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Criterion
Paper illustration for NoEstimates.
Agile
NoEstimates
Paper illustration for Intervention Mapping.
Systems Thinking
Intervention Mapping
Paper illustration for Future Reality Tree.
Systems Thinking
Future Reality Tree
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
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.Intervention Mapping translates a need for change into a planned, evaluable program. The method connects target group, determinants, actions, and measurement into a traceable chain.A Future Reality Tree shows how desired actions are meant to lead to a better system state. The method checks whether a path of change holds together logically before time flows into implementation.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
MediumHighHighHigh
Timedifferent
laufend1-5 Tage2-4 h30-90 min Setup, danach laufend
Participantsdifferent
2-124-123-81-8
Formatdifferent
Workshop + asyncWorkshop + asyncWorkshopWorkshop + async
Outputdifferent
Throughput Data, Flow Forecast, Slicing RulesLogic Model, Change Objectives, Intervention Components, Evaluation PlanFuture Reality Tree, Negative Branches, Assumption List, Improved InjectionsForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
EstimationForecastingFlow
ChangeSystems thinkingCapability
Theory of ConstraintsSystems thinkingChange
ForecastingFlowDelivery
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