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Criterion
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration of Power-Interest Grid with a method-specific labelled workspace.
Facilitation
Power Interest Grid
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.When many stakeholders compete for attention at once, the Power Interest Grid sorts them by influence and stake. It turns individual contributions into a visible selection. The result is captured as a Power Interest Grid and a stakeholder-specific strategy.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
HighLowHigh
Timedifferent
1-4 Wochen30-60 min30-90 min Setup, danach laufend
Participantsdifferent
6-30 Experten2-81-8
Formatdifferent
AsyncWorkshopWorkshop + async
Outputdifferent
Expert Forecast, Consensus Range, Assumption NotesPower Interest Grid, Strategy per StakeholderForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
ForecastingExpertsDecisionStrategy
StakeholdersFacilitationAlignmentPlanning
ForecastingFlowDelivery
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Often compared together

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

Paper illustration for Alignment Mapping.
Facilitation
Alignment Mapping
Paper illustration for Communication Plan
Delivery
Communication Plan
Stakeholder Mapping
Facilitation
Stakeholder Mapping
Paper illustration of Stakeholder Salience Model with its method-specific working model.
Facilitation
Stakeholder Salience Model