Strategic Foundation (Prerequisites)

Before discovery can be effective, these strategic elements must be in place. Discovery is "tethered to strategy" - not random exploration.

Product Vision

Where are we going? The aspirational future state that guides all product decisions.

Product Strategy

How will we get there? The deliberate choices about where to play and how to win.

Portfolio Context

Where does this fit? Existing products, planned initiatives, resource constraints.

Context Decision: What type of discovery is this?

New Product / Venture → Full Business Model Canvas approach. Draft business model hypotheses in Stage 0, validate throughout, finalize in Stage 4.
Feature for Existing Product → Business model delta assessment. Reference existing model, note new assumptions (e.g., new pricing tier).

Three Essential Perspectives

Effective discovery requires input from three functional perspectives. Whether from one person wearing multiple hats or distributed across team members.

Product / Business

Strategy & Viability — What should we build and why?

Key Activities: 0.1 Stakeholder Alignment, 1.1 Segment Selection, 2.2 Solution Evaluation, 3.5 Viability Validation

Design / User

User Needs — What do users actually need?

Key Activities: 1.2-1.4 JTBD Research, 2.4 Prototype Scope & Design, 3.2 Desirability Testing, 3.3 Usability Testing

Engineering / Technical

Technical Feasibility — What can we actually build?

Key Activities: 0.4 Technical Landscape, 2.3 Assumption Mapping, 2.5 Prototyping, 3.4 Feasibility Validation

The Discovery Evolution

Artifacts evolve through stages. Key artifacts (highlighted) form the "North Star" that guides all subsequent work.

Stage 0
Problem Hypothesis → Research Plan
Stage 1
Job Statement → Job Steps Map → Customer Needs → Opportunities
Stage 2
OST Canvas → Evaluated Solutions → Job Stories → Prototype
Stage 3
D/U/F/V Evidence → Validated Solution → Confidence Assessment
Stage 4
Handoff Package → Success Metrics → Retrospective

Iteration Loops & Continuous Discovery

Discovery is not linear. These loops happen frequently as you learn and adapt.

Stage 3 Validation Loop

The most common loop. Test assumptions, learn from results, iterate on solution, re-test until confidence is sufficient.

Test → Learn → Iterate → Re-test ↺

Stage 2-3 Design Loop

When validation reveals solution gaps, return to Solution Design to refine before testing again.

Design → Prototype → Test → Refine ↺

Stage 1-2 Problem-Solution Loop

When solutions don't address needs well, return to Problem Discovery to ensure understanding is correct.

Frame → Ideate → Evaluate → Reframe ↺

Continuous Discovery

After launch, continue learning from real usage to inform the next discovery cycle.

Ship → Measure → Learn → Discover ↺
Stage 0

Initiation

Judgment Points Reference (JP1-JP19)

The 19 Judgment Points represent critical decision moments across discovery. Click any JP to see detailed guidance, pitfalls, and examples.

JP1Are the signals strong enough to warrant discovery investment?
JP2Have we selected the right customer segments to research?
JP3Is the job-to-be-done clearly defined with validated job steps?
JP4Are we pursuing the highest-value opportunities (score > 12)?
JP5Is the problem scope appropriately bounded for this discovery?
JP6Have we explored sufficient solution options?
JP7Are we pursuing the best solution candidates?
JP8Have we identified the assumptions that must be true?
JP9Are we testing the riskiest assumptions first?
JP10Is the prototype scope appropriate for testing?
JP11Are experiments well-designed to test critical assumptions?
JP12Are we interpreting test results accurately?
JP13Can we distinguish meaningful patterns from noise?
JP14Is our confidence level appropriate to the evidence?
JP15Should we proceed, pivot, or stop based on evidence?
JP16Have we defined clear, measurable success criteria?
JP17Are we tracking the right signals post-launch?
JP18Did we achieve intended outcomes? What does it mean?
JP19What did we learn and how do we capture it?

Domain 1: Problem Judgment (JP1-JP5)

Determines whether you're pursuing something worth solving. Errors here compound through everything that follows.

Domain 2: Solution Judgment (JP6-JP10)

Covers decisions about what to build and how. Bridges understanding to testing.

Domain 3: Validation Judgment (JP11-JP15)

Covers decisions about evidence and confidence. Translates test results into decisions.

Domain 4: Learning Judgment (JP16-JP19)

Covers decisions about outcomes and organizational learning. Closes the loop back to capability improvement.

Discovery vs. Engineering Work

Discovery is for work that changes what users can do or how they experience the product. Bug fixes, technical debt, and infrastructure work are engineering-led.

✓ Requires Discovery

  • • New Product / Venture
  • • New Feature (Major or Minor)
  • • Optimization (user-facing)
  • • Spike / Experiment

Validates user value: Do users need this? Will it work for them?

✗ Engineering-Led (No Discovery)

  • • Bug Fix / Defect
  • • Technical Debt
  • • Security / Compliance
  • • Infrastructure

Validates technical correctness: Does it work? Is it maintainable?

Escalation Triggers: Engineering work graduates to discovery if: "bug" is actually a design gap, fix requires UX change, tech debt has user-facing performance impact, or API changes affect external developers.

Discovery Types & Interview Guidance

Discovery Type Interview Target Prototype Fidelity Timeline
New Product / Venture 10-15 interviews Low → High 8-12 weeks
Major Feature 8-12 interviews Medium → High 4-8 weeks
Minor Feature 5-8 interviews Medium 2-4 weeks
Optimization 3-5 interviews Low-Medium 1-2 weeks
Spike / Experiment 3-5 interviews Varies 1-2 weeks

Key Artifacts Reference

Artifact Created In Used By Description
Job Statement Stage 1 (1.3) All subsequent The validated high-level job customers are trying to accomplish
Job Steps Map Stage 1 (1.3) Stages 2, 3, 4 Complete workflow showing all steps to accomplish the job
Customer Needs Stage 1 (1.3-1.5) Stage 2 OST Pain points at each job step with I/S scores
Opportunity Scores Stage 1 (1.5) Stage 2 Prioritized list using ODI algorithm (I + (I-S))
OST Canvas Stage 2 (2.1) Stages 2, 3 Visual tree connecting outcomes to solutions
Job Stories Stage 2 (2.4) Stage 3 Bridge from JTBD to development with acceptance criteria
Assumption Map Stage 2 (2.3) Stage 3 All assumptions by type (D/U/F/V) prioritized by risk
Confidence Assessment Stage 3 (3.7) Gate 4, Stage 4 Overall confidence by dimension, threshold 75%
Handoff Package Stage 4 (4.1) Development Complete documentation for development team