Opportunity

Origin & evolution

The word has long meant "an unmet need worth pursuing", but its current product-management precision comes from Teresa Torres and the Opportunity Solution Tree, formalised in Continuous Discovery Habits (2021). Torres defines an opportunity as "an unmet customer need, pain point, or desire", and arranges discovery as a tree: a single desired outcome🌟Desired OutcomeUserWhat the user hopes to achieveView reference → at the root, branching into opportunities, each branching into candidate solutions, each tested by assumptions🤔AssumptionStrategyA belief taken as true that underpins a strategyView reference →.

Torres's sharpest contribution is a test for whether something is genuinely an opportunity. Ask: is there more than one way to address this? "I want to go out to eat" fails the test, because it already names the solution. Ask "why?" and the real opportunities appear: "I don't have time to cook", "I want something tastier than I can manage myself", each of which admits many solutions. An opportunity that admits only one solution is a solution in disguise, and treating it as an opportunity quietly kills the team's option space before discovery begins.

The structure also encodes a sequencing rule the field had been missing. Opportunities are sized and prioritised before any solution is committed, which keeps teams from falling in love with the first idea. This built on earlier dual-track and continuous-discovery thinking, and it gave product teams a shared visual artefact for an argument that used to happen in scattered documents.

How it works in practice

A subscription🔂SubscriptionSales & RevenueA recurring subscriptionView reference → product sets the outcome🏆OutcomeStrategyA desired business or user outcomeView reference → "lift trial-to-paid conversion from 22% to 30%". Discovery interviews surface several distinct gaps. One recurs: trial users who connect their data on day one convert at 41%, while those who do not convert at 9%, and most never connect because the setup asks for admin credentials they do not have. That gap becomes an opportunity: "I want to see the product working with my own data without waiting on my IT team." It passes Torres's test, because there are several ways to address it: a read-only demo dataset, a delegated-invite flow, a lightweight CSV import. The team sizes this opportunity against two others on the tree, picks it because the conversion delta is largest and the addressable population widest, and only then starts generating solutions. The framing keeps the conversation on the gap until the evidence🔎EvidenceValidationData supporting or refuting a hypothesisView reference → justifies a bet.

Opportunity vs. its neighbours

• Solution is the how; the opportunity is the what. One opportunity should carry several competing solutions beneath it, which is precisely how the graph wires opportunity_drives_solutionOpportunitydrivesSolutioncausal. Collapsing the two is the most common discovery failure.
• Problem tends to be framed from the company's side ("our activation funnel⬇️FunnelGrowthA conversion funnel tracking user progressionView reference → leaks"). An opportunity is framed from the customer's side as something they want or struggle with, which is what makes it actionable in discovery and testable with real users.
• Outcome is the business or product result the opportunity serves ("increase activation by 8 points"). The outcome sits above opportunities and is reached through them; the graph imports this relationship as outcome_reveals_opportunityOutcomerevealsOpportunitycausal.
• Insight🔦InsightUser ResearchA synthesised finding from researchView reference → is a single piece of evidence from research; an opportunity is the validated, recurring gap that several insights point to. Insights feed opportunities through insight_surfaces_opportunityInsightsurfacesOpportunitycross-domain, never the reverse.

In the graph

The opportunity is the anchor of the Discovery, Research & Validation region, a deliberately cyclic space whose model is question to hypothesis🧪HypothesisValidationA testable belief about a solutionView reference → to test to evidence to decision⚖️DecisionStrategyA recorded decision with context, rationale, and consequencesView reference →, then loop. It earns the anchor role by sitting on the region's import border: outcomes (outcome_reveals_opportunityOutcomerevealsOpportunitycausal), market trends📉Market TrendMarket IntelligenceAn emerging trend in the marketView reference → (market_trend_creates_opportunityMarket TrendcreatesOpportunitycross-domain), and feature requests🙏Feature RequestCustomer FeedbackA user-submitted feature requestView reference → (feature_request_creates_opportunityFeature RequestcreatesOpportunitycross-domain) all flow in and become opportunities, while research evidence hardens them through evidence_supports_opportunityEvidencesupportsOpportunitycross-domain and learning_validates_opportunityLearningvalidatesOpportunitycross-domain. Downstream, opportunity_drives_solutionOpportunitydrivesSolutioncausal opens the solution space and opportunity_addresses_needOpportunityaddressesNeedcross-domain ties the gap back to the user it serves. That position, fed by strategy and research and feeding solution work, is why an unvalidated opportunity is visibly orphaned in the graph.