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| Criterion |  Product Discovery Outcome-Driven Innovation |  Decision Making Constraint Analysis |  Innovation Contradiction 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. | When a system should improve while another measure suffers as a result, the method makes the underlying conflict precisely formulable. It separates the desired effect from its side effect. This makes solutions possible that address the contradiction deliberately instead of half-heartedly. | 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 | 60-120 min | 30-90 min |
Participantsdifferent | 2-6 researchers plus sample | 2-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Contradiction Statement, Abstraction Notes, Solution Principles, Concept Ideas | Decision Tree, Option Map, Assumption List |
Tagsno overlap | OutcomesInnovationResearchQuantitative | ConstraintsDecisionPlanningOptions | ContradictionsInnovationProblem solving | DecisionTreeOptions |