Which one is worth a quarter?
Lesson 18 of 24, level 01Index
Five real problems, one team, twelve weeks. The founder wants all five and has said so in front of the team.
Confidence is the honest column
RICE is Reach times Impact times Confidence, divided by Effort. Reach and impact are estimates dressed as numbers. Confidence is where you record how much you actually know.
Which is why teams that adopt RICE and get nothing from it are the ones who set every confidence to 100 percent. The framework does not make the decision. It makes your assumptions visible so the argument is about the right thing.
A prioritisation score helps a team discuss assumptions consistently. It does not remove judgment or make a weak estimate objective by giving it decimal places.
Use your chosen course project throughout. The additional examples below are fictional practice cases; transfer the method to your own evidence.
Choose comparable inputs
For a RICE exercise, use reach over the same period, a shared impact scale, confidence as a fraction, and effort in the same unit. Define each scale before scoring. If one proposal uses annual reach and another monthly reach, the ranking is an artifact of the spreadsheet rather than a meaningful comparison.
Attach evidence to confidence
Confidence should reflect the support behind reach and impact, not how much someone likes the idea. Record the source and date next to each estimate. Keep dependencies, mandatory work, and strategic constraints visible outside the score; not every decision belongs in the same ranking exercise.
Test ranking stability
Vary uncertain inputs and see whether the order changes. If two options swap after a small adjustment, treat them as close and discuss evidence or a smaller test. The next best action may be research that improves confidence rather than immediate delivery of the current highest-scoring feature.
Make the score auditable
- Reach: Same period
- Impact: Shared scale
- Confidence: Evidence quality
- Effort: Same work unit
How much confidence changes the choice?
Interactive teaching example · All numbers and tickets are fictional.
A = 100 reach × 2 impact × 0.5 confidence ÷ 2 person-months. B = 80 × 1 × 0.8 ÷ 1 = 64. A needs confidence above 64% to lead. Evidence must justify that change.
Doing it with AI, and where it breaks
Build the scoring sheet, then ask which of these scores is not supported by the evidence I have described.
It will accept your numbers as given and do arithmetic on them, which flatters you. Make it attack the inputs rather than compute the output.
Your AI workbench
Start with your own notes or clearly labelled practice data. Remove private details before sharing. Replace the placeholders, run the prompt in your chosen AI tool, and keep the output beside its source.
Audit this prioritisation table [paste]. Check periods, scales, confidence fractions, effort units, dependencies, and source quality. Recalculate each score transparently and show which plausible input changes reverse the ranking. Do not choose confidence values just to support my preferred idea.
Before you use the output
- All proposals use consistent units
- Confidence has an evidence rationale
- Dependencies and close rankings remain visible
Stuck? Try this next
Ask AI to argue for the lower-ranked option using only supplied facts. This can expose a missing constraint, but it cannot manufacture evidence for that option.
Keep a brief AI log: input used, useful output, what you checked, and what you rejected. The decision remains yours.
Build it
A scored shortlist where the confidence column is the honest one.
Checkpoint
If you did the build, these take two minutes. If you cannot answer one of them, that is the part to go back to.
Moving on marks this lesson complete. Finish the build first, it is the part that counts.