Decision Matrix (MCDA)

⚖️ Decision Matrix (MCDA / EEV)

Philosophy: Complex decisions fail because people optimize for one variable while ignoring five others.

1. When to Use

• Choosing between 2+ options with multiple trade-offs
• Any decision where "it depends" is the current answer
• When stakeholders disagree on priorities

2. Execution Workflow

STEP 1: LIST OPTIONS
  └─ Must have ≥2 distinct options (no straw men)

STEP 2: DEFINE CRITERIA
  └─ List 3-7 evaluation criteria
  └─ Each criterion must be measurable or scorable (1-10)

STEP 3: WEIGHT CRITERIA
  └─ Assign percentage weights (must sum to 100%)
  └─ Force-rank: "If you could only optimize for ONE criterion, which?"

STEP 4: SCORE EACH OPTION
  └─ Score 1-10 per criterion per option
  └─ Justify each score in one sentence

STEP 5: COMPUTE EEV
  └─ EEV = Σ (Score × Weight) for each option
  └─ Rank options by total EEV

STEP 6: SANITY CHECK
  └─ Does the winner "feel" right?
  └─ If not, a hidden criterion exists — surface it and re-run

3. Output Format

# Decision: [Question]

## Criteria & Weights
| # | Criterion | Weight |
|---|-----------|--------|
| 1 | [Name]    | [X]%   |
| 2 | [Name]    | [X]%   |

## Scoring Matrix
| Option | C1 | C2 | C3 | **EEV** |
|--------|----|----|-----|---------|
| A      | 8  | 6  | 7   | **7.1** |
| B      | 5  | 9  | 4   | **6.2** |

## Recommendation
[Winner] with EEV of [X]. Key differentiator: [criterion].

## Sensitivity Analysis
If [criterion weight] changed by ±10%, would the winner change? [Yes/No]

4. Rules

• Never let one criterion dominate (max weight 40%)
• If an option scores 0 on a criterion, flag it as a potential dealbreaker
• Always run sensitivity analysis on the top weight

skill #decision-making #analysis #framework