The 6 Best Engineering KPIs for Software Development

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Whether you manage a handful of software developers or a large software engineering department, you need to know how your employees are performing.

However, choosing the right engineering KPI can be difficult.

Should you use a KPI for engineering startups since they’re highly agile, or stick with more common metrics used by big businesses?

In this post, we’ll help you answer that question.

Let’s start by looking at two different buckets that engineering KPIs typically fall into.

Engineering KPIs: the Good and the Bad

Too often, we assume the amount of effort or code produced is the best measurement for engineering success.

But writing hundreds of lines of code and logging a full eight-hour day isn’t success in and of itself. Those activities are only valuable because they produce a positive outcome.

Think about it this way; if your employees were to spend their time working on a passion project or writing bad code, you, as a manager, wouldn’t care how many hours they put into it, because it wouldn’t deliver the results you were after.

At the same time, you wouldn’t be mad if a developer finished their weekly tasks an hour early and moved on to a passion project while they waited for the rest of the team to complete their deliverables.

As a result, we need to break away from the standard productivity metrics and focus more heavily on value-based KPIs.

The Best Engineering KPIs

Here are six engineering KPI examples that teams should be tracking and measuring consistently.

1. Measurable Impact

Your team could spend weeks writing millions of lines of code, but it doesn’t matter if the feature isn’t production-ready by the deadline. Users won’t be able to navigate or use it the way you intended.

Given that, you should focus on results rather than productivity.

By setting a goal to achieve a certain business outcome by the deadline (i.e. unveiling a new integration or enhancing an existing functionality), you can both measure your team’s current performance and figure out how to best allocate your available resources in the future.

2. Closed Support Tickets

Support tickets are inevitable.

But the more you let them pile up, the more problems you can run into.

Not only do lengthy queues frustrate customers — which often leads to churn and a tarnished business reputation, but they can bog down projects too, as developers are forced to spend more time resolving tickets each day to stay on top of customer requests.

Luckily, there are a few different ways you can evaluate the speed and quality of your customer support efforts.

You can measure your average response time, the total number of open tickets, the number of tickets closed each day, or customer satisfaction with each resolution.

No matter which way you choose to go, you’ll find meaningful insight that you can use to improve.

3. Technical Debt

Unless you’re disciplined, code quality issues representing technical debt can build up over time and negatively impact security, scalability, reliability, and the overhead of adding new features.

This, in turn, can negatively impact the performance of your solution and decrease your team’s productivity until it’s dealt with.

As a result, tracking the amount of technical debt you have is a must.

One of the easiest ways to do this is by measuring the impact of technical debt on your organization in the form of your cycle time, product stability, security risks, and increased technology costs.

In following the ups and downs of these metrics, you’ll have a good idea of how much technical debt you have and how quickly you need to address it.

4. Implementation Speed

Whether customers are requesting a specific functionality, or you’ve reached the next phase of your product roadmap, you need to get new features to market as fast as possible.

Not only because doing so strengthens your product offering, but because it enables your company to capitalize on opportunities too.

Naturally, this means implementation speed is a critical metric for your engineering team.

By tracking the overall time-to-market for each feature and the amount of time spent on each task, you can get an idea of how optimized your workflow is and improve your sprint planning.

5. Tasks Finished Per Iteration

Each user story comes with a laundry list of tasks that need to be finished before you can officially deploy the product.

But not all of these tasks will get done during the first iteration. Some won’t even be looked at until your team is working on the second or third version.

That being said, the more work you can get done early on, the easier it will be to fix bugs and polish the user interface later on.

So it’s best to keep tabs on how many tasks get done during each project sprint and their total estimated size, typically denominated in “story points.”

In doing so, you might even identify some best practices you can share with your engineering team to increase productivity.

6. Overtime Hours

No matter the reason, letting your team habitually work long hours is problematic.

Not only can it lead to burnout in the short-term, but long-term it can decrease productivity, lower employee happiness, and in some cases reduce your employee retention rates too.

As a result, it’s important to keep a close eye on the extra hours your software engineers are putting in every week.

If you find that they’re regularly staying late to finish a task or resolve a support ticket, it may be time to sit down and discuss work-life balance or find additional resources to help out.

The Bottom Line

Choosing the right KPIs for your team is a challenge.

After all, there are dozens of good options (both quantitative and qualitative) to choose from.

However, by focusing on value rather than productivity, you’ll be able to pick the right software engineering KPI metrics to measure employee performance.

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