The best-performing software engineering teams measure both output and outcomes.

Measuring only one often means underperforming in the other.

While debates persist about which is more important, our research shows that measuring both is critical.

Otherwise, you risk landing in Quadrant 2 (building the wrong things quickly) or Quadrant 3 (building the right things slowly and eventually getting outperformed by a competitor).

As an organization grows and matures, this becomes even more critical. You can't rely on intuition, politics, or relationships—you need to stop "winging it" and start making data-driven decisions.

How do you measure outcomes?
Outcomes are the business results that come from building the right things. These can be measured using product feature prioritization frameworks.

How do you measure output?
Measuring output is challenging because traditional methods don’t accurately measure this:

1. Lines of Code: Encourages verbose or redundant code.
2. Number of Commits/PRs: Leads to artificially small commits or pull requests.
3. Story Points: Subjective and not comparable across teams; may inflate task estimates.
4. Surveys: Great for understanding team satisfaction but not for measuring output or productivity.
5. DORA Metrics: Measure DevOps performance, not productivity. Deployment sizes vary within & across teams, and these metrics can be easily gamed when used as productivity measures. Measuring how often you’re deploying is meaningless from a productivity perspective unless you’re also measuring _what_ is being deployed.

We propose a different way of measuring software engineering output.

Using an algorithmic model developed from research conducted at Stanford, we quantitatively assess software engineering productivity by evaluating the impact of commits on the software's functionality (ie. we measure output delivered).

We connect to Git and quantify the impact of the source code in every commit.

The algorithmic model generates a language-agnostic metric for evaluating & benchmarking individual developers, teams, and entire organizations.