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This past week I was in London speaking at Mind the Product. As usual, the Mind the Product team hosted a phenomenal event. You can watch the video here:
Full Transcript
This transcript is the script of the talk as it was written. It is not word-for-word the talk as given.
Hi everyone, I’m thrilled to be here today. I’m excited to introduce a visual critical thinking tool I’ve been developing, which I believe can significantly enhance how product teams operate. To truly illustrate its value, I’ll start with a relatable story about a product challenge, setting the stage for understanding this tool.
In 2008, I was a product manager at a startup focused on building online communities for university alumni associations. Like many product teams, we faced our share of hurdles.
Initially, when a new community launched, alumni would flock to explore their site. However, over time, traffic would consistently dwindle to a mere trickle.
While alumni associations, our direct customers, were satisfied with our product, the alumni themselves, our end-users, were not fully engaged. Each launch saw an initial surge of activity as alumni checked out their new platform. But this excitement was short-lived, and engagement predictably declined.
Our user research revealed that alumni loved the messaging feature within their community. They used it to seek advice on diverse topics, from career transitions to finding housing in new cities. This was precisely the type of interaction we aimed to foster.
The core issue? Our system inadvertently enabled users to spam their entire alumni network. Alumni in Dallas were receiving irrelevant messages about items for sale in Chicago, rental properties in Boston, and internships in San Francisco.
We recognized that to boost engagement, we had to address this problem of unwanted messages. Reducing spam was crucial to improving the user experience and fostering a more valuable community environment.
If you’re anything like me, your mind is already racing with potential solutions to this spam problem. But when I posed the challenge to my team and suggested a brainstorming session, I received an unexpected response. Seth, one of our engineers, immediately proposed, “Let’s integrate Google Maps!” Seth envisioned leveraging the Google Maps API to incorporate a map displaying the global locations of alumni.
I was taken aback. Seth’s suggestion seemed completely detached from the spam issue we were trying to solve. I struggled to see how Google Maps would help us reduce unwanted messages. When I questioned Seth, he admitted, “Oh, it won’t, but it will drive engagement because it’s cool!” Seeking support, I turned to the rest of the team, and to my dismay, they concurred with Seth. Maps were deemed “cool” and engaging.
At that moment, I lacked the vocabulary to articulate my frustration. Intuitively, I felt that simply building “cool” features wasn’t sufficient. Knowing alumni locations didn’t strike me as a pressing need, and adding Google Maps felt like a superficial gimmick.
This anecdote isn’t about proving Seth wrong and myself right. The reality, as we’ll soon see, is more nuanced. It’s a story about my struggle as a product manager to involve my team in product decision-making regarding what to build, while lacking the tools to facilitate productive collaboration.
Today, as a product discovery coach, I observe this scenario repeating across numerous teams. We often struggle to bridge the gap between a desired outcome, like increased engagement, and the execution of solutions that effectively achieve that outcome.
To address this gap, I began deconstructing the problem, and my analysis revealed several recurring patterns.
The Pitfalls of Idea Fixation
One common pitfall is that we fall in love with our initial ideas. This emotional attachment often prevents us from critically evaluating their merit.
It’s natural for us to generate ideas quickly. Upon identifying a need, we often jump to a solution almost instantaneously.
This rapid solution generation can be satisfying, leading us to develop an emotional connection to our ideas.
Consequently, when we become enamored with an idea, we neglect to examine it critically. We fail to pause, reflect, and ask the crucial question: “Is this idea actually good?”
This is precisely what happened with Seth. He discovered the Google Maps API and became enthusiastic about its potential. Driven by excitement, he shared his idea, and the team quickly shared his enthusiasm, overlooking whether it truly addressed the core problem.
The Limitation of Narrow Idea Consideration
Another critical mistake is that we don’t consider a sufficient breadth of ideas.
When we become fixated on a single idea, we limit our exploration of alternative solutions.
My team, captivated by the Google Maps concept, was eager to start building immediately. They sought a quick solution to boost engagement, focusing solely on this singular idea.
While the Google Maps idea might indeed hold potential, research on brainstorming techniques demonstrates that generating a larger quantity of ideas leads to higher quality ideas overall.
Generating more ideas leads to generating better ideas. – Tweet This
Crucially, exploring multiple ideas allows us to make informed decisions through comparison and contrast, rather than settling for a simple “whether or not” evaluation of a single idea.
Evaluating “Is this idea good or not?” is challenging because “good” is treated as an absolute quality.
Instead, we should frame our decision-making as a compare and contrast exercise: “Which of these ideas appears most promising?” This approach is more effective because it acknowledges that “good” is a relative attribute.
Consider Usain Bolt running alone on a track. Is he fast? It’s difficult to judge. Now picture him racing against other runners. His speed becomes undeniably apparent. A compare and contrast approach makes evaluating relative qualities much easier.
Ask “compare and contrast” questions, not “whether or not” questions. – Tweet This
For those who believe they already consider numerous ideas, you likely do. Many teams generate a high volume of ideas. However, the issue often lies in the focus of idea generation, a point I will revisit shortly.
Returning to my team’s challenges, we not only became attached to our initial idea and failed to explore alternatives, but we also…
Lack of Alignment on Target Opportunity
Another critical oversight was that we didn’t achieve alignment on the target opportunity or the specific problem we were aiming to solve.
Seth’s Google Maps idea frustrated me not because I believed it was inherently bad, but because it seemed irrelevant to the problem I was focused on solving.
However, I failed to ensure that my team was genuinely aligned on the problem definition before diving into idea generation. Consequently, while Seth was focused on the overarching goal of engagement, he wasn’t addressing spam reduction, the specific problem I prioritized.
Even when teams do agree on an opportunity…
Insufficient Opportunity Exploration
A further challenge is that we rarely consider a sufficient range of opportunities.
Both Seth and I entered our brainstorming session already fixated on a single opportunity.
I assumed spam reduction was the primary opportunity, while Seth aimed to facilitate connections among alumni in the same geographic area. We were each operating within a limited scope, considering only one opportunity.
Similar to idea evaluation, we should avoid “whether or not” questions when prioritizing opportunities. Instead of asking, “Is this opportunity worth pursuing?” we should ask, “Which of these opportunities appears most promising?” This requires having a set of opportunities to compare and contrast. Without this broader perspective, we risk solving problems that are ultimately insignificant.
We should have initially stepped back to consider: “What are all the opportunities that could potentially boost alumni engagement?”
Product teams often fail to explore enough opportunities before rushing into solutions. – Tweet This
So, how can we avoid these common pitfalls and enhance our critical thinking in product development?
Opportunity Solution Tree: A Visual Thinking Tool
To address these challenges, I want to introduce the concept of an Opportunity Solution Tree. This tool helps visualize your thinking and facilitates better decision-making.
Anders Ericsson, in his book Peak, summarizes the key distinctions between experts and novices.
I draw upon the work of Anders Ericsson, author of Peak, who dedicated his career to understanding the differences between novices and experts. He argues that experts possess more sophisticated mental representations than novices.
He defines mental representations as:
“… representations are preexisting patterns of information—facts, images, rules, relationships, and so on—that are held in long-term memory and that can be used to respond quickly and effectively in certain types of situations.”
The primary advantage of sophisticated mental representations is their ability to aid in understanding, interpreting, organizing, and analyzing information.
He further emphasizes, “The key benefit of mental representations lies in how they help us deal with information: understanding and interpreting it, holding it in memory, organizing it, analyzing it, and making decisions with it.”
This is precisely what product teams need – a mechanism to understand, interpret, organize, and analyze information effectively to make superior product decisions.
Reflecting on my team’s challenges, I realized the issue stemmed from differing mental representations. I brought deep user knowledge from recent user research, while Seth possessed technical expertise regarding the Google Maps API.
We both entered the brainstorming session with distinct information patterns and relied on our individual mental representations for decision-making.
However, effective product teams require rapid decision-making based on a shared mental representation of their collective knowledge.
Product teams must make decisions based on their combined knowledge. – Tweet This
The opportunity solution tree emerged as my answer to the question: “How can we externalize our individual mental representations and align our teams around a shared understanding?”
Starting with a Clear Desired Outcome
The foundation of an Opportunity Solution Tree is starting with a clear desired outcome.
A product team must have a well-defined objective.
My team’s desired outcome was clear: to increase alumni engagement.
However, as illustrated by my team’s experience, a clear outcome alone isn’t sufficient. We needed to delve deeper and ask, “What factors will drive engagement?” Before jumping to solutions, we should have mapped out the opportunity landscape.
Opportunities can be viewed as customer needs or pain points, but also encompass areas for delight and replicating successes.
Research-Driven Opportunity Identification
Opportunities should emerge from generative research, specifically customer interviews and observations. To maintain a user-centric approach, framing opportunities in customer language is beneficial.
Opportunities should stem from generative research—customer interviews and customer observations. – Tweet This
My team had recently completed alumni interviews, providing a rich source of potential opportunities, such as:
We should have leveraged our customer interviews to identify key opportunities.
- “I receive too much email.” – My identified opportunity.
- “I’m moving to a new city and want to connect with local alumni.” – Seth’s opportunity.
- “I need assistance finding a job.”
- “I want to stay connected with my alma mater.”
- “I’m interested in knowing what my college friends are doing.”
- “I’m looking for engaging content to read or learn.”
- “I want to follow my school’s sports teams.”
- “I’m seeking to hire recent graduates.”
- “I’m willing to donate but want to understand the impact.”
- “I’d like to contribute back to the community.”
- “I would enjoy mentoring current students or recent graduates.”
This list reflects direct feedback from our alumni interviews.
The common next step is to prioritize this list, asking which opportunity is most critical to address.
However, comparing aspirational opportunities like “I’d like to give back to the community” with specific needs like “I want to hire a recent grad” is ineffective. Prioritizing a list of dissimilar items is inherently challenging.
Furthermore, the items on this list are not entirely distinct. Hiring a graduate or mentoring a student are both forms of community contribution. We’d be comparing apples and oranges, hindering effective prioritization.
Avoid prioritizing a list of dissimilar and overlapping items. – Tweet This
Opportunity Solution Tree for Simplified Prioritization
The Opportunity Solution Tree simplifies prioritization by grouping similar opportunities.
Grouping related opportunities makes the prioritization process more manageable. In our example, we can categorize the alumni feedback into three distinct groups:
- “I need help.”
- “I want to stay connected to my alma mater.”
- “I want to give back to the community.”
Instead of grappling with a lengthy list, we can initially prioritize these three broader categories.
Our research indicated that the most prevalent opportunity was “I need help.”
Consider where my “I get too much email” opportunity now fits. It falls under the broader “I need help” category, specifically as a barrier to effectively receiving helpful information.
Suddenly, Seth’s idea appears more relevant.
With this structured approach, Seth and I could have elevated our discussion. Instead of debating “too much email” versus “alumni proximity,” we could have focused on prioritizing the top-level opportunity categories. Agreeing that “I need help” was paramount for alumni would have been easier. We could then have shifted our focus to prioritizing the sub-opportunities within “I need help.”
However, I might have argued that “I need help” is intrinsically linked to “I get too much email.” Effectively connecting those needing help with those offering it is hampered if users are overwhelmed by irrelevant messages.
This realization suggests our initial opportunity structure wasn’t optimal. If opportunities are inherently connected, they should be positioned closer in the tree to reflect that relationship. Let’s refine the structure.
Iterating on Opportunity Structure
Opportunity structures are not fixed and can be adjusted. The structure should reflect customer feedback and facilitate sound prioritization decisions.
There isn’t a single “correct” way to structure opportunities. The structure should reflect insights from customer interviews and support effective prioritization.
Firstly, I combined “I want help” and “I want to give back” into a single overarching opportunity: “I want to connect with other alumni.”
Beneath this, we have:
- “I want to connect with alumni professionally.”
- “I want to connect with people near me.”
- “I don’t know who to connect with.”
This revised structure brings both sides of the alumni network – those seeking help and those offering it – closer together under a common opportunity. This simplifies prioritizing different connection types (professional, location-based, etc.) without favoring one group over the other.
This revised structure also minimizes the conflict between my perspective and Seth’s. We could both agree on focusing on the “I want to connect with other alumni” branch. Our disagreement would then narrow to which sub-opportunity is most critical. This allows us to use data to resolve our differences, for example, by asking: “How many alumni want to connect with local alumni?” versus “How many alumni struggle to identify relevant connections?”
Finding the optimal structure may require several iterations. The key is ensuring it accurately reflects customer insights and enables effective decision-making regarding prioritization.
The structure of your opportunities should reflect your findings from customer interviews. – Tweet This
Remember, there are no definitive right or wrong answers in structuring your tree. The structure will evolve as your team gains deeper customer understanding. The value of visualizing your thinking lies in facilitating team alignment and resolving differing perspectives.
Once satisfied with the opportunity structure, you can move on to generating solutions.
Addressing Idea Overload
Earlier, I mentioned the challenge of not considering enough ideas, which might not resonate with everyone. This is because many teams actually face the opposite problem: too many ideas. Let me clarify.
The issue isn’t a lack of ideas overall, but rather a lack of ideas for a specific target opportunity. Teams may generate numerous ideas, but they are often scattered across various parts of the opportunity tree, as shown here:
The true benefit of generating numerous ideas is to move beyond the initial, obvious solutions, stimulate creativity, and arrive at truly innovative approaches. Brainstorming across the entire tree may yield many ideas, but these tend to be superficial, first-level ideas.
This approach not only diminishes the creative potential of brainstorming, but also results in a collection of solutions that are difficult to prioritize. Remember, prioritizing a diverse list of unrelated items is challenging.
Focused Ideation on a Target Opportunity
Instead of scattered ideation, focus idea generation on a single, prioritized target opportunity. Choose a target opportunity by prioritizing row by row in the tree, and then generate a range of solutions specifically for that opportunity.
Instead, we should delve deeply into a single opportunity, generating multiple solutions to compare and contrast and determine the best approach.
I advocate for generating a substantial number of ideas for a single target opportunity.
Generate ideas for one target opportunity, rather than across multiple opportunities. – Tweet This
After generating these ideas, the natural inclination might be to prioritize the list and immediately experiment with the top idea. However, this leads back to a “whether or not” decision: “Is this top idea good or not?” Instead, frame the decision as a compare and contrast exercise: “Which of these solutions appears most promising?” When starting with numerous ideas, I recommend two methods for comparison and contrast.
Dot Voting for Idea Selection
First, use dot voting to narrow down a large list of ideas to a manageable set of 3-5. Research indicates that groups are more effective than individuals at evaluating ideas, and dot voting provides a quick way to gather team input.
Experimentation for Solution Comparison
Next, use experiments to compare and contrast the remaining 3-5 ideas to identify the most promising solution.
Utilize dot voting to reduce a large idea list to a smaller set. Employ experiments to evaluate the smaller set. – Tweet This
A crucial point: Most teams use experiments to validate a single idea – a “whether or not” approach. I advocate using experiments to choose amongst a set of viable ideas, facilitating a compare and contrast decision.
The most effective way to do this is to identify the key assumption underlying each idea and then design experiments to test these assumptions.
Run experiments to compare and contrast your top solution ideas.
For example, if our top solutions for reducing email spam are: recommending message recipient criteria based on location, automatically matching messages with recipients, and sending messages only to friends-of-friends, key questions to test for each solution might be:
- Will users seeking help trust our recipient recommendations?
- Test: Prototype the user interface and gauge user response.
- Can we accurately predict suitable message recipients?
- Test: Machine learning team conducts feasibility experiments.
- Are friends-of-friends more likely to offer help?
- Test: Analyze database to see if friends-of-friends respond more to past messages.
A common question is: “How do I determine if experiment results are good?” For example, is a 15% conversion rate sufficient? This is akin to asking, “Is Usain Bolt fast?” when he runs alone. It’s hard to judge in isolation. However, by experimenting with multiple solutions, you can ask, “Which solution performs best based on the data?” – a much easier question to answer, just as Usain Bolt’s speed is clear when compared to other runners.
Use experiments to choose between solutions, not simply to validate a single solution. – Tweet This
Benefits of the Opportunity Solution Tree
The Opportunity Solution Tree offers numerous benefits.
If you, like me, aim to involve your entire team in product decisions but encounter challenges like my Google Maps scenario or team disagreements, I recommend adopting the opportunity solution tree.
Taking the time to visually map your thinking helps teams identify and avoid common critical thinking errors, such as creating “whether or not” decisions instead of compare and contrast decisions.
The tree also serves as a discovery roadmap, aligning teams around a shared understanding of the opportunity space and potential paths to achieving desired outcomes.
Like traditional roadmaps, it facilitates communication of learning and progress to leadership and the wider company.
Your opportunity solution tree acts as a discovery roadmap—facilitating team alignment and communication. – Tweet This
Getting Started with Your Opportunity Solution Tree
Here are tips to begin using your own Opportunity Solution Tree.
Use these tips to get started with your own opportunity solution tree.
Begin with a clear desired outcome.
Next, map out the opportunity space, ensuring opportunities are derived from generative research: customer interviews and customer observations.
Experiment with different opportunity structures. Different structures reveal different possibilities.
Prioritize opportunities row by row to select a target opportunity.
Focus idea generation specifically on your target opportunity.
Finally, run experiments to evaluate your set of potential solutions.
If you implement an Opportunity Solution Tree, I’d be interested to hear about your experience. Feel free to email me or reach out on Twitter. For further reading on the research referenced, I’ve compiled a list of sources for you.
Thank you.
