Discovery Backlog & Pipeline Template

Purpose

This template helps teams capture discovery intake, triage and prioritize prospects, define stage exit criteria, and run a manageable pipeline of experiments. Use it to keep learning discoverable and reusable rather than letting ideas become a graveyard.

How to use this template

1. Capture every idea with the Intake Fields below.
2. Run a quick triage using the Prioritization Rubric to decide whether to archive, groom, or advance to a ready-for-experiment stage.
3. Apply the Stage Definitions and Exit Criteria before moving work forward.
4. Record experiment results and lessons so knowledge is retained.

Intake fields (core canonical set)

Keep these fields consistent across submissions so triage, reporting and dashboards stay reliable.

• Title — short, descriptive (5–8 words).
• Problem / Opportunity — one-paragraph description of the need.
• Evidence — customer quotes, data, incidents, metrics, or observations that show the problem exists.
• Desired outcome / success metric — what will count as success and how it will be measured.
• Owner — person responsible for driving the discovery work.
• Supporters / stakeholders — teams or roles that should be informed.
• Initial hypothesis — concise testable hypothesis (If X, then Y because Z).
• Suggested experiment types — interview, prototype, funnel test, A/B, field trial, pilot.
• Estimated effort — short/medium/long or days (helpful for planning).
• Strategic alignment — which objective/OKR or customer priority this supports.
• Constraints & risks — compliance, capacity, technical limits, customer impact.
• Tags / taxonomy — product, process, customer segment, technology, experiment method.

Example intake (short)

Title: Reduce onboarding dropout. Problem: 18% of new users drop out during setup. Evidence: analytics funnel + support tickets. Hypothesis: A guided checklist reduces dropouts by 30%. Owner: Product lead. Estimated effort: 3 days prototype. Success metric: % dropouts at day 7.

Stage definitions & exit criteria

Define clear, evidence-based gates so work advances because learning justifies it.

• Intake — Idea logged with required intake fields filled. Exit to triage: minimum fields complete and owner assigned.
• Triage / Discovery Backlog — Quick evidence check and priority score applied. Exit to Ready for Experiment: Priority score above threshold OR sponsor approval with clear next-step experiment plan.
• Ready for Experiment — Experiment design, measurement plan, resources and timeline agreed. Exit to Running Experiment: experiment plan and data collection ready.
• Running Experiment — Execute, collect data, and capture observations. Exit to Validated or Failed: experiment completed and results analyzed.
• Validated / Scaled — Evidence shows meaningful improvement and plan exists to scale/hand off to delivery teams.
• Archived — Ideas not prioritized or disproven hypotheses; include reasons and lessons learned so they can be revisited later.

Prioritization rubric (simple, evidence-friendly)

Use three dimensions: Impact, Confidence, Effort. Score each 1–5 (higher better for Impact & Confidence; lower better for Effort). Calculate priority with a lightweight formula.

Scoring fields

• Impact (1–5): potential value if hypothesis is true (customer value, revenue, waste reduction, strategic importance).
• Confidence (1–5): strength of evidence behind the idea (data, customer feedback, prior tests).
• Effort (1–5): estimated cost/time/complexity (1 = very low, 5 = very high).

Priority score (example formula): (Impact × Confidence) / Effort. Higher scores indicate higher urgency to test.

Interpretation (example):

• Score > 7 — strong candidate for immediate experiment.
• Score 4–7 — groom: refine evidence or reduce effort (prototype, quick interviews).
• Score < 4 — archive or monitor; revisit if new evidence appears.

Sample calculation: Impact 4 × Confidence 3 = 12; Effort 2 → 12 / 2 = 6 (groom and consider for next experiment sprint).

Suggested cadences & roles

• Daily/Weekly — Owners update running experiments and blockers asynchronously.
• Weekly — Intake steward reviews new submissions and assigns owners.
• Biweekly — Pipeline grooming session: triage committee (product, design, research, engineering lead) reviews priorities and moves items between stages.
• Monthly — Strategic review: check alignment to objectives and resource allocation.
• Quarterly — Archive old items, evaluate learning reuse, and refresh taxonomy.
• Roles: Intake steward, Triage committee, Experiment owner, Executive sponsor, Knowledge librarian (captures lessons).

Keeping organizational memory

Always attach an experiment result summary with each completed item. Use standard fields: hypothesis, method, duration, key metrics, decision (validated, failed, unclear), actions, and lessons learned. Tag lessons so future discovery can find them by customer segment, hypothesis type, or outcome.

Quick-start checklist

1. Create one canonical intake form with the fields above.
2. Agree triage rubric and priority thresholds with stakeholders.
3. Run a pilot pipeline for one month with 3–5 items to validate cadence and roles.
4. Establish a single place (board, repo, or THE collection) to store experiment reports and lessons.

Common pitfalls & tips

• Don’t let intake become a backlog graveyard: apply a triage decision within a short SLA (e.g., 7 business days).
• Avoid prioritizing by the loudest voice: use the rubric plus a sponsor override that must be documented with rationale.
• Favor fast, low-cost probes early to increase confidence cheaply.
• Design tags and fields for findability so lessons are discoverable beyond the immediate team.

Next steps & capability opportunities

Turning this template into an interactive intake form and saved experiment registry will make the pipeline easier to operate at scale. Consider adding an Interactive intake form that pre-populates the prioritization calculator, stores submissions, and supports simple dashboards for status and outcomes.