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| Criterion |  Knowledge Modeling PARA Method |  Decision Making Decision Tree |  Product Discovery Hypothesis Prioritization Canvas |  Product Discovery Experiment Canvas |
|---|---|---|---|---|
Purposedifferent | The PARA Method organizes knowledge into Projects, Areas, Resources, and Archives. It creates order when digital notes, files, and tasks no longer cleanly fit current work. | 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 many hypotheses compete for attention, it brings order to their learning sequence and importance. It separates problem, assumption, solution, and evidence. The result is captured as a prioritization canvas and a hypothesis backlog. | When experiments become unreadable after the fact, it arranges hypothesis, signal, and learning goal on a single canvas. It separates problem, assumption, solution, and evidence. The result is captured as a Completed Experiment Canvas and a Success Metric. |
Complexitydifferent | Medium | Medium | Medium | Low |
Timedifferent | 1-3 h Setup, laufend | 30-90 min | 60-90 min | 30-60 min |
Participantsdifferent | 1 | 1-6 | 3-8 | 1-5 |
Formatdifferent | Async | Workshop + async | Workshop | Workshop + async |
Outputdifferent | PARA Structure, Project Notes, Knowledge Archive | Decision Tree, Option Map, Assumption List | Prioritization Canvas, Hypothesis Backlog | Completed Experiment Canvas, Success Metric |
Tagsno overlap | KnowledgeProductivityOrganization | DecisionTreeOptions | ExperimentsPrioritizationDiscoveryHypothesis | ExperimentsValidationDiscoveryHypothesis |