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Criterion
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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
When an initiative stalls, the limit often lies not in the idea but in hard or soft boundary conditions. Constraint Analysis separates these limits and shows which of them can actually be shaped.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.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
LowHighHighMedium
Timedifferent
30-90 min30-90 min Setup, danach laufend1-4 Wochen30-90 min
Participantsdifferent
2-81-86-30 Experten1-6
Formatdifferent
Workshop + asyncWorkshop + asyncAsyncWorkshop + async
Outputdifferent
Constraint List, Hard/Soft Classification, Option Impact Notes, Decision BoundariesForecast Percentiles, Throughput Dataset, Risk CommunicationExpert Forecast, Consensus Range, Assumption NotesDecision Tree, Option Map, Assumption List
Tagsno overlap
ConstraintsDecisionPlanningOptions
ForecastingFlowDelivery
ForecastingExpertsDecisionStrategy
DecisionTreeOptions
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