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Criterion
Paper illustration for Option Framing.
Decision Making
Option Framing
Anonymous individual judgments pass through feedback loops to form a distribution.
Decision Making
Delphi Method
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Purposedifferent
In early decisions, alternatives are often still vague, incomplete, or blended together. Option Framing brings every possibility into a comparable form and makes visible which variant actually fits the question.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.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.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
MediumHighHighMedium
Timedifferent
45-120 min1-4 Wochen30-90 min Setup, danach laufend30-90 min
Participantsdifferent
3-86-30 Experten1-81-6
Formatdifferent
Workshop + asyncAsyncWorkshop + asyncWorkshop + async
Outputdifferent
Option Frames, Assumption Notes, Comparable Shortlist, Decision InputsExpert Forecast, Consensus Range, Assumption NotesForecast Percentiles, Throughput Dataset, Risk CommunicationDecision Tree, Option Map, Assumption List
Tagsno overlap
OptionsDecision framingStrategyComparison
ForecastingExpertsDecisionStrategy
ForecastingFlowDelivery
DecisionTreeOptions
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