Make the trade-off visible before you commit.
Make the decision visible, show what it depends on, and test the risky part first.
Try saying
“Here are the options and evidence. What should we learn before we commit?”
Name the choice
Write down the decision in plain English.
Compare evidence
See what supports or weakens each option.
Choose a test
Turn uncertainty into a small next step.
Prioritization Matrix
What this is for
Choose what to do next when there are more plausible ideas than available capacity.
When this helps
- Roadmap decisions follow seniority or volume instead of value.
- Teams debate scores without agreeing on the evidence behind them.
- A prioritization list goes stale when new signals arrive.
How it works
The matrix combines opportunity information, customer evidence, confidence, effort, and a selected framework such as RICE, ICE, or a saved custom weighting. RICE uses Reach × Impact × Confidence ÷ Effort; ICE uses Impact × Confidence ÷ Effort; the custom model normalizes Reach (0–1,000 users/month), Impact (0–3), Confidence (0–100%), and inverse Effort (0–20 weeks) into a transparent 0–100 score using your workspace weights. Specky can suggest scores from the graph, but the team owns the final decision.
Before you start
- A set of opportunities or feature ideas.
- Evidence, expected impact, confidence, and effort estimates.
- A scoring framework and a decision horizon.
- Optional custom weights for Reach, Impact, Confidence, and Effort; they are normalized to 100%.
What you should see
- A ranked list and quadrant view.
- Visible assumptions behind each score.
- A decision you can link to the roadmap, PRD, or OKR.
Try it now
- Open Prioritization and add or import the opportunities you are comparing.
- Choose RICE, ICE, or Weighted.
- If you choose Weighted, open Configure weights, give Reach, Impact, Confidence, and Effort the relative importance your team agrees on, and save. Specky normalizes the weights automatically.
- Review the evidence and adjust scores where the model lacks context. Weighted scoring stays blank until every criterion with a non-zero weight has an input.
- Compare the top candidates, record the decision, and link the winner to a roadmap item.
A real example
Your team sets Weighted to Reach 40, Impact 30, Confidence 20, and Effort 10. A feature reaching 500 users/month, scoring 2.5/3 for impact, 80% confidence, and taking 4 weeks receives a transparent 69.0/100; a low-reach executive request does not win simply because it is loud.
Your next move
Map the winning opportunity in Opportunity Tree, then draft it with Generating Your First PRD.
Ready to apply this?
Start with your own product and keep the first read grounded. You'll create an account before the guided result so it can be saved to your workspace.