Throughput
Throughput
Throughput is an Agile metric that measures the number of work items completed by a team during a specific period of time.
In simple terms, Throughput tells us how much work a team successfully finishes within a given timeframe, such as a day, week, sprint, or month.
Throughput = Number of completed work items during a specific time period.
Throughput helps Scrum Masters, Agile Coaches, Product Owners, and stakeholders understand the delivery capacity of a team and forecast future work more accurately.
What Does Throughput Measure?
Throughput measures output rather than effort. It focuses on completed work items instead of the number of hours spent working.
Common work items measured through Throughput include:
- User Stories
- Tasks
- Bug Fixes
- Features
- Product Backlog Items (PBIs)
- Support Tickets
Throughput Formula
The time period can be measured in days, weeks, sprints, or months depending on the team's reporting needs.
Simple Example
Suppose a Scrum Team completes 25 user stories during a two-week sprint.
| Metric | Value |
|---|---|
| Total Completed Stories | 25 |
| Sprint Duration | 2 Weeks |
| Throughput | 25 Stories per Sprint |
Therefore, the team's Throughput is 25 completed stories during the sprint.
Another Example
Imagine an Agile team completed the following number of work items each week:
| Week | Completed Items |
|---|---|
| Week 1 | 18 |
| Week 2 | 22 |
| Week 3 | 20 |
| Week 4 | 24 |
Total Completed Items = 84
Average Weekly Throughput:
Why Throughput Matters
Throughput helps teams understand their delivery capability and provides valuable insights for planning and forecasting future work.
Benefits of Measuring Throughput
- Measures team productivity.
- Supports release planning.
- Improves delivery forecasting.
- Identifies workflow bottlenecks.
- Tracks process improvements over time.
- Provides data-driven decision making.
Throughput vs Velocity
Throughput and Velocity are often confused because both measure team output. However, they are calculated differently.
| Throughput | Velocity |
|---|---|
| Counts completed work items. | Counts completed story points. |
| Focuses on quantity. | Focuses on effort completed. |
| Easy to measure. | Requires story point estimation. |
| Common in Kanban. | Common in Scrum. |
Example: Throughput vs Velocity
Suppose a team completes:
| User Story | Story Points |
|---|---|
| Story A | 3 |
| Story B | 5 |
| Story C | 8 |
| Story D | 2 |
Throughput: 4 completed stories
Velocity: 18 story points
Throughput measures the number of completed items, while Velocity measures the effort completed.
Throughput in Scrum
Scrum teams often track Throughput to understand how many backlog items are completed during each sprint.
Consistent Throughput generally indicates a stable and predictable delivery process.
Significant fluctuations may indicate:
- Changing team capacity.
- Technical challenges.
- Poor backlog refinement.
- External interruptions.
- Resource constraints.
Throughput in Kanban
Throughput is one of the most important metrics in Kanban because Kanban focuses on flow and continuous delivery.
Kanban teams use Throughput along with Lead Time and Cycle Time to optimize workflow performance.
Factors Affecting Throughput
| Factor | Impact |
|---|---|
| Team Size | Larger teams may complete more work. |
| Skill Level | Experienced teams often achieve higher throughput. |
| Technical Debt | Reduces development speed. |
| Dependencies | Can slow completion rates. |
| Work Item Size | Larger stories reduce throughput. |
| Automation | Can significantly increase throughput. |
How Scrum Masters Can Improve Throughput
- Break large stories into smaller stories.
- Remove impediments quickly.
- Improve backlog refinement.
- Reduce dependencies.
- Automate testing and deployments.
- Limit Work In Progress (WIP).
- Improve team collaboration.
Throughput in Jira
Jira can automatically track completed issues and display Throughput trends through dashboards and reports.
Scrum Masters often use these reports to:
- Monitor team performance.
- Predict future delivery dates.
- Identify process bottlenecks.
- Support release planning.
Real-World Example
Consider a software team working on a customer portal.
During a two-week sprint, they complete:
| Work Item Type | Completed Items |
|---|---|
| User Stories | 15 |
| Bug Fixes | 8 |
| Tasks | 12 |
| Total Throughput | 35 Items |
The team's Throughput for the sprint is 35 completed work items.
Common Mistakes When Using Throughput
| Mistake | Why It Is a Problem |
|---|---|
| Using Throughput as a performance target. | Teams may sacrifice quality to complete more items. |
| Comparing different teams. | Each team works differently. |
| Ignoring work item size. | Not all stories require the same effort. |
| Focusing only on quantity. | Quality and customer value remain important. |
Key Takeaways
- Throughput measures the number of completed work items over a period of time.
- It focuses on output rather than effort.
- Throughput helps teams forecast future delivery capacity.
- It is widely used in both Scrum and Kanban environments.
- Higher Throughput generally indicates better flow efficiency.
- Throughput should be analyzed alongside Lead Time and Cycle Time for a complete picture.
Conclusion
Throughput is a valuable Agile metric that helps teams understand how much work they complete over time. By tracking Throughput, Agile teams can improve planning accuracy, identify bottlenecks, optimize workflows, and deliver value more consistently. When used together with other Agile metrics such as Lead Time and Cycle Time, Throughput provides powerful insights into overall team performance and process effectiveness.