Delivery Velocity

Overview

Delivery velocity measures how frequently a development team delivers big increments of value such as epics, initiatives, and features over a defined period. It provides insights into the team’s efficiency and productivity, reflecting their ability to deliver the major features that leadership stakeholders tend to think about instead of individual stories and tasks. This metric is crucial for assessing team performance, optimizing workflows, and improving project forecasting.

Description

Delivery velocity is a key performance indicator (KPI) that tracks how fast a team can deliver finished work, such as epics, initiatives, features, or other units of work, within a given time frame. This metric is essential for understanding the pace at which a team is generating value. By monitoring delivery velocity, organizations can assess their development process’s health, predict future capacity, and identify areas for improvement.

Factors influencing delivery velocity include:

• Team Size & Capacity: A larger team or additional resources may contribute to faster delivery.

• Task Complexity: More complex tasks may slow delivery velocity, while simpler tasks may increase it.

• External Dependencies: Delays or disruptions caused by third parties or other teams can affect velocity.

• Process Maturity: More mature processes typically lead to more stable and predictable velocity.

How is Delivery Velocity Calculated?

Delivery velocity is calculated by measuring the number of completed parent objects over time. By default, it looks at the last 90 days and groups the data in weekly increments, but users can change the date range and date groupings to whatever they desire. All Parent Objects from the Jira or ADO projects enabled in your workspace, that were transitioned to a completed status in your selected timeframe, will display in the metric.

Parent Objects are typically things like Epics, Initiatives, and Features. If your organization uses any custom parent objects, ask your Customer Success representative to set those objects as “Parent Types” so they will be counted in Delivery metrics.

Parent objects such as Epics, Initiatives, and Features often aren’t assigned to people on your team. The may be assigned to a PM, or they may not be assigned to anyone at all. For these reasons, Delivery Velocity ignores your workspace roster by default. If you want to filter the deliverables being tracked by this metric, you can configure that using advanced filters.

Questions You Can Answer with Delivery Velocity Data

• How consistent is the team's delivery velocity over time?
  Determine whether the team is able to maintain a steady pace or if there are fluctuations that require investigation.

• What is the average number of epics or features delivered per iteration or sprint?
  Understand the team’s baseline performance to inform project timelines and expectations.

• How does delivery velocity vary across different teams or projects?
  Compare delivery velocity between teams to assess performance discrepancies and identify best practices.

• What factors or dependencies consistently impact the team's delivery velocity?
  Identify external or internal obstacles that may be slowing down delivery, such as dependencies on other teams or unplanned scope changes.

• How does delivery velocity compare to initial estimations or expectations for the project?
  Measure how well the team’s actual delivery aligns with initial projections, helping to refine future estimates.

• How can the team improve its velocity?
  Analyze patterns to uncover bottlenecks or inefficiencies that could be addressed to increase the team’s output.

Key Takeaways from Delivery Velocity Data

• Improved Planning & Forecasting: Delivery velocity data helps teams estimate how much work can realistically be completed in future sprints or iterations, leading to more accurate project timelines and resource allocation.

• Project Health & Predictability: Consistent and predictable delivery velocity indicates a well-functioning project, while large fluctuations can signal potential issues such as bottlenecks, overwork, or lack of clarity in requirements.

• Continuous Learning & Adaptation: By regularly reviewing delivery velocity, teams can spot trends, celebrate successes, and identify areas for improvement. This promotes a culture of continuous learning and helps teams refine their processes.

• Iterative Improvement: Delivery velocity serves as feedback for process optimization. If velocity is stagnating or declining, teams can dig deeper into the cause (e.g., task complexity, external dependencies, or team collaboration issues) and experiment with solutions for improvement.

Conclusion

Delivery velocity is a critical metric for understanding how efficiently a team delivers work, providing insights into their productivity and pace. By tracking and analyzing delivery velocity, teams can improve their forecasting accuracy, identify obstacles that slow down progress, and continually optimize their workflows for better performance. With consistent monitoring, delivery velocity helps to foster transparency, build trust with stakeholders, and ensure that projects stay on track to deliver value quickly and efficiently.