Opportunity Solution Tree (OST) Skill

Opportunity Solution Tree (OST)

Teresa Torres' framework from Continuous Discovery Habits. An OST visualizes the path from a desired outcome to the assumption tests that will validate or invalidate candidate solutions.

When to use this skill

Prioritizing discovery work for a quarter
Structuring weekly customer touchpoints
Mapping multiple solutions to one problem (vs jumping to solution)
Auditing whether roadmap actually moves outcomes
Coaching a team into continuous discovery rhythm
Pivoting discovery away from a dead-end branch

The tree structure

                  [Outcome]
                      |
        +-------------+-------------+
        |             |             |
   Opportunity   Opportunity   Opportunity
        |             |             |
     +--+--+      +--+--+      +--+--+
     |     |      |     |      |     |
   Solution Solution ...
        |
   +----+----+
   |         |
 Assumption  Assumption
   Test        Test

Levels

Outcome — a single, specific, measurable business / product outcome
Opportunities — customer needs/pains/desires that, if addressed, drive the outcome
Solutions — candidate ways to address each opportunity
Assumption tests — experiments validating that the solution will deliver

Clarify First

Before building the tree, confirm these inputs. If any is unknown or vague, ASK — do not assume:

[ ] The one outcome — a single, measurable, bounded outcome (the tree root; "ship X" or "make users happy" produces an invalid tree)
[ ] Customer evidence source — interviews / tickets / analytics that populate the opportunity layer (opportunities must come from research, not the team's imagination)
[ ] Engagement type — net-new tree vs auditing an existing roadmap (net-new builds top-down; an audit maps current solutions back onto outcomes)

Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.

Workflow

Step 1 — Pick ONE outcome

A good outcome is:

Behavioral (something users do) or business (revenue, retention)
Measurable (specific metric, baseline, target)
Bounded (this quarter / half)
Within team's influence

Examples:

"Increase week-1 activation rate from 28% to 40% by end of Q3"
"Reduce admin-panel time-on-task by 30%"
"Lift NRR from 105% to 115% by end of year"

NOT outcomes:

"Build [feature]" (output, not outcome)
"Improve user experience" (vague)
"Hit revenue target" (too high; needs to decompose)

Step 2 — Generate opportunities (from research)

Opportunities come from customer evidence, not the team's imagination:

Interview transcripts
Support ticket themes
Sales objection patterns
Behavioral analytics
Survey free-text

Opportunities are customer problems/needs, not solutions:

✓ "Users abandon during email-verification step"
✓ "Admins want to bulk-invite from CSV"
✗ "Add a CSV import feature" (that's a solution)

Step 3 — Cluster + dedupe opportunities

Group similar opportunities. Aim for 3-7 distinct opportunity clusters per outcome.

Step 4 — Generate multiple solutions per opportunity

For each opportunity, brainstorm 3-5 solutions. Resist jumping to one.

Multiple solutions matter because:

It surfaces underlying assumption: which solution best solves this?
Allows comparison of cost/effort
Reveals the team has bias toward a specific approach

Step 5 — Identify assumptions + tests

For each candidate solution, list:

Value assumption — will users want this?
Usability assumption — can users use it?
Feasibility assumption — can we build it?
Viability assumption — is it good for the business?

For each top assumption, design a cheap test (interview, prototype, A/B, landing page, prefab Wizard-of-Oz).

Step 6 — Run `ost_validator.py`

Audit for: missing outcome, opportunities written as solutions, single-solution branches, no assumption tests, tree without recent updates.

python3 project-management/discovery/opportunity-solution-tree/scripts/ost_validator.py \
  --input ost.json --format markdown

Step 7 — Iterate weekly

OST is a living artifact. Each week:

Add opportunities from new interviews
Move opportunities up/down based on evidence
Add solutions
Track assumption test results
Kill solutions that failed tests
Promote validated solutions to roadmap

Decision frameworks

Choosing the outcome

Wrong: "Build the new dashboard" (output) Wrong: "Make customers happy" (vague) Wrong: "Hit $20M ARR" (too high; many teams)

Right: One number a team can move. Decompose company OKRs to team-level outcome. See project-management/execution/north-star-metric.

Opportunity vs solution test

If the statement is a thing to build → solution. If the statement is a customer pain / desire / need → opportunity.

| Statement | Type | |-----------|------| | "Add bulk CSV import" | Solution | | "Admins want to invite many users at once" | Opportunity | | "Build SAML SSO" | Solution | | "Enterprise IT requires SSO to approve purchase" | Opportunity | | "Replace the onboarding video" | Solution | | "New users can't find the start button" | Opportunity |

Sizing opportunities

For each opportunity:

How many customers experience it (% of base)?
How severe (workaround cost in time/$)?
How often (frequency per user)?
Strategic fit with outcome?

Score = impact × frequency × strategic fit. Prioritize accordingly.

Multiple solutions discipline

Don't allow single-solution branches. If only one solution comes up:

Ask: "What if we couldn't build that?"
Borrow from analogous problems
Get team brainstorm input
Look at how competitors solve it

Goal: at least 3 candidate solutions per opportunity worth pursuing.

Assumption test ladder

For each solution, the cheapest test first:

Customer interview / desirability test (~$0)
Landing page / smoke test (~hours)
Wizard-of-Oz / concierge MVP (~days)
Low-fidelity prototype (~1 week)
High-fidelity prototype (~2 weeks)
A/B test in production (~weeks-months)

Spend the minimum to learn the most.

Common engagements

"Help me set up an OST for our team this quarter"

Confirm the outcome (1 number).
Pull existing discovery evidence; cluster into opportunities.
Brainstorm 3-5 solutions per top opportunity.
Identify top 3 assumption tests for the quarter.
Schedule weekly OST update rhythm.

"Our roadmap is full of features but outcomes aren't moving"

Map current roadmap to OST.
Identify orphan solutions (no opportunity → no outcome).
Identify gaps (opportunities without solutions in roadmap).
Reshape roadmap around outcome-supporting solutions.

"Audit our discovery practice"

Look at the OST: when last updated?
How many interviews per week feed it?
Are opportunities written as needs (not solutions)?
How many solutions per opportunity (1 = under-divergent)?
How many assumption tests in progress?

Anti-patterns to avoid

Outcome = output. "Ship X" is not an outcome.
Opportunities = solutions. Strip solutions out of the opportunity layer.
Single solution per opportunity. Force 3+ alternatives.
No assumption tests. Tree without tests = wishful thinking.
Static tree. Update weekly or it dies.
Tree built without customer input. Designed in vacuum; full of bias.
One huge outcome. Decompose to team-level.
All opportunities equally important. Prioritize explicitly.

References

references/ost-fundamentals.md — Teresa Torres framework deep
references/ost-anti-patterns.md — common failures + fixes

Related skills

project-management/discovery/identify-assumptions — assumption surfacing
project-management/discovery/brainstorm-experiments — test design
project-management/discovery/customer-interview-script — interview prep
project-management/discovery/interview-synthesis — turn interviews into opportunities
project-management/execution/north-star-metric — outcome definition
project-management/strategy-frameworks/lean-canvas — strategic context
product-team/research-summarizer — interview synthesis

Agent Skills: Opportunity Solution Tree (OST)

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