A lot has changed since the dawn of project management. Project-thinking has significantly shifted into product-thinking, comprehensive upfront planning has evolved into more iterative, "plan-as-you-go" approaches towards value (as regarded by users) creation, and simply doing things a certain way because "it has always been done like this" has stopped being enough.
But, as much as we've progressed past the most traditional paradigms for creating products and services, there's one often overlooked but crucial aspect that during the last few years has seen some pretty interesting advances: Product Discovery. Also called Product Inception or the "Discovery Space" from a process perspective, Product Discovery merely focuses on exploring the different options people assess in order to decide what to build. The ultimate goal? To accelerate the learning process.
Product Discovery & Product Delivery
Through Product Discovery we consider meaningful questions to test the depth of our understanding of the product and the people that will use it (more on this later) with questions like:
- Are we meeting stakeholder needs?
- Do customers want our solution?
- Are we solving a problem customers care about?
- Can customers use our product?
- Are we driving towards a desired outcome?
The natural counterpart of Product Discovery is Product Delivery; it's what gives the discovery space meaning. After all, it wouldn't make much sense to build something without first thinking about what to build and why. Strictly referring to definitions, the Delivery space is all about building the actual product, with the ultimate goal of building and shipping it fast! There are other important considerations in the delivery space, like quality and supportability, but we won't focus as much on them here.
Modern product management is starting to think about Discovery and Delivery as intertwined and iterative constituents of the Product creation, not isolated parts that happen in specific stages of the product lifecycle. Product Discovery is better framed in means of Product Delivery, while the latter only can draw significant meaning from the former.
Despite this, there still was a heavy prevalence of traditional thinking about investing more resources in the Delivery space rather than the Discovery space. One of the most interesting developments in the Product Discovery space that has been how this phenomenon is transforming and tipping the scales towards a more balanced Discovery-Delivery ratio. This shift comes from the User Experience & Design thinking movement, and consists of asking one powerful question: are we solving the right problems for our customers?. The power of this question lies in how in essence it helps us to "frame our work as problems to solve" and to really put ourselves in the right perspective, to really scan and understand what problems – or to use a more adequate word, opportunities – we should resolve. We have to go back to our original Discovery questions and think deeply about what outcomes are we trying to achieve.
The Opportunity Solution Tree
One of the greatest tools I've found that really comes in handy for making sense of the Build-Measure-Learn cycle and guiding the Discovery space of Product creation is the Opportunity Solution Tree. It helps you beautifully keep tabs on the many ideas that might be shifting throughout the product evolution on a strategic level and then organize downstream tactical work in the Delivery space in an articulate manner.
The Opportunity Solution Tree is, conceptually speaking, a visual aid that helps the Product Discovery process through the organization of non-linear ideation flows, experimentation, and the identification of gaps. Simply put, an OST is a visual plan for how to reach a clear desired outcome. It was created by Teresa Torres , an awesome Product Discovery Coach whose ideas, posts, and talks inspired this post, out of a solution tree map that aims to streamline the discovery process and help make a better sense of its continuous evolution.
Here's what an Opportunity Solution Tree looks like:
As you can see, the Opportunity Solution Tree is primarily composed of 4 tiers: The Desired Outcome on the top, several Opportunities that branch out from the latter, then Solutions that could satisfy the identified Opportunities, and lastly, any Experiments that can serve as a measure of validation for Solutions. At this point, you might be wondering: what's all of this about? how can we use it? So for the sake of practicality let's explain things with the following scenario as an example:
- "I'm the manager of a recording studio that works with many record labels across the country, and one of my major concerns is customer retention & satisfaction; for a long time I haven't had as many returning musicians to record on my studio and record labels aren't sending me as many artists as before. What can I do about this?"
After conducting user interviews and assessing the Studio customer base's satisfaction with its services, we were able to map things out. The example will be illustrated with the Opportunity Solution Tree template by Miro, our preferred e-Whiteboard tool.
First, Define a Clear, Desired Outcome You Want to Achieve
To put it as a simple question: What does success look like? Outcomes are all about betterment from the point of view of the users, customers, or organizations associated with a given product. Perhaps there are specific behaviors or pain points that you'd like to address. Generally speaking, it's a good thing to frame outcomes as something that can be measured. If you use OKRs, then you can use one of your Key Results to answer this question. If you don’t, then you can use any other metric that can represent progress in means of your desired outcome. The key part here is that the whole team must be in agreement with the desired outcome.
It's also important to note that even if your team might want to take on many different outcomes at the same time, each must be represented in its own Opportunity Solution Tree.
Back to our sample scenario: We know for a fact that the desired outcome revolves around improving the customer retention and satisfaction at the recording studio, but in order to make it relevant, we must address specific key results for it:
Second, Identify Opportunities to Drive the Desired Outcome
As Teresa Torres states thoroughly in her blog posts and talks, most of us are prone to jump directly into solutions without really assessing the actual problems in detail. But this exercise is all about identifying key market opportunities; the best way for doing so is to learn about the customers as much as possible: Who are they? What do they need? What are their pain points, and what problems they are trying to solve?
You'll then be in a better position to start thinking about Opportunities, i.e., how we could reach the previously defined Outcome in a satisfactory way. Keep in mind that this process is fueled by your research.
Back to our scenario: After doing some research, we found out the main pain points for users and customers of the studio. These can be our Opportunities, that if solved, could help drive our desired outcome:
Third, Generate Solutions that Deliver on Those Opportunities
At this point, we're ready to start thinking about the Solutions that could fuel all the Opportunities we already identified. This is a great place to conduct an open brainstorming discussion with your team, making sure that everyone's opinion and ideas are accounted for. The solution ideation can also greatly benefit from having partners from different areas of expertise.
Back to our scenario: After brainstorming several solutions for the opportunities we discovered, we ended with something like this:
Fourth, Iterate and Experiment
Once you've settled for potential solutions and have a clearer outlook on how to move forward, you can start brainstorming experiments for testing them. This will give you the empirical ground to continuously drive your efforts forward and keep track of the evolution of Opportunities, potential Solutions, and any experiments you might conduct to test them.
There are a couple of experiments that we could conduct and measure for impact in our example scenario, this will help us understand if we are on the right track and should persevere or if we should pivot and reassess our efforts:
It's also noteworthy to remember, as previously stated, that Discovery is best framed as an iterative process; don't limit your exploration and make sure you come back to your Opportunity Solution tree as a baseline of your efforts and learning. A straightforward way of guiding this process is to use Teresa Torres' Continuous Discovery framework, which puts the Opportunity Solution Tree into a wider and more holistic context:
In this way, you'll be able to seize the benefits of this powerful tool to facilitate the way in which you navigate all of your products.
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