Better Decisions Prelim 1 Review

Module 1: Professor Russo

Lecture 1 Key Concepts

Part 1: The Importance of a Decision Process

  • Decision Components: Implementation + Decision Process + Chance = Decision Outcome

  • 4 Phases of Decision Process:

    • They do not always occur in a complete cycle; some phases may happen without deliberate control.

  • Good Process:

    • Can be developed, largely self-taught, crucial for managerial decision-making.

    • Good results stem from good processes.

    • Quote: "The closest you can come to guaranteeing a good decision outcome is a good decision process."

Part 2: Overconfidence

  • Decision Making Components: Primary Knowledge + Metaknowledge = Decision Making

    • Primary Knowledge: What you know.

    • Metaknowledge: What you know about what you know.

  • Confidence: The belief in the certainty of another belief.

  • Overconfidence: Greater belief in a belief than justified.

  • The Confidence Game:

    • Overconfident individuals (incorrect experts) ultimately face losses.

  • Misprecision: The size of one's confidence interval range.

  • Misestimation: The accuracy of one’s predictions.

  • Misplacement: Accuracy in self-belief compared to others.

  • More information can lead to overconfidence.

  • Accurate, timely, repeated feedback enhances metaknowledge.

Lecture 2

Part 1: Thinking Frames

  • Frames: Borrowed, complete, coherent, with highlights and shadows that can be changed and compete.

  • Examples of Thinking Frames:

    • Crowdfunding appeals (independent want, dependent need).

    • Masculine vs. feminine management styles (e.g., Nikki Haley's warmth).

    • The matchmaker story (an invitation context).

    • Students framed as learners, customers, revenue sources, or alumni.

    • Politics and economics: Can use frames for manipulation.

Analyzing Frames

  • Frame Audit Analysis: Evaluate issues, boundaries, metrics, metaphors, and emphases.

  • Examples:

    • Evaluating shadows vs. highlights in a Cornell Major.

    • Distinction between suppliers vs. partners for Boeing.

    • Use of endorsements vs. honors for Duncan Hines.

Part 2: Decision Frames

  • Constructed Frame: Tailored to organize thinking, requires time and effort.

    • Example: Evaluating creditworthiness based on repayment history, income, occupation, etc.

  • Frames can overlook criteria and need updates.

  • Yardsticks/Metrics: Measure criteria (relative percentage vs. absolute).

  • Conflicting Frames: Offensive and defensive framing may lead to overconfidence.

Lecture 3 & 4 Key Concepts

Group Decision-Making

  • Common Pitfalls:

    • Striving for Influence: Some members dominate discussions, impairing fairness.

    • Striving for Harmony: Conflict avoidance can cause groupthink and poor decisions.

    • Striving for Efficiency: Rushing to decisions can hinder thorough option exploration.

Framing Problems in Groups

  • Frame Conflict: Different perspectives lead to misunderstandings.

  • Spending Too Little Time Framing: Rushing to decisions without comprehending the issue.

  • Single Shared Frame: Premature convergence may miss better alternatives.

Psychological Biases in Groups

  • Groupthink: Pressure to conform stifles critical thinking.

  • Egocentrism Bias: Team members exaggerate their contributions.

  • Overconfidence Bias: Groups may reinforce overconfidence instead of minimizing it.

Managing Conflict for Better Decisions

  • Task Conflict: Focusing on ideas rather than individuals improves decision-making.

  • Psychological Safety: Encourages dissent without fear of retaliation.

  • Techniques: Utilizing devil’s advocacy and second-chance meetings can enhance decisions.

Learning from Experience

  • Experience vs. Learning: Experience shows what happened; learning reveals why.

Barriers to Learning

  • Ignored Feedback: Neglecting negative feedback hides key lessons.

  • Self-Serving Bias: Attributing success to skill and failures to external factors.

  • Illusion of Control: Overestimating influence over outcomes.

  • Hindsight Bias: Misremembering outcomes as predictable when they were not.

Learning from Failure

  • Analyzing failures systematically rather than dismissively.

Learning from Success

  • Misattributing success to skill rather than luck can be misleading.

  • Effective leaders analyze successes and failures for deeper understanding.

Techniques for Improving Learning

  • Structured Postmortems: Reflecting on past decisions for learning.

  • "Lessons Learned" Meetings: Analyzing both failures and successes.

  • "Failure Résumé": Documenting and learning from mistakes.

  • Unlearning Outdated Beliefs: Adapting to changing environments.

Module 2: Tom Gilovich

Lecture 1 Terms to Know

  • The Stroop Task

  • Intuitive vs Reflective Systems of Reasoning

  • The Affect Heuristic

  • The Mere Exposure Effect

  • The Identifiable Victim Effect

  • The Availability Heuristic

Attribute Substitution

  • A process where a difficult question is unconsciously replaced with an easier one.

  • Examples:

    • Choosing a college ranked higher rather than evaluating personal fit.

    • Selecting a career based on potential earnings rather than personal satisfaction.

Headwinds-Tailwinds Asymmetry

  • We focus more on obstacles (headwinds) than advantages (tailwinds) due to the effort needed to overcome challenges.

  • Examples considered: Difficulty faced by ag students vs. hotel students regarding career opportunities.

Representativeness Heuristic

  • Judging probabilities based on similarity to a prototype rather than actual probabilities.

  • Can lead to base rate neglect and conjunction fallacy.

  • Example: Assuming danger from rustling noise at night based on stereotypes.

Linda Problem

  • Description of Linda as a character leading to intuitive responses in probability tasks.

  • Questions:

    • A) Linda is a bank teller.

    • B) Linda is a bank teller and active in the feminist movement.

Regression Effect / Regression Fallacy

  • Regression Effect: Tendency for extreme values to be followed by closer means.

  • Regression Fallacy: Failing to foresee regression effects leading to superstitious beliefs about outcomes.

  • Example: Ineffective medical remedies appearing effective because of natural healing processes at low points.

Superforecasters

  • Approach problems from an outside perspective before diving deep.

  • Skeptical of fate; constantly revise their predictions.

Discussion Questions

  • How does the representativeness heuristic lend credibility to pseudoscientific beliefs?

  • What is the relationship between the regression effect and the regression fallacy?

  • How can the regression effect cause ineffective medical interventions to appear helpful?

  • What is base rate neglect?

  • Distinction between strength and weight of a body of evidence?

  • How do "superforecasters" differ from others in their approach to problem-solving?