How should you accurately interpret DORA metrics?

DORA metrics have rapidly become a standard of the industry, thanks to the book Accelerate which popularized them. These 4 KPIs have been promoted as the essential set to measure and assess the effectiveness of an engineering organization. But as organizations are getting to learn these concepts, it appears that it is not so easy to ensure the success of an engineering team through DORA metrics alone.

Engineering success in 3 concepts: alignment, performance, and an healthy environment

At Echoes, we believe that the success of an engineering organization relies on 3 pillars:

• Alignment with business objectives,

• Engineering performance,

• A virtuous and respectful environment for engineers.

DORA metrics will help you monitor engineering performance. You will be able to spot when a team is drifting on the slippery slope of inefficiency, by anticipating potential issues and bottlenecks early in the development and deployment process.

What you should pay attention to, as an engineering manager? 

A minor increase in Lead Time for changes?

• Metric: the time it takes for a code change to go from commit to deploy.

• What to look for: an increase in lead time may indicate inefficiencies or obstacles in the development process, allowing teams to address issues before they impact the overall project timeline.

A small decrease in Deployment Frequency?

• Metric: how often code changes are deployed to production.

• What to look for: a sudden decrease in deployment frequency may signal problems with the release process, code stability, or integration issues. Identifying and addressing these issues early can prevent further delays.

A rise of Mean Time to Recover (MTTR)?

• Metric: the average time it takes to restore service after a failure.

• What to look for: a rise in MTTR may indicate challenges in incident response or resolution processes. Addressing these issues early can help minimize downtime and improve overall system reliability.

A high Change Failure Rate?

• Metric: the percentage of changes that result in a failure in production.

• What to look for: a high change failure rate may suggest issues with code quality, testing procedures, or deployment processes. Recognizing and rectifying these issues early can prevent common problems and outages.

Detect friction before it's becoming an issue

By regularly monitoring these DORA metrics, an engineering team can learn about its own performance, team members can see how they can improve themselves as a team and quickly identify rising issues. 

Early identification of problems is a virtuous reflex to develop, as an engineering team. It allows  quick corrections and improvements, and hence, fosters a positive developer experience, by aiming at engineering excellence. 

But keep in mind that the specific metrics and their thresholds may vary depending on the organization and its goals. You would be better setting up your own targets.