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Criterion
Paper illustration of a Polarity Map with two poles and four quadrants
Systems Thinking
Polarity Mapping
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
Polarity Mapping makes tensions between two opposing poles tangible, such as standardization and adaptation or control and autonomy. The method guards against making apparent either-or decisions prematurely.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 h1-4 Wochen30-90 min
Participantsdifferent
3-126-30 Experten1-6
Formatdifferent
WorkshopAsyncWorkshop + async
Outputdifferent
Polarity Map, Warning Signs, Balance ActionsExpert Forecast, Consensus Range, Assumption NotesDecision Tree, Option Map, Assumption List
Tagsno overlap
Systems thinkingTradeoffsLeadership
ForecastingExpertsDecisionStrategy
DecisionTreeOptions
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Trade-off Analysis.
Decision Making
Trade-off Analysis
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Paper illustration of a decision table with criteria rows, weighted ratings, and a narrowly leading alternative.
Decision Making
Decision Matrix
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB