How would you probabilistically forecast 40 stories using throughput data?
Tests probabilistic forecasting literacy using historical throughput. Good answers gather 8–12 periods of throughput, run Monte Carlo resampling, and present percentile delivery curves (e.g., 50th/85th/95th).
Tests whether you understand probabilistic delivery planning over deterministic promises. A strong response gathers 8–12 recent periods of throughput, treats that history as a distribution, and uses Monte Carlo or percentile bootstrapping to simulate how many sprints or weeks 40 stories will take. You should present an S-curve or table with 50th, 85th, and 95th percentile dates, explicitly noting that a single date ignores variance.
Read the original → focusedobjective.com
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- #monte-carlo
- #probabilistic-planning
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