capacity-planning

Team capacity for a sprint in Azure DevOps is calculated by fetching iteration data, team member capacities, and days off, then applying a focus factor to determine real available hours against assigned remaining work.

Workload monitoring prevents team burnout by tracking assigned work against available capacity, calculating real-time utilization percentages, and issuing proactive alerts for individuals or the team nearing capacity thresholds.

The best way to track resource allocation and prevent over-commitment is comparing available team hours, derived from headcount and sprint duration minus time off, against assigned remaining work to ensure realistic story point commitments.

Yes, you can use Azure DevOps iteration data to identify overloaded team members by fetching their individual capacities and days off, calculating their real available hours with a focus factor, and flagging those exceeding workload thresholds.

Capacity planning relies on subtracting planned time off from total available hours to compute real capacity. Without days off data, workload utilization calculations will be inaccurate, increasing the risk of missing overload alerts.

Your team exceeds sprint capacity because real available hours require applying a focus factor to total headcount hours. Without this focus factor, assigned remaining work appears to match capacity but actually exceeds realistic workload thresholds.