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| Criterion |  Product Discovery Opportunity Interview |  Decision Making Constraint Analysis |  Decision Making Decision Tree |  Product Discovery Opportunity Solution Tree |
|---|---|---|---|---|
Purposedifferent | When opportunities are still hidden behind signals of need, it structures conversations around needs and obstacles. It looks for patterns that lead to new product opportunities. | When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped. | For decisions with follow-on paths and dependencies, a linear comparison is often not enough. A Decision Tree shows how options branch under conditions and which consequences hang on each branch. | When discovery keeps swinging between goals, ideas, and learning loops, it creates clear steering logic. It connects the desired outcome, opportunities, and experiments into a legible structure. |
Complexitydifferent | Medium | Low | Medium | Medium |
Timedifferent | 30-60 min je Interview | 30-90 min | 30-90 min | 1-2 h Setup, laufend |
Participantsdifferent | 5-12 Interviews | 2-8 | 1-6 | 2-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Interview Notes, Opportunity Themes, Customer Quotes | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Decision Tree, Option Map, Assumption List | Opportunity Solution Tree, Experiment Backlog, Learning Log |
Tagsno overlap | DiscoveryInterviewsOpportunityCustomer | ConstraintsDecisionPlanningOptions | DecisionTreeOptions | DiscoveryOutcomesExperimentsOpportunity |