Scenario war room
Cross-functional what-if modeling for cascading multi-variable scenarios.
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| name | description | license | metadata |
|---|---|---|---|
| scenario-war-room | 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?' | MIT | 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 — 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
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?" "What if 3 engineers quit AND we need to ship by Q3?" "What if our market shrinks 30% AND a competitor raises $50M?"
What This Is Not
- Not a single-assumption stress test (that's
/em:stress-test) - Not financial modeling only — every function gets modeled
- Not worst-case-only — models 3 severity levels
- Not paralysis by analysis — outputs concrete hedges and triggers
Framework: 6-Step Cascade Model
Step 1: Define Scenario Variables (max 3)
State each variable with:
- What changes — specific, quantified if possible
- Probability — your best estimate
- Timeline — when it hits
Variable A: Top customer (28% ARR) gives 60-day termination notice
Probability: 15% | Timeline: Within 90 days
Variable B: Series A fundraise delayed 6 months beyond target close
Probability: 25% | Timeline: Q3
Variable C: Lead engineer resigns
Probability: 20% | Timeline: Unknown
Step 2: Domain Impact Mapping
For each variable, each relevant role models impact:
| Domain | Owner | Models |
|---|---|---|
| Cash & runway | CFO | Burn impact, runway change, bridge options |
| Revenue | CRO | ARR gap, churn cascade risk, pipeline |
| Product | CPO | Roadmap impact, PMF risk |
| Engineering | CTO | Velocity impact, key person risk |
| People | CHRO | Attrition cascade, hiring freeze implications |
| Operations | COO | Capacity, OKR impact, process risk |
| Security | CISO | Compliance timeline risk |
| Market | CMO | CAC impact, competitive exposure |
Step 3: Cascade Effect Mapping
This is the core. Show how Variable A triggers consequences in domains that trigger Variable B's effects:
TRIGGER: Customer churn ($560K ARR)
↓
CFO: Runway drops 14 → 8 months
↓
CHRO: Hiring freeze; retention risk increases (morale hit)
↓
CTO: 3 open engineering reqs frozen; roadmap slips
↓
CPO: Q4 feature launch delayed → customer retention risk
↓
CRO: NRR drops; existing accounts see reduced velocity → more churn risk
↓
CFO: [Secondary cascade — potential death spiral if not interrupted]
Name the cascade explicitly. Show where it can be interrupted.
Step 4: Severity Matrix
Model three scenarios:
| Scenario | Definition | Recovery |
|---|---|---|
| Base | One variable hits; others don't | Manageable with plan |
| Stress | Two variables hit simultaneously | Requires significant response |
| Severe | All variables hit; full cascade | Existential; requires board intervention |
For each severity level:
- Runway impact
- ARR impact
- Headcount impact
- Timeline to unacceptable state (trigger point)
Step 5: Trigger Points (Early Warning Signals)
Define the measurable signal that tells you a scenario is unfolding before it's confirmed:
Trigger for Customer Churn Risk:
- Sponsor goes dark for >3 weeks
- Usage drops >25% MoM
- No Q1 QBR confirmed by Dec 1
Trigger for Fundraise Delay:
- <3 term sheets after 60 days of process
- Lead investor requests >30-day extension on DD
- Competitor raises at lower valuation (market signal)
Trigger for Engineering Attrition:
- Glassdoor activity from engineering team
- 2+ referral interview requests from engineers
- Above-market offer counter-required in last 3 months
Step 6: Hedging Strategies
For each scenario: actions to take now (before the scenario materializes) that reduce impact if it does.
| Hedge | Cost | Impact | Owner | Deadline |
|---|---|---|---|---|
| Establish $500K credit line | $5K/year | Buys 3 months if churn hits | CFO | 60 days |
| 12-month retention bonus for 3 key engineers | $90K | Locks team through fundraise | CHRO | 30 days |
| Diversify to <20% revenue concentration per customer | Sales effort | Reduces single-customer risk | CRO | 2 quarters |
| Compress fundraise timeline, start parallel process | CEO time | Closes before runways merge | CEO | Immediate |
Output Format
Every war room session produces:
SCENARIO: [Name]
Variables: [A, B, C]
Most likely path: [which combination actually plays out, with probability]
SEVERITY LEVELS
Base (A only): [runway/ARR impact] — recovery: [X actions]
Stress (A+B): [runway/ARR impact] — recovery: [X actions]
Severe (A+B+C): [runway/ARR impact] — existential risk: [yes/no]
CASCADE MAP
[A → domain impact → B trigger → domain impact → end state]
EARLY WARNING SIGNALS
- [Signal 1 → which scenario it indicates]
- [Signal 2 → which scenario it indicates]
- [Signal 3 → which scenario it indicates]
HEDGES (take these actions now)
1. [Action] — cost: $X — impact: [what it buys] — owner: [role] — deadline: [date]
2. [Action] — cost: $X — impact: [what it buys] — owner: [role] — deadline: [date]
3. [Action] — cost: $X — impact: [what it buys] — owner: [role] — deadline: [date]
RECOMMENDED DECISION
[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 — 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.
Common Scenarios by Stage
Seed:
- Co-founder leaves + product misses launch
- Funding runs out + bridge terms unfavorable
Series A:
- Miss ARR target + fundraise delayed
- Key customer churns + competitor raises
Series B:
- Market contraction + burn multiple spikes
- Lead investor wants pivot + team resists
Integration with C-Suite Roles
| Scenario Type | Primary Roles | Cascade To |
|---|---|---|
| Revenue miss | CRO, CFO | CMO (pipeline), COO (cuts), CHRO (layoffs) |
| Key person departure | CHRO, COO | CTO (if eng), CRO (if sales) |
| Fundraise failure | CFO, CEO | COO (runway extension), CHRO (hiring freeze) |
| Security breach | CISO, CTO | CEO (comms), CFO (cost), CRO (customer impact) |
| Market shift | CEO, CPO | CMO (repositioning), CRO (new segments) |
| Competitor move | CMO, CRO | CPO (roadmap response), CEO (strategy) |
References
references/scenario-planning.md— Shell methodology, pre-mortem, Monte Carlo, cascade frameworksscripts/scenario_modeler.py— CLI tool for structured scenario modeling
| 1 | |
| 2 | name "scenario-war-room" |
| 3 | 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?'" |
| 4 | license MIT |
| 5 | metadata |
| 6 | version 1.0.0 |
| 7 | author Alireza Rezvani |
| 8 | category c-level |
| 9 | domain strategic-planning |
| 10 | updated 2026-03-05 |
| 11 | python-tools scenario_modeler.py |
| 12 | frameworks scenario-planning |
| 13 | |
| 14 | |
| 15 | # Scenario War Room |
| 16 | |
| 17 | Model cascading what-if scenarios across all business functions. Not single-assumption stress tests — compound adversity that shows how one problem creates the next. |
| 18 | |
| 19 | ## Keywords |
| 20 | 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 |
| 21 | |
| 22 | ## Quick Start |
| 23 | |
| 24 | |
| 25 | python scripts/scenario_modeler.py # Interactive scenario builder with cascade modeling |
| 26 | |
| 27 | |
| 28 | Or describe the scenario in natural language: |
| 29 | |
| 30 | > "What if we lose our top customer AND miss the Q3 fundraise?" |
| 31 | > "What if 3 engineers quit AND we need to ship by Q3?" |
| 32 | > "What if our market shrinks 30% AND a competitor raises $50M?" |
| 33 | |
| 34 | ## What This Is Not |
| 35 | |
| 36 | **Not** a single-assumption stress test (that's `/em:stress-test`) |
| 37 | **Not** financial modeling only — every function gets modeled |
| 38 | **Not** worst-case-only — models 3 severity levels |
| 39 | **Not** paralysis by analysis — outputs concrete hedges and triggers |
| 40 | |
| 41 | ## Framework: 6-Step Cascade Model |
| 42 | |
| 43 | ### Step 1: Define Scenario Variables (max 3) |
| 44 | State each variable with: |
| 45 | **What changes** — specific, quantified if possible |
| 46 | **Probability** — your best estimate |
| 47 | **Timeline** — when it hits |
| 48 | |
| 49 | |
| 50 | Variable A: Top customer (28% ARR) gives 60-day termination notice |
| 51 | Probability: 15% | Timeline: Within 90 days |
| 52 | |
| 53 | Variable B: Series A fundraise delayed 6 months beyond target close |
| 54 | Probability: 25% | Timeline: Q3 |
| 55 | |
| 56 | Variable C: Lead engineer resigns |
| 57 | Probability: 20% | Timeline: Unknown |
| 58 | |
| 59 | |
| 60 | ### Step 2: Domain Impact Mapping |
| 61 | |
| 62 | For each variable, each relevant role models impact: |
| 63 | |
| 64 | | Domain | Owner | Models | |
| 65 | |--------|-------|--------| |
| 66 | | Cash & runway | CFO | Burn impact, runway change, bridge options | |
| 67 | | Revenue | CRO | ARR gap, churn cascade risk, pipeline | |
| 68 | | Product | CPO | Roadmap impact, PMF risk | |
| 69 | | Engineering | CTO | Velocity impact, key person risk | |
| 70 | | People | CHRO | Attrition cascade, hiring freeze implications | |
| 71 | | Operations | COO | Capacity, OKR impact, process risk | |
| 72 | | Security | CISO | Compliance timeline risk | |
| 73 | | Market | CMO | CAC impact, competitive exposure | |
| 74 | |
| 75 | ### Step 3: Cascade Effect Mapping |
| 76 | |
| 77 | This is the core. Show how Variable A triggers consequences in domains that trigger Variable B's effects: |
| 78 | |
| 79 | |
| 80 | TRIGGER: Customer churn ($560K ARR) |
| 81 | ↓ |
| 82 | CFO: Runway drops 14 → 8 months |
| 83 | ↓ |
| 84 | CHRO: Hiring freeze; retention risk increases (morale hit) |
| 85 | ↓ |
| 86 | CTO: 3 open engineering reqs frozen; roadmap slips |
| 87 | ↓ |
| 88 | CPO: Q4 feature launch delayed → customer retention risk |
| 89 | ↓ |
| 90 | CRO: NRR drops; existing accounts see reduced velocity → more churn risk |
| 91 | ↓ |
| 92 | CFO: [Secondary cascade — potential death spiral if not interrupted] |
| 93 | |
| 94 | |
| 95 | Name the cascade explicitly. Show where it can be interrupted. |
| 96 | |
| 97 | ### Step 4: Severity Matrix |
| 98 | |
| 99 | Model three scenarios: |
| 100 | |
| 101 | | Scenario | Definition | Recovery | |
| 102 | |----------|------------|---------| |
| 103 | | **Base** | One variable hits; others don't | Manageable with plan | |
| 104 | | **Stress** | Two variables hit simultaneously | Requires significant response | |
| 105 | | **Severe** | All variables hit; full cascade | Existential; requires board intervention | |
| 106 | |
| 107 | For each severity level: |
| 108 | Runway impact |
| 109 | ARR impact |
| 110 | Headcount impact |
| 111 | Timeline to unacceptable state (trigger point) |
| 112 | |
| 113 | ### Step 5: Trigger Points (Early Warning Signals) |
| 114 | |
| 115 | Define the measurable signal that tells you a scenario is unfolding **before** it's confirmed: |
| 116 | |
| 117 | |
| 118 | Trigger for Customer Churn Risk: |
| 119 | - Sponsor goes dark for >3 weeks |
| 120 | - Usage drops >25% MoM |
| 121 | - No Q1 QBR confirmed by Dec 1 |
| 122 | |
| 123 | Trigger for Fundraise Delay: |
| 124 | - <3 term sheets after 60 days of process |
| 125 | - Lead investor requests >30-day extension on DD |
| 126 | - Competitor raises at lower valuation (market signal) |
| 127 | |
| 128 | Trigger for Engineering Attrition: |
| 129 | - Glassdoor activity from engineering team |
| 130 | - 2+ referral interview requests from engineers |
| 131 | - Above-market offer counter-required in last 3 months |
| 132 | |
| 133 | |
| 134 | ### Step 6: Hedging Strategies |
| 135 | |
| 136 | For each scenario: actions to take **now** (before the scenario materializes) that reduce impact if it does. |
| 137 | |
| 138 | | Hedge | Cost | Impact | Owner | Deadline | |
| 139 | |-------|------|--------|-------|---------| |
| 140 | | Establish $500K credit line | $5K/year | Buys 3 months if churn hits | CFO | 60 days | |
| 141 | | 12-month retention bonus for 3 key engineers | $90K | Locks team through fundraise | CHRO | 30 days | |
| 142 | | Diversify to <20% revenue concentration per customer | Sales effort | Reduces single-customer risk | CRO | 2 quarters | |
| 143 | | Compress fundraise timeline, start parallel process | CEO time | Closes before runways merge | CEO | Immediate | |
| 144 | |
| 145 | |
| 146 | |
| 147 | ## Output Format |
| 148 | |
| 149 | Every war room session produces: |
| 150 | |
| 151 | |
| 152 | SCENARIO: [Name] |
| 153 | Variables: [A, B, C] |
| 154 | Most likely path: [which combination actually plays out, with probability] |
| 155 | |
| 156 | SEVERITY LEVELS |
| 157 | Base (A only): [runway/ARR impact] — recovery: [X actions] |
| 158 | Stress (A+B): [runway/ARR impact] — recovery: [X actions] |
| 159 | Severe (A+B+C): [runway/ARR impact] — existential risk: [yes/no] |
| 160 | |
| 161 | CASCADE MAP |
| 162 | [A → domain impact → B trigger → domain impact → end state] |
| 163 | |
| 164 | EARLY WARNING SIGNALS |
| 165 | - [Signal 1 → which scenario it indicates] |
| 166 | - [Signal 2 → which scenario it indicates] |
| 167 | - [Signal 3 → which scenario it indicates] |
| 168 | |
| 169 | HEDGES (take these actions now) |
| 170 | 1. [Action] — cost: $X — impact: [what it buys] — owner: [role] — deadline: [date] |
| 171 | 2. [Action] — cost: $X — impact: [what it buys] — owner: [role] — deadline: [date] |
| 172 | 3. [Action] — cost: $X — impact: [what it buys] — owner: [role] — deadline: [date] |
| 173 | |
| 174 | RECOMMENDED DECISION |
| 175 | [One paragraph. What to do, in what order, and why.] |
| 176 | |
| 177 | |
| 178 | |
| 179 | |
| 180 | ## Rules for Good War Room Sessions |
| 181 | |
| 182 | **Max 3 variables per scenario.** More than 3 is noise — you can't meaningfully prepare for 5-variable collapse. Model the 3 that actually worry you. |
| 183 | |
| 184 | **Quantify or estimate.** "Revenue drops" is not useful. "$420K ARR at risk over 60 days" is. Use ranges if uncertain. |
| 185 | |
| 186 | **Don't stop at first-order effects.** The damage is always in the cascade, not the initial hit. |
| 187 | |
| 188 | **Model recovery, not just impact.** Every scenario should have a "what we do" path. |
| 189 | |
| 190 | **Separate base case from sensitivity.** Don't conflate "what probably happens" with "what could happen." |
| 191 | |
| 192 | **Don't over-model.** 3-4 scenarios per planning cycle is the right number. More creates analysis paralysis. |
| 193 | |
| 194 | |
| 195 | |
| 196 | ## Common Scenarios by Stage |
| 197 | |
| 198 | **Seed:** |
| 199 | Co-founder leaves + product misses launch |
| 200 | Funding runs out + bridge terms unfavorable |
| 201 | |
| 202 | **Series A:** |
| 203 | Miss ARR target + fundraise delayed |
| 204 | Key customer churns + competitor raises |
| 205 | |
| 206 | **Series B:** |
| 207 | Market contraction + burn multiple spikes |
| 208 | Lead investor wants pivot + team resists |
| 209 | |
| 210 | ## Integration with C-Suite Roles |
| 211 | |
| 212 | | Scenario Type | Primary Roles | Cascade To | |
| 213 | |--------------|---------------|------------| |
| 214 | | Revenue miss | CRO, CFO | CMO (pipeline), COO (cuts), CHRO (layoffs) | |
| 215 | | Key person departure | CHRO, COO | CTO (if eng), CRO (if sales) | |
| 216 | | Fundraise failure | CFO, CEO | COO (runway extension), CHRO (hiring freeze) | |
| 217 | | Security breach | CISO, CTO | CEO (comms), CFO (cost), CRO (customer impact) | |
| 218 | | Market shift | CEO, CPO | CMO (repositioning), CRO (new segments) | |
| 219 | | Competitor move | CMO, CRO | CPO (roadmap response), CEO (strategy) | |
| 220 | |
| 221 | ## References |
| 222 | `references/scenario-planning.md` — Shell methodology, pre-mortem, Monte Carlo, cascade frameworks |
| 223 | `scripts/scenario_modeler.py` — CLI tool for structured scenario modeling |
| 224 |
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