Decision Analysis Complexity and Evolution

• Extension from 2 choices/outcomes/stages to 3 of each creates really complicated setup
• Deliberately avoided showing revision calculations for prior probabilities and future probabilities
• Bottom line: good chance of messy bush (complex decision trees)
• Used in Chevron's decision analysis manual
• Provides insights into value of information (next lecture topic)

Dynamic Strategy vs Static Planning

• Decision analysis doesn't produce simple plan
• Instead of single directive (e.g., "take raincoat"), creates conditional strategy:
  • Listen to weather forecast
  • If one outcome → take raincoat
  • If another outcome → don't take raincoat
• Not step-by-step phases (phase 1, 2, 3) but dynamic decision-making
• Example: Build plant first stage
  • If growth → expand
  • If no growth → do nothing
  • If failing → close
• Strategy = dynamic plan lasting through time, not single fixed plan

Educational Value and Client Benefits

• Process complexity serves as education for client
• Demonstrates dynamic strategy superiority over step-by-step planning
• Phased "this is what we'll do through time" plans generally don't work out
• Often second-best strategy is optimal for any single outcome

Insurance Example Analysis

• Car ownership decision with accident risk
• Post-outcome analysis shows:
  • If accident occurs: driving seems like bad idea
  • If no accident: insurance seems wasteful ("didn't use it")
• Optimal choice (drive with insurance) never best choice for specific outcomes:
  • No accident scenario: money wasted on unused insurance
  • Bad accident scenario: shouldn't have engaged in risky activity
• Demonstrates optimal strategy isn't necessarily best for all possible outcomes

Decision Analysis vs Flexibility Analysis Comparison

Decision Analysis Characteristics:

• Assumes ability to define choices at any stage
• Essential for building decision trees
• Must specify stage 2 and stage 3 options upfront
• Focuses on few distinct choices ("do this, that, or the other")
• Limited granularity
• Not easily scalable for complex scenarios

Flexibility Analysis Advantages:

• Encourages exploration of what decisions to take and when
• Doesn't prescribe specific actions or timing
• Simulation analysis enables easy exploration
• Via Excel: granular analysis as desired
• Can process 2,000 simulations in seconds
• Not possible with traditional decision analysis

Historical Context and Current Relevance

• Decision analysis was popular breakthrough "long time ago"
• Revolutionary for its time in systematic thinking
• Still exists and used today but less relevant
• Has valuable insights, particularly regarding value of information
• Flexibility analysis more suited to current analytical capabilities