What are the challenges in using velocity-based forecasting in Agile projects

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Velocity-based forecasting is widely used in Agile, but I’ve noticed it doesn’t always give reliable estimates. What challenges should I expect when using velocity for forecasting, and how can I improve accuracy?
Apr 4 in PMP by Parshvi
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1 answer to this question.

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Velocity is useful in estimating future sprint capability, but it is not a failsafe. Key challenges include:

  • Team Performance Fluctuations - Velocity varies depending on team experience, task complexity, and external disturbances.

  • Scope Creep and Changing Priorities - If velocity projections need to change throughout a sprint, they become incorrect.

  • New Teams Face Difficulties - Establishing a consistent velocity baseline is hard due to a lack of historical data.

  • External Dependencies - If work is dependent on outside teams or vendors, their delays affect overall velocity.

  • Ignoring Non-Development Work - Administrative tasks, meetings, and unexpected roadblocks can diminish actual work time.

To improve accuracy, real historical data can be used to refine velocity computations and update forecasts on a regular basis based on observed patterns.

answered Apr 4 by Naira

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