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Criterion
Story Splitting method illustration showing its working structure
Agile
Story Splitting
Paper illustration for Monte Carlo Forecasting.
Delivery
Monte Carlo Forecasting
Paper illustration for Planning Poker.
Agile
Planning Poker
Purposedifferent
When a story becomes too large for a clean flow, it breaks scope down along value and risk. It shapes the work into a form that ships earlier and is easier to verify.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 estimates within the team diverge too much, it puts differing expectations on a common test bench. It separates rough complexity from unspoken assumptions.
Complexitydifferent
MediumHighLow
Timedifferent
30-60 min30-90 min Setup, danach laufend2-5 min je Item
Participantsdifferent
2-61-83-9
Formatsame
Workshop + asyncWorkshop + asyncWorkshop + async
Outputdifferent
Smaller Stories, Acceptance Criteria, Split RationaleForecast Percentiles, Throughput Dataset, Risk CommunicationRelative Estimates, Assumption Notes, Split Candidates
Tagsno overlap
BacklogIterationDelivery
ForecastingFlowDelivery
EstimationAgileRelative sizingTeam
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Often compared together

Methods with strong topical overlap with the current selection, not yet in the comparison.

Paper illustration for Affinity Estimation.
Agile
Affinity Estimation
Paper illustration of Dual Track Agile with its method-specific working model.
Product Discovery
Dual-Track Agile