Strategy: Morphological Scenario

Methodology

General Morphological Analysis (Zwicky) combined with Cross-Consistency Assessment (Ritchey). Systematically enumerate all possible combinations of key uncertainty parameters, filter for internal consistency, and assess surviving configurations as plausible scenarios.

Key principles:

• Completeness: Every relevant parameter dimension is included
• MECE values: Each parameter has mutually exclusive, collectively exhaustive values
• Pairwise consistency: Filter via CCA matrix before narrative construction
• Combinatorial discipline: Let the morphological field drive discovery, not intuition

Execution Flow

1. Identify drivers → spawn scenario-driver-identification

• Input: research context, planning horizon
• Output: 5-8 key uncertainty drivers

1. Enumerate parameters → spawn parameter-enumeration

• Input: driver list
• Output: Zwicky Box (parameter × value matrix)

1. Consistency filtering → spawn consistency-pair-evaluation

• Input: Zwicky Box
• Output: CCA matrix, surviving configurations

1. Narrative construction → spawn scenario-narrative-construction (per surviving config)

• Input: parameter configuration
• Output: scenario narrative

1. Impact assessment → spawn scenario-impact-assessment (per scenario)

• Input: scenario narrative, research approach
• Output: impact analysis

1. Robustness scoring → spawn robustness-scoring

• Input: all impact assessments
• Output: robustness index

1. Synthesis → spawn scenario-synthesis

• Input: all scenarios, robustness scores
• Output: final scenario portfolio report

Budget Gate

| Step | Token Budget | Notes | |------|-------------|-------| | Driver identification | 8K | Single pass | | Parameter enumeration | 10K | May iterate once | | Consistency filtering | 15K | O(n²) pairwise | | Narrative construction | 12K × N | N = surviving configs (typically 4-8) | | Impact assessment | 10K × N | Per scenario | | Robustness scoring | 8K | Aggregation | | Synthesis | 12K | Final compilation |

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Available Tactics

Optional, no fixed order; the final leaf is always a sop.

| Tactic | When to use | | --- | --- | | cross-consistency-filtering | Orchestrates pairwise consistency evaluation and narrative construction to filter the morphological field | | parameter-space-construction | Orchestrates driver identification and parameter enumeration to build the complete morphological field | | strategy-robustness-testing | Orchestrates impact assessment and robustness scoring to evaluate research approach resilience across scenarios |

Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use | | --- | --- | | experiment-execution-consistency-pair-evaluation | Pairwise consistency assessment using Cross-Consistency Assessment (CCA) matrix | | parameter-enumeration | Enumerate possible values for each uncertainty driver using MECE principles | | robustness-scoring | Compute robustness index across scenarios with sensitivity analysis | | scenario-driver-identification | Identify key uncertainty drivers using PESTEL framework scanning | | scenario-impact-assessment | Assess each scenario's impact on the research approach across multiple dimensions | | scenario-narrative-construction | Build rich narratives for surviving morphological configurations using Shell method | | scenario-synthesis | Comprehensive scenario analysis report synthesizing all scenario work |

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