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Criterion
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
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
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.Helps clarify scope, sequence, and delivery flow in concrete terms. It makes work, boundaries, and order steerable. The result is captured as Forecast Percentiles, Throughput Dataset, and Risk Communication.
Complexitydifferent
HighMediumHigh
Timedifferent
1-4 Wochen30-90 min30-90 min Setup, danach laufend
Participantsdifferent
6-30 Experten1-61-8
Formatdifferent
AsyncWorkshop + asyncWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesDecision Tree, Option Map, Assumption ListForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
ForecastingExpertsDecisionStrategy
DecisionTreeOptions
ForecastingFlowDelivery
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Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Paper illustration of Cost of Delay with its method-specific working model.
Delivery
Cost of Delay
Paper illustration of DIBB with its method-specific working model.
Product Strategy
DIBB
Paper illustration of the Force Field Analysis working structure.
Decision Making
Force Field Analysis