The Engineering KPIs That Actually Matter (and Why Jira Metrics Mislead CTOs)

Introduction — Why Traditional Metrics Fail

Jira and Agile dashboards were built for project managers, not for engineering leaders.
They measure how work is organized, not how it actually gets done.

Story points, burndown charts, and ticket velocity might make a project look healthy, but they often hide what’s really happening inside your engineering team. A team can close 100 tickets and still struggle with rework, slow reviews, or inefficient collaboration.

CTOs today need visibility into the real flow of code — where time goes, where progress stalls, and how those patterns affect cost, quality, and delivery speed.
That’s where CodeInteliG comes in.

Why Jira Metrics Don’t Work for CTOs

Jira is a great project coordination tool, but it’s not built to measure engineering performance.
It’s built to track tasks — not outcomes.

Here’s why those metrics fall short:

• Velocity can be gamed by inflating story points.

• Ticket completion doesn’t reflect code complexity or review quality.

• Cycle time in Jira measures ticket duration, not the real pull request flow.

• Burndown charts measure planning accuracy, not delivery efficiency.

CTOs don’t need to know how many tickets were closed — they need to know where their engineering teams are fast, slow, blocked, or reworking code. That insight lives in your codebase, not your task tracker.

The Engineering KPIs That Actually Matter

CodeInteliG goes beyond task tracking to analyze developer activity directly from GitHub and GitLab.
It captures every commit, pull request, and review — transforming raw activity into performance signals that reveal team efficiency, collaboration, and throughput.

Here are the KPIs that matter most to modern CTOs:

• Commits – Show throughput and engagement, reflecting how actively developers are contributing.

• Pull Requests (PRs) – Indicate delivery volume and collaboration patterns.

• PR Cycle Time – Measures time from PR creation to merge, revealing speed and bottlenecks.

• Merge Velocity – Tracks how quickly reviewed code moves to production.

• Review Responsiveness – Measures how fast PRs get reviewed; highlights team collaboration and reviewer load.

• PR Review Coverage – Shows what percentage of PRs are properly reviewed before merging.

• Rework Rate – Tracks how often code is rewritten soon after merge; reveals quality and technical debt issues.

• Contributor Health – Highlights top and at-risk contributors, helping identify burnout or uneven workload.

Example — Frontend Team Dashboard

In a recent CodeInteliG report, the Frontend Team completed 127 commits across 18 PRs.
The data revealed:

• Average merge velocity: 2.4 days

• Review responsiveness: 94%

• PR review coverage: 45%

• Top contributor: Aaron Smith

• At-risk contributors: Two team members flagged for low or inconsistent activity

This paints a clear picture: strong collaboration and high output — but room to improve on review coverage.
These are the kinds of insights Jira can’t surface.

Why These Metrics Work

These KPIs matter because they are:

• Objective – Sourced directly from code activity, not manual inputs.

• Contextual – Filterable by team, repo, or timeframe for deeper insight.

• Correlated – Connected to cost, throughput, and ROI so CTOs can see financial impact.

• Predictive – Highlight risks before they turn into delivery delays or quality issues.

Together, they form the foundation of true engineering intelligence — turning everyday developer activity into executive-level visibility.

The Data Pyramid for CTOs

Think of your engineering data in three layers:

1. Raw Data – Commits, Pull Requests, and Reviews.

2. Engineering Metrics – Cycle Time, Review Responsiveness, Merge Velocity.

3. Business Outcomes – Cost, Speed, Quality.

CodeInteliG automates this pyramid, pulling data from your codebase, calculating KPIs, and connecting them directly to business performance — bridging the gap between technical data and leadership decisions.

From Chaos to Clarity

You can’t improve what you can’t measure — and Jira isn’t measuring what matters.
CodeInteliG brings visibility to the real drivers of performance, empowering CTOs to lead with data instead of instinct.

Stop tracking tickets. Start understanding teams.

Ready to See How CodeInteliG Tracks the Metrics That Matter?

Visit codeintelig.com to explore how leading CTOs are using CodeInteliG to connect engineering performance with business impact.