When one team runs several things at once

Epic/Feature Monte Carlo

A single team rarely works on just one thing. Once several Features or Epics are drawing from the same pool of throughput, "how long will ten items take?" becomes "how will throughput be split, and what does that mean for each Feature?"

Animated chart showing forecasted completion ranges for several Epics/Features at once, ranked by priority

Monte Carlo with Feature-level WIP built in

Feature Monte Carlo applies the same simulation principles as single-team forecasting, but adds Feature-level work in progress as a variable, so each Feature in flight gets its own range of likely completion dates and its own confidence level.

One team, several Features or Epics in parallel

Use this the moment a single team is carrying more than one Feature or Epic at a time and stakeholders want a completion forecast for each one individually, not just for the backlog as a whole.

When there's only one thing in flight, or the work spans multiple teams

If your team only has one Feature or Epic active at a time, plain single-team Monte Carlo is simpler and just as accurate. If the initiative spans more than one team, use Multi-team Monte Carlo instead.

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Windows
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See the maths behind Feature-level forecasting

Beyond Burnups shows exactly how Feature WIP multiplies the number of possible outcomes, and how to simulate it properly.

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