The Opportunity-Solution Tree (OST) is a powerful framework that can help you focus your efforts and make better decisions as you build your business.
It is a hierarchical visual framework for systematically exploring the opportunities and potential solutions related to a specific problem or goal. It was developed by Teresa Torres, an expert in product discovery, to help product teams identify the best opportunities and make more informed decisions.
The OST consists of three main elements: the Goal (also called Objective, or Expected Outcome), Opportunities (also called Themes), and Solutions. The fourth element, Experiments, is a modern product discovery class of techniques for achieving solution validation as quickly and inexpensively as possible.
- Goal: The Goal is the desired outcome you want to achieve. Best of the goal is stated in a way that is clear, measurable, and achievable in order to set the direction for your exploration.
- Opportunities: Opportunities are the customer needs, pain points, or desires that, when addressed, can help you reach your goal. They are derived from user research, data analysis, and domain expertise. Opportunities should be ranked based on their potential impact and aligned with your business strategy.
- Solutions: Solutions are the possible ways to address the identified opportunities. Each opportunity may have multiple potential solutions, and you should generate as many ideas as possible to evaluate and iterate on them.
- Experiments: Experiments are the activities that are undertaken to validate the efficacy of the solution in achieving the goal.
*C. Todd Lombardo, Bruce McCarthy, Evan Ryan, Michael Connors - Product Roadmaps Relaunched: How to Set Direction while Embracing Uncertainty
Here are the steps to create an Opportunity-Solution Tree.
- Define your Goal: Start by setting a clear and measurable goal that aligns with your business strategy.
- Discover Opportunities: Conduct user research, analyze data, and use your domain expertise to uncover the most promising opportunities that can help you achieve your goal.
- Generate Solutions: Brainstorm different ways to address the identified opportunities. Be creative and encourage divergent thinking.
- Evaluate and Prioritize: Assess the potential impact and feasibility of each solution. Rank them based on how well they align with your goal and business strategy.
- Experiment, Iterate and Learn: As you test and refine your solutions, continue to iterate on the OST, adding new opportunities and solutions, and updating the tree based on your learnings.
The benefit of the OST technique is you can systematically explore a wide range of possibilities, make better decisions, and ultimately, build a more successful product or business. Remember that the OST is a living document; as you learn more about your customers and the market, you should continue to iterate and refine your tree to keep it up-to-date and relevant.
The reason it’s valuable is many teams generate a lot of ideas when they go through a journey-mapping or user experience-mapping exercise. However, it's easy to become overwhelmed by the mass of problems, solutions, needs, and ideas without a clear structure or priority.
The is a hierarchy that simplifies decision-making by breaking it down into objectives, themes, and solutions. Each decision becomes a comparison among a small number of similar things. By working through this hierarchy level-by-level, teams can focus their efforts on solving one problem at a time, making decision-making a breeze.
Opportunity-Solution Trees greatly improve the way teams make decisions by distinguishing solutions from problems, needs, or other opportunities, while also logically tying them together.
In addition to Teresa Torres’ book Continuous Discovery Habits, and her personal blog, another book that covers the concept is Product Roadmaps Relaunched. This is where I learned the technique.
Remember, the approach starts with a clear desired outcome. This hierarchy simplifies decision-making by separating decisions among objectives, themes, solutions, and experiments. Each decision is a comparison among a small number of like things. Working down this hierarchy, level-by-level, allows teams to narrow their testing and development efforts to solving one problem at a time.
