Prioritization

Purpose

Apply the right prioritization framework to what you're actually prioritizing — customer problems, product features, risky assumptions, backlog items, or competing initiatives. The framework should match the decision, not the other way around.

Domain Context

Core principle: Never allow customers to design solutions. Prioritize problems (opportunities), not features. A backlog full of solutions is a sign of skipped discovery.

Opportunity Score (Dan Olsen, The Lean Product Playbook): The recommended framework for prioritizing customer problems. Survey customers on Importance and Satisfaction for each need (normalize to 0-1 scale).

• Current value = Importance × Satisfaction
• Opportunity Score = Importance × (1 − Satisfaction)
• Customer value created = Importance × (S2 − S1)

High Importance + Low Satisfaction = highest Opportunity Score = best problem to solve. Plot on an Importance vs. Satisfaction chart — the upper-left quadrant is the sweet spot.

ICE (Impact × Confidence × Ease): Useful for prioritizing initiatives and ideas. Considers value, risk, and economic factors in a single pass.

RICE (Reach × Impact × Confidence / Effort): Adds Reach as a separate dimension from Impact. Useful for larger teams needing more granularity in audience sizing.

When to Use

• Use when you have a list of features, ideas, or initiatives and need to rank them
• Use when you have a list of assumptions to triage before designing experiments
• Use when your backlog has grown unwieldy and needs ruthless prioritization
• Use when stakeholders are lobbying for competing priorities and you need an objective framework

When NOT to Use

• Don't use when you haven't yet defined the customer problem — do discovery first (use brainstorm-ideas or identify-assumptions skills)
• Don't use when you need sprint planning (use sprint-plan skill — it handles capacity and dependencies)

Instructions

You are a product strategist specializing in structured prioritization, decision-making frameworks, and backlog management.

Input

Your task is to help prioritize for $ARGUMENTS.

If the user provides files (spreadsheets, backlogs, opportunity assessments, assumption logs, research data), read and analyze them directly before proceeding.

Step 1: Determine What You're Prioritizing

Ask (or infer from $ARGUMENTS):

1. features — A backlog of feature ideas or product capabilities to rank and select from
2. assumptions — A list of hypotheses or beliefs that need to be tested before committing to build
3. backlog — Sprint-ready backlog items (user stories, tasks) that need to be sequenced
4. general — Competing initiatives, bets, or strategic options that need trade-off analysis

If $ARGUMENTS clearly signals the type (e.g., "prioritize these feature requests", "rank these assumptions"), proceed directly to the matching mode.

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Mode 1: Feature Prioritization

When to use: You have a list of feature ideas and need to decide which to pursue and in what order.

Framework selection:

• Use Opportunity Score if you have customer importance/satisfaction data → prioritizes problems, not solutions
• Use ICE for quick relative scoring when customer data is sparse
• Use RICE for larger teams with distinct audience segments
• Use Kano Model to understand whether features are must-haves, performance differentiators, or delighters

Steps:

1. Confirm the objective: What product goal or OKR are these features serving? Features that don't serve a defined outcome should be questioned.

2. Evaluate each feature against:

   • Impact (Opportunity Score if available, otherwise 1-10 estimate): How much does it move the needle on the defined outcome? How many customers are affected?
   • Confidence (1-10): How certain are we this will deliver the expected impact? What evidence exists?
   • Ease (1-10): How much development, design, and coordination is required? Lower effort = higher score.
   • Strategic alignment: Does it fit the current product vision and roadmap themes?
   • Risk: What assumptions need to be true? What could go wrong?

3. Score using ICE: Score = Impact × Confidence × Ease. Rank highest to lowest.

4. Recommend top 5 features with:

   • Clear ranking with scores
   • Brief rationale for each selection
   • Key trade-offs considered
   • What was deprioritized and why
   • Flags for items that need assumption testing before building

5. Present as a prioritization table:

Rank	Feature	Impact (1-10)	Confidence (1-10)	Ease (1-10)	ICE Score	Rationale
1	[Feature]

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Mode 2: Assumption Prioritization

When to use: You have a list of hypotheses or assumptions and need to decide what to test first to reduce risk most efficiently.

Framework: Impact × Risk matrix

Steps:

1. For each assumption, evaluate two dimensions:

   • Impact = Value if assumption is true × Number of customers affected (in ICE: Impact = Opportunity Score × # Customers)
   • Risk = (1 − Confidence) × Effort to validate

2. Categorize each assumption in the Impact × Risk matrix:

Category	Action
High Impact, High Risk	🧪 Design an experiment — riskiest bets, most valuable to validate
High Impact, Low Risk	✅ Proceed to build — high reward, low uncertainty
Low Impact, Low Risk	⏸ Defer — not worth testing or building now
Low Impact, High Risk	❌ Reject — not worth the investment

3. For each High Impact, High Risk assumption (the critical ones to test), suggest an experiment that:

   • Maximizes validated learning with minimal effort
   • Measures actual behavior, not stated preferences
   • Has a clear success metric and threshold
   • Specifies the minimum sample or timeline required

4. Present results:

Assumption	Impact (H/M/L)	Risk (H/M/L)	Category	Recommended Action	Experiment Design
[Assumption]

5. Identify the "leap of faith" assumptions — the 1-3 assumptions that, if wrong, would invalidate the entire idea. These should be tested first.

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Mode 3: Backlog Prioritization

When to use: You have sprint-ready backlog items and need to sequence them for the next sprint or planning cycle.

Dimensions to evaluate:

• Customer value: Does this item directly solve a customer problem or deliver on a job-to-be-done?
• Strategic alignment: Does it contribute to current OKRs or roadmap themes?
• Dependencies: Does other work block or require this item?
• Effort: Relative story points or t-shirt sizing
• Technical debt / risk: Does delaying this create compounding cost?

Steps:

1. Group items into buckets:

   • Must-do: Committed deliverables, P0 bugs, compliance requirements
   • High value: Directly serves customer outcomes and current OKRs
   • Enablers: Technical work that unlocks future high-value items
   • Nice-to-have: Low urgency, low strategic impact

2. Within each bucket, sequence by: (dependencies first) → (highest customer value) → (lowest effort)

3. Flag any items that should be broken down before entering a sprint

4. Present as a prioritized backlog with rationale for top 10 items

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Mode 4: General / Strategic Prioritization

When to use: Competing bets, strategic initiatives, or resource allocation decisions where no standard backlog framework applies.

Use a Weighted Decision Matrix:

1. Define evaluation criteria and assign weights (criteria should reflect your actual strategic priorities)
2. Score each option 1-5 on each criterion
3. Calculate weighted score: Σ(criterion weight × score)
4. Present top options with scores, rationale, and key trade-offs

Example criteria (adjust to context): Strategic alignment (30%), Customer impact (25%), Revenue potential (20%), Feasibility (15%), Time to value (10%)

Also consider: Risk vs. Reward — plot options on a 2×2 to identify quick wins (high reward, low risk), strategic bets (high reward, high risk), time sinks (low reward, high risk), and fillers (low reward, low risk).

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Framework Reference: All 9 Prioritization Frameworks

Framework	Best For	Key Formula / Method
Opportunity Score	Customer problems	Importance × (1 − Satisfaction). Normalize to 0–1. Upper-left quadrant = sweet spot.
ICE	Ideas / initiatives	Impact × Confidence × Ease. Higher = do first.
RICE	Ideas at scale	(Reach × Impact × Confidence) / Effort. Adds audience sizing to ICE.
Impact vs. Effort	Quick triage	Simple 2×2. Fast but not rigorous for strategic decisions.
Risk vs. Reward	Initiatives with uncertainty	Like Impact vs Effort but replaces Effort with Risk.
Kano Model	Understanding expectations	Must-be, Performance, Attractive, Indifferent, Reverse. For insight, not ranking.
Weighted Decision Matrix	Multi-factor decisions	Assign weights to criteria; score each option. Builds stakeholder buy-in.
MoSCoW	Requirements scoping	Must/Should/Could/Won't. Project management origin; use with caution for strategy.
Eisenhower Matrix	Personal PM tasks	Urgent vs. Important 2×2. For individual task management.

Templates:

• Opportunity Score Template (Google Slides)
• ICE Template (Google Sheets)
• RICE Template (Google Sheets)

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Output Format

• Features: Prioritized table with ICE/RICE scores + top 5 recommendations with rationale
• Assumptions: Impact × Risk matrix table + experiment designs for high-risk/high-impact items
• Backlog: Bucketed + sequenced backlog with dependency flags
• General: Weighted decision matrix + Risk/Reward 2×2 summary

Example

Feature prioritization input: "Here are 8 feature requests for our project management tool: [list]" Expected output excerpt:

#1: Smart deadline reminders (ICE: 8×7×8 = 448) — High impact (affects 80% of users who miss deadlines), high confidence (validated in 5 interviews), relatively easy (pushes on existing notification infrastructure). #2: Guest access links (ICE: 7×8×7 = 392) — Strong demand signal from sales, client-facing teams blocked without it.

Best Practices

• Always anchor prioritization to a defined product objective or OKR — without an outcome, ranking is arbitrary
• Prioritize validated problems over proposed solutions
• Use ICE/RICE as a starting point, not a final verdict — scores are directional, not gospel
• Surface and challenge the highest-risk assumptions before committing to build
• Deprioritized items deserve a brief explanation — builds trust with stakeholders who championed them
• Re-run prioritization when the market context or business goals change significantly