Technical debt has become an increasingly visible barrier to the technological progress of companies. According to the KPMG Global Tech Report 2024, 57% of surveyed tech leaders say their systems experience failures every week, directly affecting business operations. In Spain, the report includes insights from 100 executives on the challenges of digital transformation and how technical debt influences their decisions.
What Is Technical Debt?
Technical debt refers to the accumulated cost of making quick technological decisions that are not sustainable long term. It’s like building a structure on unstable foundations—it may work at first, but over time, cracks begin to show. In technology, these “cracks” are systems that are hard to maintain, update, or scale.
A Global—and Local—Concern
Globally, companies are under constant pressure to innovate. That urgency can lead to rushed decisions that increase technical debt. The KPMG report shows many IT leaders are struggling to keep up with the pace of change, worsening the issue.
In Spain, businesses are investing more in tools like artificial intelligence and cloud computing. However, many still rely on legacy systems that are hard to integrate with newer technologies. This mix creates both operational and strategic tension.
Main Causes of Technical Debt
There are several reasons why technical debt builds up, with the most common being:
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Tight deadlines: Teams opt for quick fixes to meet delivery dates.
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Unclear requirements: Poorly defined project goals from the start lead to long-term issues.
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Weak design: Poor system architecture makes software harder to maintain and evolve.
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Unreviewed AI-generated code: Automated tools, if unsupervised, may introduce subtle errors.
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Lack of testing and documentation: Without basic controls, problems go unnoticed until they grow.
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Tightly coupled systems: Changing one part can break others, making improvements harder.
How to Manage Technical Debt
Managing technical debt doesn’t mean eliminating it entirely—it means handling it strategically. Here are some best practices:
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Measure and track debt: Knowing how much there is and its impact helps prioritize actions.
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Review AI-generated code: Ensures quality and consistency.
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Clear governance and standards: Strong processes prevent repeated mistakes.
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Smart prioritization: Focus on debt that affects security or user experience first.
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Progressive refactoring: Improve the code gradually without halting operations.
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Automated testing: Catches issues before they escalate.
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Up-to-date documentation: Makes work easier and prevents future errors.
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Culture of quality: Promoting best practices from the start reduces risk.
Technical debt isn’t inevitable, but ignoring it has consequences. Managing it wisely is essential for a truly sustainable digital transformation.
