Many Agile teams confuse velocity with capacity. Both measure work, but they serve different purposes. Understanding the difference is key to better planning and execution.
Agile’s rise in popularity is no surprise—it helps teams deliver on time. Velocity tracks completed work over time, guiding future estimates. Capacity measures available resources, ensuring realistic commitments.
Misusing these metrics can lead to missed deadlines and inefficiencies. Used correctly, they boost productivity and streamline workflows.
In this blog, we’ll break down velocity vs. capacity, highlight their differences, and share best practices to ensure agile success for you.
Agile velocity measures the amount of work a team completes in a sprint, typically using story points. It reflects a team’s actual output over time. By tracking velocity, teams can predict future sprint capacity and set realistic goals.
Velocity is not fixed—it evolves as teams improve. New teams may start with lower velocity, which grows as they refine their processes. However, it is not a direct measure of efficiency. High velocity does not always mean better performance.
Understanding velocity helps teams make data-driven decisions. It ensures sprint planning aligns with past performance, reducing the risk of overcommitment.
Velocity is calculated by averaging the total story points completed over multiple sprints.
Example:
Average velocity = (30 + 25 + 35) ÷ 3 = 30 story points per sprint
This means the team can reasonably commit to about 30 story points in upcoming sprints.
Agile capacity is the total available working hours for a team in a sprint. It factors in team size, holidays, and non-project work. Unlike velocity, which shows actual output, capacity focuses on potential workload.
Capacity planning helps teams set realistic expectations. It prevents burnout by ensuring workload matches availability.
Capacity fluctuates based on external factors. A fully staffed sprint has more capacity than one with multiple absences. Tracking it ensures smoother sprint execution and better resource management.
Capacity is based on available working hours in a sprint. It factors in team size, work hours per day, and non-project time.
Example:
If one member is on leave for 2 days, the adjusted capacity is:
(4 × 8 × 10) + (1 × 8 × 8) = 384 hours
Velocity shows past output, while capacity shows available effort. Both help teams plan sprints effectively.
While both velocity and capacity deal with workload, they serve different roles. The confusion arises when teams assume high capacity means high velocity.
But velocity depends on factors beyond available hours—such as efficiency, experience, and blockers.
Here’s a deeper look at their key differences:
Velocity is measured in story points, reflecting completed work. It captures complexity and effort rather than just time. Capacity, on the other hand, is measured in hours or workdays. It represents the total time available, not the work accomplished.
For example, a team with a capacity of 400 hours may complete only 30 story points. The work done depends on efficiency, not just available hours.
Velocity helps predict future output based on historical data. It evolves with team performance. Capacity only shows available effort in a sprint. It does not indicate how much work will actually be completed.
A team may have 500 hours of capacity but deliver only 35 story points. Predictability relies on velocity, while availability depends on capacity.
Velocity changes as teams gain experience and refine processes. A team working together for months will likely have a higher velocity than a newly formed team. Capacity remains fixed unless team size or sprint duration changes.
For example, two teams with the same capacity (400 hours) may have different velocities—one completing 40 story points, another only 25. Experience and engineering efficiency are the reasons behind this gap.
Capacity is affected by leaves, training, and holidays. Velocity is influenced by dependencies, technical debt, and workflow efficiency.
Example:
External factors impact both, but their effects differ. Capacity loss is predictable, while velocity fluctuations are harder to forecast.
Capacity helps determine how much work the team could take on. Velocity helps decide how much work the team should take on based on past performance.
If a team has a velocity of 30 story points but a capacity of 500 hours, taking on 50 story points will likely lead to failure. Sprint planning should balance both, prioritizing past velocity over raw capacity.
Velocity is dynamic. It shifts due to process improvements, team changes, and work complexity. Capacity remains relatively stable unless the team structure changes.
For example, a team with a velocity of 25 story points may improve to 35 story points after optimizing workflows. Capacity (e.g., 400 hours) remains the same unless sprint length or team size changes.
Velocity improves with Agile maturity, while capacity remains a logistical factor.
Using capacity as a performance metric can mislead teams. A high capacity does not mean a team should take on more work. Similarly, a drop in velocity does not always indicate lower performance—it may mean more complex work was tackled.
Example:
Misinterpreting these metrics can lead to overloading, burnout, and poor sprint outcomes.
Here are some best practices to follow to strike the right balance between agile velocity and capacity:
Understanding the difference between velocity and capacity is key to Agile success.
Companies can enhance agility by integrating AI into their engineering process with Typo. It enables AI-powered engineering analytics that tracks both metrics, identifies bottlenecks, and optimizes sprint planning. Automated fixes and intelligent recommendations help teams improve velocity without overloading capacity.
By leveraging AI-driven insights, businesses can make smarter decisions and accelerate delivery.
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