As a development manager, keeping track of your team’s performance across multiple departments and specializations can present quite a challenge. But it’s compounded when you have to measure the success of your engineering team. Especially if you’re from a non-technical background, the overabundance of metrics and indicators available can be overwhelming.
At 7pace, we’re all too familiar with this challenge. That’s why we’re creating a dedicated guide to the most important engineering KPIs to track as a development lead, useful for both Agile and waterfall development environments.
We’ll start by understanding the important distinction between metrics and KPIs, follow up with some best practices for goal-setting, and provide a list of important deliverables and performance indicators for evaluating your engineering team. Let’s begin!
Metrics are quantifiable measurements that help you track and assess the performance of specific processes or activities within an organization.
In the context of software engineering, they can encompass a wide range of data points, such as code quality, bug count, number of commits, test coverage, and more.
Metrics help you monitor progress and to identify areas of improvement or areas that need attention.
For example, an engineering team might track metrics like:
Code Review Turnaround Time: The time it takes to review and approve code changes
Code Churn: The amount of code added, modified, or deleted in a given time period
Deployment Frequency: The number of times software is deployed to production in a given time period
Key Performance Indicators
KPIs, on the other hand, are a subset of metrics that are specifically chosen to indicate progress towards strategic goals or objectives. (These are the important success indicators — the ones that get people promoted or fired.)
They’re tied to the organization’s overall business goals and help provide a clearer picture of how well the team is performing in terms of meeting those goals. Leaders often use KPIs to track progress, make data-driven decisions, and align team efforts with the company’s objectives.
For a software engineering team, KPIs may include:
On-time Project Completion Rate: The percentage of projects completed within the planned timeline
Customer Satisfaction Score: A measure of customer satisfaction with the software product or service
Mean Time to Resolution (MTTR): The average time it takes to resolve issues, such as bugs or incidents
How to Build a KPI Tree for Engineering Departments
KPI trees are hierarchical structures that visually represent the relationships between an organization’s strategic goals, the department’s objectives, and the indicators used to measure progress towards these objectives.
If you’re an engineering leader or engineering manager working on a KPI tree for your development team, here’s a step–by-step framework to help you get started!
Step 1: Understand organizational goals.
Start by gaining a clear understanding of the overall goals of the organization. This will help you identify the areas where your engineering department can contribute to the achievement of these goals.
Step 2: Define department objectives.
Based on the organization’s goals, define specific objectives and sub-objectives for your engineering department.
Objectives should be clear, measurable, and achievable. Consider factors such as product quality, delivery timelines, customer satisfaction, and resource utilization.
Step 3: Identify relevant metrics.
List all the potential metrics that can help you measure progress towards the department’s objectives. These metrics should cover different aspects of the software development process, such as code quality, productivity, deployment frequency, etc.
Step 4: Select your KPIs.
Not all metrics are equally important or relevant to your objectives. Evaluate the list of metrics based on their relevance, measurability, and impact on the department’s objectives. Choose a few key metrics that directly align with your objectives and can serve as KPIs. Remember that fewer, well-chosen KPIs are more effective than a large number of loosely related ones.
Step 5: Set target thresholds.
For each KPI, establish specific targets and thresholds that indicate the desired level of performance. These targets should be realistic, achievable, and aligned with the department’s objectives.
Step 6: Develop tree structure.
Arrange the selected KPIs in a hierarchical tree structure, with the organizational goals at the top, followed by the department objectives, sub-objectives, and finally, the KPIs at the bottom. This structure will help to illustrate the relationships between the different elements and demonstrate how individual KPIs contribute to overall goals.
Engineering KPIs to Choose From for Software Teams
Lead time measures the total time it takes for a task or feature to go from initial request to completion, including the time spent waiting in queues. This KPI is essential for understanding how quickly the team can deliver new features or address customer requests. Reducing lead time can help improve customer satisfaction, increase agility, and optimize resource utilization.
Cycle time measures the time it takes to complete a task or feature once the team starts working on it, excluding any waiting time. This KPI focuses on the actual work being done and helps identify bottlenecks or inefficiencies in the development process. Reducing cycle time can lead to faster delivery of features and improvements in team productivity.
Time to Market (TTM)
Time to market is the duration from the inception of a product or feature idea to its release in the market. This KPI is critical for competitive advantage, as shorter TTM can help organizations respond more quickly to market needs, capitalize on opportunities, and stay ahead of competitors.
Mean Time to Resolution (MTTR)
MTTR measures the average time it takes for the team to resolve issues, such as bugs or incidents, from the moment they’re reported to the time they’re fixed. A shorter MTTR indicates a more efficient incident response process, which helps maintain system stability, minimize downtime, and improve customer satisfaction.
Deployment frequency is the number of times the team deploys new features, updates, or bug fixes to production within a specific time period, such as per week or per month. This KPI can help you gauge the team’s agility and responsiveness to customer needs, as well as the effectiveness of their development and deployment processes. Higher deployment frequency often indicates a mature DevOps culture and the adoption of continuous delivery practices.
Time to Value (TTV)
Time to value measures the duration it takes for a customer or user to start benefiting from a new feature or product after its release. This KPI helps assess the effectiveness of the team’s efforts in delivering value to customers quickly and can be an indicator of user satisfaction and adoption rates.
Time to First Response (TTFR)
TTFR measures the time it takes for the team to provide an initial response to a customer issue, request, or inquiry. A shorter TTFR demonstrates the team’s commitment to addressing customer concerns promptly and can positively impact customer satisfaction.
Time in Queue
Time in queue measures the waiting time for a task or feature before the team starts working on it. This KPI helps identify bottlenecks or inefficiencies in task allocation and prioritization, enabling the team to optimize their processes to minimize waiting times.
Code Review Turnaround Time
Code review turnaround time is the duration it takes for a team member to review, provide feedback, and approve or request changes to a code submission. Tracking this KPI can help identify bottlenecks in the code review process and ensure the team maintains high standards of code quality while minimizing delays in development.
Time Between Failures (TBF)
TBF measures the average time between system failures or incidents. This KPI can help evaluate the stability and reliability of the software and provide insights into the effectiveness of the team’s efforts in maintaining and improving system resilience.
Time to Deploy (TTD)
Time to deploy is the duration it takes to deploy a new release, update, or bug fix to production. This KPI helps you to evaluate the efficiency of the deployment process, and can guide the team in optimizing their practices to reduce deployment time and minimize the risk of errors or downtime.
Time to Feedback (TTF)
Time to feedback measures the duration from releasing a new feature or update to receiving feedback from users or customers. It helps assess how quickly the team can gather insights on the user experience and make data-driven decisions for improvements or new features.
Why Time Is the Most Vital KPI for your Engineering Team
Time-based KPIs, like lead time, cycle time, time to market, and mean time to resolution, help you to assess how quickly and efficiently the engineering team can deliver new features, fix issues, and respond to customer needs. These KPIs can provide valuable insight into your team’s productivity, agility, and overall performance, which are key factors in achieving the organization’s strategic goals.
But beyond their usefulness for evaluating performance, KPIs relating to time management can also fuel forecasts and predictions for future projects. For example, by averaging all data points about your team’s performance during similar projects in the past, you can develop milestones for future projects that are more realistic and deliverable.
Of course, time tracking tools and extensions are the most important source of data on time-based KPIs, so it’s important for individual developers and engineers to track the amount of time they spend on any kind of engineering work, from production to testing to monitoring.
If you’re looking for an engineer-friendly time-tracker that’ll boost your team’s productivity without being a constant source of anxiety in the workplace, try 7pace, a time-tracking tool that integrates natively with dev environments and informs decisions about performance evaluation, without any of the micromanagement. (Because nobody likes being micromanaged!)