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| Criterion |  Product Discovery Outcome-Driven Innovation |  Engineering Failure Scenario Analysis |  Decision Making Decision Tree |  Decision Making Constraint Analysis |
|---|---|---|---|---|
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. | In critical processes, it is not enough to plan only for the normal case. Failure Scenario Analysis looks at the path into failure and shows which failures, chains, and control gaps cause the most damage. | 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 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 | High | Medium | Medium | Low |
Timedifferent | Mehrere Wochen | 1-3 h | 30-90 min | 30-90 min |
Participantsdifferent | 2-6 researchers plus sample | 3-8 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Failure Scenarios, Risk Notes, Control Gaps, Test and Response Actions | Decision Tree, Option Map, Assumption List | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries |
Tagsno overlap | OutcomesInnovationResearchQuantitative | FailureResilienceRisk | DecisionTreeOptions | ConstraintsDecisionPlanningOptions |