Naresh Ghawalkar
Menu
Framework Library
DiscoveryReferenced framework

Opportunity Solution Tree

A visual structure connecting a desired outcome to customer opportunities, possible solutions, and experiments.

Use it when: A team needs to align around an outcome.

Primary output: Outcome statement

Core principle: Frameworks support judgment; they do not replace evidence or accountability.

Opportunity Solution Tree visual diagram

Why it exists

The problem it solves

Teams jump from a business outcome to one favored solution without exploring the opportunity space or alternative approaches.

Ownership and attribution

Referenced framework

An established framework presented with attribution, application guidance, and portfolio-specific extensions.

Use guidance

When to use it

  • A team needs to align around an outcome.
  • Customer evidence reveals multiple needs or pain points.
  • Several solution options are being considered.
  • Continuous discovery needs a shared visual map.

Context matters

When not to use it

  • As a substitute for direct customer evidence.
  • When the desired outcome is undefined.
  • When every branch is treated as a committed roadmap item.

Method

Inputs and process

The framework is designed to produce decisions and learning, not simply artifacts.

01Desired product outcome
02Customer interview and observation evidence
03Opportunity statements
04Solution ideas
05Key assumptions and experiment options
  1. 01

    Set outcome

    Choose a measurable outcome the product team can influence.

  2. 02

    Map opportunities

    Organize customer needs, pain points, and desires from evidence.

  3. 03

    Generate solutions

    Explore multiple ways to address selected opportunities.

  4. 04

    Identify assumptions

    Expose desirability, usability, feasibility, viability, and ethical assumptions.

  5. 05

    Design experiments

    Choose tests that create decision-quality evidence.

  6. 06

    Update continuously

    Revise the tree as evidence and decisions evolve.

Decision quality

Key decision points

01

Is the outcome measurable and influenceable?

02

Is each opportunity grounded in evidence?

03

Have multiple solutions been explored?

04

Which assumption is most important and uncertain?

05

What evidence changes the tree?

Outputs

What it produces

  • Outcome statement
  • Opportunity map
  • Solution alternatives
  • Assumption map
  • Experiment backlog
  • Discovery decision record

Success

How it is measured

  • Opportunity evidence coverage
  • Solution alternatives considered
  • Assumptions tested
  • Experiment cycle time
  • Outcome movement

Skills

What it demonstrates

Opportunity mappingContinuous discoveryExperimentationOutcome alignmentEvidence synthesisFacilitation

Portfolio application

How I apply it

I adapt the tree for enterprise and AI products by adding assumption risk, evidence status, operational constraints, and human-oversight considerations.

Common pitfalls

How the framework is misused

  • Inventing opportunities in a workshop.
  • Turning the tree into a feature backlog.
  • Mapping too much without prioritizing.
  • Treating branches as mutually exclusive facts.
  • Failing to update the tree.

Interview preparation

Discussion prompts

  • How do you distinguish an opportunity from a solution?
  • How do you keep the tree evidence-based?
  • What enterprise constraints would you add?
  • How does the tree change roadmap conversations?

References

Attribution and sources

Opportunity Solution Trees - Product Talk

Established framework developed by Teresa Torres. This portfolio page explains my application and extensions.