Which Engineering Metrics Actually Drive Outcomes?

DORA metrics are the default to measure team’s velocity. But is your measurement model built for how your teams actually work or just how DORA assumes they do?

Most orgs apply one formula and one benchmark across every team.

• An infrastructure team deploying once every two weeks gets flagged as underperforming.
• A mobile team batching App Store releases looks slow.
• A backend team running trunk-based deployments looks fine.

None of those numbers reflect reality, they reflect a measurement model that wasn’t built for how each team actually works.

We see this pattern repeatedly across engineering organizations in all shapes & sizes.. The problem isn’t DORA as a framework.

It’s applying one definition of “good” to teams with completely different architectures, release constraints, and risk profiles.

Join us on March 18 for Part 1 of a three-part series. Live demo.

What we’ll cover:

• Why DORA breaks down in complex organizations: the patterns we see repeatedly, and why one formula applied everywhere gives leadership a false picture of engineering health.
• How to define measurement that fits how your team actually works: team-specific formulas, benchmarks, and the qualitative signals that tell you what the numbers can’t
• How to unify-team level metrics into a single view leadership can trust, without flattening your organization into a number that means nothing

Bring your questions. Let’s figure it out together!