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| Criterion |  Product Discovery Outcome-Driven Innovation |  Decision Making Constraint Analysis |  Decision Making Trade-off Analysis |  Decision Making Decision Tree |
|---|---|---|---|---|
Purposedifferent | 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. | With limited resources, quality, speed, cost, and risk almost always compete with each other. Trade-off Analysis makes these tensions explicit and prevents decisions from producing hidden side effects. | 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. |
Complexitydifferent | High | Low | Medium | Medium |
Timedifferent | Mehrere Wochen | 30-90 min | 45-120 min | 30-90 min |
Participantsdifferent | 2-6 researchers plus sample | 2-8 | 2-8 | 1-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Trade-off Matrix, Criteria List, Decision Rationale, Accepted Downsides | Decision Tree, Option Map, Assumption List |
Tagsno overlap | OutcomesInnovationResearchQuantitative | ConstraintsDecisionPlanningOptions | TradeoffsDecisionCriteriaOptions | DecisionTreeOptions |