Throughput
Throughput measures the total number of completed work items over a specific period of time. It reflects how much value a team delivers and provides insight into execution capacity and delivery pace.
Calculation
A completed item is typically defined as any task, story, bug, or ticket that meets the team’s Definition of Done. Some teams include only stories or features, while others include all completed issues.
This metric is calculated by counting the number of completed items in a time window:
throughput = completed work items ÷ time period
Goals
Throughput helps teams evaluate how consistently they are delivering completed work over time. It answers questions like:
- How many items do we typically complete in a sprint or week?
- Are we improving our ability to deliver value over time?
- Are systemic blockers or overcommitments affecting completion rates?
Used correctly, this metric supports forecasting and helps teams align delivery scope with capacity. For an applied example, see Actionable Metrics at Siemens Health Services, which discusses how throughput and flow-based metrics helped stabilize and improve Agile performance in a complex environment.
Variations
Throughput may also be referred to as Ticket Completion Rate, Issue Throughput, or Work Item Velocity. Common segmentations include:
- By time interval, such as per sprint, week, or month
- By work type, like bugs, stories, chores, or spikes
- By team, to observe load distribution or trends
- By ticket size, to separate large efforts from quick wins
- By contributor, for capacity planning—not performance comparison
Some teams normalize throughput by team size or use a rolling average to smooth short-term variation.
Limitations
Throughput measures quantity, not quality or complexity. A team that delivers many small tasks may appear more productive than one working on fewer, more impactful items.
It also doesn’t account for partially completed work or how long items took to complete. Use it as a trend indicator, not a standalone measure of success.
To put throughput in better context, combine it with:
| Complementary Metric | Why It’s Relevant |
|---|---|
| Cycle Time | Shows how long work takes to complete and reveals speed relative to output volume. |
| Planning Accuracy | Indicates whether throughput aligns with what was planned or committed. |
| Work in Progress | Highlights whether too much concurrent work is affecting throughput stability. |
Optimization
Improving Throughput involves reducing blockers, optimizing work intake, and helping teams finish work consistently and predictably.
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Break work into smaller units. Large, unscoped tasks delay completion. Smaller items are easier to track, finish, and measure.
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Finish before starting more. High Work in Progress leads to context switching and delivery drag. Prioritize closing active items before opening new ones.
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Smooth intake with clear criteria. Use a shared Definition of Ready to ensure that new work is fully defined before it enters development.
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Visualize and manage flow. Track bottlenecks in review, testing, or validation stages to keep items moving toward done.
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Use throughput for forecasting. This metric supports planning conversations and capacity estimates, but shouldn’t be used to compare or rank individual performance.
Healthy throughput trends support predictable delivery and planning confidence. The goal isn’t to maximize output at all costs, it’s to deliver work consistently, without friction or overload.
