3 posts tagged with "roi"

A VP of Engineering walks into the quarterly review with a clean DORA dashboard: lead time down from 9 days to 4, deployment frequency up from 1.2 per week to 2.8, change failure rate trimmed from 18% to 11%. The CFO listens patiently, then asks the only question that matters: "What did that save us in dollars?" The room goes quiet. The DORA tool does not know. The finance tool does not know either, because it does not see deployment data. The CTO ends up arguing on principle. Two quarters later, the platform team's budget is cut to fund a sales hire.

Most engineering organizations track DORA and cost in two separate systems. Sleuth, Swarmia, LinearB show you DORA. Jellyfish (its standalone finance module) and Faros show you cost. The DORA State of DevOps reports explicitly link the four DORA metrics to organizational performance, but only at the outcomes layer, not the dollar layer. To translate "we cut lead time from 9d to 4d" into a real number the CFO defends, you need both data sources in the same query. This article walks through the four integration points, then a worked Q1 → Q2 example with a 2.73x quarterly ROI.

A VP of Engineering presents a $1.2M microservices migration to the board. ROI projection: "we save 30% on infra and ship 2x faster." The CFO asks: "Show me the math." The answer is a single number, 240%, with no method behind it. The board says no. Two quarters later, a competitor closes the same migration in eight months and starts winning enterprise deals on latency. The project was good. The math was the problem.

There is no single "engineering ROI formula." There are five distinct calculation methods, each built for a different question. McKinsey's Developer Velocity Index research found top-quartile teams generate 4–5x the revenue per developer of bottom-quartile teams. That ratio means nothing without specifying how you measured it. Pick the wrong method for the question being asked and you will lose a defensible project. This article walks through all five with worked numbers.

Every quarter, CTOs face the same uncomfortable meeting. The CEO asks: "We spent $2.4M on engineering last quarter. What did we get for it?" And the answer is usually a list of shipped features — not a financial return.

Engineering is the largest cost center in most technology companies, yet it's the one with the least financial accountability. Marketing can show customer acquisition cost. Sales can show revenue per rep. Engineering shows... velocity points? McKinsey's analysis of software developer productivity highlights this gap: engineering output is measurable, but most organizations haven't built the systems to do it.

It's time to change that.