Better Decisions Prelim 1 Review

Module 1: Professor Russo

Lecture 1 Key Concepts

Part 1: The Importance of a Decision Process

  • Implementation + Decision Process + Chance = Decision Outcome

  • 4 Phases of Decision Process (from Shoemaker et al. (2018))

    • These phases do not always occur in a complete cycle

    • Some phases may occur without deliberate control

  • Good Process

    • Can be developed and is largely self-taught

    • Important for managerial decision making

    • Good results stem from good processes

    • "A good decision process gets you the closest to a guaranteed good decision outcome"

Lecture 1 (cont.)

Part 2: Overconfidence

  • Decision Making Components

    • Primary Knowledge: What you know

    • Metaknowledge: What you know about what you know

  • Confidence: The belief about the certainty of another belief

  • Overconfidence: Greater belief in a belief than is justified

  • The Confidence Game

    • Overconfident (incorrect experts) eventually lose

  • Misprecision: The size of your confidence interval range

  • Misestimation: The accuracy of predictions

  • Misplacement: Accuracy compared to others

  • Information Overload: More information can lead to overconfidence

  • Feedback Importance: Accurate, timely, and repeated feedback improves metaknowledge

Lecture 2

Part 1: Thinking Frames

  • Frame Characteristics: Borrowed, complete, coherent with highlights and shadows

    • Can change and compete

  • Examples of Frames:

    • Crowdfunding appeals (independent needs vs dependent needs)

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

    • The matchmaking story

    • Different perspectives on students (learners, customers, alumni)

    • Political and economic framing

  • Frames & Manipulation:

    • Using frames can manipulate perceptions and decisions

Analyzing Frames

  • Frame Audit Analysis: Issues, boundaries, metrics, metaphors assessed

    • Example: Highlights vs. shadows of a Cornell major

    • Requires viewing from another's perspective

    • Example: Suppliers vs. partners for Boeing

  • Endorse vs. Honored: Framing implications for brands like Duncan Hines

Part 2: Decision Frames

  • Constructed Frame: Organized thinking about a topic or situation

    • Tailored, requiring time and effort

    • Example: Frame regarding a person's creditworthiness (based on repayment history, occupation, etc.)

  • Updating Frames: Sometimes criteria may need revision

    • Example: Meeting planning company frame update

  • Metrics: Measuring criteria (absolute vs relative percentages)

  • Conflicting Frames: Offensive vs. defensive framing

    • Rigid frames can lead to overconfidence

Lecture 3 & 4 Key Concepts

Common Pitfalls in Group Decision-Making

  • Striving for Influence: Dominant members impacting fairness

  • Striving for Harmony: Avoiding conflict causes groupthink

  • Striving for Efficiency: Rushing leads to shallow decision exploration

Framing Problems in Groups

  • Frame Conflict: Diverse perspectives may lead to misunderstandings

  • Too Little Time on Framing: Rushed decisions jeopardize understanding

  • Single Shared Frame: Premature convergence overlooks alternatives

Psychological Biases in Groups

  • Groupthink: Conformity pressure stifles critical thinking

  • Egocentrism Bias: Overestimating one’s contributions

  • Overconfidence Bias: Groups may reinforce overconfidence

Managing Conflict for Better Decisions

  • Task Conflict: Focus on ideas improves decision-making

  • Psychological Safety: Encouraging dissent enhances discussion

  • Techniques for Improvement: Devil’s advocacy and second-chance meetings bolster choices

Learning from Experience

Experience vs. Learning

  • Experience: Knowledge of what occurred

  • Learning: Understanding why it occurred

Barriers to Learning

  • Ignored Feedback: Avoiding negative feedback hinders growth

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

  • Illusion of Control: Overestimating influence on outcomes

  • Hindsight Bias: Misremembering past outcomes as predictable

Learning from Failure

  • Analyzing failures systematically is crucial

Learning from Success

  • Misattributing success to skill instead of luck can be misleading

  • Leaders must assess both successes and failures for causality

Techniques for Improving Learning

  • Structured Postmortems: Reflect on decisions made

  • Lessons Learned Meetings: Analyze both successes and failures

  • Failure Résumé: Document mistakes for future reference

  • Unlearning Outdated Beliefs: Adapt to new realities

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

  • Process of unconsciously replacing difficult questions with easier ones

    • Example: Choosing a college

      • Difficult: Which should you attend?

      • Easier: Which is ranked higher?

    • Example: Career choice

      • Difficult: Which should you choose?

      • Easier: Which career makes a lot of money?

Headwinds Tailwinds Asymmetry

  • Tendency to focus on obstacles (headwinds) over advantages (tailwinds)

  • Questions on comparative difficulties in various student fields

Representativeness Heuristic

  • Judging probabilities based on similarity to prototypes rather than actual data

  • Can lead to base rate neglect and conjunction fallacy

  • Example: Misjudging danger based on context cues (e.g., late-night rustling sounds)

Linda Example

  • Profile of Linda: 31, single, outspoken, philosophy major concerned with discrimination and justice

  • Questions about her likelihood:

    • A) Bank teller

    • B) Bank teller and active in feminist movement

Regression Effect / Regression Fallacy

  • Regression Effect: Tendency for extreme values to be followed by values closer to the mean

  • Regression Fallacy: Failure to anticipate regression effects leading to mistaken beliefs

    • Example: Misattribution of healing to ineffective remedies during illness

Superforecasters

  • Approach problems from an outside perspective before delving deeper

  • Do not believe in fate

  • Constantly revise answers based on new information

Discussion Questions

  1. In what ways does the representativeness heuristic lend credibility to pseudoscientific beliefs?

  2. What is the connection between the regression effect and regression fallacy?

  3. How might the regression effect create the illusion of effectiveness in invalid medical treatments?

  4. Define base rate neglect.

  5. Distinguish between the strength of evidence vs. its overall weight.

  6. How do superforecasters differ from typical decision-makers?