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Zhongwei Li
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# Chain Estimation → Decision → Storytelling Template
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## Workflow
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Copy this checklist and track your progress:
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```
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Analysis Progress:
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- [ ] Step 1: Gather inputs and define decision scope
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- [ ] Step 2: Estimate costs, benefits, and probabilities
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- [ ] Step 3: Calculate expected value and compare alternatives
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- [ ] Step 4: Structure narrative with clear recommendation
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- [ ] Step 5: Validate completeness with quality checklist
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```
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**Step 1: Gather inputs and define decision scope**
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Clarify what decision needs to be made, identify 2-5 alternatives to compare, list key uncertainties (costs, benefits, probabilities), determine audience (executives, technical team, finance), and note constraints (budget, timeline, requirements). Use [Quick Template](#quick-template) structure below.
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**Step 2: Estimate costs, benefits, and probabilities**
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For each alternative, quantify all relevant costs (development, operation, opportunity cost), estimate benefits (revenue, savings, productivity gains), assign probabilities to scenarios (best/base/worst case), and use ranges rather than point estimates. See [Estimation Guidelines](#estimation-guidelines) for techniques.
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**Step 3: Calculate expected value and compare alternatives**
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Compute probability-weighted outcomes for each alternative, compare using appropriate decision criteria (NPV, IRR, payback, utility), identify which option has best risk-adjusted return, and test sensitivity to key assumptions. See [Decision Analysis](#decision-analysis) section.
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**Step 4: Structure narrative with clear recommendation**
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Follow storytelling framework: problem statement, alternatives considered, analysis summary, clear recommendation with reasoning, and next steps. Tailor level of detail to audience. See [Narrative Structure](#narrative-structure) for guidance.
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**Step 5: Validate completeness with quality checklist**
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Use [Quality Checklist](#quality-checklist) to verify: all alternatives considered, estimates are justified, probabilities are reasonable, expected value is calculated correctly, sensitivity analysis performed, narrative is clear and persuasive, assumptions stated explicitly.
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## Quick Template
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Copy this structure to create your analysis:
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```markdown
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# Decision: {Decision Question}
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## 1. Decision Context
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**What we're deciding:** {Clear statement of the choice}
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**Why this matters:** {Business impact, urgency, strategic importance}
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**Alternatives:**
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1. {Option A}
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2. {Option B}
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3. {Option C}
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**Key uncertainties:**
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- {Variable 1}: {Range or distribution}
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- {Variable 2}: {Range or distribution}
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- {Variable 3}: {Range or distribution}
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**Constraints:**
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- Budget: {Available resources}
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- Timeline: {Decision deadline, implementation timeline}
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- Requirements: {Must-haves, non-negotiables}
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**Audience:** {Who needs to approve this decision?}
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---
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## 2. Estimation
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### Alternative 1: {Name}
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**Costs:**
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- Initial investment: ${Low}k - ${High}k (most likely: ${Base}k)
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- Annual operational: ${Low}k - ${High}k per year
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- Opportunity cost: {What we give up}
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**Benefits:**
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- Revenue impact: +${Low}k - ${High}k (most likely: ${Base}k)
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- Cost savings: ${Low}k - ${High}k per year
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- Strategic value: {Qualitative benefits}
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**Probabilities:**
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- Best case (30%): {Scenario description}
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- Base case (50%): {Scenario description}
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- Worst case (20%): {Scenario description}
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**Key assumptions:**
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- {Assumption 1}
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- {Assumption 2}
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- {Assumption 3}
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### Alternative 2: {Name}
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{Same structure}
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### Alternative 3: {Name}
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{Same structure}
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---
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## 3. Decision Analysis
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### Expected Value Calculation
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**Alternative 1: {Name}**
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- Best case (30%): ${Amount} × 0.30 = ${Weighted}
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- Base case (50%): ${Amount} × 0.50 = ${Weighted}
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- Worst case (20%): ${Amount} × 0.20 = ${Weighted}
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- **Expected value: ${Total}**
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**Alternative 2: {Name}**
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{Same calculation}
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**Expected value: ${Total}**
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**Alternative 3: {Name}**
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{Same calculation}
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**Expected value: ${Total}**
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### Comparison
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| Alternative | Expected Value | Risk Profile | Time to Value | Strategic Fit |
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|-------------|----------------|--------------|---------------|---------------|
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| {Alt 1} | ${EV} | {High/Med/Low} | {Timeline} | {Score/10} |
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| {Alt 2} | ${EV} | {High/Med/Low} | {Timeline} | {Score/10} |
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| {Alt 3} | ${EV} | {High/Med/Low} | {Timeline} | {Score/10} |
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### Sensitivity Analysis
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**What if {key variable} changes?**
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- If {variable} is 20% higher: {Impact on decision}
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- If {variable} is 20% lower: {Impact on decision}
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**Most sensitive to:**
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- {Variable 1}: {Explanation of impact}
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- {Variable 2}: {Explanation of impact}
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**Robustness check:**
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- Conclusion holds if {conditions}
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- Would change if {conditions}
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---
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## 4. Recommendation
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**Recommended option: {Alternative X}**
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**Reasoning:**
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{1-2 paragraphs explaining why this is the best choice given the analysis}
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**Key factors:**
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- {Factor 1}: {Why it matters}
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- {Factor 2}: {Why it matters}
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- {Factor 3}: {Why it matters}
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**Tradeoffs accepted:**
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- We're accepting {downside} in exchange for {upside}
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- We're prioritizing {value 1} over {value 2}
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**Risks and mitigations:**
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- **Risk**: {What could go wrong}
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- **Mitigation**: {How we'll address it}
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- **Risk**: {What could go wrong}
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- **Mitigation**: {How we'll address it}
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---
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## 5. Next Steps
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**If approved:**
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1. {Immediate action 1} - {Owner} by {Date}
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2. {Immediate action 2} - {Owner} by {Date}
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3. {Immediate action 3} - {Owner} by {Date}
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**Success metrics:**
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- {Metric 1}: Target {value} by {date}
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- {Metric 2}: Target {value} by {date}
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- {Metric 3}: Target {value} by {date}
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**Decision review:**
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- Revisit this decision in {timeframe} to validate assumptions
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- Key indicators to monitor: {metrics to track}
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**What would change our mind:**
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- If {condition}, we should reconsider
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- If {condition}, we should accelerate
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- If {condition}, we should pause
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```
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---
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## Estimation Guidelines
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### Cost Estimation
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**Categories to consider:**
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- **One-time costs**: Development, implementation, migration, training
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- **Recurring costs**: Subscription fees, maintenance, support, infrastructure
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- **Hidden costs**: Opportunity cost, technical debt, switching costs
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- **Risk costs**: Probability-weighted downside scenarios
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**Estimation techniques:**
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- **Analogous**: Similar past projects (adjust for differences)
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- **Parametric**: Cost per unit × quantity (e.g., $150k per engineer × 2 engineers)
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- **Bottom-up**: Estimate components and sum
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- **Three-point**: Best case, most likely, worst case → calculate expected value
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**Expressing uncertainty:**
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- Use ranges: $200k-$400k (not $300k)
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- Assign probabilities: 60% likely $300k, 20% $200k, 20% $400k
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- Show confidence: "High confidence" vs "Rough estimate"
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### Benefit Estimation
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**Categories to consider:**
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- **Revenue impact**: New revenue, increased conversion, higher retention
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- **Cost savings**: Reduced operational costs, avoided hiring, infrastructure savings
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- **Productivity gains**: Time saved × value of time
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- **Risk reduction**: Probability of bad outcome × cost of bad outcome
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- **Strategic value**: Market positioning, competitive advantage, optionality
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**Quantification approaches:**
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- **Direct measurement**: Historical data, benchmarks, experiments
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- **Proxy metrics**: Leading indicators that correlate with value
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- **Scenario modeling**: Best/base/worst case with probabilities
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- **Comparable analysis**: Similar initiatives at comparable companies
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### Probability Assignment
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**How to assign probabilities:**
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- **Base rates**: Start with historical frequency (e.g., 70% of projects finish on time)
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- **Adjustments**: Modify for specific circumstances (this project is simpler/more complex)
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- **Expert judgment**: Multiple estimates, average or calibrated
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- **Reference class forecasting**: Look at similar situations
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**Common probability pitfalls:**
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- **Overconfidence**: Ranges too narrow, probabilities too extreme (5% or 95%)
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- **Anchoring**: First number becomes reference even if wrong
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- **Optimism bias**: Best case feels more likely than it is
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- **Planning fallacy**: Underestimating time and cost
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**Calibration check:**
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- If you say 70% confident, are you right 70% of the time?
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- Test with past predictions if available
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- Use wider ranges for higher uncertainty
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---
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## Decision Analysis
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### Expected Value Calculation
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**Formula:**
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```
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Expected Value = Σ (Outcome × Probability)
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```
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**Example:**
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- Best case: $500k × 30% = $150k
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- Base case: $300k × 50% = $150k
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- Worst case: $100k × 20% = $20k
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- Expected value = $150k + $150k + $20k = $320k
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**Multi-year NPV:**
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```
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NPV = Σ (Cash Flow_t / (1 + discount_rate)^t)
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```
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**When to use:**
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- **Expected value**: When outcomes are roughly linear with value (money, time)
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- **Decision trees**: When sequence of choices matters
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- **Monte Carlo**: When multiple uncertainties interact
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- **Scoring/weighting**: When mix of quantitative and qualitative factors
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### Comparison Methods
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**1. Expected Value Ranking**
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- Calculate EV for each alternative
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- Rank by highest expected value
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- **Best for**: Decisions with quantifiable outcomes
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**2. NPV Comparison**
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- Discount future cash flows to present value
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- Compare NPV across alternatives
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- **Best for**: Multi-year investments
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**3. Payback Period**
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- Time to recover initial investment
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- Consider in addition to NPV (not instead of)
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- **Best for**: When liquidity or fast ROI matters
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**4. Weighted Scoring**
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- Score each alternative on multiple criteria (1-10)
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- Multiply by importance weight
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- Sum weighted scores
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- **Best for**: Mix of quantitative and qualitative factors
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### Sensitivity Analysis
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**One-way sensitivity:**
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- Vary one input at a time (e.g., cost ±20%)
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- Check if conclusion changes
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- Identify which inputs matter most
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**Tornado diagram:**
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- Show impact of each variable on outcome
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- Order by magnitude of impact
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- Focus on top 2-3 drivers
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**Scenario analysis:**
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- Define coherent scenarios (pessimistic, base, optimistic)
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- Calculate outcome for each complete scenario
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- Assign probabilities to scenarios
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**Break-even analysis:**
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- At what value of {key variable} does decision change?
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- Provides threshold for monitoring
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---
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## Narrative Structure
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### Executive Summary (for executives)
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**Format:**
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1. **The decision** (1 sentence): What we're choosing between
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2. **The recommendation** (1 sentence): What we should do
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3. **The reasoning** (2-3 bullets): Key factors driving recommendation
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4. **The ask** (1 sentence): What approval or resources needed
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5. **The timeline** (1 sentence): When this happens
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**Length:** 4-6 sentences, fits in one paragraph
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**Example:**
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> "We evaluated building custom analytics vs. buying a SaaS tool. Recommendation: Buy the SaaS solution. Key factors: (1) $130k lower expected cost due to build risk, (2) 6 months faster time-to-value, (3) proven reliability vs. custom development uncertainty. Requesting $20k implementation budget and $120k annual subscription approval. Implementation begins next month with value delivery in 8 weeks."
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### Detailed Analysis (for stakeholders)
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**Structure:**
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1. **Problem statement**: Why this decision matters (1 paragraph)
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2. **Alternatives considered**: Show you did the work (bullets)
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3. **Analysis approach**: Methodology and assumptions (1 paragraph)
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4. **Key findings**: Numbers, comparison, sensitivity (1-2 paragraphs)
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5. **Recommendation**: Clear choice with reasoning (1-2 paragraphs)
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6. **Risks and mitigations**: What could go wrong (bullets)
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7. **Next steps**: Implementation plan (bullets)
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**Length:** 1-2 pages
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**Tone:** Professional, balanced, transparent about tradeoffs
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### Technical Deep-Dive (for technical teams)
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**Additional detail:**
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- Estimation methodology and data sources
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- Sensitivity analysis details
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- Technical assumptions and constraints
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- Implementation considerations
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- Alternative approaches considered and why rejected
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**Length:** 2-4 pages
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**Tone:** Analytical, rigorous, shows technical depth
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---
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## Quality Checklist
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Before finalizing, verify:
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**Estimation quality:**
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- [ ] All relevant costs included (one-time, recurring, opportunity, risk)
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- [ ] All relevant benefits quantified or described
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- [ ] Uncertainty expressed with ranges or probabilities
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- [ ] Assumptions stated explicitly with justification
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- [ ] Sources cited for estimates where applicable
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**Decision analysis quality:**
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- [ ] Expected value calculated correctly (probability × outcome)
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- [ ] All alternatives compared fairly
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- [ ] Sensitivity analysis performed on key variables
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- [ ] Robustness tested (does conclusion hold across reasonable ranges?)
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- [ ] Dominant option identified with clear rationale
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**Narrative quality:**
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- [ ] Clear recommendation stated upfront
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- [ ] Problem statement explains why decision matters
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- [ ] Alternatives shown (proves due diligence)
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- [ ] Analysis summary appropriate for audience
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- [ ] Tradeoffs acknowledged honestly
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- [ ] Risks and mitigations addressed
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- [ ] Next steps are actionable
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**Communication quality:**
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- [ ] Tailored to audience (exec vs technical vs finance)
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- [ ] Jargon explained or avoided
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- [ ] Key numbers highlighted
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- [ ] Visual aids used where helpful (tables, charts)
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- [ ] Length appropriate (not too long or too short)
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**Integrity checks:**
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- [ ] No cherry-picking of favorable data
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- [ ] Downside scenarios included, not just upside
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- [ ] Probabilities are calibrated (not overconfident)
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- [ ] "What would change my mind" conditions stated
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- [ ] Limitations and uncertainties acknowledged
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---
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## Common Decision Types
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### Build vs Buy
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- **Estimate**: Dev cost, maintenance, SaaS fees, implementation
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- **Decision**: 3-5 year TCO with risk adjustment
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- **Story**: Control vs. cost, speed vs. customization
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### Market Entry
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- **Estimate**: TAM/SAM/SOM, CAC, LTV, time to profitability
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- **Decision**: NPV with market uncertainty scenarios
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- **Story**: Growth opportunity vs. execution risk
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### Hiring
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- **Estimate**: Comp, recruiting, ramp time, productivity impact
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- **Decision**: Cost per output vs. alternatives
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- **Story**: Capacity constraints vs. efficiency gains
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### Technology Migration
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- **Estimate**: Migration cost, operational savings, risk reduction
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- **Decision**: Multi-year TCO plus risk-adjusted benefits
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- **Story**: Short-term pain for long-term gain
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### Resource Allocation
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- **Estimate**: Cost per initiative, expected impact
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- **Decision**: Portfolio optimization or impact/effort ranking
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- **Story**: Given constraints, maximize expected value
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