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| Criterion |  Product Discovery Outcome-Driven Innovation |  Product Strategy ICE Scoring |  Decision Making Constraint 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 ideas need sorting quickly, it condenses impact, confidence, and effort into one compact score. It connects customer value, product logic, and decision priorities. The result is captured as an ICE table and top-ideas list. | 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. |
Complexitydifferent | High | Low | Low | Medium |
Timedifferent | Mehrere Wochen | 30-60 min | 30-90 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 | ICE Table, Top Idea List | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Decision Tree, Option Map, Assumption List |
Tagsno overlap | OutcomesInnovationResearchQuantitative | PrioritizationScoringGrowthDecision | ConstraintsDecisionPlanningOptions | DecisionTreeOptions |