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:

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:

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.

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

References

• references/scenario-planning.md — Shell methodology, pre-mortem, Monte Carlo, cascade frameworks
• scripts/scenario_modeler.py — CLI tool for structured scenario modeling