Opportunity Solution Tree (OST)
Last christmas I wrote a couple of articles for Bekks advent calendar. This is an English translation for my Norwegian 🇳🇴 post titled Prøv OST før jul, enjoy!
“What should we create next?” This is always an important question in a product team. Opportunity Solution Tree (OST) is a useful technique for answering this question, helping us to systematically explore the team’s solution space.
What is Opportunity Solution Tree
Opportunity Solution Tree was popularized by Teresa Torres as a tool to help product teams find the best solutions for the most valuable opportunities or problems ahead of them. The method makes it easier to avoid common pitfalls such as jumping to solutions too early (the building trap), spending too much time on analysis before experimenting (the analysis trap), or spending too much time solving the wrong problem.
“How can we find the most valuable contribution our team can make now?”
Opportunity Solution Tree is one way to do this, and the method consists of four main components:
- Ambition - start by defining a clear and concrete goal. This gives direction for the rest of the process.
- Opportunities or Problems - identify a range of opportunities, problems, or user needs that can help you reach the goal. This step requires an understanding of the domain and the users, preferably from already acquired insights.
- Solutions - generate different solution ideas for each identified opportunity.
- Experiments - find experiments that allow us to test the solution to verify that it actually works in reality. These typically become development tasks.
These elements are put together in a tree, and the team chooses the path in the tree they believe in most at any given time. Experiments are developed and tested in production. If the experiments have the desired effect, fantastic! We are one step closer to success. If not, try a new experiment. Continue this way until the ambition is reached or patience runs out.
Practical Implementation
Let’s go through how Opportunity Solution Tree can be used in a product team. We assume that the team is interdisciplinary, at least has competence in both development and design, has a product that can be changed in production, and that the effects of the product can be measured (qualitatively or preferably quantitatively).
Ambition
The first step is for the team and the organization to agree on an ambition. The ambition is the effect we want from what we create. This can be business value (value for the organization), user value (users can use the product for something useful) or ideally both at the same time. Ambitions can, of course, be very different from place to place, but traditionally we have three different archetypes of ambitions:
- Learning Ambitions - when we tackle something new and don’t know exactly what we should achieve or what is realistic.
- Hypothesis-Driven Ambitions - when we know well what we want to achieve, but are unsure of the way there.
- Milestone Ambitions - when we know well what we want to achieve, and we have a good idea of what it takes to reach that ambition.
The type of ambition that makes sense for the team depends on the degree of understanding and the maturity of the team and the organization. Milestone ambitions are suitable for well-researched issues, learning ambitions when we are uncertain. Hypothesis-driven ambitions are most often fitting.
The ambition we choose may come from an existing goal management process, for example, an ambition or a key indicator from OKR, but it must still have certain properties:
- It makes sense on its own, creates focus, and makes it easier to say no.
- It has the potential to be important and deliver value.
- The team can influence the outcome of the ambition.
The last point is particularly important. Teams that have ambitions without being able to influence them have poor conditions for success.
Opportunities / Problems and Solutions
Now it’s time for at least one workshop with the whole team and other stakeholders with deep domain knowledge. No ideas are wrong here; the goal is to come up with many suggestions for opportunities and problems first, then solution ideas. The team’s interdisciplinarity should shine, and all team members must contribute their competence and imagination.
Miro or another digital board is good for documenting what the team comes up with, but an analog session with post-its is also a classic. Just remember that workshop participants must feel safe that their contributions will be taken further. Forgotten notes on the workshop floor have low value.
Here the solution space should be explored, and the art is to actually dare to go where the good suggestions are. Forget the backlog, think outside the box, and be creative. Selection and reality orientation come afterward.
Experiments
This is the last step before actual changes to the product. It can be conducted in the same workshop as mentioned above, or in a separate session. As before, it’s a green zone, but this step is a bit more difficult: the experiments should actually be carried out, and the results of them must be measurable (or at least objective enough for us to say whether they succeeded or not).
Experiments are actual changes in the product that, if precise and carried out successfully, will enable the solution and thus reduce a problem or realize an opportunity on the way to the ambition.
Find the Golden Path
All points are put together into a tree, and the selection can begin!
We choose one path to explore first. The first step is easy, the ambition is already fixed. Then we choose one opportunity/problem, one of its solutions, and one experiment that can validate the solution.
This chosen experiment is the first thing the team will work on.
The selection can be difficult and should be based on the entire team’s expertise. However, a product team is not a democracy, so do not necessarily let dot-voting or other consensus processes determine the final choice. A good product or team leader ensures that the different professional fields in the team contribute their part and ensures that the choice is made based on knowledge and professional intuition, and not least, quickly!
To be able to choose the right experiment to start with, it is wise to consider the feasibility. Can we carry out this experiment right away, or is there something that prevents us? The faster experiments can be verified in production, the greater the chance of succeeding in creating value.
Summary
Opportunity Solution Tree is a powerful method for product teams that want to make informed decisions based on user insights and data. It helps teams focus on the most valuable opportunities while simultaneously verifying solutions effectively and systematically. By integrating Opportunity Solution Tree with other methods such as OKR, we can ensure that we set the right goals and find the best ways to achieve them. The method increases the visibility of the complexity in the domain around the team, and makes it easier to both communicate with the organization and actually deliver real value in the real world.