The Science Behind Impact Score: Going Beyond Lines of Code

If you're looking for a better way to measure engineering contributions than lines of code or commit counts, Impact Score provides a research-backed alternative. This guide explains how it works and how to use it responsibly.

Lines of code is a terrible metric. We've all heard the jokes: "I deleted 2,000 lines today—guess I had negative productivity." But if not LOC, then what?

At Velocinator, we developed the Impact Score to answer this question. It's a composite metric that weighs contributions based on factors that actually correlate with engineering value.

Why Traditional Metrics Fail

Lines of Code

A developer who copy-pastes 1,000 lines from Stack Overflow scores higher than a developer who writes 50 elegant lines that solve the same problem better. LOC rewards verbosity and punishes expertise.

Commit Count

Breaking work into many small commits looks good on a commit graph, but says nothing about the value of those commits. A single, well-thought-out commit can be worth a hundred trivial ones.

PR Count

Similar problem. Opening 20 tiny PRs that each fix a typo is less valuable than one PR that implements a critical feature.

Time Spent

Hours worked is not hours of value delivered. A developer who solves a hard problem in 2 hours is more impactful than one who struggles with the same problem for 20 hours.

The Impact Score Formula

Impact Score weighs several factors, each backed by research on what correlates with engineering effectiveness.

Factor 1: Complexity of Changed Code

Not all files are equal. We analyze the historical complexity of files being modified:

• Files with high cyclomatic complexity
• Files that are dependencies for many other files
• Files in critical paths (authentication, payments, data persistence)
• Files that haven't been touched in a long time (often the hardest to modify safely)

Changing complex, critical code is higher impact than changing isolated, simple code.

Factor 2: Net Contribution vs. Churn

We distinguish between net-positive contributions and churn.

Adding 100 lines and deleting 50 is different from adding 500 lines and deleting 450. The first is extending functionality; the second is thrashing.

We also credit deletions when they simplify the codebase. Removing dead code is high-impact work that's often invisible in traditional metrics.

Factor 3: Review Influence

Impact isn't just about code you write—it's about code you shape.

We track review contributions:

• Comments that lead to changes
• Approvals on complex PRs
• Blocking comments that prevent bugs from shipping

A senior engineer who writes little code but reviews 30 PRs a week is often the most impactful person on the team.

Factor 4: Cross-Team Collaboration

Contributing to codebases outside your immediate team takes more effort. You need to understand unfamiliar code, coordinate with other teams, and often navigate politics.

We weight cross-team contributions higher than contributions to code you own.

Factor 5: Issue Resolution

When we can trace code changes to issue completion (via Jira integration), we factor in:

• Story point value of resolved issues
• Priority/severity of resolved bugs
• Time the issue was open (closing a 90-day-old bug is harder than a 1-day-old one)

What Impact Score Looks Like

A typical developer's Impact Score might be:

• 45% from authored code
• 25% from code reviews
• 15% from cross-team contributions
• 15% from bug fixes

But this distribution varies dramatically by role:

A tech lead might have:

• 20% authored code
• 55% code reviews
• 20% architecture/cross-team
• 5% bug fixes

A junior developer might have:

• 80% authored code
• 5% code reviews
• 10% bug fixes
• 5% other

Neither distribution is "better"—they reflect different roles contributing in different ways.

Using Impact Score Correctly

For Teams

Track team-level Impact Score over time. Is the team becoming more impactful as it matures? Are there periods of high churn that indicate instability?

For Individuals

Use Impact Score to appreciate diverse contributions. The developer with the highest Impact Score might not be the one with the most commits—and that's okay.

For Planning

If a developer's Impact Score is dropping, investigate. Are they blocked? Burning out? Over-committed to meetings? Dealing with technical debt that doesn't show up as visible progress?

For Career Conversations

Impact Score provides data for promotion discussions. "This developer's Impact Score has grown 40% year-over-year, indicating increased scope and effectiveness."

What Impact Score Is NOT

Impact Score is not a productivity ranking. We deliberately don't let you sort developers by Impact Score or create leaderboards.

It's also not a replacement for judgment. A developer could have a low Impact Score because they were:

• On parental leave
• Dealing with a health issue
• Learning a new domain
• Doing unglamorous but necessary work that doesn't show up in code

Context always matters. Impact Score is a conversation starter, not a verdict.

The Research Behind It

Impact Score isn't something we invented from scratch. It's based on:

• Microsoft Research's studies on code complexity and defect rates
• DORA research on deployment frequency and stability
• Academic research on social coding and collaboration
• Our own analysis of thousands of teams using Velocinator

We continuously refine the weights based on outcome data: which contributions actually correlated with team success, feature delivery, and low defect rates?

See Your Impact

Connect your GitHub and Jira to Velocinator, and Impact Scores calculate automatically for everyone on your team.

Finally, a metric that values what actually matters.

For more on why LOC fails, see our guide on moving beyond lines of code. And to understand how to use metrics for growth conversations, read about data-driven career conversations.