Stakeholder preference elicitation skill for structured value and weight gathering
Elicits stakeholder preferences and weights for multi-criteria decision analysis using structured methods.
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The Stakeholder Preference Elicitor skill provides structured methods for gathering value judgments and weights from decision stakeholders. It supports multiple elicitation techniques, consistency checking, and preference aggregation for group decisions.
# Configure elicitation session
session_config = {
"decision": "Enterprise Software Selection",
"criteria": [
{"name": "Total Cost of Ownership", "unit": "USD", "direction": "minimize"},
{"name": "Implementation Time", "unit": "months", "direction": "minimize"},
{"name": "Functionality Fit", "unit": "percent", "direction": "maximize"},
{"name": "Vendor Stability", "unit": "score", "direction": "maximize"},
{"name": "Integration Capability", "unit": "score", "direction": "maximize"}
],
"stakeholders": [
{"id": "S1", "name": "CIO", "role": "Decision Maker", "weight": 0.3},
{"id": "S2", "name": "CFO", "role": "Decision Maker", "weight": 0.3},
{"id": "S3", "name": "IT Director", "role": "Technical Expert", "weight": 0.2},
{"id": "S4", "name": "Business Lead", "role": "User Representative", "weight": 0.2}
],
"elicitation_method": "swing_weights"
}
# Swing weight process
swing_weight_protocol = {
"step_1_ranges": {
"description": "Define worst and best levels for each criterion",
"ranges": {
"Total Cost of Ownership": {"worst": 2000000, "best": 500000},
"Implementation Time": {"worst": 24, "best": 6},
"Functionality Fit": {"worst": 60, "best": 95},
"Vendor Stability": {"worst": 3, "best": 9},
"Integration Capability": {"worst": 2, "best": 10}
}
},
"step_2_reference": {
"description": "Imagine all criteria at worst level. Which would you most want to swing to best?",
"responses": {
"S1": "Functionality Fit",
"S2": "Total Cost of Ownership",
"S3": "Integration Capability",
"S4": "Functionality Fit"
}
},
"step_3_relative_weights": {
"description": "If most important swing = 100, rate the value of other swings",
"responses": {
"S1": {
"Functionality Fit": 100,
"Total Cost of Ownership": 80,
"Integration Capability": 60,
"Implementation Time": 40,
"Vendor Stability": 30
}
# ... other stakeholders
}
}
}
# Trade-off elicitation
tradeoff_questions = {
"format": "matching",
"questions": [
{
"id": "TQ1",
"question": "You can have software with 95% functionality fit. How much extra cost would you accept to maintain this level vs. 75% fit?",
"criteria_pair": ["Functionality Fit", "Total Cost of Ownership"],
"anchors": {"Functionality Fit": {"from": 75, "to": 95}}
},
{
"id": "TQ2",
"question": "Implementation in 6 months vs 12 months: how much more would you pay for the faster option?",
"criteria_pair": ["Implementation Time", "Total Cost of Ownership"],
"anchors": {"Implementation Time": {"from": 12, "to": 6}}
}
]
}
# Check for consistency
consistency_check = {
"method": "transitivity",
"checks": [
{
"stakeholder": "S1",
"issue": "weight_inconsistency",
"details": "Cost weight (80) + Fit weight (100) implies Cost > Time, but trade-off suggests otherwise",
"severity": "warning",
"recommendation": "Revisit cost vs. time comparison"
}
],
"overall_consistency": 0.85
}
# Aggregate preferences
aggregation_config = {
"method": "weighted_geometric_mean",
"stakeholder_weights": {"S1": 0.3, "S2": 0.3, "S3": 0.2, "S4": 0.2},
"individual_weights": {
"S1": {"TCO": 0.26, "Time": 0.13, "Fit": 0.32, "Stability": 0.10, "Integration": 0.19},
"S2": {"TCO": 0.35, "Time": 0.15, "Fit": 0.25, "Stability": 0.15, "Integration": 0.10},
# ... etc.
},
"aggregated_weights": {
"TCO": 0.29,
"Time": 0.14,
"Fit": 0.28,
"Stability": 0.12,
"Integration": 0.17
},
"disagreement_metrics": {
"highest_variance_criterion": "Total Cost of Ownership",
"coefficient_of_variation": 0.15
}
}
{
"session_config": {
"decision": "string",
"criteria": ["object"],
"stakeholders": ["object"],
"method": "string"
},
"elicitation_data": {
"method": "swing|direct|tradeoff|pairwise",
"responses": "object"
},
"aggregation_config": {
"method": "geometric_mean|arithmetic_mean|majority",
"stakeholder_weights": "object"
}
}
{
"individual_weights": {
"stakeholder_id": {
"criterion": "number"
}
},
"aggregated_weights": {
"criterion": "number"
},
"consistency": {
"individual_scores": "object",
"issues": ["object"]
},
"disagreement_analysis": {
"high_variance_criteria": ["string"],
"stakeholder_clusters": "object",
"discussion_points": ["string"]
},
"documentation": {
"methodology": "string",
"assumptions": ["string"],
"limitations": ["string"]
}
}
| Method | Best For | Complexity |
|---|---|---|
| Swing Weights | Trading off criteria | Medium |
| Direct Rating | Quick assessment | Low |
| Pairwise Comparison | Systematic comparison | High |
| Trade-off | Understanding value | Medium |
| Point Allocation | Intuitive weights | Low |
| Bias | Description | Mitigation |
|---|---|---|
| Anchoring | Over-reliance on first information | Randomize order |
| Availability | Weight by memorable events | Use structured data |
| Overconfidence | Narrow probability ranges | Calibration training |
| Order Effects | Influenced by question sequence | Vary order across stakeholders |
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