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Criterion
Paper illustration for Intervention Mapping.
Systems Thinking
Intervention Mapping
Paper illustration for NoEstimates.
Agile
NoEstimates
Systems Mapping method illustration showing its working structure
Systems Thinking
Systems Mapping
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Purposedifferent
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.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.Systems Mapping arranges elements, relationships, and boundaries so a complex field becomes legible at a glance. The overview stabilizes the overall picture before detail work or steering begins.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
HighMediumMediumHigh
Timedifferent
1-5 Tagelaufend1-3 h30-90 min Setup, danach laufend
Participantsdifferent
4-122-123-121-8
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Logic Model, Change Objectives, Intervention Components, Evaluation PlanThroughput Data, Flow Forecast, Slicing RulesSystem Map, Dependencies, Leverage PointsForecast Percentiles, Throughput Dataset, Risk Communication
Tagsno overlap
ChangeSystems thinkingCapability
EstimationForecastingFlow
Systems thinkingMappingBoundariesChange
ForecastingFlowDelivery
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