You have developer productivity metrics. Now what?

Developer productivity metrics are on everyone’s mind, and we’ve been hearing a lot of questions like “How do we know if we’re moving as fast as we can?” or “How can I measure the impact of tooling investments, like using GenAI for coding?” Right now, a lot of conversations about metrics are focused on what to measure. While we don’t believe that problem is perfectly solved, starting with a framework like the DX Core 4 helps you skip through a lot of the brute forcing and guessing as to what metrics really matter.

Now we can bring the conversation up the problem ladder and talk about another thorny problem: Once you have metrics, what on earth are you supposed to do with them?

It’s very common for teams to struggle with interpreting and acting upon developer productivity metrics – even high-performing teams that effectively use data in other parts of their work. Using data for continuous improvement is a separate skill that needs support at the organizational level.

We frequently talk with organizations who say “We’ve just spent the last 6 months setting up DORA metrics, and now we’re trying to figure out what to do with them.”

The key to making metrics useful is to integrate them into decision-making processes at every level—engineering teams, leadership, and platform teams. In this guide, DX’s CTO Laura Tacho describes how to do this while ensuring that the right people are looking at the right data, at the right time.

In this guide, you’ll learn:

• Common use cases for measurement
• Diagnostic vs improvement metrics, and how to choose the right one for your use case
• How to use metric mapping to turn data into meaningful improvements