Hypothesis Prioritization

Hypothesis Prioritization

Overview

You can't build everything. Hypothesis prioritization helps you choose which ideas to pursue next using proven scoring frameworks. This skill covers RICE, ICE, Value-vs-Effort quadrants, and assumption-based prioritization — choose the right framework for your context.

When to Use

• Choosing which solution to build next
• Ranking experiment ideas with limited testing capacity
• Aligning stakeholders on priorities with a transparent framework
• Deciding between competing feature requests
• Don't use for: comparing fundamentally different products (apples to oranges), urgent bug fixes (just fix them), strategic bets (different framework needed)

Instructions

1. Define Your Candidates

List the solutions, features, or experiments to prioritize. Each needs:

• Name and one-line description
• The hypothesis you're testing
• Who it serves

2. Choose a Framework

RICE (best for product features):

• Reach: How many users will this impact in a given time period? (scale 1-10)
• Impact: How much impact per user? (scale: 0.25=minimal, 0.5=low, 1=medium, 2=high, 3=massive)
• Confidence: How confident are we in our estimates? (scale: 50%=low, 80%=medium, 100%=high)
• Effort: How many person-months? (estimate in person-months)
• Score: (Reach × Impact × Confidence) / Effort

ICE (best for experiments):

• Impact: How impactful will this be? (1-10)
• Confidence: How confident are we? (1-10)
• Ease: How easy is this to test? (1-10)
• Score: (Impact + Confidence + Ease) / 3

Value vs. Effort Quadrant (best for stakeholder alignment):

• Plot items on a 2x2 matrix: Value (Y) vs. Effort (X)
• Quick wins (high value, low effort) → do first
• Big bets (high value, high effort) → plan carefully
• Fill-ins (low value, low effort) → do when idle
• Avoid (low value, high effort) → don't do

3. Score Your Items

Be transparent about scoring. Document:

• Who assigned the scores
• What data informed each score
• ✅ means there's supporting evidence
• ⚠️ means it's an estimate (flag low-confidence items)

4. Review as a Team

Scores are a starting point, not gospel. Discuss:

• Does the ranking feel right? If not, what are we missing?
• Are there dependencies? (Item B is worthless without Item A)
• Are there strategic considerations the framework doesn't capture?

5. Define the Cut Line

Given your capacity, how many items will you work on? Mark the cut line. Items below it go to the backlog, not the trash — revisit next cycle.

Sample Output

RICE Score for Feature Ideas:

| Feature | Reach | Impact | Confidence | Effort (pm) | RICE Score | |---------|-------|--------|------------|-------------|------------| | Quick search | 500 users | 2 | 90% | 1 | 900 | | Email reports | 200 users | 3 | 70% | 2 | 210 | | API integration | 50 users | 3 | 50% | 4 | 18.75 | | Mobile app | 300 users | 2 | 80% | 6 | 80 | | Team dashboard | 400 users | 2.5 | 85% | 2 | 425 |

Recommendation: Quick search (900) and Team dashboard (425) — these 2 items deliver highest RICE and fit within next sprint capacity.

Common Pitfalls

1. Fake precision — Scoring to 3 decimal places doesn't make it accurate. Use whole numbers
2. Framework bias — RICE favors reach. If impact > reach matters more, adjust the formula
3. Not capturing dependencies — Feature A might unlock Features B and C. The framework misses this
4. Confidence ≠ effort — A low-confidence high-effort item is riskier than the score suggests
5. Static ranking — New information should change your scores. Re-evaluate regularly

Verification Checklist

• [ ] All candidates listed with a one-line description
• [ ] Framework chosen and appropriate for the context
• [ ] Scores documented with reasoning
• [ ] Low-confidence items flagged (⚠️)
• [ ] Team reviewed the ranking
• [ ] Cut line defined based on capacity

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: uthumany
• Source: uthumany/uthy-legacy-os
• License: MIT
• Homepage: https://uthumany.github.io/uthy-legacy-os/

Install and usage instructions live in the source repository linked above.