技能 产品商业 功能优先级排序框架指南

功能优先级排序框架指南

v20260618
feature-prioritisation
本技能提供一套完整的、可辩护的产品功能优先级排序流程,囊括RICE、MoSCoW、Kano等主流模型。它生成的不仅是简单的列表,而是一份包含得分、推荐构建顺序、明确排除项和假设记录的完整文档,是产品经理进行科学、战略决策的最佳工具。
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概览

Feature Prioritisation Skill

Apply the right prioritisation framework to any backlog and produce a clear, defensible ranking with rationale — not just a sorted list.

Required Inputs

Ask the user for these if not provided:

  • List of features or initiatives to prioritise
  • Goal or metric being prioritised against (OKR, launch, sprint)
  • Preferred framework (or recommend based on context below)
  • Team data: reach estimates, effort estimates, velocity (for RICE)

Framework Selection Guide

Ask the user which framework they prefer, or recommend based on context:

Situation Recommended Framework
Need a quick, data-driven score RICE
Stakeholder alignment meeting MoSCoW
Understanding customer delight vs expectations Kano
Early-stage startup, fast decisions ICE
Identifying underserved customer needs Opportunity Scoring
Strategic portfolio decisions Value vs Effort Matrix

RICE Scoring

Formula: (Reach × Impact × Confidence) ÷ Effort

Factor Definition Scale
Reach Users impacted per quarter Actual number
Impact Effect on goal per user 0.25 / 0.5 / 1 / 2 / 3
Confidence How certain are you? 50% / 80% / 100%
Effort Person-months required Actual number

Output table:

Feature Reach Impact Confidence Effort RICE Score Priority

MoSCoW Method

Categorise each feature as:

  • Must Have — non-negotiable for launch/sprint; product fails without it
  • Should Have — important but not critical; workarounds exist
  • Could Have — nice to have; include only if time allows
  • Won't Have (this time) — explicitly out of scope now; may revisit

Always ask: "Must have for what?" — define the scope (launch, sprint, quarter) before categorising.


ICE Scoring (Startup/fast mode)

Formula: Impact + Confidence + Ease (each 1–10)

Quick, subjective — good for early decisions before data exists.


Kano Model

Classify features into:

  • Basic (Must-be): Expected; absence causes dissatisfaction
  • Performance: More = better satisfaction; linear relationship
  • Excitement (Delighters): Unexpected; creates delight; absence is neutral
  • Indifferent: Users don't care either way
  • Reverse: Some users want it, others don't

Recommend building: all Basic features first → Performance features for key use cases → 1–2 Excitement features per release.


Output Format

Feature Prioritisation — [Product/Team] — [Date]

Framework Used: [RICE / MoSCoW / ICE / Kano / Custom] Scope: [Sprint / Quarter / Release] Goal being prioritised against: [Metric or objective]

[Scored table using selected framework]

Recommended Build Order:

  1. [Feature] — [1-line rationale]
  2. [Feature] — [1-line rationale]
  3. ...

Explicitly Deprioritised:

  • [Feature] — Reason: [brief]

Assumptions Made:

  • [Any estimates or judgements used in scoring]

Guidelines

  • Always anchor prioritisation to a specific goal or metric — never prioritise in a vacuum
  • Flag when two features have similar scores but very different risk profiles
  • If stakeholder politics are influencing prioritisation, name it explicitly and suggest separating the framework score from the final decision
  • Recommend revisiting priorities every 2 weeks minimum
  • Never produce a single-column ranked list without rationale — explain the top 3 and bottom 3 decisions

Quality Checks

  • Every item is scored against the same goal or metric (not different goals per item)
  • Deprioritised items are explicitly listed with reasons (not just absent from the ranked list)
  • Assumptions used in scoring are documented
  • Stakeholder politics or personal preferences are separated from framework score
  • Prioritisation is anchored to a specific scope (sprint / quarter / launch)

Anti-Patterns

  • Do not score items against different goals — every item in a prioritisation session must be scored against the same objective
  • Do not omit deprioritised items — explicitly listing what was cut and why is as important as the ranked list
  • Do not let stakeholder politics override framework scores without documenting the override and reason
  • Do not mix RICE, ICE, or MoSCoW scores across frameworks in a single session — pick one framework per prioritisation exercise
  • Do not treat the output as final without documenting the assumptions used in scoring — assumptions change, and the list must be revisitable
信息
Category 产品商业
Name feature-prioritisation
版本 v20260618
大小 4.94KB
更新时间 2026-06-19
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