Delivery metrics let engineering leaders cut cycle time from hundreds of hours to tens, boost deployment frequency, and improve reliability without extra work, by turning data into process improvements.
Engineering leaders at Splice faced a delivery slowdown as the org grew from five to over fifty engineers. By instrumenting delivery metrics they reduced average lead time from several hundred hours to the low tens, even hitting 20-hour weeks, without longer hours or weekends. The data-driven approach gave the team a clear view of bottlenecks and a way to accelerate software flow.
The piece argues that measuring only the delivery segment-code commit to production-yields actionable insight because the design phase is too variable. It highlights four core DORA metrics: delivery lead time, deployment frequency, mean time to restore, and change failure rate, and adds practical signals like build time, code churn, and time to merge. With these numbers the team could see exactly where the process stalled and prioritize fixes.
Adopting metrics requires a clear outcome definition and team trust. Leaders should explain why they measure, involve engineers in the proposal, and use simple tools like surveys to establish a baseline. Once a baseline exists, incremental targets (e.g., moving from monthly to daily deployments) become concrete goals, and continuous iteration beats multi-year roadmaps.
The article warns against using metrics as performance weapons. When metrics are framed as a shared language for prioritizing work and removing blockers, they enable engineers to argue for better sizing, reduce parallel work, and keep focus on quality. The overall message is that disciplined, outcome-focused metrics can restore control, scale delivery, and keep teams motivated.
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