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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of an IBIS map with issues, positions and arguments
Knowledge Modeling
IBIS
Paper illustration of Riskiest Assumption Test with a method-specific labelled workspace.
Product Discovery
Riskiest Assumption Test
Paper illustration of Experiment Canvas with a method-specific labelled workspace.
Product Discovery
Experiment Canvas
Purposedifferent
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.IBIS structures thinking about complex questions as a sequence of issues, ideas, and arguments. The method keeps discussions open without forcing them into premature consensus.When an idea hinges on one critical unknown, it prioritizes testing that exact piece of uncertainty first. It separates problem, assumption, solution, and evidence. The result is captured as a prioritized list of assumptions, a test plan, and a result report.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
MediumMediumMediumLow
Timedifferent
30-90 min1-3 h1-2 Wochen pro Iteration30-60 min
Participantsdifferent
1-62-82-61-5
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Decision Tree, Option Map, Assumption ListIssue Map, Positions, Argument NotesPrioritized Assumption List, Test Plan, Results ReportCompleted Experiment Canvas, Success Metric
Tagsno overlap
DecisionTreeOptions
RationaleKnowledgeDecision
ExperimentsValidationDiscoveryAssumptions
ExperimentsValidationDiscoveryHypothesis
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