under $2000.” Real cost? 53 deaths, many injuries, $6 million lawsuit, and costly hit to reputation, 1.5 million pintos recalled in 1978. Page 4

5. The Fixed-Action Response in Ethology

6. Fixed Action Patterns

7. Herbert Simon’s Model Decision making is not perfectly rational; it is boundedly rational: –Limited information processing (cannot evaluate all potential alternatives in limited time) –Satisficing (stop when the solution is “good enough”– pick radio station) –Judgemental heuristics

8. Assumptions of the Rational Model

9. Factors Influencing Decision Making Time Pressure Incomplete information Limited resources Cannot know or investigate all possible alternatives Conflicting goals; difficult to find optima Bounded Rationality

10. Kahneman and Tversky: Maps of Bounded Rationality Intuition (system 1): Fast, parallel, automatic, effortless Reasoning (system 2): Slow, serial, controlled, effortful

11. Economist.com subscription-- $59.00 One year subscription to Economist.com. Includes online access to all articles Print subscription-- $125.00 One year subscription to the print edition Print and Web subscription-- $125.00 One year subscription to the print edition plus online access to all articles

12. Cognitive Biases in Decision Making Human cognition relies on schemas and scripts which help us deal with what would otherwise be informational overload Schemas structure knowledge in memory. They provide a basis for making predictions and they offer theories behind action that enable sensemaking.

13. Blowing Up

14. Types of Heuristics Representativeness error: thinking overly influenced by what is typically true (e.g., doctors fail to consider possibilities that contradict their mental templates of a disease.) Availability bias: Tendency to judge likelihood of an event by the ease with which relevant examples come to mind (e.g., this venture will fail because it failed for my friends who tried it) Confirmation bias: Confirming what one expects by selectively accepting (or ignoring) supporting (disconfirming) information (e.g., the problem is the staff) Affective error: Tendency to make decisions based on what we wish were true (to accept otherwise would be psychologically hurtful).

15. Shoreham Nuclear Power Plant GE plant in NY, 60 miles from Manhattan Designed to produce 540-820 megawatts Initial estimated cost: $65 million Final cost: $6billion After 11 years (’73- ’84), never opened! Construction flaws Labor unions Public concerns over safety Escalation of commitment, or failed persistence?

16. Escalation of Commitment: The Flip Side of Persistence

17. Reducing Escalation of Commitment Set minimum targets for performance, and force decision makers to compare against these targets Stimulate opposition using “devil’s advocacy” Rotate managers through roles Reduce ego-involvement Provide and study more frequent feedback about project completion and costs Reduce risk and penalties for “failure” Make explicit the costs of persistence

18. Delusional Optimism Due to both cognitive biases and organizational pressures: - exaggerate own talents; downplay luck - self-serving attributions: in annual reports - scenario planning tends to reward most optimistic appraisals. - anchoring - competitor neglect. - pessimism often interpreted as disloyalty

19. How to Take The Outside View Select a reference class: –choose a class that is broad enough to be statistically meaningful but narrow enough to be truly comparable to project at hand-- movies in same genres, similar actors Assess the distribution of outcomes: –Identify the average and extremes in the refer- ence-class projects’ outcomes--the studio executive’s reference-class movies sold $40 million in tickets on average. But 10% sold less than $2 mil- lion and 5% sold more than $120 million. Predict, intuitively: –where you fall in the distribution– executive predicted $95 million Estimate reliability of your prediction –correlation between forecast and actual outcome expressed as a coefficient ranging from 0 to 1. Correct the intuitive estimate for unreliability –less reliable the prediction, more needs to be adjusted towards the mean.