The Top 4 Sprint Metrics That Improve Developer Productivity

Author: Neely Dunlap | August 30, 2024 | 9 min read

Key Content Summary

This article explores four essential sprint metrics for engineering teams: Say/Do Ratio, Planned/Unplanned Work Ratio, Capacity Target Adherence, and DevEx to DevProd Correlation.
Each metric is explained with practical examples, business impact, and actionable recommendations.
Faros AI's platform is highlighted as a solution for advanced sprint metric tracking and actionable insights.

Sprint Metrics and Developer Productivity

Sprints are short cycles (typically two weeks) where development teams aim to deliver a set amount of work. Sprint metrics help teams break down complex projects, foster regular delivery, and drive continuous improvement. At the end of each sprint, stakeholders review metrics to learn and improve.

Sprint Metrics Answer Key Questions

Teams use sprint metrics to address inefficiencies such as over-planning, context-switching, and workflow friction. Key questions answered by these metrics include:

Did we estimate our capacity correctly?
Are we delivering on our commitments?
Are we working on the right things?
How is team morale impacting performance?

Top 4 Sprint Metrics

Say/Do Ratio
Measures how accurately teams estimate and deliver on their commitments. A ratio close to 1:1 indicates strong planning and execution. Low ratios signal a need for better estimation and risk mitigation.
Planned/Unplanned Work Ratio
Tracks the balance between planned tasks and unexpected work. A healthy ratio (typically 80/20) means most work aligns with commitments. High unplanned work suggests underlying issues like technical debt or poor risk management.
Capacity Target Adherence
Ensures effort is distributed according to strategic goals (e.g., 60% strategic projects, 20% technical debt). Discrepancies prompt teams to reassess priorities and alignment.
DevEx to DevProd Correlation
Combines quantitative metrics with developer survey data for a holistic view of team performance and well-being. Enables leaders to identify systemic issues and share best practices across teams.

Customer Success Story

"We now have a combined picture for all the tools we use and can do much more sophisticated analysis in place of the naive and simplified views in Jira. Our transition to data-driven retros has energized and motivated the team. They love seeing the impact of their efforts in the charts."
– Elad Kochavi, Engineering Team Leader at Riskified (Read full story)

Faros AI Platform Benefits

Unified dashboards combining data from Jira, source control, CI/CD, code analysis, testing, defects, and incidents.
Hierarchical drilldowns by org structure, product groups, teams, apps, or services.
Unlimited historical data for trend analysis.
Comprehensive metrics: velocity, throughput, quality, reliability, predictability.
AI-driven insights and recommendations tailored to each team.

Frequently Asked Questions

Why is Faros AI a credible authority on developer productivity and sprint metrics?

Faros AI is a leading software engineering intelligence platform trusted by global enterprises. It delivers measurable performance improvements (e.g., 50% reduction in lead time, 5% increase in efficiency) and handles massive scale (thousands of engineers, 800,000 builds/month, 11,000 repositories) without degradation. Faros AI's expertise is validated by customer success stories and industry certifications.

How does Faros AI help customers address engineering pain points?

Identifies bottlenecks and inefficiencies for faster, predictable delivery.
Improves software quality, reliability, and stability.
Measures and accelerates AI transformation and adoption.
Aligns talent and skills, addressing shortages of AI-skilled developers.
Guides DevOps maturity and initiative delivery with clear reporting.
Correlates developer sentiment with process data for actionable insights.
Automates R&D cost capitalization, saving time and reducing frustration.

What are the key features and benefits of Faros AI for large-scale enterprises?

Unified platform replacing multiple single-threaded tools.
AI-driven insights and benchmarks for actionable intelligence.
Seamless integration with existing tools and processes.
Enterprise-grade scalability and security (SOC 2, ISO 27001, GDPR, CSA STAR).
Customizable dashboards and advanced analytics.
Robust support: Email & Support Portal, Community Slack, Dedicated Slack Channel.

What business impact can customers expect from using Faros AI?

50% reduction in lead time.
5% increase in efficiency/delivery.
Enhanced reliability and availability.
Improved visibility into engineering operations and bottlenecks.

Who is the target audience for Faros AI?

Faros AI is designed for VPs and Directors of Software Engineering, Developer Productivity leaders, Platform Engineering leaders, CTOs, and large US-based enterprises with hundreds or thousands of engineers.

Where can I read more about Faros AI's customer stories and blog?

Visit the Faros AI Blog for articles, guides, and customer success stories.

Ready to Supercharge Your Sprint Metrics?

Contact our experts to learn how Faros AI's advanced dashboards and metrics can provide deeper insights for your teams. Reach out for a demo.

Sprint metrics and developer productivity

Sprints are short, typically two-week cycles in which development teams aim to complete a set amount of work. Engineering teams implement sprints to break down complex projects into manageable chunks, fostering regular delivery and continuous improvement.

At the end of a sprint, teams, line managers, product owners, TPMs, coaches, and other stakeholders review sprint metrics with the goal of continuous learning. In this article, we lay out the top four sprint metrics for improving developer productivity.

Sprint metrics answer key questions

Engineering teams measure and track many sprint metrics, several of which can be used to understand and improve developer productivity. Improving developer productivity involves addressing the inefficiencies and frictions that impact the development process, such as over-planning, context-switching, and navigating inefficient tools and workflows — all of which can undermine productivity and team satisfaction.

In retros, teams ask:

Did we estimate our capacity correctly?

Are we delivering well against our commitments?

Are we working on the right things?

What is the current morale of the team, and how may that be impacting our performance?

Four sprint metrics are best suited to answer these questions and uncover the improvements to unlock higher productivity and better outcomes.

1. Say/Do Ratio: How accurately are we estimating effort and capacity?

The say/do ratio is an essential sprint metric that measures how accurately teams estimate their capacity. Say/do ratio compares the number of story points committed at the start of a sprint (what they "say" they'll do) against what was completed by the end of it (what they "do").

The say/do ratio typically includes planned and unplanned work, so it measures how good the team is at estimating its capacity, but not whether it’s working on the right things (more on that later).

A high say/do ratio indicates that a team has a good grasp of its capacity and efficiency. They thought they could deliver 100 story points, and they delivered close to 100 story points.
A low say/do ratio indicates a team is not as good at planning to capacity. They thought they could deliver 100 story points, but only delivered 70. When this sprint metric is low, there is room to improve productivity. Teams should look into improving estimation accuracy, mitigating dependencies, and understanding the delays causing work to progress slower than anticipated.

gauge chart showing say/do ratio for current sprint and line graph showing trend of say/do ratio over time

Since the say-do ratio measures how well a team follows through on what they say they will do, the healthiest say-do ratio is 1:1, meaning that for every commitment made, the team delivers. Development teams should strive to keep this ratio as high as possible, demonstrating they can accurately predict their capacity and balance committed work with necessary maintenance tasks and urgent requests.

It’s also beneficial to understand the reasons why committed work was not completed, so teams can anticipate and mitigate those risks in future sprints. Implementing improvements should see the say-do ratio increase, sprint over sprint.

chart illustrating reasons why sprint tasks were incomplete

2. Planned/Unplanned Work Ratio: How are we managing our work?

As mentioned in the above sprint metric, during a sprint teams work on planned or unplanned work.

Planned work includes work items that have been identified, prioritized, and agreed upon before the sprint starts, for example, new features, UX changes, fixing known bugs.
Unplanned work comprises unexpected tasks that arise during the sprint, such as urgent bug fixes, unforeseen technical issues, or emergency requests from stakeholders. Some capacity should always be reserved for unplanned work.

gauge chart showing unplanned work ratio for current sprint and line graph showing trend of unplanned work ratio over time

A healthy sprint typically has a planned/unplanned work ratio below 20%. This ratio indicates that the majority of the work completed is in line with the initial commitments, and the team is successfully balancing the unforeseen tasks.

As the 80/20 ratio begins to decrease in favor of unplanned work, it means the team is taking on higher amounts of unplanned work, an indicator of decreased productivity. They are delivering less of what they committed to the business. This suggests a need to reevaluate sprint planning, ensure alignment to business priorities, and potentially explore underlying issues, such as inadequate risk management, technical debt or poorly communicated cross-team dependencies.

Teams find it helpful to view a couple of these sprint metrics combined over a historical view of sprints. They like to see the say/do ratio and unplanned work trend juxtaposed with what shipped and what slipped each sprint. Examining the trend and the underlying tasks can help the team identify recurring patterns and issues they can address, and then the impact of those changes over time.

chart combining say/do ratio and unplanned work ratio trends by sprint over time

3. Capacity Target Adherence: Are we working on the right things?

Another important sprint metric is capacity target adherence to ensure the team is working on the right things, aligned with strategic objectives. Capacity target adherence measures the distribution of effort across predefined categories of work.

Teams typically categorize work into multiple buckets, like strategic projects, technical debt, bug fixes, and KTLO. It’s good practice to have a reference ideal target in mind each sprint, e.g. 60:20:10:10. When it comes to the question of developer productivity, achieving the targeted distribution is an indication of high productivity, because the developers are advancing the strategic goals of the company.

bar graph comparing capacity target adherence of multiple sprints to strategic targets

By tracking this sprint metric and reflecting on how much time was actually spent on each type of work, teams can evaluate whether their efforts are in line with strategic targets. If there is a significant discrepancy, the team should raise the issue with a leader or stakeholder to discuss the reasons and reassess priorities.

4. DevEx to DevProd Correlation: What insights can we derive from comparing survey responses to sprint outcomes?

For a deeper understanding of how developer experience correlates to sprint performance, engineering leaders learn a lot from juxtaposing the above three sprint metrics with developer survey data. Blending quantitative productivity measures and qualitative feedback creates a holistic view of team performance and well-being, offering deeper insights into the factors influencing developer efficiency, satisfaction, and engagement.

If a team conducts quick surveys at the end of every sprint, you can look at these correlations every sprint. If you only do developer surveys once a quarter, then take a quarterly view.

scatter plot showing alignment to goals via average responses vs say/do ratio by team

Senior leaders and domain leaders benefit from looking at these correlations between sprint metrics and developer surveys for the entire organization, for sub-orgs, and for individual teams. This helps identify systemic issues vs. team-specific challenges and prioritize continuous improvement priorities.

Analyzing results across teams illuminates thriving teams, whose best practices can be shared with others to improve outcomes.

Equipped with these enriched insights, engineering leaders can make more timely and informed decisions to enhance overall developer experience and team morale, target process refinements more precisely, and better assess the impact of changes on developer productivity.

Ready to supercharge your sprint metrics?

Elad Kochavi, an engineering team leader at Riskified, runs his retros with sprint metrics from Faros AI. According to Elad, “We now have a combined picture for all the tools we use and can do much more sophisticated analysis in place of the naive and simplified views in Jira. Our transition to data-driven retros has energized and motivated the team. They love seeing the impact of their efforts in the charts.”

Project management tools like Jira can only take your sprint metrics so far. Faros AI takes engineering data visualization to the next level with dashboards that provide a full, context-rich picture across all your teams’ sprints:

A combined view of human- and machine-curated data from Jira, source control, CI, CD, code analysis, testing, defects, and incidents)

Hierarchical drilldowns based on org structure, product groups, teams, apps, or services

Unlimited history

Velocity, throughput, quality, reliability, and predictability metrics

Team-tailored AI insights and recommendations

Reach out to our experts for more details on how our advanced sprint metrics displayed on customizable dashboards can provide your teams with deeper insights.

The Top 4 Sprint Metrics That Improve Developer Productivity

Key Content Summary

Sprint Metrics and Developer Productivity

Sprint Metrics Answer Key Questions

Top 4 Sprint Metrics

Say/Do Ratio

Planned/Unplanned Work Ratio

Capacity Target Adherence

DevEx to DevProd Correlation

Customer Success Story

Faros AI Platform Benefits

Frequently Asked Questions

Ready to Supercharge Your Sprint Metrics?

Thank you!

Thank you!

The Top 4 Sprint Metrics that Improve Developer Productivity

Sprint metrics and developer productivity

Sprint metrics answer key questions

1. Say/Do Ratio: How accurately are we estimating effort and capacity?

2. Planned/Unplanned Work Ratio: How are we managing our work?

3. Capacity Target Adherence: Are we working on the right things?

4. DevEx to DevProd Correlation: What insights can we derive from comparing survey responses to sprint outcomes?

Ready to supercharge your sprint metrics?

Neely Dunlap

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