| name | fermi-roi |
| description | Run a Fermi ROI analysis to prioritize initiatives by estimated return on investment. Uses orders-of-magnitude estimation (powers of ten) instead of false-precision scoring. Best for: (1) Ranking a backlog where cost/effort tradeoffs matter, (2) Choosing between investments with different scales of impact and effort, (3) Quick prioritization that resists estimation error. Not ideal for: choosing between options that differ on strategic fit rather than ROI (use Binstack), exploring a problem space (use HEAD), or decisions where effort is irrelevant. Trigger on: 'fermi roi', 'estimate ROI', 'prioritize by ROI', 'which is the best investment', 'rank these by return', or when the user needs to compare initiatives by impact-per-effort. Based on: https://longform.asmartbear.com/roi-rubric/ |
Fermi ROI
A prioritization framework that replaces spreadsheet ROI with orders-of-magnitude estimation. Use only powers-of-ten values where the two adjacent choices are obviously wrong.
Why
Traditional rubrics produce noise, not signal. A feature scored at 60 impact / 4 effort (ROI = 15) that actually delivers 48 impact / 6 effort (ROI = 8) shows 50% ROI variance from minor estimation errors. Fermi estimation eliminates this noise. Rankings stay stable even when individual estimates shift by 50%.
Process
1. List the Candidates
Name every initiative, feature, or investment under consideration.
2. Define One Impact Metric
Pick a single measure of impact. Constrain it to powers of ten where intermediate values are absurd.
Quantitative options:
| Metric | Fermi Scale |
|---|
| Monthly revenue increase | $1K, $10K, $100K, $1M |
| New customers per month | 1, 10, 100, 1,000, 10,000 |
| Adoption rate | 1%, 10%, 50% |
| Active user penetration | 0.1%, 1%, 10%, 50% |
Choose the metric most relevant to the decision. Do not combine metrics — pick one.
Qualitative option (multi-factor):
When no single metric captures impact, break it into factors where ALL must succeed together. Multiply the scores.
Define each factor with concrete descriptions at each level — never use generic 1-5 scales.
Example factors:
| Factor | Question | Scale |
|---|
| Reach | How many customers care? | 0, 30, 70, 100 |
| Intensity | How much do they care? | 0, 1, 10, 100, 1000 |
| Insight | How novel is our perspective? | 0, 1, 10, 100, 1000 |
| Relevance | How well does the solution address the insight? | 0, 1, 10, 100, 1000 |
Each level needs a specific definition. Examples for Intensity:
- 1000 — Mission-critical to project success
- 100 — Serious internal concern we've discussed
- 10 — I'm curious, tell me more
- 1 — Meh
- 0 — Don't waste my time
3. Estimate Effort
Use only three brackets:
| Bracket | Duration |
|---|
| 2d | Two days |
| 2w | Two weeks |
| 2m | Two months |
Round up. Whatever you think the real estimate is, choose the next bracket. This forces scope clarity and accounts for underestimation bias.
For multi-part projects, group related items into epics and accept or reject them as complete sets.
4. Calculate ROI
Single metric:
ROI = Impact / Effort
Example:
| Initiative | Revenue | Effort | ROI |
|---|
| A | $100K/mo | 2m (45d) | 2,200 |
| B | $10K/mo | 2w (10d) | 1,000 |
| C | $1K/mo | 2d | 500 |
Multi-factor:
Combined Score = Factor1 × Factor2 × Factor3 × Factor4
Multiply when all factors must succeed together. Add when factors represent independent alternatives. Rank by combined score.
5. Break Ties
Most items cluster into 5-10 unique ROI values. When candidates tie, use one of these methods:
Add precision (sparingly). Shift the scale from powers of 10 to powers of 3 (1, 3, 9, 27) or add custom gaps (800 vs. 1000) to signal slight preference.
Run-off. Among tied items, score on a single new dimension:
| Dimension | Scale | Definitions |
|---|
| Team excitement | 0, 1, 10, 100 | 0 = no one interested; 1 = one person; 10 = half the team; 100 = everyone |
| Confidence | 0, 1, 10, 100 | 0 = no chance; 1 = can try, don't expect success; 10 = probably succeed; 100 = within expertise, done it before |
| Strategic alignment | 0, 1, 10, 100 | Define levels specific to your strategy |
Filter. Drop all factors except one and rank on that alone.
6. State the Decision
Present the ranked list with a narrative, not just numbers.
Priority 1: Initiative A — $100K/mo impact justifies the 2-month investment. ROI: 2,200.
Priority 2: Initiative B — Lower impact but ships in two weeks. Strong fallback if A proves harder than expected.
Deprioritized: Initiative C — Lowest ROI. Worth revisiting only if scope shrinks to under a day.
Explain rankings in terms of impact magnitude, not decimal differences. "A has dramatically larger impact; worth the extra time" beats "A scored 15.3 vs. B's 12.1."
Output Template
## Fermi ROI Analysis: [Decision Context]
### Impact Metric
[Metric name and Fermi scale used]
### Scoring
| Initiative | Impact | Effort | ROI | Notes |
|---|---|---|---|---|
| [Name] | [Value] | [2d/2w/2m] | [Score] | [Key assumption] |
### Ranking
1. **[Winner]** — [Why it ranks first]
2. **[Runner-up]** — [Why it ranks second; fallback narrative]
3. ...
### Ties Broken By
[Method used and result, if applicable]
### Key Assumptions
- [Assumption 1]
- [Assumption 2]
Caveats
- Impact only, no strategic fit. Fermi ROI maximizes return per effort. It does not account for strategic alignment, team morale, or market positioning. If those matter more than ROI, use Binstack.
- One metric at a time. Combining multiple metrics compounds estimation error. Pick one or use the multi-factor multiplication approach where all factors are required for success.
- Round up effort. Effort is almost always underestimated. The three-bracket system compensates for this bias.
- Estimation errors don't cancel out. They compound. Fermi estimation works because it keeps estimates coarse enough that rankings remain stable despite individual errors.
