The Art and Science of Decision-Making May 12, 2014 Robert S. Duboff

2 Themes All decisions have an emotional component; most have a rational component as well o The process can be structured, scientific o Making the actual decision is always art – science can be used, but you can’t turn off type 1 thinking All decisions (big and small) are influenced by biases, prior events, priming and the like Some decisions are about puzzles; some are about mysteries o Recognizing which is which is critical Decision-making will and should vary depending on context (and whether it is a group decision or not) o Risk o Consequences o Etc.

3 A Good Decision Meets objective(s) Has no interaction effect (i.e., “scientist is not part of the experiment”) Considered everything Would be reaffirmed if did it over Felt right Worked out well?

4 A Rational Decision-Making Process Define the problem Identify the criteria Weight the criteria Generate alternatives (can use decision tree/Bayes) Conduct research/information gathering where relevant and influential Rate each alternative on each criterion Compute the optimal decision Source: Judgment in Managerial Decision-Making, Max Bazerman.

5 Process Ideas – Week 1 Distinguish “yes/no” from rheostat Prioritize Develop a scale and weights Use a spreadsheet Talk it out/get advice Imagine yourself in the future

6 “How to Take the Outside View” – Lovallo and Kahneman To protect against “Delusions of Success” in forecasting: 1.Select a reference class (an “art and science”) 2.Assess the distribution of outcomes 3.Make an intuitive prediction 4.Assess the reliability of your estimate 5.Correct the estimate (i.e., multiply 3x4)

7 To Have an Adequate Picture of What Could Change – Sydney Finkelstein Five questions: 1.Perfect Storm (more than one event) 2.Star Wars Error (are new discoveries needed) 3.Big Picture Illusion 4.Wrong Competitors (“Usual Suspect Syndrome”) 5.Static Business Model (Possible transformation)

8 Ways to Improve Decisions At the Onset “Hope for the best but plan for the worst” o Build in guard rails Delineate the decision as: o Value-based o Fact-based Specify the desired outcome(s) and criteria Identify type of intelligence that will be useful: o IQ and/or EQ o Fluid intelligence and/or “crystalized intelligence”

9 Ways to Improve Decisions (continued) Characterize the future situation o Knowable or unknowable o Puzzle or mystery Do a pre-mortem Enumerate all the possible outcomes o How would you explain each one? o Who will/might be affected? Discuss biases/preconceptions o What would the blink decision be? Consider timing o When must decision be made Pros/cons of quicker decision List all possible decisions (e.g., alternatives, yes/no, etc.) o What is BATNA?

10 Ways to Improve Decisions (continued) During the Process Form teams to advocate o Weigh toward less favored alternative(s) o Assign a critic Gather information organized by hypotheses and extent to which it might impact on decision Use decision tree/Bayesian analysis Develop check lists Consult with (influential/credible) experts Use an arbiter and/or fresh perspective Develop scenarios and rate likelihood Quantify, if possible, the economics (and/or important) of the decision and budget time and research accordingly

11 Ways to Improve Decisions (continued) During the Process Post-audit prior relevant decisions Clarify roles of people involved in the decision Identify sunk costs (and worry re loss aversion) Identify linkage/ripple effects List key questions Assess if there can be a pilot test Determine if there are relevant analogies/beacons Consider breaking habits and “usual suspects” Should decision be delegated/assigned to others? o Would wisdom of crowds or Delphi be useful?

12 Ways to Improve Decisions (continued) Making the Decision Work to align your gut with your head Utilize science when making the decision o Energy o Lack of accidental priming

13 Ways to Improve Decisions (continued) Kahneman’s (with Lovallo and Sirony) check list Check for self-interested biases Check for affect heuristic Check for group think Check for saliency bias Check for confirmation bias Check for availability bias Check for anchoring bias Check for halo effect Check for sunk-cost fallacy, endowment effort Check for overconfidence, especially in base case Check for disaster neglect Check for loss aversion Source: HBS, June 2011.

14 Final Thoughts “ ‘Facts’ may not always be facts, but feelings will always be feelings.” “If, for an important decision, you can get your head aligned with your heart you will have conquered the art and science of decision-making.”