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| Criterion |  Product Discovery Solution Interview |  Decision Making Decision Tree |  Product Discovery Outcome-Driven Innovation |  Decision Making Constraint Analysis |
|---|---|---|---|---|
Purposedifferent | When a solution idea is already on the table, it checks how it is understood and evaluated. It looks for resonance, objections, and missing fit early in the conversation. | 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. | Outcome-Driven Innovation clarifies customer problems, solution opportunities, and evidence. It separates jobs, desired outcomes, importance, satisfaction, and opportunity, and captures results as desired outcome statements, an opportunity landscape, and segments by underserved needs. | 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. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | 30-60 min je Interview | 30-90 min | Mehrere Wochen | 30-90 min |
Participantsdifferent | 5-10 Interviews | 1-6 | 2-6 researchers plus sample | 2-8 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Solution Feedback, Objection List, Validation Notes | Decision Tree, Option Map, Assumption List | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries |
Tagsno overlap | ValidationInterviewsPrototype | DecisionTreeOptions | OutcomesInnovationResearchQuantitative | ConstraintsDecisionPlanningOptions |