Ran build-vs-buy-vs-open-source through proper MCDA and showed where each stakeholder's view diverges

You are a decision scientist specializing in Multi-Criteria Decision Analysis (MCDA). Apply rigorous MCDA methods to my complex decision.\n\nDECISION: {{decision_question}}\nOPTIONS TO EVALUATE: {{alternatives — e.g., 'Vendor A, Vendor B, Build in-house, Use open source'}}\nDECISION CONTEXT: {{context}}\nKEY STAKEHOLDERS WITH DIFFERENT PRIORITIES: {{stakeholders}}\n\nOUTPUT — Multi-Criteria Decision Analysis:\n\n## 1. DECISION STRUCTURING\n**Problem formulation**: Frame the decision correctly\n**Options clarification**: Ensure options are MECE (Mutually Exclusive, Collectively Exhaustive) — are we missing any?\n**Fundamental objectives**: What are we REALLY trying to achieve? (separate means from ends)\n\n## 2. CRITERIA HIERARCHY (Value Tree)\nDecompose the decision into a hierarchy:\n\n**Strategic Criteria** (why this matters long-term):\n- C1: [Criterion name] — Definition — Measurement scale\n - Sub-criterion 1.1\n - Sub-criterion 1.2\n\n**Operational Criteria** (day-to-day impact):\n- C2: [Criterion name] — Definition — Measurement scale\n - Sub-criterion 2.1\n - Sub-criterion 2.2\n\n**Risk Criteria** (downside protection):\n- C3: [Criterion name]\n\n**Constraint Criteria** (must-haves for qualification):\n- [List go/no-go criteria]\n\nGenerate 8-12 criteria total across categories.\n\n## 3. WEIGHT ELICITATION (AHP Method)\nUse pairwise comparisons to determine criteria weights:\n\nCompare each pair of criteria: Which is more important and by how much?\nScale: 1=Equal, 3=Moderate, 5=Strong, 7=Very strong, 9=Extreme\n\n| | C1 | C2 | C3 | C4 | C5 | Row Sum | Weight |\n|----|----|----|----|----|----|---------|--------|\n| C1 | 1 | | | | | | |\n| C2 | | 1 | | | | | |\n| C3 | | | 1 | | | | |\n| C4 | | | | 1 | | | |\n| C5 | | | | | 1 | | |\n\n**Consistency Check**:\n- Calculate Consistency Ratio (CR)\n- If CR > 0.1, flag inconsistent judgments and suggest revision\n- Explain which pairwise comparisons seem inconsistent\n\n## 4. PERFORMANCE SCORING\nScore each option on each criterion:\n\n| Option | C1 [w] | C2 [w] | C3 [w] | C4 [w] | C5 [w] | ... |\n|--------|--------|--------|--------|--------|--------|-----|\n| {{alternatives}} | | | | | | |\n\nScoring scales:\n- Quantitative criteria: Use actual measurements (normalized 0-100)\n- Qualitative criteria: Use anchored rating scales with behavioral descriptions for each level (1-5 or 1-10)\n- Cost criteria: Invert so higher = better\n\n## 5. AGGREGATION METHOD SELECTION\nChoose and apply the appropriate MCDA method:\n\n**Method A: Weighted Sum Model (WSM)**\nSimplest: Score = Σ(weight_i × performance_ij)\nBest for: Compensatory decisions where trade-offs are acceptable\n\n**Method B: Analytic Hierarchy Process (AHP)**\nUses pairwise comparisons for both weights and scores\nBest for: Hierarchical decisions with many criteria\n\n**Method C: TOPSIS**\nRank by proximity to ideal and distance from anti-ideal solution\nBest for: When you want a reference-based ranking\n\n**Method D: ELECTRE (Outranking)**\nBuilds pairwise dominance relationships with veto thresholds\nBest for: When certain criteria are non-compensatory (must meet minimum)\n\n**Method E: PROMETHEE**\nPreference flows based on pairwise comparisons with preference functions\nBest for: Complex trade-offs with non-linear preferences\n\n**Recommendation**: Apply [Method] because [justification]. Show results from at least 2 methods for robustness.\n\n## 6. RESULTS & RANKING\n\n| Option | WSM Score | WSM Rank | TOPSIS Score | TOPSIS Rank | ELECTRE Rank | Average Rank | Final Rank |\n|--------|-----------|----------|-------------|-------------|-------------|-------------|------------|\n\n**Sensitivity analysis**: Does the winner change if weights shift?\n- Identify 'swing weights': How much must [criterion X] weight change for the ranking to flip?\n- Scenario: What if {{stakeholders}}'s priorities are weighted more heavily?\n\n## 7. STAKEHOLDER PERSPECTIVE ANALYSIS\nRe-run analysis from each stakeholder's perspective:\n\n| Option | Overall Rank | Stakeholder A Rank | Stakeholder B Rank | Stakeholder C Rank | Rank Variance |\n|--------|-------------|--------------------|--------------------|--------------------|---------------|\n\nWhere do stakeholders disagree most? What criteria drive the disagreement?\n\n## 8. DECISION RECOMMENDATION\n- Recommended option with full rationale\n- Key trade-offs being made (what are we giving up?)\n- Conditions under which the second-best option becomes preferable\n- Implementation considerations for the recommended option\n- Monitoring: What to watch to confirm this was the right decision