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Criterion
Paper illustration for Feynman Technique.
Knowledge Modeling
Feynman Technique
Growth Experiment workspace showing the question, observations, and next decision.
Growth
Growth Experiment
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Purposedifferent
The Feynman Technique checks understanding by explaining a topic so that it stays easy for others to understand. It makes knowledge gaps visible before they become costly in everyday work.When growth ideas surface quickly, the temptation to build immediately instead of learning is high. A Growth Experiment frames an assumption so target group, lever, and measurement are clear before the first deployment.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 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
LowMediumLowMedium
Timedifferent
20-60 min1-2 Wochen30-90 min30-90 min
Participantsdifferent
11-62-81-6
Formatdifferent
AsyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Plain-language Explanation, Knowledge Gaps, Study NotesExperiment card, Result summary, Next betConstraint List, Hard/Soft Classification, Option Impact Notes, Decision BoundariesDecision Tree, Option Map, Assumption List
Tagsno overlap
LearningKnowledgeUnderstanding
MarketingGrowthExperimentsLearning
ConstraintsDecisionPlanningOptions
DecisionTreeOptions
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