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Criterion
Paper illustration of Product Kata with its method-specific working model.
Product Discovery
Product Kata
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Purposedifferent
Product Kata helps clarify customer problems, solution ideas, and evidence through a repeatable improvement routine. It captures direction, current metric, target metric, experiment notes, and learning.When knowledge is distributed and direct dominance should be avoided, groups quickly fall under the sway of their opinion leaders. The Delphi Method gathers assessments iteratively and gradually brings expert judgments closer together.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
MediumHighMedium
Timedifferent
1-2 Wochen je Loop1-4 Wochen30-90 min
Participantsdifferent
3-106-30 Experten1-6
Formatdifferent
Workshop + asyncAsyncWorkshop + async
Outputdifferent
Direction, Current metric, Target metric, Experiment note, Learning reportExpert Forecast, Consensus Range, Assumption NotesDecision Tree, Option Map, Assumption List
Tagsno overlap
OutcomesDiscoveryLearningIterationCoaching
ForecastingExpertsDecisionStrategy
DecisionTreeOptions
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for OODA Loop.
Decision Making
OODA Loop
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB