Gartner estimates that 90% of organisations will suffer from technical debt by 2026, costing 20 to 40% of their technology budget annually. That means for every dollar spent on new features, 20 to 40 cents goes toward compensating for shortcuts taken in previous development cycles.
Technical debt is the accumulated cost of choosing faster, easier solutions over better engineered ones. A hardcoded configuration instead of a proper settings system. A database query that works for 1,000 records but collapses at 100,000. A test suite that covers 15% of the codebase. Each shortcut saves time when it is taken and costs time every day afterward.
How to Measure Technical Debt
Four metrics provide a practical starting point.
Deployment frequency. How often can you deploy to production? Organisations with low technical debt deploy multiple times per day. High debt organisations deploy weekly or monthly because each deployment carries risk proportional to the untested, poorly understood code it touches.
Lead time for changes. How long does it take from code commit to production deployment? Technical debt extends this timeline by adding manual testing steps, approval gates that exist because automated tests are insufficient, and deployment procedures that require careful sequencing because components are tightly coupled.
Change failure rate. What percentage of deployments cause production incidents? High change failure rates indicate insufficient test coverage, poor separation of concerns, and fragile integrations. These are all forms of technical debt.
Dependency age. How many of your third party dependencies are more than two major versions behind current? Outdated dependencies accumulate security vulnerabilities and compatibility issues. They also become harder to update over time because the gap between your version and the current version widens.
These four metrics together give leadership a quantifiable picture of technical debt’s impact on delivery speed, reliability, and security.
How to Manage It
The 20% rule. Allocate 20% of each sprint or development cycle to technical debt reduction. This is not a wish. It is a line item in sprint planning with specific tickets, assigned owners, and measurable outcomes. Teams that skip this allocation accumulate debt faster than they can repay it.
Prioritise by blast radius. Not all technical debt is equal. A poorly designed authentication system is more dangerous than a messy UI component. Prioritise debt reduction work by the potential impact of failure in each area.
Automate quality gates. Linting, test coverage thresholds, dependency scanning, and security checks should run on every pull request. These gates prevent new debt from entering the codebase. Paying down existing debt is pointless if you are adding new debt at the same rate.
Refactor incrementally. Large scale rewrites fail. They take too long, cost too much, and introduce new bugs. The Strangler Fig pattern, replacing small sections of legacy code with improved implementations while the rest of the system continues operating, produces better outcomes with lower risk.
How to Stop Creating It
Most technical debt is created by deadline pressure. Teams know the right approach but do not have time to implement it. The solution is not to eliminate deadlines. It is to make the cost of shortcuts visible at the time they are taken.
Require a “debt ticket” for every shortcut. When a developer takes a shortcut, they create a ticket documenting what was skipped, why, and the estimated cost of fixing it later. This creates a running inventory of new debt and makes the trade off visible to product owners.
What This Means for Your Business
Technical debt is a financial problem disguised as a technical problem. Measuring it in terms that leadership understands (deployment frequency, incident rate, delivery speed) turns it from an engineering complaint into a budget line item that can be managed.
FortySeven’s Software Engineering and IT Consulting practices help enterprises measure, manage, and reduce technical debt. We conduct codebase health assessments, implement quality automation, and build incremental modernisation plans that reduce debt without halting feature delivery.
