How to Measure Your Developer Team’s Efficiency the DORA Way
After years of working as a software engineer in the tech industry, I often wondered: “Is my team truly performing well? Where can we improve?” Relying on gut feelings isn’t enough to measure your development team’s efficiency. You need data-driven insights that reflect both speed and quality. Even as a team member or lead, finding clear answers to these questions can be challenging.
A few weeks ago, I attended a tech meetup and unexpectedly discovered a solution to my questions. It was there that I first heard about "DORA".
What is DORA
DORA (DevOps Research and Assessment) is a research program focused on software delivery performance. Their mission is to identify the practices and capabilities that drive high-performing software teams. DORA’s research has produced four key metrics that help teams measure the outcomes of their software delivery process.
These four metrics serve as both leading and lagging indicators:
- Leading indicators highlight potential future shifts in organizational performance and team well-being.
- Lagging indicators provide insight into the effectiveness of your software development and delivery practices.
The Four Keys Metrics
Deployment Frequency (DF)
This metric tracks how often your team deploys code to production. Top-performing teams deploy several times a day, enabling them to deliver value continuously and respond quickly to feedback.
✅ Good: The team can deploy on demand whenever the business needs it.
⚠️ Avoid: The team must wait for a scheduled release window.
Lead Time for Changes (LT)
This metric measures how long it takes for a code change to move from commit to production. Short lead times mean your team can deliver features and fixes quickly, reducing risk and increasing agility.
✅ Good: Code changes reach production in less than an hour instead of a day.
⚠️ Avoid: Code changes are delayed for days or weeks due to manual processes or bottlenecks.
Change Failure Rate (CFR)
This is the percentage of deployments that result in a failure in production, such as hotfixes, rollbacks, or user-facing bugs. A low CFR reflects strong testing and deployment practices.
✅ Good: Fewer than 15% of deployments require a fix or rollback.
⚠️ Avoid: Frequent production issues after deployments.
Mean Time to Restore (MTTR)
MTTR measures how quickly your team can recover from a production incident. Fast recovery minimizes user impact and demonstrates operational resilience.
✅ Good: Average incident resolution time is under an hour.
⚠️ Avoid: Outages or issues linger for hours or days.
Measurement
| Metric | What It Measures |
|---|---|
| Deployment Frequency | Deployments per time frame (daily, weekly, or monthly) per team |
| Lead Time for Changes | Time from code commit to successful production deployment |
| Change Failure Rate | Percentage of deployments that result in a failure in production |
| Mean Time to Restore | Time from incident detection to full-service resolution |
How to Start
Metrics alone won’t improve your team’s efficiency — they should spark conversations and drive action. Here are some recommendations:
- Team Commitment: Make sure everyone understands the value of these metrics and is committed to improving them.
- Set clear baselines: Know your current performance before making changes.
- Collaborate across teams: Involve all relevant stakeholders in the measurement process. Isolating teams can lead to misaligned goals and ineffective practices.
- Use data to drive decisions: Let the metrics guide your process improvements, rather than relying on intuition.
Final Thoughts
Every metric tells a story. By understanding and acting on the DORA metrics, you can foster a culture of continuous improvement within your development team. Remember, the goal is not just to measure, but to enhance collaboration and streamline processes. Start small and let the data guide you.