What is throughput in software development?

As a consistent measure, throughput reveals a team's actual production capability rather than its theoretical or estimated capacity. This metric is especially valuable in Agile and Lean software development approaches where teams aim to maintain a steady, predictable flow of work through their development pipeline. An understanding of throughput allows teams to answer the question: "How much can we realistically deliver by a certain date?"

Throughput is important because it lets teams make accurate planning and forecasting based on real historical performance instead of optimistic estimates. Teams with a clear understanding of their throughput can set realistic expectations with stakeholders and avoid overcommitting to work they cannot deliver. Throughput is also useful as an early warning system, signaling when delivery capacity changes due to shifts in team composition, process changes, or external factors.

Another important aspect of throughput is that it provides a baseline for continuous improvement efforts. A regular measurement of throughput determines the effect of process changes or new practices on a team's delivery capability. Specific data provides results that focus on improvements without subjective assessments. It is helpful to distinguish velocity from throughout. While velocity measures the amount of work a team completes during a sprint in story points, throughput focuses on completed work items. As story points can be abstract, throughput provides a more accurate representation of a team's performance. Throughput can be combined with other metrics like cycle time and quality indicators to build a comprehensive view of work.

To calculate throughput, count the total number of completed work items within a specific time period. To produce accurate results, it is important for teams to define what "complete" means with a clear definition of done. With these criteria, teams use the formula for throughput:

Another important consideration is to standardize the size of work items or track throughput using consistent units, such as story points or function points. This reduces the chance of inaccurate or unbalanced calculations. For example, a development team completed 12 user stories in a two-week sprint that included 34 story points. Their throughput could be expressed as either 6 stories per week or 17 story points per week and would look like this: 17 = 34 / 2.

Teams interested in improving the rate at which they complete work can implement throughput boosters into their workflow with AI monitoring tools such as Enji.ai. These tools support high productivity and good throughput with the following features:

• AI agents: Provide real-time analytics of workflows to keep teams on track. Enji's Copilot shows inefficiencies and can create alerts and reminders.
• Automated alerts: Notify teams when tasks remain unchanged for too long. Enji's alerts appear in group messenger channels and can highlight specific employees for quick responses.
• Project visibility: Ensure all stakeholders have access to essential information. Enji features visual dashboards that keep everyone informed in minutes.