Cross-functional what-if modeling for compound adversity scenarios. Models cascading multi-variable risks across all business functions simultaneously. Unlike single-assumption stress tests, this shows how one problem creates the next. Use when facing complex risk scenarios, strategic decisions with major downside, multi-variable threats, or when someone asks "what if X AND Y both happen?
Tier: POWERFUL Category: C-Level Advisory Tags: scenario planning, war room, risk modeling, cascade effects, contingency planning, pre-mortem, crisis simulation
The Scenario War Room models cascading what-if scenarios across all business functions. Not single-assumption stress tests -- compound adversity that shows how one problem creates the next, and where the cascade can be interrupted. Every scenario produces concrete hedges with costs, owners, and deadlines.
More than 3 variables creates analysis paralysis, not insight. Choose the 3 that actually keep leadership awake at night.
For each variable, specify:
| Field | Description | Example |
|---|---|---|
| What changes | Specific, quantified | "Top customer (28% of ARR) gives 60-day termination notice" |
| Probability | Your best estimate | 15% |
| Timeline | When it could hit | Within 90 days |
| Detection signal | How you would know it is happening | Sponsor goes dark, usage drops 25% MoM |
Variable Template:
Variable A: [Specific change]
Probability: [X]% | Timeline: [When]
Detection: [Early warning signal]
First-order impact: [Immediate consequence]
Variable B: [Specific change]
Probability: [X]% | Timeline: [When]
Detection: [Early warning signal]
First-order impact: [Immediate consequence]
Variable C: [Specific change]
Probability: [X]% | Timeline: [When]
Detection: [Early warning signal]
First-order impact: [Immediate consequence]
For each variable, assess impact across every business function:
| Domain | Key Questions | Typical Impact Areas |
|---|---|---|
| Finance (CFO) | Burn impact? Runway change? Bridge options? | Cash, runway, covenant triggers |
| Revenue (CRO) | ARR gap? Churn cascade? Pipeline affected? | NRR, expansion, new logo risk |
| Product (CPO) | Roadmap derailed? PMF at risk? Customer need shift? | Delivery timeline, feature priority |
| Engineering (CTO) | Velocity hit? Key person risk? Technical debt impact? | Capacity, architecture, hiring |
| People (CHRO) | Attrition cascade? Hiring freeze? Morale impact? | Retention, culture, bench strength |
| Operations (COO) | Capacity affected? Process breaks? OKR impact? | SLAs, efficiency, scale |
| Market (CMO) | CAC affected? Competitive exposure? Brand risk? | Pipeline generation, positioning |
| Legal/Compliance | Regulatory timeline risk? Contract exposure? | Obligations, deadlines, penalties |
This is the most valuable step. Map how Variable A triggers consequences that amplify Variable B.
Cascade Diagram:
TRIGGER: Customer churn ($560K ARR)
│
├──▶ CFO: Runway drops 14 → 8 months
│ │
│ └──▶ CHRO: Hiring freeze imposed
│ │
│ └──▶ CTO: 3 open engineering reqs frozen, roadmap slips 2 months
│ │
│ └──▶ CPO: Q4 feature launch delayed → 2 more customers at risk
│ │
│ └──▶ CRO: NRR drops → additional churn risk (DEATH SPIRAL ENTRY)
│
└──▶ CRO: Revenue concentration increases (next largest = 22%)
│
└──▶ Investors: Concentration risk flagged → Series A terms worsen
Name the cascades explicitly. Common cascade patterns:
| Cascade Pattern | Description | Interruption Point |
|---|---|---|
| Revenue-to-Runway Death Spiral | Customer churn → lower runway → hiring freeze → slower product → more churn | Emergency revenue diversification |
| Key Person Cascade | Star leaves → team morale drops → followers leave → velocity collapses | Retention bonuses before departure |
| Market Squeeze | Competitor raises → price war → margins compress → can't invest in product | Differentiation, not price matching |
| Trust Cascade | Incident → customer concern → churn → press → more churn | Swift, transparent communication |
| Fundraise-Burn Spiral | Miss target → raise delayed → bridge at bad terms → burn cuts → team loss | Parallel fundraise tracks |
Model three scenarios with increasing severity:
| Scenario | Variables Hit | Definition | Recovery Difficulty |
|---|---|---|---|
| Base | 1 of 3 | Single shock, others don't materialize | Manageable with prepared response |
| Stress | 2 of 3 | Compound shock, cascade begins | Requires significant pivot, board involvement |
| Severe | All 3 | Full cascade, existential territory | Requires emergency action, may need board intervention |
For each severity level, quantify:
BASE SCENARIO (Variable A only):
Runway impact: [X] months → [Y] months
ARR impact: -$[X] ([Y]% of total)
Headcount impact: [freeze / reduction / none]
Timeline to critical: [X] months
Recovery plan: [specific actions]
STRESS SCENARIO (Variables A + B):
Runway impact: [X] months → [Y] months
ARR impact: -$[X] ([Y]% of total)
Headcount impact: [specifics]
Timeline to critical: [X] months
Recovery plan: [specific actions]
SEVERE SCENARIO (All three):
Runway impact: [X] months → [Y] months
ARR impact: -$[X] ([Y]% of total)
Headcount impact: [specifics]
Timeline to critical: [X] months
Existential: [yes/no]
Emergency plan: [specific actions requiring board approval]
Define measurable signals that tell you a scenario is unfolding BEFORE it is confirmed. The value of this exercise is acting early, not reacting late.
Signal Design Criteria:
| Variable | Signal | Threshold | Response |
|---|---|---|---|
| Customer churn | Sponsor stops responding | > 3 weeks silence | Exec escalation, QBR request |
| Customer churn | Usage drops | > 25% MoM decline | CS outreach, value review |
| Fundraise delay | Term sheets | < 3 after 60 days in process | Parallel bridge conversations |
| Fundraise delay | Investor requests | > 30 day DD extension | Reduce burn, extend runway |
| Key person departure | Market compensation | Counter-offer required in last 90 days | Retention package, succession plan |
| Key person departure | External engagement | Engineer presenting at conferences for competitors | Direct conversation, role expansion |
For each scenario: actions to take NOW (before the scenario materializes) that reduce impact if it does. Hedges have costs -- the goal is cheap insurance, not paranoia.
Hedge Evaluation Criteria:
| Criterion | Question |
|---|---|
| Cost | What does this hedge cost to implement? |
| Reversibility | Can we undo it if the scenario doesn't happen? |
| Lead time | How long to implement? (Must be shorter than detection-to-impact window) |
| Coverage | Which scenarios does this hedge protect against? |
| Side effects | Does this hedge cause other problems? |
Hedge Table Template:
| Hedge | Cost | Protects Against | Owner | Deadline | Status |
|---|---|---|---|---|---|
| Establish $500K credit line | $5K/year | Runway shortfall (Base + Stress) | CFO | 60 days | Not started |
| 12-month retention bonus for 3 key engineers | $90K | Key person departure (all scenarios) | CHRO | 30 days | In progress |
| Diversify to <20% revenue per customer | Sales effort (6 months) | Single-customer dependency | CRO | 2 quarters | Planning |
| Start parallel fundraise track | CEO time (10 hrs/week) | Fundraise delay (Stress + Severe) | CEO | Immediate | Not started |
| Pre-negotiate bridge terms with existing investors | 2 board conversations | Runway crisis (Severe) | CFO + CEO | 45 days | Not started |
| Document architecture for bus factor reduction | 2 engineering weeks | Key person departure | CTO | 30 days | Not started |
Every war room session produces this structured output:
SCENARIO: [Name]
DATE: [Date of analysis]
PARTICIPANTS: [Who was involved]
VARIABLES:
A: [Description] — Probability: [X]%, Timeline: [When]
B: [Description] — Probability: [X]%, Timeline: [When]
C: [Description] — Probability: [X]%, Timeline: [When]
MOST LIKELY PATH: [Which combination actually plays out, with reasoning]
SEVERITY LEVELS:
Base (A only): Runway [X]→[Y]mo, ARR impact -$[X]
Recovery: [2-3 specific actions]
Stress (A+B): Runway [X]→[Y]mo, ARR impact -$[X]
Recovery: [3-4 specific actions]
Severe (A+B+C): Runway [X]→[Y]mo, ARR impact -$[X]
Existential: [yes/no]
Emergency: [actions requiring board approval]
CASCADE MAP:
[A] → [domain impact] → [triggers B amplification] → [domain impact] → [end state]
Interruption points: [where cascade can be broken]
EARLY WARNING SIGNALS:
1. [Signal] → indicates [scenario], threshold: [specific]
2. [Signal] → indicates [scenario], threshold: [specific]
3. [Signal] → indicates [scenario], threshold: [specific]
HEDGES (implement now):
1. [Action] — cost: $[X] — protects: [scenarios] — owner: [role] — deadline: [date]
2. [Action] — cost: $[X] — protects: [scenarios] — owner: [role] — deadline: [date]
3. [Action] — cost: $[X] — protects: [scenarios] — owner: [role] — deadline: [date]
RECOMMENDED DECISION:
[One paragraph: what to do, in what order, and why]
REVIEW DATE: [When to re-run this analysis — typically 90 days or after any variable shifts]
| Skill | Use When |
|---|---|
| ceo-advisor | Strategic decisions that scenarios inform |
| cfo-advisor | Financial modeling for scenario impacts |
| coo-advisor | Operational contingency planning |
| internal-narrative | Communicating scenario outcomes to stakeholders |
| cs-onboard | Company context that feeds scenario variables |
| Problem | Likely Cause | Resolution |
|---|---|---|
| Scenarios feel too abstract to act on | Variables not specific or quantified enough | Require dollar amounts, percentages, and timelines for every variable; "revenue drops" is not actionable, "$420K ARR at risk over 60 days" is |
| Team generates only obvious, low-probability scenarios | Conformity bias; not applying Shell scenario planning method of challenging mental models | Use inversion technique: "What would guarantee our failure?"; bring in external perspective; reference industry-specific historical precedents |
| Cascade mapping stops at first-order effects | Facilitator not pushing past immediate consequences | Require minimum 3 levels of cascade for each variable; use "and then what?" prompting for each domain impact |
| Hedges identified but never implemented | No ownership, deadline, or cost attached | Every hedge must have: cost estimate, owner name, deadline, and status tracking; review in weekly leadership meeting |
| War room sessions take too long (> 4 hours) | Too many variables or trying to model every scenario | Enforce maximum 3 variables and 3-4 scenarios per session; use severity matrix to focus on highest-impact combinations |
| Early warning signals not being monitored | Signals assigned but not integrated into existing reporting | Add signals to existing dashboards and weekly scorecards; assign specific person to monitor each signal |
| Participants reluctant to name worst-case scenarios | Fear of being seen as negative or alarmist | Establish ground rules explicitly; cite Shell's experience: "the value is in surfacing what others won't say"; reward naming hard truths |
| Skill | Integration | Data Flow |
|---|---|---|
ceo-advisor | Strategic decisions informed by scenario analysis | War room scenarios → CEO decision inputs |
cfo-advisor | Financial modeling for scenario impacts and hedge costs | War room financial impacts → CFO stress test models |
coo-advisor | Operational contingency planning and cascade interruption | War room cascade map → COO contingency plans |
executive-mentor | Pre-mortem failure modes feed into scenario variables | Mentor failure modes → War room variables |
internal-narrative | Crisis scenarios require pre-built communication plans | War room crisis scenarios → Narrative crisis templates |
org-health-diagnostic | Health dimension scores surface scenario variables | Health red flags → War room variable candidates |
strategic-alignment | Scenario outcomes may require strategic realignment | War room outcomes → Alignment reassessment |
| Tool | Purpose | Usage |
|---|---|---|
scripts/scenario_builder.py | Build structured scenarios with variables, probabilities, detection signals, and severity levels | python scripts/scenario_builder.py --name "Customer Concentration Risk" --variable "Top customer churns" --probability 20 --impact 500000 --timeline 90 --json |
scripts/impact_matrix_calculator.py | Calculate compound impact across multiple variables with severity matrix and cascade risk scoring | python scripts/impact_matrix_calculator.py --variables "churn:500000:0.2" "fundraise_delay:0:0.3" "key_departure:0:0.15" --arr 2000000 --runway-months 14 --json |
scripts/decision_tree_analyzer.py | Build and evaluate decision trees with expected value calculations for strategic options | python scripts/decision_tree_analyzer.py --decision "Enter Japan market" --option "Direct:0.6:2000000:-500000" --option "Partnership:0.75:1000000:-200000" --option "Wait:1.0:0:0" --json |