When you think about what makes a development team productive, code complexity probably isn’t the first thing that comes to mind. But in reality, it can be a big roadblock—one that’s easy to ignore until it starts slowing everything down.
Complex code is like a hidden productivity drain, quietly growing as teams rush to deliver features quickly. What starts as a quick fix can slowly turn into a tangled mess that drags down development and puts the whole engineering team at risk.
For engineering leaders or managers, understanding the nuances that come with the topic of code complexity, and its overall impact on developer productivity is essential for maintaining a high-performing engineering team.
This blog does a deep dive into the impact of complex code on developers and provides practical strategies to tackle it head-on.
How Code Complexity Impacts Developer Productivity
In any engineering team, keeping things moving smoothly is key.
We call this the flow of work.
When the codebase is clean and well-organized, everything just flows—developers can focus on building features, fixing bugs, and getting updates out the door without too much hassle. But when complexity starts creeping in, that flow can get disrupted before you even realize it.
It usually starts with subtle signs. Tasks that used to be straightforward suddenly take longer, and developers spend more time digging through code than actually writing it. The pace slows down, and it feels like more energy is going into untangling the code than into productive work. Reviews start dragging on, and there’s a growing sense that the engineering team is losing momentum.
The challenge with a complex codebase is that it doesn’t just slow things down—it also makes the work itself harder.
Developers might find themselves spending hours just trying to figure out how different parts of the code interact or what might break if they make a simple change. This can lead to lower output and rising frustration levels, which quietly eat away at productivity.
Over time, this complexity starts affecting more than just the immediate tasks. Onboarding new team members becomes a challenge, as they struggle to get up to speed with the tangled codebase. Senior developers might find their focus shifting from strategic work to firefighting immediate issues.
And as these delays add up, they can really start to impact your engineering team’s deployment frequency.
Let’s consider a scenario that highlights what can happen when code complexity gets out of hand.
Real-World Scenario of a Team Struggling with Code Complexity
An engineering team is currently in the middle of a big transition. Maybe they’ve moved from a monolithic architecture to microservices, or they’ve adopted new coding standards to boost scalability and maintainability. At first glance, these changes seem like a win—streamlining processes and setting the product up for the future.
However, as interdependencies grew and logic paths became more convoluted, developers started struggling to navigate the codebase. New hires quickly became overwhelmed, and even seasoned engineers began facing unexpected challenges. Bugs that should’ve been caught were slipping through reviews, causing more rework than anyone anticipated.
The tricky part? These problems didn’t just appear overnight. The complexity had been building for a while and largely ignored in the old system. Now, in the midst of this change, the full impact of these long-standing issues is becoming painfully clear.
This situation is a good reminder of why it’s important to keep an eye on code complexity, even when things seem to be going smoothly. If these concerns had been tackled earlier, the engineering team might have been better prepared for the transition, without the added struggle of trying to fix productivity issues while also reinventing their development process.
Now, the leadership has their hands full: they need to boost developer productivity, simplify the codebase, rethink the development cycle, and make sure they don’t end up in the same spot down the road.
But how to address this problem efficiently? Our next section of the blog dives into this.
How to Address the Challenge of Code Complexity Within Your Engineering Team?
Before you can tackle code complexity, the first step is recognizing that it’s an issue. It’s easy to get used to the way things are, but if you’re starting to notice patterns that suggest things aren’t running as smoothly as they should, it might be time to step back and reassess.
1. Spotting the Problem
The first step in addressing code complexity is to acknowledge that it’s causing issues. This can be tricky because complexity often creeps in gradually, making it hard to spot until it starts causing significant problems. Your developers are on the front lines—they deal with the code every day and likely have a good sense of where things are getting tangled.
Getting everyone on the same page about the problem is crucial. Once the team agrees that there’s an issue, you’re in a much better position to start making meaningful improvements.
After you’ve recognized that there’s an issue, it’s time to dig deeper. Use tools that measure code complexity, like cyclomatic complexity metrics, to identify the most tangled parts of your code. This will give you a clearer idea of where the biggest challenges lie. But don’t stop there—bring in your senior developers to review the code and provide their perspectives. They might spot issues that automated tools overlook.
2. Understanding the Impact on Developer Productivity
Code complexity can have a ripple effect on your engineering team’s productivity, but it hits developers the hardest since they’re the ones in the code every day. To really understand the impact, you need to see how it’s affecting their work.
Start by looking at how long tasks are taking compared to what you’d expect. If tasks that used to be quick are now dragging on for days or even weeks, that’s a clear sign complexity is slowing things down. Another clue is the number of bugs that are slipping through. Complex code is harder to review and test, so it’s easier for bugs to sneak into production, which just creates more work and frustration for everyone involved.
Onboarding new hires is another area where complexity rears its head. If new developers are taking longer to get up to speed because they’re struggling to understand the codebase, it’s a sign that complexity is a significant hurdle. This not only delays their contributions but also pulls senior developers away from their work to help them out.
By tying code complexity to specific productivity issues—like longer task completion times, more bugs, and slow onboarding—you can make a stronger case for why it needs to be addressed. Plus, it helps you figure out which areas to tackle first, ensuring your efforts are focused where they’ll have the most impact.
3. Making a Plan
Once you’ve identified the problem areas, it’s time to make a plan to tackle them. This plan should be realistic, actionable, and focused on long-term improvement rather than quick fixes. Start by deciding which areas to address first. These could be the parts of the codebase that are causing the most pain for your engineering team, such as a particularly complex module or a set of interdependent functions that are frequently the source of bugs.
Set some realistic goals for each sprint. For example, you might dedicate a portion of each sprint to refactoring the most problematic areas of the code. This doesn’t mean overhauling the entire codebase at once—rather, it’s about making consistent, incremental improvements. Updating your coding standards can also be part of the plan. Ensuring that new code adheres to best practices for simplicity and clarity will prevent new complexity from creeping in as you address the existing issues.
In the next section, we’ll cover the strategic steps you can take to boost developer productivity by improving code complexity.
Strategies to Improve Code Complexity and Boost Developer Productivity
Tackling code complexity can feel like an uphill battle, especially when it has been building up over time and is impacting your engineering team's overall productivity. However, with the right strategies in place, engineering leaders can effectively manage and reduce complexity, paving the way for a more productive and agile team.
Here’s how to address this challenge head-on:
1. Adopt Clear and Consistent Coding Standards
Clear coding standards help keep things simple. When everyone on the engineering team uses the same styles, names, and patterns, the code is easier to understand and work with. This means developers can spend more time writing new code and less time figuring out confusing parts. Get the team together to define these standards and ensure everyone’s on the same page.
To help the team stay on track, consider using a system like RAG (Red, Amber, Green) status. It’s a simple way to see where an individual or team’s effort is most needed.
As code reviews become a regular part of your workflow, think about using data to further improve how you work.
2. Use Data to Drive Decisions
Using data to guide decisions on code complexity can really boost your engineering team’s productivity. Data-driven practices help you make smart choices about where to focus your efforts, ensuring you’re tackling the most important areas first. Start by setting clear benchmarks for things like code quality, complexity, and performance. For instance, keeping an eye on cycle time—how long it takes to complete a task from start to finish—can help you spot bottlenecks. If certain parts of your codebase consistently take longer to develop or deploy, that’s a sign those areas need attention.
Deployment frequency is another useful metric. Frequent deployments often mean a more streamlined, less complex codebase, while less frequent ones might suggest the team is struggling with complexity. By analyzing this data, you can spot trends and address issues before they turn into bigger problems.
Also, consider using tools that automatically gather and analyze these metrics as part of your CI/CD pipeline. This way, you’re continuously monitoring the health of your codebase and can make adjustments as needed, instead of waiting for issues to pop up.
3. Break Down Long Functions into Smaller, Focused Methods
When developers encounter massive functions that do too much, it slows them down. Refactoring these large functions into smaller, focused methods not only makes the code easier to understand but also speeds up development. For instance, instead of having a single method that processes orders, validates data, updates the database, and sends notifications, break it down into validateOrder, processPayment, updateInventory, and sendNotification. This approach allows developers to quickly understand and modify specific parts without getting bogged down by unnecessary complexity. This makes the code easier to maintain, test, and update, allowing developers to spend more time on productive work.
While focusing on current standards and practices is crucial, it’s equally important to plan for future growth to keep complexity in check.
4. Plan for Scalability
As your software grows, so does its complexity. Planning for scalability from the start can help you avoid problems down the road. This means designing systems that can handle more load, complexity, and features without becoming too hard to manage. By thinking about future growth and using scalable architecture patterns, you can keep the codebase clean and easy to work with, even as your software evolves.
Enhancing Developer Productivity by Tackling Code Complexity
Addressing code complexity is an investment in your engineering team's efficiency and morale. As we’ve explored, code complexity isn’t just a technical challenge—it’s a major factor that can drain motivation and make even the most dedicated developers feel stuck.
No one enjoys constantly looking back to fix a broken structure. It’s far more satisfying to build something from the ground up rather than continually revisiting old problems. The same applies to how code complexity impacts productivity. When developers are bogged down by a tangled codebase, it slows everything down and makes the entire process more frustrating.
By taking active measures to simplify the codebase, you make work more straightforward and create an environment where your team can focus on what they do best—building great features, solving interesting problems, and delivering quality software. It’s a win-win for both developer productivity and team morale.
If you think other factors might be affecting productivity in your engineering team, now’s a great time to talk to our productivity experts. They’re here to help!
