How to Set Up Engineering OKRs Based on Team Metrics

ana buadzeana buadze
7 min read

Introduction

Engineering OKRs (Objectives and Key Results) are essential for aligning software development teams with broader company goals. However, setting effective OKRs isn't as simple as choosing arbitrary targets. To truly drive performance and meaningful progress, OKRs must be grounded in data—specifically, in the actual performance metrics of engineering teams.

In this blog post, we'll walk through how to use engineering metrics to create impactful, measurable, and realistic OKRs. We'll also explore common mistakes, provide examples, and offer tips for integrating these OKRs into your team's day-to-day workflow.

What Are OKRs and Why They Matter for Engineering Teams

OKRs stand for Objectives and Key Results. They are a goal-setting framework designed to help teams set measurable goals and track their outcomes.

  • Objective: A clearly defined goal.

  • Key Results: Measurable steps to achieve the objective.

While OKRs are popular across various business functions, engineering teams often struggle to create OKRs that are both ambitious and achievable. That’s where team metrics come in. By leveraging actual performance data, you can make sure your objectives are realistic and your key results are quantifiable.

Why Metrics Should Drive Your Engineering OKRs

Relying solely on intuition or subjective assessments can result in vague or ineffective OKRs. By using metrics like cycle time, deployment frequency, pull request review time, and team sentiment, you ground your OKRs in reality.

Benefits of metric-driven OKRs:

  • Enhanced alignment with actual team performance

  • Easier tracking and evaluation

  • Increased team accountability

  • Improved prioritization of engineering work

Key Engineering Metrics to Consider

Before setting OKRs, it’s important to know which metrics can actually inform valuable goals. Here are some of the most actionable ones:

Cycle Time

The time it takes from work starting on a task to it being deployed. Shorter cycle times generally reflect a more efficient workflow.

Lead Time for Changes

This metric shows the time between code commit and release. It’s key for understanding delivery speed.

Deployment Frequency

How often you deploy to production. Frequent deployments typically indicate a healthy DevOps culture.

Change Failure Rate

The percentage of deployments causing a failure in production. This helps evaluate the reliability of your releases.

Mean Time to Restore (MTTR)

How quickly the team can recover from a failure. Lower MTTR = better incident response.

PR Review Time

Long review times delay delivery and frustrate developers. Tracking this can reveal workflow bottlenecks.

Team Sentiment/Burnout Signals

Metrics like PTO usage, after-hours work, and anonymous feedback can reveal signs of burnout and morale dips.

Step-by-Step Guide to Creating Engineering OKRs Based on Metrics

Step 1: Identify Strategic Objectives

Start by aligning engineering goals with broader company initiatives. What is the business trying to achieve this quarter or year? For engineering, strategic objectives might include:

  • Improving delivery speed to support faster product iteration

  • Enhancing product quality to reduce customer churn

  • Reducing operational risk by improving code reliability

  • Increasing developer satisfaction to retain top talent

This step ensures that your engineering OKRs have meaningful impact—not just internally, but across the business.

Step 2: Audit Current Engineering Metrics

Before setting goals, understand where your team currently stands. Use tools like CodeMetrics, Jira, GitHub, or Linear to gather data on cycle time, pull request review duration, deployment frequency, bug counts, and more. This data gives you a realistic foundation for improvement.

For example, if your average cycle time is 7 days, this might highlight bottlenecks in your review process or unclear task definitions. A key result might be to reduce that to 4 days by streamlining reviews or investing in better task grooming. Without this baseline, you risk setting arbitrary or unrealistic goals.

Step 3: Define Objectives

Your objectives should be inspiring, outcome-oriented, and easy to communicate. Think of them as the "why" behind the metrics. They shouldn’t include numbers—that’s the job of the key results.

Examples of strong objectives:

  • Improve our team’s software delivery efficiency

  • Increase engineering team morale and satisfaction

  • Enhance the quality of our code and reduce bugs in production

  • Strengthen team collaboration and review culture

Keep objectives focused and actionable. Avoid vague or overly broad goals that are hard to measure.

Step 4: Set Key Results That Are Data-Driven

Now connect your objectives to measurable outcomes. Every key result should be:

  • Quantifiable – with a clear number or percentage

  • Based on a reliable metric – like cycle time, PR throughput, or incident response time

  • Time-bound – tied to the quarter or another specific timeframe

Here are some strong examples:

  • Reduce average cycle time from 7 days to 4 days

  • Increase deployment frequency from 2x/week to 5x/week

  • Cut average pull request review time by 30%

  • Improve code coverage from 60% to 85%

  • Raise developer satisfaction score from 6 to 8 in internal surveys

Data-driven key results ensure you're tracking progress toward real impact—not just output or effort.

Step 5: Involve the Team

OKRs are more effective when they’re not handed down from above. Involve engineers in the OKR process by:

  • Reviewing the current metrics together

  • Asking for input on which challenges they care about solving

  • Co-creating objectives and key results

This fosters transparency, ownership, and alignment. Engineers are more likely to stay motivated when they feel their voices are heard and their work directly impacts the goals.

Additionally, your team may uncover blind spots or blockers that leadership might not be aware of—like inefficient tooling, lack of test automation, or unclear requirements.

Step 6: Monitor and Adjust

Setting OKRs is just the beginning—ongoing tracking is key. Use a dashboard, a Notion doc, or weekly team meetings to check in on progress. Celebrate wins and highlight blockers early.

If a key result is off-track by mid-quarter, take time to analyze why. Ask:

  • Was the goal too aggressive?

  • Are there external blockers (like delays in design or product)?

  • Are we missing the right tooling or support?

OKRs should be ambitious but not demoralizing. Be flexible: you can revise goals based on what you learn. The goal is continuous improvement, not perfection.

Examples of OKRs Based on Engineering Metrics

Objective: Improve Delivery Speed

Key Results:

  • Reduce cycle time from 6 to 4 days

  • Increase PR merge frequency by 25%

  • Lower average PR review time to under 24 hours

Objective: Increase Engineering Quality

Key Results:

  • Reduce change failure rate from 12% to 5%

  • Raise test coverage from 60% to 85%

  • Implement 100% code review coverage on all PRs

Objective: Strengthen Developer Happiness

Key Results:

  • Increase team eNPS from +10 to +30

  • Reduce weekend commits by 50%

  • Launch 1 team offsite per quarter

Common Mistakes to Avoid

Setting Vanity Metrics

Avoid metrics that look good on paper but don’t drive meaningful change (e.g., number of lines of code written).

Not Connecting OKRs to Business Goals

Engineering metrics should tie back to business impact. For example, reducing MTTR helps improve uptime and customer satisfaction.

Ignoring Qualitative Inputs

Numbers tell a lot, but not everything. Supplement with developer feedback, surveys, and retrospectives.

Overloading on OKRs

Less is more. Focus on 1–3 meaningful objectives per quarter.

Integrating OKRs Into Your Engineering Workflow

Set regular cadences for OKR check-ins—biweekly or monthly.

Best practices:

  • Include OKRs in sprint planning and retros

  • Use dashboards to visualize key results

  • Celebrate progress publicly

Tools like CodeMetrics.ai can help you monitor your metrics in real-time and flag when things go off track.

Final Thoughts

Metrics-based OKRs are a game-changer for engineering teams. They make goals more grounded, transparent, and effective. By aligning OKRs with your actual team performance, you not only set realistic goals—you also create a culture of continuous improvement.

If you're not sure where to begin, start with your existing metrics dashboard. Look at what's trending in the wrong direction—or not improving fast enough. That’s your clue for where your next objective should be.

Remember: Great teams don’t just measure—they act on what they measure.

Need help? CodeMetrics.ai makes it easy to track engineering KPIs and set OKRs that actually move the needle. Book a demo to learn more.

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Written by

ana buadze
ana buadze