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Criterion
Paper illustration of a four-column Kanban board with limited ongoing work, a visible blocker and a review loop.
Engineering
Kanban
Paper illustration for Constraint Analysis.
Decision Making
Constraint Analysis
Decision Tree method illustration showing its working structure
Decision Making
Decision Tree
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
When work sits in too many parallel streams, throughput suffers and no one sees the bottlenecks. Kanban makes the flow of work visible and limits overload so a system becomes calmer and more predictable.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.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.
Complexitydifferent
MediumLowMediumHigh
Timedifferent
Ongoing30-90 min30-90 min30-90 min Setup, danach laufend
Participantsdifferent
2-122-81-61-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Kanban board, WIP policies, Flow metricsConstraint List, Hard/Soft Classification, Option Impact Notes, Decision BoundariesDecision Tree, Option Map, Assumption ListForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
FlowVisual managementDelivery
ConstraintsDecisionPlanningOptions
DecisionTreeOptions
ForecastingFlowDelivery
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