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| Criterion |  Decision Making Constraint Analysis |  Growth Flywheel |  Product Discovery MVP Test Matrix |  Growth A/B Testing |
|---|---|---|---|---|
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. | Growth often breaks down where a reinforcing mechanism builds up too much friction. A Flywheel shows the cycle of value, repetition, and reinforcement meant to sustain growth. | When several minimal variants compete to answer the same question, it makes comparing and choosing between them cleaner. It separates problem, assumption, solution, and evidence. The result is captured as a Test Matrix and a Test Plan. | When two variants compete, discussions quickly decide by taste rather than effect. A/B Testing checks behavior under controlled conditions and separates real improvement from chance or expectation effects. |
Complexitydifferent | Low | Medium | Medium | High |
Timedifferent | 30-90 min | 60-120 min | 45-75 min | 1-4 Wochen |
Participantsdifferent | 2-8 | 3-8 | 2-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Workshop | Async |
Outputdifferent | Constraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries | Flywheel Map, Friction Points, Growth Levers, Experiment Backlog | Test Matrix, Test Plan | Experiment results, Decision log, Learning summary |
Tagsno overlap | ConstraintsDecisionPlanningOptions | GrowthRetentionConversion | ExperimentsValidationDiscoveryOptions | ExperimentsGrowthAnalyticsValidation |