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opportunity-solution-trees skill

/skills/opportunity-solution-trees

This skill helps map customer opportunities to outcomes using Opportunity Solution Trees, enabling testable discovery and aligned product roadmaps.

npx playbooks add skill wdavidturner/product-skills --skill opportunity-solution-trees

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SKILL.md
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---
name: opportunity-solution-trees
description: Use when asked to "opportunity solution tree", "OST", "Teresa Torres", "map customer opportunities to outcomes", "structure discovery around opportunities", or "compare solutions for a customer need". Helps product teams connect outcomes to customer opportunities and test solutions with Opportunity Solution Trees (created by Teresa Torres).
---

# Opportunity Solution Trees

## What It Is

Use the Opportunity Solution Tree (OST) to connect a business outcome to the customer opportunities that drive it, then compare solutions and tests. The tree forces you to separate needs from ideas and keeps discovery tied to delivery.

## When to Use It

- Structure discovery around customer opportunities
- Tie customer needs to measurable outcomes
- Compare multiple solutions for the same opportunity
- Keep continuous discovery aligned with the roadmap
- Create a shared view of priorities with stakeholders

## When Not to Use It

- You are not doing customer research
- The solution is already decided
- The work is a commodity requirement with no real options
- You only need a quick one-off decision

## Patterns

Detailed examples showing how to apply OST correctly. Each pattern shows a common mistake and the correct approach.

### Critical (get these wrong and you've wasted your time)

| Pattern | What It Teaches |
|---------|-----------------|
| [opportunities-are-solutions](patterns/opportunities-are-solutions.md) | "Add a search bar" is a solution -- the opportunity is what's hard about finding things |
| [starting-with-solutions](patterns/starting-with-solutions.md) | Work backward from outcomes, not forward from feature ideas |
| [skipping-outcome](patterns/skipping-outcome.md) | Without a clear outcome, you can't evaluate which opportunities matter most |
| [interviewing-for-facts](patterns/interviewing-for-facts.md) | Collect stories, not preferences -- needs emerge from what happened |
| [conference-room-opportunities](patterns/conference-room-opportunities.md) | You can't hypothesize opportunities without customer research |

### High Impact

| Pattern | What It Teaches |
|---------|-----------------|
| [single-solution-thinking](patterns/single-solution-thinking.md) | Always compare at least 3 solutions for any opportunity |
| [opportunities-too-big](patterns/opportunities-too-big.md) | "Make it easier to use" is not actionable -- decompose into specific moments |
| [flat-tree-structure](patterns/flat-tree-structure.md) | Opportunities should nest hierarchically from broad to specific |
| [missing-experience-map](patterns/missing-experience-map.md) | Structure opportunities around the customer journey, not internal categories |
| [output-not-outcome](patterns/output-not-outcome.md) | "Launch feature X" is an output -- "Increase activation by 10%" is an outcome |
| [solution-testing-whole-idea](patterns/solution-testing-whole-idea.md) | Break solutions into assumptions and test the riskiest ones first |

### Medium Impact

| Pattern | What It Teaches |
|---------|-----------------|
| [tree-not-updated](patterns/tree-not-updated.md) | The OST is a living document -- update it weekly as you learn |
| [needs-not-heard](patterns/needs-not-heard.md) | Train your ear to hear opportunities customers don't explicitly state |
| [too-many-branches](patterns/too-many-branches.md) | Limit top-level opportunities to 5-7 for cognitive manageability |

## Core Structure (Overview)

- Outcome: the business result you are responsible for achieving
- Opportunities: unmet customer needs, pains, or desires
- Solutions: multiple ideas that address one opportunity
- Experiments: tests that validate the riskiest assumptions

## How to Apply It (Brief)

1. Define a measurable outcome.
2. Map the customer journey to frame opportunity areas.
3. Capture opportunities from real interviews (stories, not preferences).
4. Organize opportunities into a tree from broad to specific.
5. Generate at least three solutions per high-priority opportunity.
6. Test the riskiest assumptions before building.
7. Review and update the tree weekly.

## Common Mistakes

- Write solutions as opportunities (see [opportunities-are-solutions](patterns/opportunities-are-solutions.md)).
- Skip outcomes or use outputs instead (see [skipping-outcome](patterns/skipping-outcome.md), [output-not-outcome](patterns/output-not-outcome.md)).
- Only explore one solution (see [single-solution-thinking](patterns/single-solution-thinking.md)).
- Build from assumptions instead of research (see [conference-room-opportunities](patterns/conference-room-opportunities.md)).

## Deep Dives

Read these only when you need the extra detail.

- `references/ost-playbook.md`: experience maps, opportunity decomposition, interview prompts, assumption testing, checklists, and collaboration notes.

## Resources

**Books:**
- *Continuous Discovery Habits* by Teresa Torres
- *Nudge* by Richard Thaler

**Online:**
- Product Talk (producttalk.org)
- learn.producttalk.org

**Related Frameworks:**
- Jobs to be Done
- Design Thinking

Overview

This skill helps product teams create and use Opportunity Solution Trees (OST) to link measurable outcomes to customer opportunities and test candidate solutions. It embeds Teresa Torres' continuous discovery practices so teams separate needs from ideas, prioritize what to learn, and keep discovery tied to delivery. Use it to structure discovery, compare alternative solutions, and drive outcome-focused roadmaps.

How this skill works

The skill guides you to define a clear, measurable outcome, map the customer journey, and capture opportunities from real customer stories. It helps you organize opportunities hierarchically, generate multiple solutions per opportunity, and design experiments that validate the riskiest assumptions before building. The OST is treated as a living artifact to be reviewed and updated frequently based on learning.

When to use it

  • Structuring discovery work around customer opportunities and measurable outcomes
  • Evaluating multiple solution approaches for the same customer need
  • Planning experiments to test key assumptions before implementation
  • Aligning stakeholders on priorities and a shared visual roadmap
  • Decomposing broad problems into specific, testable opportunities

Best practices

  • Start from a measurable outcome, not from features or outputs
  • Collect stories in interviews; capture unmet needs, not preferences
  • Limit top-level opportunities to 5–7 and decompose from broad to specific
  • Generate at least three distinct solutions for each high-priority opportunity
  • Design experiments that test the riskiest assumptions first and update the tree weekly

Example use cases

  • A product manager maps opportunities to increase activation by 10% and compares onboarding flows versus targeted coaching
  • A discovery team uses customer journey mapping to expose specific opportunity areas for retention work
  • A startup tests three different acquisition concepts for the same customer job before committing engineering
  • A cross-functional team uses the OST to align roadmap bets with validated experiments and outcomes
  • Designers and researchers decompose vague goals like "make it easier to use" into actionable opportunities

FAQ

When is an OST not appropriate?

Avoid OSTs when you lack customer research, the solution is already decided, or the work is a commodity requirement with no meaningful options.

How often should the tree be updated?

Treat the OST as a living document and review or update it weekly as you collect new learning from interviews and experiments.