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Criterion
Paper illustration of Lean Startup with its method-specific working model.
Innovation
Lean Startup
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration of a Lean Canvas with nine fields, notes, and one highlighted learning risk.
Product Strategy
Lean Canvas
Paper illustration of a four-column Kanban board with limited ongoing work, a visible blocker and a review loop.
Engineering
Kanban
Purposedifferent
For uncertain business assumptions, the method forces the idea into contact with real market reactions early. It separates wishful picture, assumption, and observable behavior, so that learning becomes faster than planning. This translates uncertainty into measurable insight.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 early product bet still has too many open points, it brings target group, problem, and assumptions into a single view. It condenses the idea so core risks become nameable.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.
Complexitydifferent
MediumHighMediumMedium
Timedifferent
Wochen bis Monate je Lernzyklus30-90 min Setup, danach laufend45-90 minOngoing
Participantsdifferent
2-81-81-62-12
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Hypothesis list, MVPs, Learning reports, Pivot or persevere decisionForecast Percentiles, Throughput Dataset, Risk CommunicationLean Canvas, Core Assumptions, Experiment BacklogKanban board, WIP policies, Flow metrics
Tagsno overlap
LeanStartupValidationMVP
ForecastingFlowDelivery
StartupLeanAssumptionsBusiness model
FlowVisual managementDelivery
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