Cross-functional what-if modeling for cascading multi-variable scenarios. Unlike single-assumption stress testing, this models compound adversity across all business functions simultaneously. Use when facing complex risk scenarios, strategic decisions with major downside, or
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Cross-functional what-if modeling for cascading multi-variable scenarios. Unlike single-assumption stress testing, this models compound adversity across all business functions simultaneously. Use when facing complex risk scenarios, strategic decisions with major downside, or
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LanguagePython
LicenseMIT
๐ฆ Ships with claude-skills
</> SKILL.md
scenario-war-room.SKILL.md
---name: "scenario-war-room"
description: "Cross-functional what-if modeling for cascading multi-variable scenarios. Unlike single-assumption stress testing, this models compound adversity across all business functions simultaneously. Use when facing complex risk scenarios, strategic decisions with major downside, or when the user asks 'what if X AND Y both happen?'"
license: MIT
metadata:
version: 1.0.0
author: Alireza Rezvani
category: c-level
domain: strategic-planning
updated: 2026-03-05
python-tools: scenario_modeler.py
frameworks: scenario-planning
---# Scenario War Room
Model cascading what-if scenarios across all business functions. Not single-assumption stress tests โ compound adversity that shows how one problem creates the next.
## Keywords
scenario planning, war room, what-if analysis, risk modeling, cascading effects, compound risk, adversity planning, contingency planning, stress test, crisis planning, multi-variable scenario, pre-mortem
## Quick Start
```bash
python scripts/scenario_modeler.py # Interactive scenario builder with cascade modeling
```
Or describe the scenario in natural language:
> "What if we lose our top customer AND miss the Q3 fundraise?"
[One paragraph. What to do, in what order, and why.]
```
---
## Rules for Good War Room Sessions
**Max 3 variables per scenario.** More than 3 is noise โ you can't meaningfully prepare for 5-variable collapse. Model the 3 that actually worry you.
**Quantify or estimate.** "Revenue drops" is not useful. "$420K ARR at risk over 60 days" is. Use ranges if uncertain.
**Don't stop at first-order effects.** The damage is always in the cascade, not the initial hit.
**Model recovery, not just impact.** Every scenario should have a "what we do" path.
**Separate base case from sensitivity.** Don't conflate "what probably happens" with "what could happen."
**Don't over-model.** 3-4 scenarios per planning cycle is the right number. More creates analysis paralysis.