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| Criterion |  Delivery Monte Carlo Forecasting |  Product Strategy Lean Canvas |  Operations Waste Analysis |
|---|---|---|---|
Purposedifferent | 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. | For a process that keeps people busy but creates little value, the method exposes waste. It directs attention to unnecessary movement, waiting times, rework, and overdelivery. |
Complexitydifferent | High | Medium | Low |
Timedifferent | 30-90 min Setup, danach laufend | 45-90 min | 45-120 min |
Participantsdifferent | 1-8 | 1-6 | 2-8 |
Formatdifferent | Workshop + async | Workshop + async | Workshop |
Outputdifferent | Forecast Percentiles, Throughput Dataset, Risk Communication | Lean Canvas, Core Assumptions, Experiment Backlog | Waste Map, Prioritized Waste, Improvement Backlog |
Tagsno overlap | ForecastingFlowDelivery | StartupLeanAssumptionsBusiness model | WasteLeanProcess improvement |
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