Introduction to Decision Science

Demystifying Decision Science

Howard Friedman

Adjunct Professor at Columbia University

Welcome

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Demystifying Decision Science

What is Decision Science?

 

Multidisciplinary field:

  • Mathematics
  • Statistics
  • Psychology
  • Economics
  • Computer Science

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Demystifying Decision Science

Informed decisions

 

  1. Define problem
  2. Gather and analyze data
  3. Develop and evaluate alternatives
  4. Select and implement solution

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Demystifying Decision Science

Why perfect rationality isn't realistic

 

Traditional decision-making models assumed:

  • Perfect rationality
  • Complete information
  • Free from bias and emotion

 

Bounded rationality:

  • Humans have cognitive limits
  • Limited information and time
  • Subject to emotions and biases
Demystifying Decision Science

Data-driven decision-making

Advantages of data-driven decisions:

  • Objective insights and clarity
  • Identification of trends
  • Accurate predictions and reduced uncertainty

Real-world example (Finance forecasting):

  • Data-driven guidance on investment choices
  • Goal: Maximize growth, profitability, and minimize risk

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Demystifying Decision Science

Unconscious bias

  • Confirmation bias: Seeking information that supports existing beliefs
  • Anchoring bias: Over-relying on initial information
  • Loss aversion: Preferring to avoid losses over acquiring equivalent gains
  • Availability heuristic: Overestimating likelihood of easily recalled events

Decision science helps us to recognize and mitigate these biases

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Demystifying Decision Science

Descriptive analytics

 

  • Uses data visualization and summary statistics
  • Explains what happened historically

 

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Prescriptive analytics

 

  • Uses optimization and simulation
  • Recommends best actions based on historical data analysis

 

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Demystifying Decision Science

Decision science offers a structured framework for informed decision-making  

Success comes from:

  • Clearly understanding the decision-making process
  • Recognizing and managing human limitations and biases
  • Leveraging data-driven techniques to improve outcomes

 

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Demystifying Decision Science

Let's practice!

Demystifying Decision Science

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