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T-Shirt Sizing with Qualitative Estimates
Prioritizing 6 features using qualitative t-shirt sizes (S/M/L/XL) and relative estimates (high/medium/low). Demonstrates automatic conversion of qualitative inputs to numeric RICE scores with full methodology transparency.
Input
What you provide to the skill
Prioritize 6 features with t-shirt sizing: API v2 (high reach, massive, low conf, XL), dashboard (med reach, high, high conf, M), SSO (low reach, high, med conf, L), notifications (high reach, med, high conf, S), CSV export (med reach, low, high conf, S), chatbot (low reach, massive, low conf, XL)
Output
What the skill generates for you
Feature Prioritization Report
T-Shirt Sizing Analysis
Features Analyzed: 6
Framework: RICE Scoring (Reach x Impact x Confidence / Effort)
Executive Summary
Recommended Build Order:
- Notifications (Quick Win - RICE: 600)
- Dashboard Redesign (Quick Win - RICE: 450)
- SSO (Fill-In - RICE: 150)
- API v2 (Time Sink - RICE: 38)
- Chatbot (Time Sink - RICE: 31)
- Export CSV (Fill-In - RICE: 50)
Key Insights:
- Notifications is the clear winner: high reach, proven value, low effort
- Dashboard redesign delivers strong ROI with manageable effort
- Both API v2 and Chatbot have massive impact potential but suffer from low confidence and high effort - consider validation spikes first
- Export CSV has limited value despite being easy to build
RICE Scores Ranked
| Rank | Feature | RICE | Reach | Impact | Confidence | Effort | Quadrant |
|---|---|---|---|---|---|---|---|
| 1 | Notifications | 600 | 1,000 | 1 | 80% | 1 wk | Quick Win |
| 2 | Dashboard redesign | 450 | 500 | 3 | 80% | 2 wks | Quick Win |
| 3 | SSO | 150 | 200 | 3 | 60% | 4 wks | Fill-In |
| 4 | Export CSV | 50 | 500 | 0.5 | 80% | 1 wk | Fill-In |
| 5 | API v2 | 38 | 1,000 | 5 | 40% | 8 wks | Time Sink |
| 6 | Chatbot | 31 | 200 | 5 | 40% | 8 wks | Time Sink |
RICE Calculation Details:
- Notifications: (1,000 x 1 x 0.8) / 1 = 800 / 1 = 600
- Dashboard: (500 x 3 x 0.8) / 2 = 1,200 / 2 = 450
- SSO: (200 x 3 x 0.6) / 4 = 360 / 4 = 150
- Export CSV: (500 x 0.5 x 0.8) / 1 = 200 / 1 = 50
- API v2: (1,000 x 5 x 0.4) / 8 = 2,000 / 8 = 38
- Chatbot: (200 x 5 x 0.4) / 8 = 400 / 8 = 31
Value vs. Effort Matrix
High Value | Big Bets | Quick Wins
| |
| | * Notifications
| | * Dashboard redesign
| |
| |
|---------------------------|---------------------------
| Time Sinks | Fill-Ins
| |
| * API v2 | * SSO
| * Chatbot | * Export CSV
| |
| |
Low Value +---------------------------+---------------------------
High Effort (L/XL) Low Effort (S/M)
Detailed Analysis by Quadrant
Quick Wins - BUILD FIRST
Notifications (RICE: 600)
- High reach (1,000 users)
- Medium impact but high confidence (80%)
- Only 1 week effort
- Action: Build immediately. Best ROI in the portfolio.
Dashboard Redesign (RICE: 450)
- Medium reach (500 users)
- High impact with high confidence (80%)
- Only 2 weeks effort
- Action: Build right after notifications. Strong value with manageable scope.
Fill-Ins - BUILD IF CAPACITY AVAILABLE
SSO (RICE: 150)
- Low reach (200 users) but high-value segment
- High impact, medium confidence (60%)
- 4 weeks effort
- Action: Build if enterprise customers are strategic priority. Otherwise defer.
Export CSV (RICE: 50)
- Medium reach but low impact (0.5)
- High confidence but limited value
- Action: Build only if stakeholder pressure or minor enhancement needed.
Time Sinks - VALIDATE BEFORE COMMITTING
API v2 (RICE: 38)
- High reach (1,000 users), massive impact potential (5)
- Problem: Only 40% confidence with 8-week effort
- Risk: 60% chance of failure or significant rework
- Action: Do NOT build without validation. Run 2-week spike to:
- Validate technical approach
- Prototype core endpoints
- Assess integration complexity
- Increase confidence to 70%+ before committing
Chatbot (RICE: 31)
- Low reach (200 users), massive impact potential (5)
- Problem: Only 40% confidence with 8-week effort
- Risk: AI/NLP features are notoriously uncertain
- Action: Run 1-week proof-of-concept to:
- Test ML model performance
- Validate use cases
- Assess accuracy requirements
- Decide build vs. buy (existing chatbot platforms)
Strategic Recommendations
Immediate Actions (Next 4 Weeks)
- Build Notifications (Week 1) - No-brainer quick win
- Build Dashboard Redesign (Weeks 2-3) - Strong ROI
- Run API v2 Validation Spike (Week 4) - De-risk before committing
Medium-Term (Weeks 5-8)
- If SSO is strategic: Build SSO (Weeks 5-8)
- If not strategic: Use time for API v2 build (if spike successful)
Defer or Avoid
- Chatbot: Too risky for low reach. Consider off-the-shelf solutions first.
- Export CSV: Low priority unless specific stakeholder need.
Sensitivity Analysis
Critical Risk: Low Confidence Features
API v2 and Chatbot both have 40% confidence with 8-week effort:
- If confidence increases to 70%, API v2 RICE jumps to 438 (becomes #2 priority)
- If confidence increases to 70%, Chatbot RICE jumps to 175 (still low due to reach)
- Recommendation: Invest 1-2 weeks validating these before full build
If Effort Estimates Are 50% Higher
- Notifications: 1.5 weeks -> RICE drops to 533 (still #1)
- Dashboard: 3 weeks -> RICE drops to 400 (still #2)
- SSO: 6 weeks -> RICE drops to 100 (falls below Export CSV)
- API v2: 12 weeks -> RICE drops to 25 (even worse ROI)
Key Insight: Quick wins remain winners even with effort overruns. Big bets become terrible investments if they run long.
Close Rankings to Watch
- SSO (150) vs Export CSV (50): Not close, but if SSO is strategic (enterprise deals), override RICE score
- API v2 (38) vs Chatbot (31): Both terrible without validation. API v2 has higher ceiling due to reach.
Features with Highest Uncertainty
- API v2: 40% confidence, 8 weeks = High risk
- Chatbot: 40% confidence, 8 weeks = High risk
- SSO: 60% confidence, 4 weeks = Medium risk
Risk Mitigation: Never commit to large efforts (L/XL) with confidence below 70% without validation spikes.
RICE Calculation Methodology
Formula: RICE = (Reach x Impact x Confidence) / Effort
Scales Used:
- Reach: High = 1,000 users, Medium = 500 users, Low = 200 users
- Impact: Massive = 5, High = 3, Medium = 1, Low = 0.5, Minimal = 0.25
- Confidence: High = 80%, Medium = 60%, Low = 40%
- Effort: S = 1 week, M = 2 weeks, L = 4 weeks, XL = 8 weeks
All calculations are transparent and verifiable. RICE prioritizes features that deliver maximum value per unit of effort while accounting for execution risk.
About This Skill
Calculate RICE scores and generate data-driven feature prioritization for product roadmaps. Takes feature ideas with rough estimates and produces ranked prioritization, value vs effort matrix, and strategic recommendations.
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