Why are Flow and DORA metrics better together?

In modern software development, tracking progress isn’t just about story points or sprint velocity. To really understand how your team is doing, you need to look at both how fast you deliver and how smoothly work moves through your system. That’s where DORA and flow metrics come in.

Understanding the two metric systems

On their own, each metric tells part of the story. But when you use them together, you get a much clearer picture of your team’s performance, which helps you find bottlenecks, improve software delivery performance, and build more reliable software.

DORA metrics

DORA (DevOps Research and Assessment) metrics focus on performance outcomes. They measure:

• Deployment frequency: How often code is deployed to production.
• Lead time for changes: How long it takes from code commit to production.
• Mean time to recovery: How quickly teams recover from failures.
• Change failure rate: The percentage of deployments that cause issues.

These are widely used in DevOps teams to measure velocity, quality, and stability.

Flow metrics

Flow metrics belong to the Flow Framework. They help you understand how work moves through the value stream. They include:

• Flow velocity: The number of work items delivered over time.
• Flow time: The total time it takes for a work item to go from start to finish.
• Flow efficiency: The percentage of time a work item is actively being worked on vs. total time in the system.
• Flow load: The number of items in progress.
• Flow distribution: The breakdown of work types (features, bugs, risks, etc.)

These are often called value stream metrics because they reveal bottlenecks, delays, and imbalances in your software development process.

Why combine them?

While DORA tells you what happened and how often, flow metrics explain why it happened and where the slowdowns are. Here’s how they complement each other:

1. Broader visibility

DORA metrics show delivery outcomes, but they don’t explain underlying inefficiencies. Flow metrics fill that gap by tracking how work flows through the pipeline.

2. Root cause analysis

If your lead time spikes in DORA, flow time and flow efficiency can help you determine whether the spike is caused by long wait times or overloaded teams.

3. Balance between speed and value

DORA metrics focus on speed and recovery, while flow metrics focus on value delivery. Together, they ensure you’re not just shipping faster but smarter.

4. Stronger alignment with business goals

Flow metrics connect to business value (e.g., more features, fewer blockers), making them a great pairing with DORA for stakeholders who care about ROI.

Real-world application

Imagine your change failure rate has increased. DORA metrics signal the issue, but the flow distribution reveals too many risky items being rushed without proper QA. Together, these metrics empower smart decisions.

• The Axify article on flow metrics explains how understanding flow improves team resilience.
• Uplevel’s blog dives into how flow metrics surface hidden work like meetings and interruptions.

Final thoughts

“You can’t improve what you don’t measure,” as the saying goes. But what you measure and how you interpret it matters even more.

By blending flow metrics and DORA metrics, teams can move from just tracking delivery to truly optimizing software delivery metrics. This integrated view leads to faster, higher-quality releases and better alignment with both engineering and business outcomes.