Throughput appears often in sprint retros and delivery reports. This field adds one extra check to the general meaning.
In Agile, Scrum, and Kanban, throughput counts completed work items. These may be tickets, stories, or changes finished during a period. The count treats each item the same regardless of size. Differences in work type or size affect how you interpret and compare the count.
Count the right thing
Agile throughput normally counts completed items without weighting their size.
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Learn "Throughput" in depth →The same rate concept, applied to work items
Software-delivery throughput uses the same rate idea as general business. Here, the measure applies to completed work items. The phrase "team throughput" names the team as the measured system. Other fields use similar phrases, such as "system throughput" or "line throughput."
"Team throughput improved after we cut the approval steps -- we're completing more tickets per sprint."
"Before comparing our throughput to the other squad's, we flagged that their tickets tend to be much smaller, so a straight item-count comparison would be misleading."
"The engineering manager reported delivery throughput for the quarter as completed change requests per two-week cycle, broken out by team."
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Start the "Throughput" learning path →The domain-specific discipline: interpret the item count
Throughput counts every completed item once, regardless of size. Two teams that each close twenty items therefore have equal measured throughput. That does not prove equal effort, complexity, value, outcomes, or capacity. Different work types and size distributions can make a direct comparison misleading.
Interpret the trend using a stable definition of workflow and a reasonably stable item mix. Segment different work classes when that helps. Add cycle time, quality, and work-type context where relevant. Some teams also track estimated size or velocity. Those measures answer a different question and should not be compared across teams.
Reading a throughput number in context
One sprint's throughput number says little on its own. Trends across several periods are easier to interpret when workflow rules and item mix stay fairly stable. Investigate a sudden rise before celebrating it. A better process may explain the change, but a different work mix may also raise the count. The same caution applies to a sudden drop.
Practice scenarios
Practice using throughput in situations like:
- reporting sprint or delivery-cycle throughput in a retro
- flagging that a cross-team throughput comparison needs an item-size caveat
- distinguishing a raw completed-item count from a size-weighted metric
Useful practice phrases:
- "Team throughput improved after we..."
- "Before comparing our throughput to..., we should note that..."
- "We reported delivery throughput as completed items per..."
Report a sprint trend responsibly
Team throughput counts completed items, not the value they deliver.
Check workflow and item mix before comparing teams or periods. That context makes the number more useful.
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