Opportunity Solution Trees

Opportunity Solution Trees

Overview

A visual thinking tool introduced by Teresa Torres in 2016 that helps product teams organize discovery work, make assumptions explicit, and maintain alignment between solutions and desired outcomes. The tree structure forces teams to connect every solution idea to a customer opportunity and ultimately to a measurable outcome.

Core Principle

Product teams should map the path from desired outcomes through customer opportunities to potential solutions and experiments. This visualization prevents building features disconnected from customer needs and business goals.

The Four Layers

Layer 1: Outcome (Root)

The single business-relevant metric your team owns that reflects both customer and business value.

Characteristics:

• Measurable and trackable
• Owned by your team (not dependent on other teams)
• Reflects customer behavior change
• Time-bounded (target date)

Examples:

• "Increase weekly active users by 20% in Q2"
• "Reduce time-to-first-value to under 5 minutes"
• "Improve customer retention from 60% to 75%"

Layer 2: Opportunities (Branches)

Customer needs, pain points, desires, and jobs-to-be-done that, if addressed, will drive the outcome.

Discovery Sources:

• Weekly customer interviews
• Support ticket analysis
• Usage data patterns
• Customer feedback and surveys
• Jobs-to-be-done research

Structure:

• Multiple opportunities under one outcome (aim for 5-10 to start)
• Group related opportunities as sub-opportunities
• Prioritize based on impact potential and effort

Format: Frame as customer perspective

• "I need to understand pricing before committing"
• "I struggle to find relevant content quickly"
• "I want to collaborate without constant meetings"

Layer 3: Solutions (Leaves)

Potential ways to address each opportunity. Multiple solution ideas per opportunity to avoid anchoring on first idea.

Ideation Guidelines:

• Generate 3+ solutions per opportunity (prevents premature convergence)
• Range from incremental to transformative
• Include both product features and non-product solutions
• Challenge assumptions with "what if?" scenarios

Examples (for opportunity "I need pricing clarity"):

• Solution A: Display pricing calculator on product page
• Solution B: Provide personalized pricing in onboarding
• Solution C: Offer free tier to reduce commitment anxiety
• Solution D: Add comparison table with competitor pricing

Layer 4: Experiments (Tests)

Quick tests to validate or invalidate each solution before committing to production builds.

Experiment Types (ordered by speed):

1. One-question surveys
2. Interview-based prototype tests
3. Landing page tests
4. Wizard of Oz (fake backend)
5. Concierge (manual delivery)
6. Minimum viable product

Documentation:

• Assumption being tested
• Success criteria
• Method and timeline
• Results and learnings

Implementation Steps

Step 1: Define Your Outcome

Work with stakeholders to identify the one outcome metric your team will focus on for the quarter.

Good Outcome Test:

• Can you measure it weekly or monthly?
• Does customer behavior drive it?
• Can your team directly influence it?
• Is it meaningful to both business and customers?

Step 2: Discover Opportunities

Use continuous discovery to populate opportunity space:

• Conduct 2-3 customer interviews per week
• Ask about current pain points and workarounds
• Observe actual behavior, not stated preferences
• Synthesize patterns across interviews

Opportunity Identification Questions:

• "What prevents you from achieving [outcome-related goal]?"
• "Walk me through the last time you struggled with [related task]"
• "What workarounds have you created to deal with [pain point]?"

Step 3: Map Opportunities to Tree

Organize opportunities as branches under your outcome:

• Start with 5-10 top-level opportunities
• Group related opportunities as sub-opportunities
• Use customer language, not internal jargon
• Make relationships explicit

Visual Mapping Tips:

• Use digital tools (Miro, Mural, FigJam) for collaboration
• Color-code by confidence level (validated vs. assumed)
• Show depth through indentation or nested grouping
• Keep entire tree visible on one screen/board

Step 4: Select Target Opportunity

Choose one opportunity to focus on based on:

• Impact potential: How much will this move the outcome?
• Customer pain level: How severe is this problem?
• Confidence: How well do we understand this?
• Effort: How resource-intensive are likely solutions?

Use dot voting or weighted scoring with your product trio.

Step 5: Generate Multiple Solutions

For selected opportunity, brainstorm diverse solution approaches:

• Set timer for 10 minutes of rapid ideation
• Aim for 5-10 solution ideas minimum
• Include both obvious and creative options
• Don't evaluate or critique during generation

Divergent Thinking Prompts:

• "What if we had unlimited engineering resources?"
• "How would [competitor] solve this?"
• "What's a non-digital solution?"
• "What would delight customers beyond expectations?"

Step 6: Design Assumption Tests

For promising solutions (typically 2-3), identify:

• Desirability: Will customers want this?
• Feasibility: Can we build this?
• Viability: Should we build this (business case)?

Design fastest test that answers the most critical assumption first.

Step 7: Run Experiments and Update Tree

Execute tests, document results, and update tree:

• Green: Validated (evidence supports pursuing)
• Yellow: Uncertain (mixed results, needs more testing)
• Red: Invalidated (evidence suggests abandoning)
• Archive invalidated branches but keep history

Practical Applications

Weekly Discovery Cycle with OST

Monday: Interview + Synthesis

• Conduct 1-2 customer interviews
• Add new opportunities to tree
• Refine existing opportunity descriptions

Tuesday: Prioritization

• Review entire tree with product trio
• Dot vote on highest-impact opportunities
• Select target opportunity for week

Wednesday: Solution Ideation

• Generate solutions for target opportunity
• Add to tree under selected opportunity
• Identify critical assumptions

Thursday: Experiment Design

• Create low-fidelity prototypes or test materials
• Define success criteria for experiments
• Schedule customer feedback sessions

Friday: Testing + Documentation

• Run experiments with customers
• Document results on tree
• Share learnings with broader team

Example Tree Structure

Outcome: Increase trial-to-paid conversion by 25%

 Opportunity: I don't understand pricing until too late
    Solution: Add pricing calculator to trial dashboard
       Experiment: Prototype test with 8 trial users
    Solution: Send pricing email after first value milestone
       Experiment: Manual email to 50 trial users
    Solution: Offer flexible payment plans

 Opportunity: I can't justify cost without seeing ROI
    Solution: Build ROI calculator based on usage
       Experiment: Wizard of Oz with 10 users
    Solution: Provide case studies matched to user profile
        Experiment: Landing page test with 3 case study variations

 Opportunity: I hit friction during onboarding
     Solution: Reduce setup steps from 8 to 3
        Experiment: Prototype new onboarding flow
     Solution: Offer concierge onboarding
         Experiment: Manual onboarding for 20 trials

Common Pitfalls

Solution-First Thinking

Wrong: Starting with solutions and retrofitting opportunities Right: Discover opportunities through customer research, then ideate solutions

If you start with "We should build X," you're doing it backwards. Start with "Customers struggle with Y."

Single Solution per Opportunity

Wrong: One opportunity � one solution � build it Right: Generate multiple solutions, compare through experiments

Multiple solutions reduce anchoring bias and increase odds of finding the best approach.

No Experiments Layer

Wrong: Jumping from solution ideas directly to delivery backlog Right: Test solutions before committing to production builds

OST without experiments is just wishful thinking. The experiment layer de-risks decisions.

Ignoring the Outcome

Wrong: Building OST as brainstorming exercise disconnected from metrics Right: Constantly asking "How does this opportunity/solution impact our outcome?"

If an opportunity doesn't plausibly drive your outcome, it doesn't belong on the tree.

Tree Becomes Static

Wrong: Creating tree once at quarter start, then ignoring it Right: Living document updated weekly with new insights

Your tree should evolve as you learn. Dead trees are useless trees.

Success Metrics

Tree Health Indicators

• Opportunity diversity: 8-12 opportunities at root level
• Solution breadth: Average 3+ solutions per pursued opportunity
• Experiment velocity: 2-3 experiments completed per week
• Update frequency: Tree modified at least weekly
• Team engagement: All trio members contribute to tree

Outcome Progress

• Metric movement: Progress toward target outcome
• Validated solutions: % of experiments that validate hypotheses
• Time to validation: Days from opportunity identification to experiment results
• Solution success rate: % of built solutions that move outcome metric

Integration with Other Frameworks

Core to:

• Continuous Discovery Habits: Primary visual tool for organizing discovery work

Pairs with:

• Jobs to Be Done: Opportunities = customer jobs needing solutions
• The Mom Test: Interview technique to discover opportunities
• Dual-Track Agile: Discovery track uses OST, validated solutions move to delivery
• RICE Prioritization: Score opportunities to decide which to pursue

Complements:

• Story Mapping: OST for "why," story map for "what" and "when"
• OKRs: Outcome = key result, opportunities = hypotheses to test
• Lean Canvas: OST for product strategy, canvas for business model

When to Use

Best for:

• Product teams doing continuous discovery
• Organizations focused on outcome-based development
• Teams struggling with feature alignment and prioritization
• Cross-functional collaboration (PM, Design, Engineering)

Not ideal for:

• Solo founders (mental model sufficient, don't need formal tree)
• Maintenance/bug fix work (not discovery-focused)
• Highly prescribed feature requirements (no discovery freedom)
• Short-term tactical projects under 2 weeks

Tool Recommendations

Digital Tools

• Miro: Flexible, excellent for remote collaboration
• Mural: Similar to Miro, strong facilitation features
• FigJam: Lighter weight, integrates with Figma
• Notion: Database view for structured trees

Analog Tools

• Whiteboard + sticky notes: Best for co-located teams
• Paper sketches: Quick personal mapping before digitizing

Recommendation: Start analog for initial thinking, move to digital for team collaboration and historical tracking.

References

• "Continuous Discovery Habits" - Teresa Torres (comprehensive OST guide)
• Product Talk blog (producttalk.org) - OST origin and updates
• Mapping article by Teresa Torres on Miro blog
• Stanford d.school "Divergent Solutioning" - Bernie Roth (OST inspiration)

Related

• continuous-discovery-habits
• jobs-to-be-done
• dual-track-agile
• outcome-over-output
• product-trio
• mom-test
• lean-startup
• assumption-testing
• story-mapping