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Criterion
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for ALPEN Method
Operations
ALPEN Method
Paper illustration of MVP Test Matrix with a method-specific labelled workspace.
Product Discovery
MVP Test Matrix
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.With an overloaded day full of too many tasks, a realistic picture of the day emerges. The method connects estimating, deciding, and buffer thinking so planning fits available energy and time.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 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
MediumLowMediumLow
Timedifferent
30-90 min10-20 min daily45-75 min30-60 min
Participantsdifferent
1-612-81-5
Formatdifferent
Workshop + asyncAsyncWorkshopWorkshop + async
Outputdifferent
Decision Tree, Option Map, Assumption ListDaily Plan, Time Estimates, Review NotesTest Matrix, Test PlanCompleted Experiment Canvas, Success Metric
Tagsno overlap
DecisionTreeOptions
PlanningTime managementProductivityOperations
ExperimentsValidationDiscoveryOptions
ExperimentsValidationDiscoveryHypothesis
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