RICE + Strategic Alignment Skill

Produce a prioritisation output that balances quantitative RICE scoring with qualitative strategic fit — because the highest RICE score isn't always the right next bet.

Required Inputs

Ask the user for these if not provided:

• List of initiatives or features to prioritise (names and brief descriptions)
• Current strategic priorities or OKRs (needed to rate strategic alignment)
• Reach estimates (users affected per quarter — even rough estimates work)
• Effort estimates (person-months — from engineering if available)
• Quarter or planning period

Two-Stage Process

Stage 1: RICE Scoring

• Reach: Users affected per quarter
• Impact: 3/2/1/0.5/0.25 scale
• Confidence: 100% / 80% / 50%
• Effort: Person-months
• RICE = (R × I × C) / E

Stage 2: Strategic Alignment Score

Rate each initiative against your current strategic priorities (provided as input):

• Directly supports top OKR: +3
• Supports secondary OKR: +2
• Neutral: +1
• Contradicts strategic direction: -1

Final Priority Score

Combined Score = RICE Score + (Strategic Alignment × 10)

Validate — Flag any initiative where RICE score and strategic alignment conflict sharply (e.g., high RICE, low alignment). These require an explicit team conversation before sequencing.

Output Structure

Priority Matrix — [Quarter]

Initiative	RICE Score	Strategic Alignment	Combined Score	Quadrant	Recommendation
[name]	[score]	[score]	[combined]	[Now/Next/Later/Drop]	[action]

Quadrant Definitions

• Now: High RICE + High Strategic Alignment → Build this quarter
• Next: High RICE + Lower Alignment → Queue for next quarter
• Later: Lower RICE + High Alignment → Revisit when capacity allows
• Drop: Low RICE + Low Alignment → Remove from backlog

Recommendations

[Top 5 initiatives with rationale for sequencing]

Quality Checks

• All RICE components have an estimate (even if low confidence — flag those)
• Strategic alignment is rated against specific OKRs, not general "feels strategic"
• Conflicts between RICE rank and strategic alignment are explicitly flagged
• "Drop" recommendations are specific — not just "low priority, deprioritise"
• Confidence levels on estimates are noted where weak (drives the 50% confidence flag)