Opportunity Canvas — Brief & Test Plan

Opportunity Canvas — Brief & Test Plan

A compact, one-page template to turn curiosity into a focused experiment. Use this to clarify the problem, gather evidence, identify stakeholders, state riskiest assumptions, set measurable success criteria, and define the smallest experiment that will test your hypothesis.

How to use

Run a 60–90 minute framing session with a facilitator, a scribe, and a decision owner. Capture succinct bullet answers. The goal is not perfection but experiment-readiness: if a clear, timeboxed experiment and success criteria emerge, move it to the discovery backlog as an experiment card.

• Participants: facilitator, product/ops owner, subject-matter expert, advocate for beneficiary, and a data person if available.
• Timebox: 60–90 minutes (30–45 minutes to fill the canvas, 15–30 minutes to design the initial experiment and agree next steps).
• Outputs: completed canvas, a named experiment owner, experiment timeframe, and acceptance criteria for a quick go/no-go decision.

Sections & prompting questions

1. Opportunity statement (who, what, why now)

   Who is affected? What is the problem or unmet need? Why is it important now? Keep this to one crisp sentence and one supporting sentence for context.

2. Evidence & signals (data points and quotes)

   What facts, metrics, observations, or customer quotes support this opportunity? Distinguish signal from wishful thinking. List 3–5 strongest pieces of evidence and any known gaps.

3. Key stakeholders & beneficiaries

   Who benefits if this succeeds? Who must approve, support, or block the experiment? Note those who will be directly impacted or whose cooperation is required.

4. Assumptions & riskiest hypotheses

   What must be true for this opportunity to matter and for an experiment to succeed? Rank the top 2–4 riskiest assumptions in order of business impact and uncertainty.

5. Success metrics & target outcomes

   Which measurable outcome will convince you the idea is worth scaling? Provide a primary metric (with a clear baseline and target) and 1–2 supporting metrics (quality, adoption, cost, time saved, etc.). State the timeframe for seeing the effect.

6. Proposed experiment(s) and quick success criteria

   Describe the smallest viable experiment that will test the riskiest hypothesis. Include: what you'll build or observe, sample size or duration, required resources, and a clear go/no-go rule tied to the success metric.

Quick example (filled)

Opportunity statement: Cashier checkout delays at PeakMart cause lost sales and longer queues; reduce average checkout time by 30% in 6 weeks to improve throughput and customer satisfaction.

Evidence: POS logs show average wait of 6.5 minutes during 5–7pm; 12 customer complaints mentioning long lines in last month; manager reports 8% drop in evening conversion vs last quarter.

Stakeholders: Store manager (owner), operations team, cashiers, IT for POS changes, customers.

Riskiest assumptions: (1) A faster checkout flow will increase conversions; (2) cashiers can adopt a new workflow with minimal training.

Success metrics: Primary: checkout time reduced by 30% (baseline 6.5m → target 4.5m) within 6 weeks. Secondary: conversion up 5%, customer satisfaction up 10%.

Experiment: Run a 2-week A/B with a simplified till process at two stores (control vs new flow). Sample: evening shifts, 14 days. Go rule: if average checkout time falls ≥25% and conversion improves ≥3%, proceed to phased rollout.

Experiment design checklist

• Define owner and experiment start/end dates.
• Agree primary metric, baseline, and measurement method.
• Document required resources and minimal implementation steps.
• Identify data collection points and how results will be validated.
• Plan a short retro to capture learning, decisions, and next steps.

Common mistakes to avoid

• Vague success criteria. Without a measurable target you can't decide.
• Designing too big an experiment. Prefer smaller, faster tests that validate the riskiest assumptions.
• Neglecting stakeholders who can block or enable the experiment.
• Confusing desirable outcomes with validated customer value—test the value, not the solution.

Next steps & linking to the backlog

When the canvas is complete: attach it to a discovery backlog item, create an experiment card with owner and dates, and schedule a short check-in midway plus a learnings retro at the end. Keep the canvas living — update it with evidence from the experiment and use it as the record for the decision.

Adaptation and reuse

This canvas is intentionally concise so teams can quickly prioritize and run experiments. Tailor the sections, metrics, or experiment design to your domain and risk tolerance. Consider making an organization-specific copy that includes preset metric templates and experiment tracking fields.