Technical Debt: The Invisible Cost That Can Kill Your Digital Project (and How to Control It)

You may have lived through this scenario: software delivered “on time,” then quickly followed by bugs, slowdowns, changes that cost a fortune, and a team that no longer dares to touch the code. At that point, it’s no longer a digital project, it’s a mental burden… and a business risk.

The name of the problem is simple: technical debt. The good news is you can manage it the way you manage a budget, a roadmap, or a risk.

Technical debt: a simple definition (useful for leaders)

Technical debt is the gap between what was built “to ship fast” and what should have been built “to be robust and maintainable.”

Like financial debt, it has:

principal (what needs to be fixed),
interest (the daily extra cost: bugs, slowness, complexity),
and sometimes default (when everything collapses: rewrite, shutdown, customer loss).

The key point: technical debt isn’t always “bad.” It becomes dangerous when it’s invisible, unmeasured, and not prioritized.

The real cost of technical debt: what you pay without seeing it

1) Direct cost: maintenance that spirals

As debt increases, every change takes longer: side effects, regressions, cascading fixes.

Result: you pay more and deliver less.

2) Opportunity cost: slower time-to-market

Technical debt steals your speed. You postpone features, miss commercial windows, and leave room for a more agile competitor.

3) Human cost: turnover, dependency, “bus factor”

A hard-to-maintain codebase creates a vicious cycle: only one or two developers “get it,” and everyone else avoids touching it.

The risk becomes structural: if the key person leaves, your project slows down or stops.

The warning signs

If you tick 2 or 3 items, you have a real issue.

Estimates explode: a “small change” = 3 weeks
Too many “weird” bugs that are hard to reproduce
Risky releases: every production deployment is scary
Lots of fixes, few visible new features
Teams often say: “we’d rather rewrite it”
No documentation, few tests, “magic” code
Outdated dependencies, impossible upgrades

Why technical debt happens (even in good teams)

Time-to-market pressure without guardrails

Shipping fast is normal. The problem is shipping fast without a framework: no standards, no tests, no reviews, no architecture.

Bad early trade-offs

Choosing a “trendy” but poorly mastered tech stack, an overly complex architecture, or an unjustified pile of tools.

A product that evolves faster than the structure

Your product changes (that’s healthy), but the system doesn’t adapt: you stack patches instead of properly reworking key areas.

Lack of technical governance

If nobody owns the quality of the foundation, debt becomes “tomorrow’s problem”… until one day nothing moves forward.

How to control technical debt: a pragmatic 6-step method

1) Make debt visible (or it will win)

Create a debt register: a clear list of topics, with business impact and technical impact.

Concrete examples: “fragile payments,” “no tests,” “untouchable subscriptions module.”

2) Measure what matters (leader-focused KPIs)

You don’t need 50 metrics. Use the ones that speak to the business:

Lead time: time between “we decide” and “it’s shipped”
Incident rate: production incidents per month + severity
Regression rate: bugs reintroduced after a fix
Share of time spent maintaining vs building (e.g., 70/30 = red flag)
Deployment frequency (if it drops, fear takes over)

3) Prioritize by risk and ROI (not by “clean code”)

Not all debt is equal. Prioritize:

what impacts revenue (checkout, acquisition, billing),
what impacts security (auth, permissions, data),
what blocks speed (areas where every change becomes painful).

4) Create a repayment budget (realistic and stable)

A simple rule that works: dedicate 10% to 25% of team capacity to debt reduction (continuously).

Without a budget, you never repay. You postpone, you pile up, and then you rewrite in an emergency.

5) Add guardrails (to keep it from coming back)

What changes everything long-term:

automated tests on critical user journeys
systematic code review
CI/CD (build + test pipeline)
standardization (linting, conventions, architecture)
observability (logs, monitoring, alerting)
minimal documentation: how to run, deploy, diagnose

This isn’t luxury, it’s what protects your investment.

6) Choose the right strategy: refactor, rewrite, isolate

Three options, to decide calmly:

Refactor: when the product is solid and the codebase is salvageable
Rewrite: when the cost of change has become absurd (but beware “total rewrites” without a plan)
Isolate: progressively wrap legacy behind an API and replace parts piece by piece (often the safest)

The classic trap: “we’ll do a rewrite” (and lose 12 months)

A rewrite is sometimes necessary, but it becomes a trap when:

there’s no clear scope,
it freezes the roadmap,
it doesn’t fix governance (so debt returns),
it’s driven by “we hate the code” instead of metrics and risk.

A more robust approach: progressively replace critical areas while still shipping.

Executive checklist: 8 questions to ask your team or vendor

What are our top 3 technical risks today?
How much time goes to maintenance vs new features?
Can we deploy without stress? How often?
Do we have tests on the journeys that generate revenue?
Which area of the code is the most “untouchable”? Why?
Which dependencies are outdated or blocking?
What’s the 90-day debt reduction plan?
Who owns the quality of the foundation (and how is it tracked)?

If the answers are vague, that’s often the real warning sign.

Conclusion: technical debt is managed, not endured

A digital project doesn’t die from a single bug. It dies when the cost of change becomes so high that the company can no longer evolve. That’s exactly what technical debt does.

The solution isn’t “code slower.” The solution is discipline: make it visible, measure it, prioritize it, budget for it, and prevent it.