idea-prioritization

name	Idea Prioritization
description	ICE-based idea prioritization with evidence-guided confidence scoring. Score ideas on Impact, Confidence, and Ease to propose execution priority.

Idea Prioritization (ICE Framework)

Goal

Ingest an idea description and current state, score it on Impact, Confidence, and Ease, and compute the ICE Score = Impact x Confidence x Ease to propose an execution priority. All evaluations must follow explicit criteria and rely only on stated evidence; no inference or guesswork.

When to use

• To quickly order an idea backlog and select items for exploration and experiments
• When you have at least some explicit evidence (interviews/data/tests) and a rough team effort estimate
• Before drafting experiment plans for a leaf opportunity in an Opportunity Solution Tree

Input

• Idea title and description: goal, target metric, scope, and working hypothesis
• Idea analysis and current state: data/user/market/test evidence, execution hypothesis, risks, and effort estimate
• Optional:
  • Target metric and expected change rate (%) or range
  • Estimated effort (person-weeks)

Output

• Format: Markdown (.md)
• Location: initiatives/[initiative]/solutions/
• Filename: ice-[YYYY-MM-DD]-[slugified-idea-title].md

Scoring model

For the full scoring model details, see references/ice-scoring-model.md.

Quick reference

• Impact: Map expected metric change (%) to a 0-10 scale
• Ease: Map estimated effort (person-weeks) to a 10-1 scale (less effort = higher ease)
• Confidence: Sum weighted evidence contributions with group caps
• ICE Score = Impact x Confidence x Ease

Priority buckets

Score	Guidance
>= 250	Consider immediate execution (high expected ROI)
150-249	Promising; recommend additional precision testing
100-149	Proceed with mitigations or phase-two testing
< 100	On hold or needs strengthening

Process

1. Input validation: Verify target metric, expected change (%), evidence text, and estimated effort (person-weeks). If missing, ask clarifying questions.
2. Impact scoring: Map % change to the Impact table; if missing, apply default Impact 2.
3. Ease scoring: Map person-weeks to the Ease table; if uncertain, use conservative lower ease.
4. Evidence extraction and classification: Count only impact-related evidence from the input. Tally per type and apply group caps.
5. Confidence calculation: Sum per-type contributions, apply group caps, compute final Confidence (0-10).
6. ICE computation: Compute ICE = I x C x E; assign priority bucket.
7. Report generation: Include score table, calculation rationale, cap applications, risks/assumptions, and recommended next steps.

Output format

# ICE Evaluation -- [Idea Title]

## Overview
- **Idea:** [Title]
- **One-line Summary:** [Brief description]
- **Target Metric:** [Metric name]
- **Assumptions/Scope:** [Key assumptions]

## Score Summary
- **Impact:** [I] (basis: [expected % change or default rule])
- **Ease:** [E] (basis: [person-weeks])
- **Confidence:** [C] (see details in references/ice-scoring-model.md)

## ICE Calculation
- ICE = [I] x [C] x [E] = **[Score]**
- **Priority Guidance:** [Bucket label]

## Input Summary
- **Expected Metric Change:** [value/none -> default 1.5% applied]
- **Estimated Effort (person-weeks):** [value/uncertain]
- **Evidence Excerpts:**
  - [Excerpt 1; classified as: user/market/test/...]
  - [Excerpt 2; classified as: ...]

## Risks / Assumptions
- [Key risk]
- [Key uncertainty]

## Recommended Next Steps
- [Tests/data collection/research/prototype]
- Confidence Improvement Plan: [Which evidence to strengthen]

## Notes
- ICE is a fast comparison/sorting tool; final decisions must also consider strategy, market, and resources.

Guardrails

• Do not invent or infer evidence or over-credit weak signals
• Exclude evidence not directly tied to Impact from Confidence
• When uncertain, apply conservative caps and document in "Risks/Assumptions"
• Prevent duplicate counting of the same source/content

Customization (team tuning)

• Adjust Impact bands to your target metric sensitivity
• Adjust Ease bands to team speed/role mix
• Extend evidence keywords to your domain language, while preserving the "explicit evidence only" rule
• Recalibrate bucket thresholds per quarterly capacity/roadmap density

Follow the writing standards in _shared/writing-standards.md for all outputs.