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skills/estimation-fermi/resources/template.md

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+# Fermi Estimation Templates
+
+Quick-start templates for decomposition, component estimation, bounding, and sanity-checking.
+
+## Workflow
+
+```
+Fermi Estimation Progress:
+- [ ] Step 1: Clarify the question and define metric
+- [ ] Step 2: Decompose into estimable components
+- [ ] Step 3: Estimate components using anchors
+- [ ] Step 4: Bound with upper/lower limits
+- [ ] Step 5: Calculate and sanity-check
+- [ ] Step 6: Triangulate with alternate path
+```
+
+**Step 1: Clarify the question and define metric**
+
+Use [Clarification Template](#clarification-template) to restate question precisely with units, scope, timeframe, and decision context.
+
+**Step 2: Decompose into estimable components**
+
+Select decomposition strategy using [Decomposition Strategies](#decomposition-strategies) and build estimation tree.
+
+**Step 3: Estimate components using anchors**
+
+Ground each component in known quantities using [Component Estimation Template](#component-estimation-template).
+
+**Step 4: Bound with upper/lower limits**
+
+Calculate optimistic and pessimistic bounds using [Bounding Template](#bounding-template).
+
+**Step 5: Calculate and sanity-check**
+
+Compute central estimate and validate using [Sanity-Check Template](#sanity-check-template).
+
+**Step 6: Triangulate with alternate path**
+
+Re-estimate via different decomposition using [Triangulation Template](#triangulation-template) to validate.
+
+---
+
+## Clarification Template
+
+**Original Question**: [As stated]
+
+**Clarified Question**:
+- **What exactly are we estimating?** (metric name, definition)
+- **Units?** (dollars, people, tons, requests/sec, etc.)
+- **Geographic scope?** (US, global, city, region)
+- **Time scope?** (annual, daily, lifetime, point-in-time)
+- **Exclusions?** (what are we NOT counting?)
+
+**Decision Context**:
+- **What decision depends on this estimate?**
+- **What precision is needed?** (order of magnitude sufficient? need ±2x? ±10%?)
+- **How will estimate be used?** (go/no-go decision, budget planning, prioritization)
+- **What threshold matters?** (if >X we do Y, if <Z we don't)
+
+**Success Criteria**:
+- [ ] Question is unambiguous (two people would estimate same thing)
+- [ ] Units are specified
+- [ ] Scope is bounded (not infinite)
+- [ ] Decision context is clear
+
+---
+
+## Decomposition Strategies
+
+Choose strategy based on question structure and available knowledge.
+
+### Top-Down Filtering
+
+**When to use**: Estimating subset of total population (market sizing, target audience)
+
+**Structure**: Start with total, apply filters to narrow down
+
+**Template**:
+```
+Total population
+× Filter 1 (% that have characteristic A)
+× Filter 2 (% that have characteristic B | A)
+× Filter 3 (% that have characteristic C | A,B)
+= Target population
+```
+
+**Example - TAM estimation**:
+```
+US population (330M)
+× Adults 18-65 (65% = 215M)
+× Urban/suburban (80% = 172M)
+× Smartphone users (90% = 155M)
+× Willing to pay for app (5% = 7.75M)
+× Price point ($50/year)
+= TAM: ~$390M/year
+```
+
+### Bottom-Up Scaling
+
+**When to use**: Have data on units, want to estimate total (revenue, capacity, production)
+
+**Structure**: Start with single unit, multiply by count
+
+**Template**:
+```
+Output per unit
+× Number of units
+× Utilization rate (% of theoretical capacity actually used)
+= Total output
+```
+
+**Example - Server capacity**:
+```
+1 server handles 10k requests/sec
+× 100 servers in cluster
+× 70% utilization (peak headroom, maintenance, failures)
+= Cluster capacity: 700k requests/sec
+```
+
+### Rate × Time
+
+**When to use**: Estimating accumulation over time (customers served, miles driven, content consumed)
+
+**Structure**: Flow rate × Duration
+
+**Template**:
+```
+Rate (per time unit)
+× Time duration (in same units)
+= Total quantity
+```
+
+**Example - Annual customers**:
+```
+50 customers/day
+× 250 business days/year
+= 12,500 customers/year
+```
+
+### Density × Area/Volume
+
+**When to use**: Spatial estimation (people in stadium, cars on highway, storage capacity)
+
+**Structure**: Concentration × Space
+
+**Template**:
+```
+Density (per unit area/volume)
+× Total area/volume
+= Total quantity
+```
+
+**Example - Stadium capacity**:
+```
+4 people/sq meter (seated)
+× 10,000 sq meters seating area
+= 40,000 capacity
+```
+
+### Analogous Scaling
+
+**When to use**: Have data on similar system, adjusting for size difference
+
+**Structure**: Known comparable × Scaling factor
+
+**Template**:
+```
+Comparable system value
+× (Our scale / Their scale)^exponent
+= Our estimate
+
+Exponent = 1 for linear scaling, <1 for economies of scale, >1 for diseconomies
+```
+
+**Example - Competitor revenue**:
+```
+Competitor A revenue: $100M with 500k users
+Our users: 50k
+Estimate: $100M × (50k/500k) = $10M
+(assumes linear revenue per user)
+```
+
+---
+
+## Component Estimation Template
+
+For each component in decomposition:
+
+**Component**: [Name of quantity being estimated]
+
+**Anchor Strategy** (how will we estimate this?):
+- [ ] Known data (cite source):
+- [ ] Personal experience/intuition (describe basis):
+- [ ] Derived from other estimates (show calculation):
+- [ ] Analogous comparison (similar known quantity):
+
+**Estimate**: [Value with units]
+
+**Confidence**: (How certain are we?)
+- [ ] High (have data or strong knowledge)
+- [ ] Medium (reasonable inference)
+- [ ] Low (educated guess, wide range)
+
+**Sensitivity**: (How much does final answer depend on this?)
+- [ ] High (10% change here → >5% change in final)
+- [ ] Medium (10% change here → 1-5% change in final)
+- [ ] Low (final answer insensitive to this component)
+
+**Assumption stated**: [Explicit statement of what we're assuming]
+
+---
+
+## Bounding Template
+
+### Optimistic Bound (Upper Limit)
+
+**Scenario**: [What favorable conditions would maximize the estimate?]
+
+**Assumptions**:
+- Component 1: [Optimistic value]
+- Component 2: [Optimistic value]
+- ...
+
+**Calculation**: [Show work]
+
+**Result**: [Upper bound with units]
+
+### Pessimistic Bound (Lower Limit)
+
+**Scenario**: [What unfavorable conditions would minimize the estimate?]
+
+**Assumptions**:
+- Component 1: [Pessimistic value]
+- Component 2: [Pessimistic value]
+- ...
+
+**Calculation**: [Show work]
+
+**Result**: [Lower bound with units]
+
+### Range Assessment
+
+**Bounds**: [Lower] to [Upper]
+
+**Ratio**: Upper/Lower = [X]× range
+
+**Decision Sensitivity**:
+- [ ] Decision same across entire range → Estimate good enough
+- [ ] Decision changes within range → Need more precision or different approach
+- [ ] Range too wide (>10× span) → Decomposition may be flawed, revisit assumptions
+
+---
+
+## Sanity-Check Template
+
+### Dimensional Analysis
+
+**Units Check**: Do units cancel correctly in calculation?
+- Calculation: [Show units through formula]
+- Final units: [Should match expected units]
+- [ ] Units are correct
+
+### Reality Checks
+
+**Check 1 - Order of magnitude comparison**:
+- Our estimate: [X]
+- Known comparable: [Y]
+- Ratio: [X/Y]
+- [ ] Within factor of 10? (If not, investigate why)
+
+**Check 2 - Extreme case testing**:
+- What if assumption taken to extreme? (e.g., 100% penetration, everyone participates)
+- Result: [Calculate]
+- [ ] Does it violate physical/economic constraints? (population limits, GDP constraints, physics)
+
+**Check 3 - Internal consistency**:
+- Do derived metrics make sense? (profit margins, growth rates, per-capita figures)
+- Derived metric: [Calculate, e.g., revenue per employee, cost per user]
+- [ ] Is it in reasonable range for industry/domain?
+
+**Check 4 - Personal intuition**:
+- Does this "feel right" given your experience?
+- [ ] Passes gut check
+- [ ] Feels too high (revise assumptions)
+- [ ] Feels too low (revise assumptions)
+
+### Common Failure Modes to Check
+
+- [ ] Did I double-count anything?
+- [ ] Did I mix units (per day vs per year, millions vs billions)?
+- [ ] Am I extrapolating linearly when should be exponential (or vice versa)?
+- [ ] Did I account for utilization/efficiency factors (not everything runs at 100%)?
+- [ ] Did I consider survivor bias (basing estimate on successful cases only)?
+
+---
+
+## Triangulation Template
+
+### Primary Estimate (from main decomposition)
+
+**Method**: [Top-down, bottom-up, etc.]
+
+**Decomposition**: [Brief formula or tree]
+
+**Result**: [Value with units]
+
+### Alternate Estimate (different approach)
+
+**Method**: [Different strategy than primary]
+
+**Decomposition**: [Brief formula or tree]
+
+**Result**: [Value with units]
+
+### Comparison
+
+**Primary**: [X]
+**Alternate**: [Y]
+**Ratio**: [X/Y] = [Z]×
+
+**Assessment**:
+- [ ] Within factor of 3 (good agreement, increase confidence)
+- [ ] Factor of 3-10 (moderate agreement, average or investigate difference)
+- [ ] >10× difference (investigate: one decomposition is likely flawed)
+
+**Reconciliation** (if estimates differ):
+- Why do they differ? (which assumptions differ?)
+- Which approach is more reliable?
+- Final estimate: [Choice or average]
+
+---
+
+## Complete Estimation Template
+
+Structure for full documentation:
+
+1. **Clarification**: Original question, clarified with units/scope, decision context
+2. **Decomposition**: Strategy (top-down/bottom-up/etc), formula, estimation tree
+3. **Component Estimates**: For each component - estimate, anchor, assumption, confidence
+4. **Calculation**: Formula with numbers, central estimate (1-2 sig figs)
+5. **Bounds**: Optimistic/pessimistic scenarios, range assessment
+6. **Sanity Checks**: Units, order of magnitude comparison, extreme cases, consistency, gut check
+7. **Triangulation**: Alternate approach, comparison (within factor of 3?), reconciliation
+8. **Final Estimate**: Point estimate, range, confidence, key assumptions, sensitivity, recommendation
+9. **Next Steps**: Data collection, assumption testing, detailed modeling if precision needed