For many developers, the concept of “metrics” evokes a sense of wariness. In the past, organizations often relied on superficial measures—like counting lines of code—that offered little real insight. Worse still, these simplistic engineering metrics were sometimes used to pressure developers, treating software creation as if it were a purely mechanical task rather than a complex, creative discipline. That’s why we should look at engineering metrics differently and, above all, together.
1. Why We Still Need Metrics
Without engineering metrics, organizations and teams risk making decisions based on guesswork rather than evidence. When chosen thoughtfully, metrics provide a balanced, objective perspective that helps identify inefficiencies, validate assumptions, and ensure efforts support organizational goals.
For example, there’s hardly a better way to convince a CTO of GitHub Copilot’s value than by presenting data-backed evidence of its positive impact. Relying solely on the developer’s intuition will not be sufficient for him to make a well-informed decision.
At a small company I worked at, we used DevEx metrics because we were in a growth phase and knew we were onboarding many new colleagues and teams. After establishing these metrics, we overhauled our onboarding process, realizing that new developers were taking too long to contribute meaningfully. Improved documentation and mentoring programs halved the onboarding time, significantly enhancing team productivity and boosting the motivation of new colleagues.
Personally, I don’t favor the metric of time to first commit as it often doesn’t capture meaningful progress. Instead, I prefer measuring time to the 10th commit. By the time a developer has made ten contributions, you can truly gauge whether they’ve integrated into the workflow and are making a real impact.
By tying metrics to meaningful outcomes rather than arbitrary outputs, organizations set the stage for continuous learning, adaptation, and sustainable success.
2. Metric Frameworks
Fortunately, we are not alone on this journey toward more meaningful engineering metrics. As our understanding of effective measurement has evolved, several established frameworks have emerged to guide teams beyond superficial indicators. Each framework provides its own perspective on what “success” looks like and offers a structured path for achieving it.
DORA Metrics:
The DORA metrics—originating from the DevOps Research and Assessment team—have become a gold standard in modern software delivery. They measure four key areas:
- Deployment Frequency: How often code reaches production.
- Lead Time for Changes: How quickly changes flow from commit to deploy.
- Change Failure Rate: The percentage of deployments causing issues.
- Mean Time to Recovery (MTTR): How swiftly teams restore service after an incident.
These engineering metrics have been linked to high-performing teams and offer a clear connection between engineering practices and business outcomes.
SPACE Framework:
Developed by researchers at Microsoft and GitHub, SPACE provides a more holistic view of productivity, moving beyond speed to consider human and collaborative aspects of engineering work. It focuses on:
- Satisfaction: How developers feel about their work environment.
- Performance: How effectively teams meet their goals.
- Activity: The level and type of work being done.
- Communication/Collaboration: How well teams share knowledge.
- Efficiency/Flow: Whether processes are streamlined or laden with friction.
By embracing these dimensions, SPACE acknowledges that productivity is multifaceted—quality of experience and teamwork matter just as much as how fast features ship.
DevEx (Developer Experience):
DevEx metrics shift the lens to the developers’ point of view. Instead of only asking, “How fast can we deliver?” DevEx asks, “Do developers have the support, tools, and freedom they need to do their best work?” This perspective helps organizations invest in workflows and platforms that boost morale, enhance creativity, and ultimately lead to better products.
DX Core4 Framework:
The new kid on the block, building on lessons from DORA, SPACE, and DevEx, DX Core4 distills the essential elements of developer experience into four core metrics. Released in 2023, this framework encourages organizations to focus on the key factors that drive developer satisfaction and productivity, while grounding improvements in tangible outcomes.
4. My Personal Opinion on These Frameworks
While these frameworks provide valuable guidance, it’s important to recognize their generic approach. They often offer a “one-size-fits-all” approach, which can be challenging to apply in unique organizational contexts. Not every metric will resonate with every team, and some frameworks risk becoming checklists rather than instruments for meaningful change. Additionally, over-reliance on any single framework can lead to metric fixation—where hitting targets overshadows understanding what truly improves the team’s outcome and experience
While the first three frameworks focus strongly on process and developer experience, none fully address the crucial question: Are we building the features and products that genuinely matter to the organization’s success?
Furthermore, while the DX Core4 framework at least identifies “impact” as a key metric, it would be stronger, if that concept were more directly tied to the organization’s broader business objectives.
Overall the DX Core4 is my personal favorite and I like the direction in which the frameworks are developing. Also it includes communication guidelines that encourage companies to present it as a supportive partner rather than a strict overseer.
In my view, metrics work best when chosen collaboratively and clearly communicated. Developers should understand why certain metrics are tracked and what the organization hopes to achieve with them. On the other hand, management must accept that blindly applying frameworks won’t yield the desired effects. Instead, metrics should be adapted to the company’s unique strategy. For example, larger enterprises might emphasize operational stability to meet SLAs, while smaller, fast-growing companies prioritize rapid feature implementation, quick service rollouts, or improving the onboarding process for new team members.
Ultimately, these frameworks should be seen as starting points, not final destinations. The most effective metrics strategies embrace the principles behind these models but evolve them thoughtfully. Continuous refinement, experimentation, and developer involvement in decision-making ensure that metrics remain relevant as the organization and its goals change.
5. Using Metrics in Real Life – Action on Metrics
Selecting the right metrics is only the beginning. The real value emerges when teams consistently act on what the data reveals:
- Collect and Visualize Data: Make metrics accessible and easy to interpret through clear dashboards or reports.
- Contextualize with Qualitative Inputs: Pair quantitative metrics with developer feedback, retrospective insights, and user research. Numbers alone can mislead without understanding the “why.”
- Make Metrics a Team Sport: Involve everyone in interpreting and acting on data. When developers and leaders collaborate, metrics guide meaningful, bottom-up improvements.
- Focus on Outcomes, Not Outputs: Use metrics to confirm that changes bring the organization closer to its strategic objectives rather than just increasing activity for its own sake.
6. Conclusion
Metrics, when handled poorly, can feel like a blunt instrument. But thoughtfully chosen and responsibly applied, they serve as a compass rather than a cage. By engaging developers in deciding what to measure and why, teams gain shared purpose and clarity. By customizing metrics to align with a company’s unique goals—whether that’s operational stability in a large enterprise or rapid iteration in a growing startup—metrics can guide sustainable, meaningful progress. In an industry defined by complexity and rapid change, data-driven insights illuminate the path forward.
