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Software Development KPIs You Should Track in 2024

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Whether you oversee one team or an entire organization, you need to keep your finger on how things are going.

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A good dev learning culture teaches your team to work smarter, not harder, and a good engineering leader seeks objective data to ensure they’re creating such a culture.

So, to review everything from wait times to efficiency,  software development KPIs can help you leverage objective data to build efficient, healthy, and collaborative teams. While there are plenty of KPIs to track, some are more valuable than others. To refine your personal list of metrics, we’ll break down the top 13 software development KPIs and a few you should avoid.

Cycle time

Cycle time is a measure of how long your team takes to complete a specific task. Despite its simplicity, cycle time paints a clear picture of dev efficiency because it measures the speed of delivery. It also helps with planning by outlining how long it will take to complete a given process. By learning how long each task typically takes, you can easily spot potential bottlenecks and reduce developer toil.

A high cycle time can mean:

Suboptimal processes are slowing your devs down

Your teams may not have the right tools to finish tasks quickly

Insufficient headcount

Too much tech debt

A cumbersome review process

Code coverage

Code coverage measures the percentage of source code properly reviewed by testing processes. This metric is crucial for teams using:

Continuous delivery pipelines

Test-driven development

More often than not, you can’t bank on 100% code coverage. Still, the higher your code coverage, the more you can reliably catch bugs during testing and save time on manual reviews.  You can also note coverage on a code review checklist to better prioritize it.

Code rework

Code rework gauges how much your code changes over time. Rewriting a few lines of code isn’t an issue. In fact, it can mean your code gets the time needed for refinement. On the other hand, frequent rewrites lead to a surplus of developer toil that results in a lot of wasted work that doesn’t end up materially improving the final product.

Change failure rate (CFR)

Your change failure rate tallies the percentage of deployments and changes that cause a failure in production or after release. To calculate CFR, divide the number of changes that resulted in a failure by the total number of deployments.

Change failure rate measures the quality of your source code.

low CFR points to high-quality code with very few bugs.

high CFR means your code needs more testing and debugging.

Bottom line: A high CFR slows your development and puts a low-quality product in front of customers. Platforms like Flow can improve CFR by highlighting parts of the dev process that lead to failed changes. That way, your team can understand the effect of certain changes and reduce risk in future deployments.

Defect detection ratio (DDR)

The defect detection ratio compares the ratio of product defects found before release against the number of defects found post-release. You can also express DDR as a percentage of defects found before or after launch. A high DDR usually points to an ineffective testing process.

Bug rate

Your bug rate tracks how often you find bugs during testing. A high bug rate could mean:

Your devs rush through the coding process. If they don’t review their code before submitting it, you will run into more problems.

Your devs need to gain the necessary experience. They might be new to their role or a type of software.

A high bug rate isn’t a problem in itself. While it can point to dev issues, it also means your tests effectively catch bugs. With this metric, you can take the good with the bad to diagnose deeper problems.

Mean time to recovery (MTTR)

MTTR calculates the average time it takes a team to restore service after a system failure. This metric begins tracking time once a product fails and ends when you restore service. Depending on your field, the “R” at the end of this acronym can stand for:

Repair

Restore

Resolve

This metric is essential for SaaS companies. Because let’s face it, things will inevitably break. That’s why the most customer-centric teams have incident response plans and procedures that help them get back online fast. That said, low MTTR isn’t the goal in itself. Before you restore service, make sure you find the root of the problem to keep it from happening again.

We recommend pairing this metric with change failure rate. CFR tells you if you’re breaking things too often, whereas this metric helps you understand how long it’s taking you to get back online. Flow tracks both metrics to help you understand where problems come from and confidently implement fixes.

Velocity

Velocity notes the amount of work your team completes during a sprint. Most teams understand velocity in relation to story points. By grouping these story points and adding the hours spent on them, you get a sense of your overall velocity so you can set realistic dev goals.

While velocity is a popular metric, it’s tough to define consistently. One team can solve a problem in four hours, while another may need six to fix the same issue. Velocity becomes even harder to define when teams work on different parts of a project or offer different tech skills. So, if you’re going to compare velocity, keep the comparison within a team or specific position.

Cumulative flow

Cumulative flow expresses where most of your tasks and the time spent on them fall in the production pipeline. Cumulative flow typically maps your tasks on a flowchart or table. On the chart, you can group tasks by status, including:

Approved

In a backlog

Acknowledged

In progress

You can find bottlenecks by mapping where your tasks spend the most time. This holds team members accountable and can help identify issues with your pipeline or processes.

Deployment frequency

Deployment frequency covers how often your devs deploy code into staging, testing, or production departments. If your team uses Agile, fast, continuous development is a priority. So, by ramping up your deployment frequency, you increase your Agile maturity. A high deployment frequency increases the number of product changes and helps avoid delays.

Deployment frequency is a comprehensive metric. When calculating it, you’ll see overlap with other KPIs like:

Cycle time

Mean time to recover

Change failure rate

You’ll paint a full picture of your performance by aligning deployment frequency with the other metrics on this list. That said, think about the size of your deployments when tracking this metric. Smaller changes let you deploy more often and drill down on implicated areas of your code base when errors occur.

Queue time

Queue time refers to the average time tickets sit in a waiting state. These tickets may need to wait for feedback, confirmation from team members, or quality assurance. The time a ticket waits for these next steps goes into your queue time.

Long queue times can result from:

Receiving too many tickets for too few QA specialists

A need to adjust the requirements for what tickets get reviewed

Poor lines of communication between staff

Lackluster tools and support to move through ticket queues

Shorter queue times point to an optimized pipeline. The lower this KPI, the better.

Scope completion rate

The scope completion rate covers the percentage of tickets completed in a sprint. The lower your percentage, the fewer they finished. Keep an eye on the completion percentage to ensure your teams set achievable goals. Many teams compare it to sprint burndown and release burndown, but we’ll cover those later.

A low scope completion rate can mean:

You have too few staffers working on tickets

The goals you set for your team aren’t realistic

Your processes get in the way of a higher scope completion rate

Scope added

Your scope added ratio notes the percentage of tickets or story points added after a sprint begins. A high scope-added rate means your sprint planning didn’t account for all the work ahead of you. Additionally, the plans you made during sprint planning may go out the window to accommodate your new work.

If you want to improve this metric, you need to focus on:

Completely scoping out the requirements of the tickets you pull into a sprint

Understanding the systems or issues you would be working with when you initially committed to the scope of your sprint

Eliminating features you don’t have the time to implement

Writing a maintenance forecast on how much time and labor goes into keeping feature additions functioning in the long-term

Common software KPIs to avoid

KPI tracking is an evolving field, with new metrics coming out to refine the process. As a result, a few once-popular KPIs have moved to the sidelines. While tracking these metrics won’t hurt, you’ll find better ones above.

Code simplicity

Code simplicity measures your code’s clarity, brevity, and lack of intricacy. On paper, the metric seems valuable—after all, clean code is easier to execute, maintain, and revise. On the other hand, simplicity is harder to measure than more tangible qualities, and complex projects may demand intricate solutions.

Code stability

Code stability tracks the number of risky changes made to code that could potentially harm the program. Stable code avoids rewrites that could hurt the business. Generally, you can track code stability by:

Noting the frequency of code changes

Reporting on individual changes that pose a risk

Tracking the percentage of code that leads to crashes or downtime

Many teams avoid code stability because it’s difficult to measure. To get around this, you can lump all code changes into code churn. Although that metric doesn’t track risk, it’s far more objective.

Sprint burndown

Sprint burndown offers a narrow measure of the work completed during a sprint. Unlike velocity’s reliance on averages, sprint burndown looks at the number of tasks completed in a given time. Velocity informs predictions about your team’s bandwidth, but sprint burndown helps teams adjust when those predictions fall flat.

Sprint burndown will give less mileage than scope added and scope completion rate. These metrics paint a fuller picture of:

Your team’s workload at the beginning of a sprint

How much work you added in that time

By contrast, looking at the number of tasks completed offers less data.

Release burndown

Release burndown calculates progress during a sprint to determine if you’re behind or ahead of schedule. This metric offers a wider scope than sprint burndown by noting overall release progress. You can also share release burndown data with stakeholders and customers to build hype for the eventual release.

Like sprint burndown, release burndown is a commonly used metric. Still, scope added and scope completion offer a better alternative.

Why should you track software KPIs?

KPIs measure your progress toward meeting business goals. By reviewing these metrics after projects or sprints, you can see how well teams align with your objectives. Low-performing metrics can also indicate a need to adjust business processes or workflows. In the end, metrics contextualize your budgets, timelines, and development issues.

Even during the software development lifecycle, you can use KPIs to avoid unwanted outcomes. When tracking data, you can make predictions about your turnaround time or resources. By keeping an eye on the data, you can course correct and make the most of every sprint.

Tracking KPIs also helps you:

Identify business priorities and measure progress toward them

Refine or fix your processes and workflows

Find the minimum amount of time and money needed to deliver great software

Improve how you set goals and plan tasks

Monitor your business’s overall health

What types of KPIs should you focus on?

Software devs generally review four types of KPIs:

Coding efficiency metrics: KPIs that track how efficiently you create code

Collaboration metrics: KPIs that illustrate how your teams work together

Predictability metrics: KPIs that teach you to accurately estimate dev outcomes

Reliability metrics: KPIs that gauge the quality of your code and the effectiveness of your testing and review processes

What is a software development KPI?

Software development KPIs are metrics that gauge your devs’ performance. While you can look at broad metrics like project turnaround time or lines written per hour, these paint an incomplete picture. Instead, KPIs measure how well your software devs’ output aligns with business goals. Ultimately, these metrics show how well your devs improve business value.

What are the most important KPIs for software development?

The most pressing software KPIs depend on your dev methodology and preferred outcomes. However, a few metrics have almost universal appeal. Cycle time, code churn, and defect detection ratio apply to most teams. Whether you want to manage teams or become a developer, the most important KPIs to look out for are:

Significant: The KPI has to weigh on project success. If the value it tracks doesn’t impact performance, you can drop the KPI.

Clear: Managers need to understand what a KPI tracks and why it matters.

Measurable: Subjective and intangible KPIs don’t offer much value. You need a way to consistently quantify a KPI for it to matter.

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