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Criterion
Paper illustration for NoEstimates.
Agile
NoEstimates
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Purposedifferent
When estimating slows a team down more than it helps, it shifts the focus to flow, small slices, and real lead time. It sorts work by value, risk, and delivery ability. The result is captured as Throughput Data, Flow Forecast, and Slicing Rules.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.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
MediumMediumHighLow
Timedifferent
laufend30-90 min30-90 min Setup, danach laufend30-90 min
Participantsdifferent
2-121-61-82-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Throughput Data, Flow Forecast, Slicing RulesDecision Tree, Option Map, Assumption ListForecast Percentiles, Throughput Dataset, Risk CommunicationConstraint List, Hard/Soft Classification, Option Impact Notes, Decision Boundaries
Tagsno overlap
EstimationForecastingFlow
DecisionTreeOptions
ForecastingFlowDelivery
ConstraintsDecisionPlanningOptions
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