What is an Opportunity Solution Tree?
Last reviewed
An Opportunity Solution Tree is a visual map that connects a desired outcome to the customer opportunities that could move it, the solutions that could address those opportunities, and the experiments that test those solutions. Created by Teresa Torres, it makes the reasoning behind product decisions visible, so a team can compare options instead of committing to the first idea that appeared.
The short definition
A product team has one thing it is trying to change: an outcome. Between that outcome and the code they write sits a large space of possibilities, and the Opportunity Solution Tree is a way of drawing that space so it can be reasoned about.
The tree does not tell you what to build. It shows you what you are choosing between, and what you know about each option. That distinction is the whole point: it converts an argument about features into a comparison of problems.
The four layers
Every tree has the same four kinds of node, and each one answers a different question.
- Outcome — what change are we trying to create? One measurable outcome sits at the root.
- Opportunities— which customer needs, pains or desires, if addressed, would move that outcome? These are phrased in the customer's language and nest into sub-opportunities.
- Solutions — what could we build to address a given opportunity? Several per opportunity, so there is a genuine choice.
- Experiments — what is the cheapest test that would tell us whether this solution holds up? Attached to the solution they check.
The hierarchy is strict, and that is what gives the format its power. An opportunity belongs to exactly one outcome. A solution belongs to exactly one opportunity. If you cannot decide where a node goes, that is usually a sign the node is confused rather than the tree.
Where the format comes from
The Opportunity Solution Tree was created by Teresa Torres, a product discovery coach who writes at Product Talk. She began publishing about the format around 2016 and set it out fully in her 2021 book Continuous Discovery Habits, where it serves as the central artefact for organising ongoing customer research.
It is worth reading the original source. This guide explains the format and how we think about it in TreeFlow, but Torres is the authority on the method, and her writing goes into considerably more depth on facilitation and interviewing than a tool's documentation reasonably can.
Why teams use it
The recurring failure the tree addresses is committing to a solution before understanding the problem. A roadmap full of features looks like a plan, but it hides the decision that actually mattered: why this problem and not another one.
Three things change once a team works from a tree.
- Alternatives become visible. When three solutions sit side by side under an opportunity, the team is making a choice rather than defending an idea.
- Prioritisation moves up a level. Instead of ranking features against each other, the team compares opportunities, which is a more honest comparison because the options are the same kind of thing.
- Decisions leave a trace. Six months later the tree still shows which branch was chosen and what evidence supported it, which is the difference between a decision and a habit.
How to read a tree
A tree is diagnostic as well as descriptive. Its shape tells you things about the team that drew it.
- A wide, shallow opportunity layer usually means the team has collected themes but has not broken them down far enough to act on.
- One solution per opportunity means no comparison happened. The team recorded its existing plan rather than exploring.
- A branch with no experiments is a branch nobody has checked. That may be fine, but it should be a conscious call.
- Opportunities that read like features means the solution layer has crept upward, and the tree is now a roadmap in disguise.
Common mistakes
- Writing solutions as opportunities.The most frequent one. “Add SSO” is a solution; the opportunity is whatever pain SSO relieves.
- Treating the tree as a one-off deliverable. A tree drawn at an offsite and never revisited is a poster, not a working artefact.
- Skipping the experiment layer. Without tests, the tree records opinions in a tidy shape.
- Chasing several outcomes at once. If the root has three outcomes, you have three trees and no way to prioritise across them.
- Filling it in from memory. Opportunities that nobody heard from a customer are assumptions with good posture.
How it fits into continuous discovery
The tree is not a standalone technique. It is the artefact that makes continuous discovery manageable. Torres defines that practice as maintaining at least weekly customer touchpoints, run by the team building the product, in pursuit of a desired outcome.
Weekly conversations produce more input than anyone can retain. Each new observation has to land somewhere: it supports an existing opportunity, creates a new one, or speaks to a solution already under consideration. Without a structure to absorb them, the conversations become anecdotes that get quoted selectively in planning meetings.
What to build it in
Most teams draw their first tree on a whiteboard, and that is a reasonable place to start. The constraint appears later: a whiteboard stores shapes, so it cannot lay the tree out for you, cannot attach an interview quote to the opportunity it supports, and cannot show you which branches are unevidenced.
We built TreeFlow for the phase after the whiteboard, when the tree has to stay true for months. If you are weighing options, we have written honest comparisons with Miro, FigJam, Notion and Productboard, including the cases where the other tool is the better answer.
Frequently asked questions
What is an Opportunity Solution Tree?
An Opportunity Solution Tree is a visual map that connects a desired outcome to the customer opportunities that could move it, the solutions that could address those opportunities, and the experiments that test those solutions. It was created by Teresa Torres as part of her continuous discovery work, and it exists to make the reasoning behind product decisions visible.
Who created the Opportunity Solution Tree?
Teresa Torres, a product discovery coach and the author of Continuous Discovery Habits, created and popularised the format. She began writing about it publicly around 2016 and set it out in detail in the 2021 book.
What are the four layers of an Opportunity Solution Tree?
From the top down: the desired outcome, the opportunities that could move it, the solutions that could address each opportunity, and the assumption tests or experiments that check whether each solution holds up. Each layer answers a different question, and each node belongs to exactly one parent.
What is the difference between an opportunity and a solution?
An opportunity is a customer need, pain point or desire, described in the customer's terms. A solution is something you could build in response. If a statement names a feature, a screen or a technology, it belongs in the solution layer, not the opportunity layer.
How many opportunities should a tree have?
There is no fixed number, but the opportunity space should be broad enough to show real alternatives and structured enough to compare siblings. Teams usually start with a handful of top-level opportunities and break them down until each leaf is small enough to attack with a concrete solution.
Do you need a tool to build an Opportunity Solution Tree?
No. Many teams draw their first tree on a whiteboard or in a shared canvas, and that works well for a single session. A dedicated tool becomes useful when the tree needs to stay accurate over months and carry the evidence behind each branch.
Keep going
A worked example, a blank template and a step-by-step walkthrough.