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| Criterion |  Operations Waste Analysis |  Innovation Lean Startup |  Delivery Monte Carlo Forecasting |
|---|---|---|---|
Purposedifferent | 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. | 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. |
Complexitydifferent | Low | Medium | High |
Timedifferent | 45-120 min | Wochen bis Monate je Lernzyklus | 30-90 min Setup, danach laufend |
Participantsdifferent | 2-8 | 2-8 | 1-8 |
Formatdifferent | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Waste Map, Prioritized Waste, Improvement Backlog | Hypothesis list, MVPs, Learning reports, Pivot or persevere decision | Forecast Percentiles, Throughput Dataset, Risk Communication |
Tagsno overlap | WasteLeanProcess improvement | LeanStartupValidationMVP | ForecastingFlowDelivery |
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Methods with strong topical overlap with the current selection, not yet in the comparison.
