To determine how well your engineering team performs, you need clear metrics to understand how efficiently tasks are completed. Without the right metrics, you're working in the dark—making decisions based on assumptions instead of facts.
Engineering performance metrics allow you to see if your team is meeting goals or struggling in certain areas and foster accountability. When the right engineering KPIs and metrics are there for the team members, they can track their performance and feel more motivated to contribute.
Yet, many organizations still struggle to capture and report on key performance metrics in an effective way. A recent KPI Institute report found that 51% of respondents reported that their organizations lack software solutions for tracking and reporting KPIs.
Generally, measuring engineering team performance helps to identify areas where processes might slow down—for example, if tasks consistently get stuck during code reviews, that's a signal to investigate why. Maybe the team needs better tools, or perhaps a communication gap is causing delays.
Imagine you’ve been managing an engineering team for a while. At first, things seemed to run smoothly, but over time, you start noticing that you have no clear way to measure whether your team is truly succeeding or falling behind. This is where metrics come in to provide a way to show your team’s progress in clear numbers. Instead of relying on gut feelings, you can track specific aspects of your team’s performance and make decisions based on it.
In this article, we explain what metrics you should focus on, the best tools to help you track them, and how to choose the most effective metrics for your team’s success.
But what metrics should you look at when measuring engineering team performance? Here are the most essential ones that you might want to keep an eye on:
Lead time measures how long it takes for a task or feature to go from request to delivery. For instance, if a client asks for a new feature on Monday and it's ready by Friday, the lead time is five days. A software development team might track this metric to measure how quickly they can release new features after a customer request.
If lead times are consistent, it shows predictability, which can help in planning and meeting deadlines—provided these deadlines account for the extended lead times. Long lead times often indicate inefficiencies in processes, such as unproductive workflows or communication delays.
When we talk about issue cycle time, we're referring to how long it takes to fix an issue from the moment someone reports it until it's resolved. It’s not just about speed, but also about understanding where things might be slowing down.
If certain types of issues consistently take a long time to resolve, it may indicate a problem within the process, such as inefficiencies, bottlenecks, or unclear workflows. If you keep track of cycle times, you can understand where things get stuck and how to smooth the edges of those sections on time.
Measuring engineering team performance with the deployment frequency metric will help you understand how often your team rolls out updates to production. Frequent deployments —such as weekly or even daily—means you stay in tune with user needs. However, high frequency should be balanced with maintaining quality and addressing user needs.
Rework rate measures how often code needs to be rewritten after deployment. If your team delivers a feature and then must go back and fix it within a short period—usually under 21 days—that's considered rework.
A high rework rate often points to problems like unclear requirements, communication breakdowns, or rushed development. For instance, if a feature is pushed live and users report bugs almost immediately, the team might have to redo significant parts of the code. Tracking this helps you spot patterns and determine where things went wrong. Maybe there wasn't enough testing, or the project scope wasn't clearly defined.
The outsourcing rate is the percentage of work done by external contractors instead of your in-house team. A high outsourcing rate could mean your team needs more capacity or specific skills.
For example, if 40% of your development tasks are outsourced, it could indicate that your in-house team needs more expertise or is overwhelmed with other projects. However, outsourcing can be a smart choice for non-core tasks or specialized work.
When the team lacks internal expertise, outstaffing services may come in handy. ALLSTARSIT provides such services, helping tech companies find talent with specialized skills while reducing costs and administrative burden.
Imagine you’ve been managing an engineering team for a while. At first, things seemed to run smoothly, but over time, you start noticing that you have no clear way to measure whether your team is truly succeeding or falling behind. This is where metrics come in to provide a way to show your team’s progress in clear numbers. Instead of relying on gut feelings, you can track specific aspects of your team’s performance and make decisions based on it.
In this article, we explain what metrics you should focus on, the best tools to help you track them, and how to choose the most effective metrics for your team’s success.
To determine how well your engineering team performs, you need clear metrics to understand how efficiently tasks are completed. Without the right metrics, you're working in the dark—making decisions based on assumptions instead of facts.
Engineering performance metrics allow you to see if your team is meeting goals or struggling in certain areas and foster accountability. When the right engineering KPIs and metrics are there for the team members, they can track their performance and feel more motivated to contribute.
Yet, many organizations still struggle to capture and report on key performance metrics in an effective way. A recent KPI Institute report found that 51% of respondents reported that their organizations lack software solutions for tracking and reporting KPIs.
Generally, measuring engineering team performance helps to identify areas where processes might slow down—for example, if tasks consistently get stuck during code reviews, that's a signal to investigate why. Maybe the team needs better tools, or perhaps a communication gap is causing delays.
But what metrics should you look at when measuring engineering team performance? Here are the most essential ones that you might want to keep an eye on:
Lead time measures how long it takes for a task or feature to go from request to delivery. For instance, if a client asks for a new feature on Monday and it's ready by Friday, the lead time is five days. A software development team might track this metric to measure how quickly they can release new features after a customer request.
If lead times are consistent, it shows predictability, which can help in planning and meeting deadlines—provided these deadlines account for the extended lead times. Long lead times often indicate inefficiencies in processes, such as unproductive workflows or communication delays.
When we talk about issue cycle time, we're referring to how long it takes to fix an issue from the moment someone reports it until it's resolved. It’s not just about speed, but also about understanding where things might be slowing down.
If certain types of issues consistently take a long time to resolve, it may indicate a problem within the process, such as inefficiencies, bottlenecks, or unclear workflows. If you keep track of cycle times, you can understand where things get stuck and how to smooth the edges of those sections on time.
Measuring engineering team performance with the deployment frequency metric will help you understand how often your team rolls out updates to production. Frequent deployments —such as weekly or even daily—means you stay in tune with user needs. However, high frequency should be balanced with maintaining quality and addressing user needs.
Rework rate measures how often code needs to be rewritten after deployment. If your team delivers a feature and then must go back and fix it within a short period—usually under 21 days—that's considered rework.
A high rework rate often points to problems like unclear requirements, communication breakdowns, or rushed development. For instance, if a feature is pushed live and users report bugs almost immediately, the team might have to redo significant parts of the code. Tracking this helps you spot patterns and determine where things went wrong. Maybe there wasn't enough testing, or the project scope wasn't clearly defined.
The outsourcing rate is the percentage of work done by external contractors instead of your in-house team. A high outsourcing rate could mean your team needs more capacity or specific skills.
For example, if 40% of your development tasks are outsourced, it could indicate that your in-house team needs more expertise or is overwhelmed with other projects. However, outsourcing can be a smart choice for non-core tasks or specialized work.
When the team lacks internal expertise, outstaffing services may come in handy. ALLSTARSIT provides such services, helping tech companies find talent with specialized skills while reducing costs and administrative burden.
Let’s now discuss how to measure engineering team performance. If you're looking for the best tools to track key performance indicators for engineering department, consider the following tools:
Jira is one of the engineering teams' most popular tools to track work progress. It helps you create tasks, assign them to team members, and follow their progress from start to finish.
The key benefit is that it gives you clear visibility into where your team is with projects, and you can measure how long it takes to complete tasks (lead time) and how quickly issues are being resolved (issue cycle time).
By looking at reports and dashboards, you can determine if the team is hitting deadlines or if something is causing delays. To get the most out of this tool, it's essential to keep everything up to date—tasks should be assigned, and statuses should reflect the current stage.
Waydev is a tool designed to help engineering teams track their performance and improve how they work. It gathers data from your code repositories, project management tools, and other sources to give a clear view of team activity.
Engineering team metrics like sprint velocity, team throughput highlight where things are going well, and adjustments are needed. The goal is simple: help teams write better code, stay on schedule, and improve collaboration over time.
GitHub is a tool that enables development teams to store and manage their code in one place. Each project is stored in a "repository," a folder where all the files and changes are kept.
You can track every change made to the code, who made it, and when, which helps maintain a clear project history. Someone who wants to add a new feature or fix a bug can create a pull request, and other team members can review the code before it's merged into the main project and ensure that it meets quality standards.
GitHub also integrates with tools that automate testing, so the team can easily spot issues before they become problems.
With ClickUp, you can set up a workspace for your team and create projects and tasks within that workspace. For example, if you're managing a software development project, you can create a project for each feature or sprint and break it down into smaller tasks and sub-tasks. For measuring engineering team performance, you can use this tool's time-tracking feature to calculate how long tasks take to complete.
ClickUp integrates with tools like Slack, GitHub, and Google Drive to keep all your work and communications in one place. For example, if a task requires a code review, you can link it to the related GitHub commit, and once it's reviewed, you can mark it as complete in ClickUp. Managers can use the reporting, and dashboard features to get an overview of team performance, including KPIs for engineering teams like task completion rates.
Trello is another project management tool helping teams track progress. You can use Trello to create boards for various projects, and with each board, you create lists to represent tasks. Each card can be moved across lists, such as "To do," "In progress," and "Done," to visualize the workflow. It's excellent for measuring lead time—you can see how long a task takes to move through each stage.
What works for one team might not work for another, so you need to pick metrics for engineering teams that make sense for the business goals, workflow, and challenges.
For example, if the focus is on speed, engineering efficiency metrics like lead time or cycle time can reveal how long it takes to transition between project stages. If delays occur, these metrics can help identify where bottlenecks are happening—whether in coding, testing, or approval.
If you need frequent updates and features to be added to your product, deployment frequency or completion rates are essential for measuring your engineering team performance. These will show how often your team pushes updates and whether they stick to deadlines.
The right metrics can show you what's going well, where things might be slowing down. The key to measuring engineering team performance is to pick the ones that fit your team and your goals. The best choice is to keep things simple and focus on what helps your team succeed.
If you need to grow your engineering team or bring in skilled professionals for a project, ALLSTARSIT can help. We offer staff augmentation and dedicated team services, you can hire a top remote engineer team from anywhere. This saves time, reduces costs, and eliminates the stress of managing administrative tasks.
Contact us to make it easy to build the team you need.
Imagine you’ve been managing an engineering team for a while. At first, things seemed to run smoothly, but over time, you start noticing that you have no clear way to measure whether your team is truly succeeding or falling behind. This is where metrics come in to provide a way to show your team’s progress in clear numbers. Instead of relying on gut feelings, you can track specific aspects of your team’s performance and make decisions based on it.
In this article, we explain what metrics you should focus on, the best tools to help you track them, and how to choose the most effective metrics for your team’s success.
