Decision: 
Options to evaluate: 

Step 1: Identify evaluation criteria
   - List ALL criteria that matter (not just obvious ones)
   - Examples: cost, speed, risk, team capability, strategic fit, learning value, etc.

Step 2: Weight the criteria
   - How important is each one?
   - Assign weights (1-5 or percentages)
   - These weights reveal your actual priorities

Step 3: Score each option
   - Rate each option on each criterion (1-10 scale)
   - Be specific: why this score?
   - Note uncertainties

Step 4: Calculate weighted scores
   - (Score × Weight) for each option/criterion
   - Sum across criteria

Step 5: Sensitivity analysis
   - If you changed the top weight by ±20%, does the ranking flip?
   - Which criteria are decision-drivers?
   - How confident are you?

Step 6: Recommendation
   - Which option wins?
   - What's the gap to second place?
   - What would need to change your mind?

Examples

Input

{
  "decision": "Which paid tier structure should we launch with?",
  "options": "Simple (1 tier), Tiered (3 tiers), Usage-based, Freemium + paid"
}

Output

Complete decision matrix with weighted criteria, scored options, calculated totals, sensitivity analysis, and final recommendation with confidence level.

Sources

https://en.wikipedia.org/wiki/Multi-criteria_decision_analysis

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