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Criterion
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration of an assumption matrix with prioritized test cards
Decision Making
Assumption Surfacing
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Purposedifferent
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.Plans often contain assumptions that were never openly stated and remain dangerous precisely because of that. Assumption Surfacing makes these silent premises visible and prioritizes which of them carry the initiative or could sink it.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.
Complexitydifferent
HighMediumLowLow
Timedifferent
30-90 min Setup, danach laufend30-90 min45-90 min30-90 min
Participantsdifferent
1-81-62-82-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Forecast Percentiles, Throughput Dataset, Risk CommunicationDecision Tree, Option Map, Assumption ListAssumption List, Critical Assumptions, Learning PlanConstraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries
Tagsno overlap
ForecastingFlowDelivery
DecisionTreeOptions
AssumptionsRiskDecisionDiscovery
ConstraintsDecisionPlanningOptions
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