Simulating Strategic Scenarios
Given a decision or plan, produce three outputs:
- Scenario Matrix — 3-5 plausible futures (best case, base case, worst case, wildcard)
- Risk Forecast — likelihood × impact for key risks per scenario
- Strategic Insight — actionable recommendations that hold up across scenarios
Example trigger: "We're planning to expand into 3 new cities next year — simulate this."
Progress:
- Step 1: Clarify the decision/plan and its time horizon
- Step 2: Identify key uncertainty drivers (market, competitor, regulatory, operational, financial)
- Step 3: Build 3-5 scenarios by combining driver states
- Step 4: Score each scenario's risks (likelihood 1-5, impact 1-5)
- Step 5: Stress-test the plan against each scenario
- Step 6: Extract strategic insights that are robust across scenarios
- Step 7: Output Scenario Matrix, Risk Forecast, Strategic Insight
Step details
1. Clarify scope — Confirm: what decision, over what timeframe, at what level (national, regional, unit)?
2. Identify drivers — Pick 2-3 highest-uncertainty, highest-impact variables (e.g., demand growth, competitor entry, regulation, funding availability). Avoid drivers that are low-impact or near-certain.
3. Build scenarios — Name each scenario memorably (e.g., "Rapid Growth", "Stagnant Market", "Regulatory Shock", "Wildcard: New Entrant"). Each must be internally consistent — describe the world, not just a label.
4. Score risks — For each scenario, list top 3-5 risks with Likelihood (1-5) and Impact (1-5), compute Risk Score = L×I.
5. Stress-test — Ask: does the current plan survive in each scenario? Where does it break?
6. Extract insights — Look for actions that appear beneficial in ≥3 of the scenarios (robust moves) vs. actions that only work in one (fragile bets). Flag early-warning indicators to watch.
7. Output in the format below.
| Scenario | Key Drivers | Description | Probability (qualitative) |
|---|---|---|---|
| Best Case | ... | ... | Low/Med/High |
| Base Case | ... | ... | ... |
| Worst Case | ... | ... | ... |
| Wildcard | ... | ... | ... |
| Scenario | Risk | Likelihood (1-5) | Impact (1-5) | Score | Notes |
|---|---|---|---|---|---|
| Worst Case | ... | 4 | 5 | 20 | ... |
- Robust moves (work across most scenarios): ...
- Fragile bets (only work in one scenario, avoid over-committing): ...
- Early-warning indicators (signals to monitor): ...
- Recommended action: ...
Example 1: Input: "MusGo is considering launching a subscription tier in Q3. Simulate strategic outcomes."
Output:
| Scenario | Key Drivers | Description | Probability |
|---|---|---|---|
| Best Case | High adoption, low churn | Users convert fast, subscription becomes 30% of revenue | Medium |
| Base Case | Moderate adoption | Slow but steady growth, 10% conversion in 6 months | High |
| Worst Case | Price resistance, competitor discount war | Adoption stalls below 3%, margin pressure | Medium |
| Wildcard | Competitor launches free tier first | Market expectation shifts, our paid tier looks overpriced | Low |
| Scenario | Risk | Likelihood | Impact | Score | Notes |
|---|---|---|---|---|---|
| Worst Case | Churn from price sensitivity | 4 | 4 | 16 | Need tiered pricing fallback |
| Wildcard | Competitor pre-empts market | 2 | 5 | 10 | Monitor competitor roadmap monthly |
| Base Case | Slow feature adoption | 3 | 3 | 9 | Needs onboarding nudges |
- Robust moves: Launch with a free-trial hook (works in Best, Base, Worst)
- Fragile bets: Premium-only pricing with no tier (breaks in Worst/Wildcard)
- Early-warning indicators: Weekly conversion rate below 4% by week 3 signals Worst Case trajectory
- Recommended action: Launch with 2 tiers + 14-day trial; set a week-3 checkpoint to trigger pricing pivot if conversion < 4%
- Keep scenarios to 3-5 — more becomes unmanageable, fewer misses key uncertainty
- Make scenarios plausible, not just optimistic/pessimistic mirrors of each other
- Always include a wildcard/low-probability-high-impact scenario
- Tie every risk score back to a concrete mitigating action
- Prioritize insights that are robust across multiple scenarios over single-scenario optimizations
- Don't build scenarios that only vary one variable (e.g., "10% growth" vs "20% growth") — vary structurally different drivers
- Don't skip the wildcard scenario — it's often where the biggest strategic blind spots hide
- Don't leave risk scores unactioned — every high score needs a mitigation or monitoring plan
- Don't present scenarios without probabilities/qualitative likelihood — undifferentiated scenarios are less useful for prioritization