Engineering metrics that don't backfire

Teams usually do not fail because they have no metrics. They fail because the metrics they picked become targets faster than they become insight.

Start with decisions, not dashboards

Before choosing a metric, ask:

• What decision will this metric help us make?
• Who will make that decision?
• What action changes if the value moves up or down?

If you cannot answer those questions, you are probably collecting a dashboard ornament.

Prefer paired metrics over single metrics

Single metrics create blind spots. Pair a speed metric with a quality or stability metric.

• Deployment frequency + change failure rate
• Cycle time + rework rate
• PR throughput + confidence signal

This lowers the chance that local optimization quietly damages the system.

Watch for behavioral distortion

Metrics backfire when they become a status weapon.

If a team can improve the number without improving the underlying outcome, the metric will drift away from reality.

Design reviews for metrics should include one explicit question: How could this be gamed?

Make review cadence part of the metric

A stale metric is usually worse than no metric because it creates false confidence.

1. Define an owner for each metric.
2. Set a review cadence (monthly is usually enough).
3. Retire metrics that no longer drive decisions.

What MergeMeter is optimizing for

MergeMeter focuses on confidence at merge time because it sits close to a real operational decision: whether the organization is shipping changes with a healthy balance of speed and certainty.

As the articles section grows, we will publish more guidance on engineering metrics, quota design, and measurement tradeoffs.