{ "criteria": [ { "name": "Decision Framing & Context", "description": "Is the decision clearly defined with all viable alternatives identified?", "scoring": { "1": "Decision is vague or ill-defined. Alternatives are incomplete or include non-comparable options. No stakeholder identification.", "3": "Decision is stated but lacks specificity. Most alternatives listed but may be missing key options. Stakeholders mentioned generally.", "5": "Exemplary framing. Decision is specific and unambiguous. All viable alternatives identified (including 'do nothing' if relevant). Must-have requirements separated from criteria. Stakeholders clearly identified with their priorities noted." } }, { "name": "Criteria Quality & Coverage", "description": "Are criteria well-chosen, measurable, independent, and comprehensive?", "scoring": { "1": "Criteria are vague, redundant, or missing key factors. Too many (>10) or too few (<3). No clear definitions.", "3": "Criteria cover main factors but may have some redundancy or gaps. 4-8 criteria with basic definitions. Some differentiation between options.", "5": "Exemplary criteria selection. 4-7 criteria that are measurable, independent, relevant, and differentiate between options. Each criterion has clear definition and measurement approach. No redundancy. Captures all important trade-offs." } }, { "name": "Weighting Appropriateness", "description": "Do criterion weights reflect true priorities and sum to 100%?", "scoring": { "1": "Weights don't sum to 100%, are arbitrary, or clearly misaligned with stated priorities. No rationale provided.", "3": "Weights sum to 100% and are reasonable but may lack explicit justification. Some alignment with priorities.", "5": "Exemplary weighting. Weights sum to 100%, clearly reflect stakeholder priorities, and have documented rationale (pairwise comparison, swing weighting, or stakeholder averaging). Weight distribution makes sense for decision type." } }, { "name": "Scoring Rigor & Data Quality", "description": "Are scores based on data or defensible judgments with documented sources?", "scoring": { "1": "Scores appear to be wild guesses with no justification. No data sources. Inconsistent scale usage.", "3": "Mix of data-driven and subjective scores. Some sources documented. Mostly consistent 1-10 scale. Some assumptions noted.", "5": "Exemplary scoring rigor. Objective criteria backed by real data (quotes, benchmarks, measurements). Subjective criteria have clear anchors/definitions. All assumptions and data sources documented. Consistent 1-10 scale usage." } }, { "name": "Calculation Accuracy", "description": "Are weighted scores calculated correctly and presented clearly?", "scoring": { "1": "Calculation errors present. Weights don't match stated percentages. Formula mistakes. Unclear presentation.", "3": "Calculations are mostly correct with minor issues. Weighted scores shown but presentation could be clearer.", "5": "Perfect calculations. Weighted scores = Σ(score × weight) for each option. Table clearly shows raw scores, weights (as percentages), weighted scores, and totals. Ranking is correct." } }, { "name": "Sensitivity Analysis", "description": "Is decision robustness assessed (close calls, weight sensitivity, score uncertainty)?", "scoring": { "1": "No sensitivity analysis. Winner declared without checking if decision is robust.", "3": "Basic sensitivity noted (e.g., 'close call' mentioned) but not systematically analyzed.", "5": "Thorough sensitivity analysis. Identifies close calls (<10% margin). Tests weight sensitivity (would swapping weights flip decision?). Notes which scores are most uncertain. Assesses decision robustness and flags fragile decisions." } }, { "name": "Recommendation Quality", "description": "Is recommendation clear with rationale, trade-offs, and confidence level?", "scoring": { "1": "No clear recommendation or just states winner without rationale. No trade-off discussion.", "3": "Recommendation stated with basic rationale. Some trade-offs mentioned. Confidence level implied but not stated.", "5": "Exemplary recommendation. Clear winner with score. Explains WHY winner prevails (which criteria drive decision). Acknowledges trade-offs (where winner scores lower). States confidence level based on margin and sensitivity. Suggests next steps." } }, { "name": "Assumption & Limitation Documentation", "description": "Are key assumptions, uncertainties, and limitations explicitly stated?", "scoring": { "1": "No assumptions documented. Presents results as facts without acknowledging uncertainty or limitations.", "3": "Some assumptions mentioned. Acknowledges uncertainty exists but not comprehensive.", "5": "All key assumptions explicitly documented. Uncertainties flagged (which scores are guesses vs data). Limitations noted (e.g., 'cost estimates are preliminary', 'performance benchmarks unavailable'). Reader understands confidence bounds." } }, { "name": "Stakeholder Alignment", "description": "For group decisions, are different stakeholder priorities surfaced and addressed?", "scoring": { "1": "Single set of weights/scores presented as if universal. No acknowledgment of stakeholder differences.", "3": "Stakeholder differences mentioned but not systematically addressed. Single averaged view presented.", "5": "Stakeholder differences explicitly surfaced. If priorities diverge, shows impact (e.g., 'Under engineering priorities, A wins; under sales priorities, B wins'). Facilitates alignment or escalates decision appropriately." } }, { "name": "Communication & Presentation", "description": "Is matrix table clear, readable, and appropriately formatted?", "scoring": { "1": "Matrix is confusing, poorly formatted, or missing key elements (weights, totals). Hard to interpret.", "3": "Matrix is readable with minor formatting issues. Weights and totals shown but could be clearer.", "5": "Exemplary presentation. Table is clean and scannable. Column headers show criteria names AND weights (%). Weighted scores shown (not just raw scores). Winner visually highlighted. Assumptions and next steps clearly stated." } } ], "minimum_score": 3.5, "guidance_by_decision_type": { "Technology Selection (tools, platforms, vendors)": { "target_score": 4.0, "focus_criteria": [ "Criteria Quality & Coverage", "Scoring Rigor & Data Quality", "Sensitivity Analysis" ], "common_pitfalls": [ "Missing 'Total Cost of Ownership' as criterion (not just upfront cost)", "Ignoring integration complexity or vendor lock-in risk", "Not scoring 'do nothing / keep current solution' as baseline" ] }, "Strategic Choices (market entry, partnerships, positioning)": { "target_score": 4.0, "focus_criteria": [ "Decision Framing & Context", "Weighting Appropriateness", "Stakeholder Alignment" ], "common_pitfalls": [ "Weighting short-term metrics too heavily over strategic fit", "Not including reversibility / optionality as criterion", "Ignoring stakeholder misalignment on priorities" ] }, "Vendor / Supplier Evaluation": { "target_score": 3.8, "focus_criteria": [ "Criteria Quality & Coverage", "Scoring Rigor & Data Quality", "Assumption & Limitation Documentation" ], "common_pitfalls": [ "Relying on vendor-provided data without validation", "Not including 'vendor financial health' or 'support SLA' criteria", "Missing contract terms (pricing lock, exit clauses) as criterion" ] }, "Feature Prioritization": { "target_score": 3.5, "focus_criteria": [ "Weighting Appropriateness", "Scoring Rigor & Data Quality", "Sensitivity Analysis" ], "common_pitfalls": [ "Not including 'effort' or 'technical risk' as criteria", "Scoring 'user impact' without user research data", "Ignoring dependencies between features" ] }, "Hiring Decisions": { "target_score": 3.5, "focus_criteria": [ "Criteria Quality & Coverage", "Scoring Rigor & Data Quality", "Assumption & Limitation Documentation" ], "common_pitfalls": [ "Criteria too vague (e.g., 'culture fit' without definition)", "Interviewer bias in scores (need calibration)", "Not documenting what good vs poor looks like for each criterion" ] } }, "guidance_by_complexity": { "Simple (3-4 alternatives, clear criteria, aligned stakeholders)": { "target_score": 3.5, "sufficient_rigor": "Basic weighting (direct allocation), data-driven scores where possible, simple sensitivity check (margin analysis)" }, "Moderate (5-7 alternatives, some subjectivity, minor disagreement)": { "target_score": 3.8, "sufficient_rigor": "Structured weighting (rank-order or pairwise), documented scoring rationale, sensitivity analysis on close calls" }, "Complex (8+ alternatives, high subjectivity, stakeholder conflict)": { "target_score": 4.2, "sufficient_rigor": "Advanced weighting (AHP, swing), score calibration/normalization, Monte Carlo or scenario sensitivity, stakeholder convergence process (Delphi, NGT)" } }, "common_failure_modes": { "1. Post-Rationalization": { "symptom": "Weights or scores appear engineered to justify pre-made decision", "detection": "Oddly specific weights (37%), generous scores for preferred option, stakeholders admit 'we already know the answer'", "prevention": "Assign weights BEFORE scoring alternatives. Use blind facilitation. Ask: 'If matrix contradicts gut, do we trust it?'" }, "2. Garbage In, Garbage Out": { "symptom": "All scores are guesses with no data backing", "detection": "Cannot answer 'where did this score come from?', scores assigned in <5 min, all round numbers (5, 7, 8)", "prevention": "Require data sources for objective criteria. Define scoring anchors for subjective criteria. Flag uncertainties." }, "3. Analysis Paralysis": { "symptom": "Endless refinement, never deciding", "detection": ">10 criteria, winner changes 3+ times, 'just one more round' requests", "prevention": "Set decision deadline. Cap criteria at 5-7. Use satisficing rule: 'Any option >7.0 is acceptable.'" }, "4. Criterion Soup": { "symptom": "Overlapping, redundant, or conflicting criteria", "detection": "Two criteria always score the same, scorer confusion ('how is this different?')", "prevention": "Independence test: Can option score high on A but low on B? If no, merge them. Write clear definitions." }, "5. Ignoring Sensitivity": { "symptom": "Winner declared without robustness check", "detection": "No mention of margin, close calls, or what would flip decision", "prevention": "Always report margin. Test: 'If we swapped top 2 weights, does winner change?' Flag fragile decisions." }, "6. Stakeholder Misalignment": { "symptom": "Different stakeholders have different priorities but single matrix presented", "detection": "Engineering wants A, sales wants B, but matrix 'proves' one is right", "prevention": "Surface weight differences. Show 'under X priorities, A wins; under Y priorities, B wins.' Escalate if needed." }, "7. Missing 'Do Nothing'": { "symptom": "Only evaluating new alternatives, forgetting status quo is an option", "detection": "All alternatives are new changes, no baseline comparison", "prevention": "Always include current state / do nothing as an option to evaluate if change is worth it." }, "8. False Precision": { "symptom": "Scores to 2 decimals when underlying data is rough guess", "detection": "Weighted total: 7.342 but scores are subjective estimates", "prevention": "Match precision to confidence. Rough guesses → round to 0.5. Data-driven → decimals OK." } } }