SMART KPIs are a popular tool with applications in a range of business operations from marketing and sales to employee performance. With modern businesses embracing technology and digital solutions to stay competitive, more attention is falling on optimizing tech teams.
A key area for concern is software development. At scale, software development can be a complex endeavor. This has led to modern software teams drawing on project management techniques and tools to streamline development efforts. From a performance and productivity standpoint, SMART KPIs are necessary for ensuring that efforts are aligned toward project goals.
A key part of the modern software development life cycle (SDLC) is monitoring and analysis. Capturing the right data and using it to create actionable insights is a core feature of successful, data-driven businesses.
SMART KPIs are complementary metrics to SMART goals. SMART stands for:
In project management, SMART goals are the backbone of project planning, execution, review, and reporting. SMART KPIs are the metrics used to track how teams are progressing towards these goals throughout a project.
SMART goals are popular for team leads and project managers, as well as for individual software engineers. They are a useful tool for time management and help to ensure tasks stick to proposed deadlines. Tracking performance and progress towards goals with SMART KPIs can provide greater insight into where your development process is running smoothly, and where it has room for improvement.
To understand what’s going on as the team progresses through their work, you need better visibility into the development process. Measuring productivity in line with SMART goals means dynamically tracking how teams are working in the SDLC.
Areas you might want to keep track of:
In each of these areas, you’ll need to set up infrastructure to capture SMART KPIs to get the insights you need. Another important consideration is that KPIs are most beneficial when used over time. Time series data provides better insights into ongoing activities from project to project.
When tracking performance throughout the software development process, focus on the KPIs that actually relate to SMART development goals. Some companies make the mistake of using easy to capture metrics like:
Unfortunately, these metrics alone aren’t especially useful and can easily be gamed, even more so when teams know they’re being monitored.
The following are a few SMART KPIs that can provide more useful insights into how your teams are working.
These KPIs are typically used to gauge work capacity in teams over time. Velocity typically describes the number of story points that team members complete over the course of a sprint (or other period of time). Sprint Burndown and Burnup charts are visualizations of velocity that show workloads (as story points) as they progress towards completion.
Comparing burn-down charts against estimates can show disparities between team estimates in planning. This is useful for adjusting expectations and estimations going forward. Another benefit is being able to track how team capacity changes over time.
When reviewing Velocity, it’s important to ask why and how a team’s velocity might change from one project to another.
Cycle Time looks at how long tasks or story points take to complete. It’s a more detailed look at how developers’ time is spent. Cycle Time is calculated as the number of man-hours or days between a task’s start and its completion. It’s usually reported as time per unit of work, e.g., 3 days per task.
By tracking cycle time, it’s possible to determine which activities or tasks tend to cost the most time. With this insight, technical leads and project managers can start investigating the root causes of inefficiencies in development. When the major time consumers are known, it becomes easier to find out why.
Lead time describes the time spent on tasks from the moment a request is made to its delivery. In CI/CD development teams, this can provide insights into team agility and responsiveness. For software projects, lead time covers the duration of time between customers making a request and the team delivering finished software into production. For software in production, lead time can be used to track the average time between issues being flagged and resolved.
Over time, this provides insights into historical team performance. This can be used to benchmark team productivity or as a diagnostic aid when productivity declines. If lead times increase, it’s important to find out why. On the other hand, shorter lead times can be a good sign. Be sure to follow up on the factors influencing positive changes and work towards making them consistent.
Code Coverage measures how much of the code in a software product has been covered by unit testing. It also refers to the percentage of code that has been tested and runs as expected. Code coverage is sometimes used as a proxy measure for code quality, assuming that higher coverage means fewer defects
There is often a high correlation between low code coverage and higher rates of defects in production. Measuring code coverage in tandem with defect detection rates in development and in production can empower software decision-makers. With the insights they provide, more informed decisions can be made to balance technical debt with release expediency.
Defect Detection Rates track the number of bugs/defects detected per file or area of code in a project. Tracking the number of defects provides insights into code quality as well as Quality Assurance (QA) performance. In DevOps-based teams or teams with “left-shifted” QA, it also measures the quality of testing in development. It’s a good idea to track both the defects found in development and in production.
Defects in production typically cost six times more to fix than those found early in development. Measuring and keeping track of the number of defects found over time can provide insights into areas of code that are most prone to defects. This can be effective in pinpointing areas for improvement in development.
When looking at developer productivity, one way to measure individual contributions on a project is by looking at the size of changes they make to code. By tracking the size of changes (e.g., the number of lines of code modified in an area of development) it’s possible to quantify just how much work a developer or team contributes over time.
Some software development methodologies measure capacity in man-hours available from full-time employees but this doesn’t reflect the actual effort contributed in terms of code. Tracking the size of changes over time provides insights into ongoing team contributions. This can show trends in developer productivity from project to project.
For project managers measuring the return on investment from project to project, this is a good way to track project outcomes. The basic formula for calculating ROI is the net profit of the product divided by the cost of the project to achieve it. However, when it comes to software development, calculating ROI depends on the type of software being developed and its end uses. Business Process improvement software creates ROI by saving money over time, whereas commercial software or SaaS products generate revenue over time.
Knowing the ROI of a given software project helps when justifying further development on the product and determining the total ownership costs of product development over time. With a clearer view of what your development costs are versus what it returns, you’re in a better position to communicate the cost of inefficiencies to stakeholders.
SMART goals are a great way to organize your software projects and create actionable plans with clear expectations. As development rolls on, keeping sight of how progress is being made towards those goals is essential to successful project management. SMART KPIs are indispensable for product managers and team leads to keep sight of progress in development.
While SMART KPIs are important, progress towards goals isn’t the only concern when it comes to software projects. Given the ongoing nature of development and release cycles, keeping track of product quality, code complexity, and other key metrics are also essential to getting better performance and productivity. When it comes to optimizing processes, the right KPIs can make a world of difference. Learn more about KPIs that make a difference in development here.