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| Criterion |  Decision Making Constraint Analysis |  Operations Bottleneck Analysis |  Product Discovery Outcome-Driven Innovation |  Decision Making Decision Tree |
|---|---|---|---|---|
Purposedifferent | 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 a flow that backs up at one point, the method looks for the capacity limit with the greatest leverage. It explains why extra effort elsewhere barely improves throughput. | 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. | 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 | Low | Medium | High | Medium |
Timedifferent | 30-90 min | 1-3 h | Mehrere Wochen | 30-90 min |
Participantsdifferent | 2-8 | 3-8 | 2-6 researchers plus sample | 1-6 |
Formatsame | Workshop + async | Workshop + async | Workshop + async | Workshop + async |
Outputdifferent | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Bottleneck Map, Flow Metrics, Improvement Options, Follow-up Measures | Desired outcome statements, Opportunity landscape, Segmentation by underserved needs, Innovation hypotheses | Decision Tree, Option Map, Assumption List |
Tagsno overlap | ConstraintsDecisionPlanningOptions | FlowMeasurementConstraints | OutcomesInnovationResearchQuantitative | DecisionTreeOptions |