10 Engineering Metrics for Team Success in 2024

Engineering metrics provide invaluable insights into various aspects of the engineering process, from code quality and team productivity to product performance and customer satisfaction. By tracking the right metrics, you can make informed decisions, identify areas for improvement, and align your teams’ efforts with the broader business objectives.

In this guide, we’ll explore some key engineering metrics and KPIs, highlight their benefits, and share the best implementation practices. Plus, we’ll show you how monday dev can help you track all your metrics in one flexible platform.

What are engineering metrics?

Engineering metrics are quantitative measurements that evaluate and improve various aspects of software development processes, products, and teams. They provide valuable insights that help engineering leaders make data-driven decisions and optimize operations. However, it’s important to choose relevant metrics aligned with specific goals and use them as tools for improvement rather than as absolute measures of individual performance.

Types of engineering metrics

Engineering metrics generally fall into four main categories.

• Product metrics: Measure the quality and performance of the software product itself, including System Uptime, Response Time, Error Rates, and Customer Satisfaction.
• Process metrics: Evaluate the efficiency and effectiveness of engineering processes, such as Cycle Time, Lead Time, Deployment Frequency, and Defect Rates.
• Project metrics: Track the progress and performance of specific initiatives, including Velocity, Burndown, and Cost Metrics.
• People metrics: Provide insights into team productivity and health, such as Team Velocity and Morale scores.

The 10 most beneficial engineering metrics to track

These engineering metrics will help you optimize your development processes, enhance product quality, and drive business success.

• Lines of Code (LOC): Measures the total number of lines in a codebase. While simple, it can provide insights into project size and complexity. However, it shouldn’t be used as a productivity measure, as more lines don’t necessarily mean better code.
• Code Churn Rate: Measures how often code changes over time. It’s calculated by comparing the number of lines added, modified, and deleted to the total lines of code. A high churn rate might indicate instability or frequent changes, while a low rate could suggest a more stable codebase. Industry experts suggest a 15-25% churn rate is reasonable for most teams, with rates below 15% indicating highly efficient teams.
  • Code Churn Rate = (Lines Added + Lines Modified + Lines Deleted) / Total Lines of Code.
• Code Coverage: Measures the percentage of code executed by automated tests. Higher coverage generally indicates better-tested code, but 100% coverage doesn’t guarantee bug-free code.
  • Code Coverage = (Number of Lines Executed by Tests / Total Number of Lines) * 100
• Test Coverage: Similar to code coverage, but specifically focuses on the proportion of test cases that cover the requirements. It helps ensure that all specified functionalities are tested.
• Build Time: Measures how long it takes to compile the code and create an executable version. Shorter build times generally indicate a more efficient development process.
• Number of Commits: Tracks how often code changes are submitted to version control. It can indicate development activity but should be considered alongside other metrics for context.
• Pull Request Flow Ratio: Measures the efficiency of the code review process. A higher ratio indicates a smoother review process.
  • Pull Request Flow Ratio = Number of Merged PRs / Number of Opened PRs
• Code Review Time: Measures how long it takes for code to be reviewed after submission. Shorter review times can lead to faster development cycles, but shouldn’t come at the expense of quality.
• Defect Density: Measures the number of known defects per unit of code. Lower defect density generally indicates higher code quality.
  • Defect Density = Number of Defects / Size of Code (e.g., per 1000 lines)
• Technical Debt: Measures the amount of unresolved technical issues or shortcomings in software code or architecture. It helps teams understand the impact of accumulated technical debt and prioritize refactoring efforts.

What is an engineering KPI?

An engineering KPI (Key Performance Indicator) is a quantifiable metric that measures teams’ success, progress, and effectiveness over time. Engineering KPIs help teams gauge whether they are meeting their strategic goals and provide insights into the software development process.

The key characteristics of engineering KPIs include:

• Quantifiability: KPIs are measurable and can be expressed numerically.
• Alignment: KPIs are tied to specific engineering goals or business objectives.
• Time-bound: KPIs are typically measured over defined periods — e.g. sprints, months, and quarters.
• Actionability: KPIs provide insights for improved decision-making.

Types of engineering KPIs

Engineering KPIs generally fall into eight main categories.

• Quantitative indicators: Numerical data, such as percentages and ratios, represent these metrics. Examples include Number of Commits, Development Cycle Time, and DORA metrics like Lead Time for Changes.
• Qualitative indicators: These KPIs are based on subjective assessments or non-numerical data, like Code Quality Assessments and Customer Satisfaction Surveys.
• Leading indicators: Predict future performance or outcomes — for example, Sprint Burndown Charts and Velocity Trends.
• Lagging indicators: Measure past performance or results — for example, Cycle Time, Deployment Frequency, and Change Failure Rate (CFR).
• Input indicators: Assess the resources required for a project, such as team size and budget allocation.
• Process indicators: Measure the efficiency of engineering processes, such as Code Review Time and Build Time.
• Output indicators: Measure the direct results of engineering efforts, like Features Delivered or Bugs Fixed.
• Outcome indicators: Measure the impact of engineering work on business goals — for example, Customer Satisfaction and Revenue per Engineer.

Engineering KPIs vs. engineering metrics

Engineering metrics and KPIs are related but distinct concepts.

Engineering metrics are a broader set of quantifiable measurements that may or may not directly relate to strategic goals. Organizations use them to:

• Track various aspects of engineering processes, products, and teams
• Measure data points related to engineering activities
• Monitor and manage day-to-day activities

Engineering KPIs are a subset of metrics that directly align with business priorities and outcomes. Leaders specifically choose them to:

• Measure progress toward strategic goals and objectives
• Evaluate overall engineering performance and success
• Report to executives and stakeholders

In essence, all KPIs are metrics, but not all metrics are KPIs.

The top 10 KPIs to track for software engineering success

Here are ten KPIs you could use in your organization.

• Cycle Time: Measures how long it takes to complete a task from start to finish. It provides insight into team productivity and efficiency.
• Deployment Frequency: Tracks how often code is successfully released to production. It indicates agility and the ability to deliver changes quickly.
• Change Failure Rate (CFR): Percentage of deployments resulting in failures or rollbacks. Lower rates signal higher quality and stability.
• Mean Time to Recovery (MTTR): Shows how quickly a team can recover from failures in production. It indicates incident response capabilities. Lower MTTR is better.
• Lead Time for Changes: Measures the time from code commit to successful deployment in production. It reflects the efficiency of development and deployment processes.
• Velocity: Measures the amount of work a team completes in a given period, such as a Scrum sprint. It helps with capacity planning and estimating future work.
• On-time Delivery: Highlights the percentage of projects or features delivered on schedule. It indicates the team’s ability to meet deadlines.
• Bug Fix Rate: Measures the rate at which engineers identify and resolve bugs in the software. It reflects efficiency in debugging and problem-solving.
• Customer Satisfaction Score (CSAT): Measures product performance and usability from the customer’s perspective.
• Developer Satisfaction: While not always quantitative, this KPI is crucial for team morale and productivity. You can measure it through surveys and feedback sessions.

What are the benefits of tracking engineering metrics?

When used properly, engineering metrics can significantly improve software development processes and outcomes. The key is to choose metrics that align with business goals and provide actionable insights, rather than just tracking numbers for the sake of it.

Here are ten key benefits you can expect from tracking your engineering metrics.

• Improved decision-making: Metrics provide data-driven insights that allow for more informed and scientific decision-making, rather than relying solely on intuition or anecdotes.
• Process optimization: Tracking metrics helps identify inefficiencies and areas for improvement in development processes, leading to increased productivity and profitability.
• Product excellence: Metrics can help improve product quality by measuring factors like defect rates, performance, and user satisfaction.
• Business alignment: Engineering metrics can help align engineering efforts with broader business objectives and improve cross-team communication.
• Increased visibility: Metrics clarify priorities, processes, and objectives for engineering teams, helping them understand what outcomes matter most.
• Performance monitoring: Metrics allow teams to measure progress over time and benchmark against goals or industry standards.
• Problem identification: Metrics can help quickly identify issues or bottlenecks in the development process.
• Resource allocation: Data from metrics can inform better resource allocation and cost management.
• Continuous improvement: Metrics enable teams to systematically drive improvements in capabilities and outcomes over time.
• Culture of accountability: Tracking metrics can help instill a high-performance culture focused on meaningful results.

Best practices for implementing engineering metrics

Organizations can drive continuous improvement in their software development processes by implementing and analyzing engineering metrics. Ultimately, the metrics result in better products, more efficient teams, and stronger alignment with business goals.

Follow these best practices for implementing engineering metrics to get the most value for your teams.

• Ensure metrics support business objectives: Metrics should be tied to relevant business goals and outcomes. Engineering work should impact the organization’s bottom line.
• Establish benchmarks: Set benchmarks related to business outcomes and goals. This allows teams to measure progress and see the impact of changes over time.
• Iterate on metrics as needed: Be prepared to adjust your metrics to ensure they remain aligned with evolving business priorities and goals.
• Focus on quality over quantity: Start with 3-5 key metrics and add more over time as needed. Too many metrics can lead to data overload.
• Continuously monitor metrics: Review metrics regularly in team meetings to keep everyone aligned on current status and objectives. Make metrics visible and easily accessible.
• Choose metrics that provide actionable insights: Metrics should help identify areas for improvement and drive decision-making.
• Balance quantitative and qualitative indicators: While quantitative metrics are essential, you should also use qualitative measures alongside regular check-ins and team conversations.
• Align metrics across different levels: Ensure consistency between high-level KPIs and more granular team/individual metrics.
• Avoid common pitfalls: Be wary of vanity metrics, gaming of metrics, siloed metrics, and analysis paralysis from too much data.
• Communicate and get buy-in: Share the purpose and importance of metrics with the team. Solicit feedback and suggestions from team members.
• Use metrics for improvement, not punishment: The goal should be continuous improvement, not penalizing individuals or teams.
• Leverage tools and automation: Use project management tools, software, and custom dashboards to collect and visualize metric data efficiently.

Track your engineering metrics with monday dev

Built on top of monday.com Work OS, monday dev enables the different stakeholders in your organization to track and visualize engineering metrics effectively in one flexible platform.

• Customizable dashboards: Automatically update dashboards with data from up to 50 boards and external sources to monitor engineers’ productivity in real time.

• Third-party integrations: Import metrics like Code Coverage and Technical Debt from third party sources into customized dashboards. For example, the Engineering Performance Dashboard tracks tickets within a sprint along with their corresponding Git status in GitHub.

• Agile boards: Visualize metrics like Cycle Time across sprints and identify any potential problems or bottlenecks through progress tracking. For example, compare the actual remaining effort with the ideal progress in Burndown charts.

• Collaborative platform: Manage team productivity, workload, and morale across your organization from one workspace.

• AI assistant: Create complex formulas for data analysis from simple AI prompts, making it easier to calculate and track metrics and turn your data into actionable insights.

Start your free, 14-day trial today to see how you can track your engineering metrics with our flexible platform.