How Technical Debt Can Impact Innovation and How to Fix It

A new research study has uncovered the staggering impact that technical debt, especially stemming from software architecture issues, is having on enterprise innovation and the economy at large. 

vFunctionsurveyed more than 1,000 architecture, development, and engineering leaders across industries about software architecture technical debt. The report, titled "Microservices, Monoliths, and the Battle Against $1.52 Trillion in Technical Debt," found that architectural technical debt, caused by structural deficiencies, lack of modularity, and violating design principles, was ranked as the most damaging and impactful type of debt for applications.

Top findings include:

The Monolith vs. Microservices Divide

The research exposed architectural disparities, with organizations that use monolithic software architectures facing more pronounced challenges compared with those with microservices architectures.

Monolithic architecture companies were 2.1 times more likely to experience issues with slow engineering velocity, limited scalability, and poor resiliency.

Fifty-seven percent of monolithic architecture organizations allocated more than 25% of IT budgets to technical debt remediation, versus just 49% of microservices-based companies.

Lack of Clear Ownership Is a Challenge

The study also revealed that there is a lack of clear ownership and processes for addressing technical debt within organizations, contributing to the problem. Multiple roles and teams, including enterprise architects, engineering leaders, product owners, and others, were cited as being responsible for remediation efforts.

"While everyone recognizes the impact of accumulated technical debt and the majority have enterprise-wide initiatives to remediate it, there's no clear consensus on who owns it within the organization," vFunction CEO and co-founder Moti Rafalin told ITPro Today.

Rafalin noted that the responsibility varies depending on whom you ask, and different organizations handle it differently.

"Personally, I believe that the head of the IT organization, such as a CIO, needs to address technical debt; otherwise it won't be properly handled," he said.

Why Technical Debt Continues to Be Misunderstood

Rafalin said enterprises are facing what he refers to as boiling frog syndrome when it comes to technical debt.

"Everyone knows it's an issue, and the clock is ticking, but organizations continue to prioritize releasing new features over maintaining a solid architecture," he said. "With the rise of AI, developers are becoming more and more productive, but this also means they will generate more technical debt. It's inevitable."

In Rafalin's view, addressing technical debt requires a strategic vision. While quick patches may save companies in the short term, eventually technical debt will manifest in more outages and vulnerabilities. Technical debt needs to be addressed constantly and proactively as part of the software development life cycle, he said.

Looking for a Quick Fix for Technical Debt? Not So Fast

For organizations just trying to get a quick handle on technical debt, where do they start and what should they do?

According to Rafalin, the reality is technical debt that's been accumulating for a long time has no quick fix, especially architectural technical debt. There is no single line of code fix or framework upgrade that solves these architectural issues.

It's important, he said, to review technical debt on an ongoing basis. Particularly with software architecture, which is sacrificed over time when new features are delivered, teams need to be able to consistently observe it and understand the changes to combat architectural technical debt.

It's also a good idea to take a domain-based approach. A business domain-based prioritization approach allows organizations to align their technical debt management efforts with their most critical business and application modernization goals, Rafalin explained. By sorting tasks based on domain importance, teams can ensure that they are addressing the most pressing issues first.

Not coincidentally, Rafalin's company vFunction also takes this approach to tackle architectural technical debt. He explained that vFunction applies machine learning and AI to understand the architecture and identify areas for improvement, focusing on making the architecture more resilient so organizations have fewer outages and more scalable applications, effectively shifting left for resiliency.

"By using architectural observability and shifting left to improve architecture, organizations can reduce outages, mitigate scalability problems, and accelerate their engineering velocity," he said. "Dealing with the root cause and refining architecture yields benefits in the long run."