CODE TUNER INSIGHTS
How Much Engineering Time Should You Spend on Technical Debt?
There is no universal percentage of engineering capacity that should go to technical debt. Here is a practical way to decide what is right for your software.
There is no universal percentage of engineering capacity that should go to technical debt. The useful starting point is the condition of your software, the work planned for it and the cost of leaving problems alone.
One component may be slowing delivery every week. Another may contain awkward code that rarely changes. A third may be healthy enough that extra maintenance would simply displace valuable feature work. Giving all three the same allocation can be an expensive mistake.
Why a fixed percentage cannot make the decision for you
Reserving capacity for maintenance can be a useful discipline. It prevents urgent feature requests from consuming every available hour. But an allocation tells you how much you plan to spend, not whether you are spending it in the right place.
In a 2020 McKinsey survey, CIOs reported diverting 10–20% of budgets intended for new products to technical-debt issues. Accenture’s research discusses a 15% IT-budget allocation alongside deliberate measurement and prioritisation. These figures concern technology budgets, not a direct prescription for the percentage of each sprint.
A benchmark can start a conversation. Your own evidence should determine the decision. Fifteen per cent might be enough in one organisation and poorly targeted in another.
Match the response to the condition of the codebase
1. The software is healthy enough
If important indicators are stable or improving, changes remain predictable and critical areas are not deteriorating, a major remediation programme may have little justification. Keep routine maintenance in place and protect capacity for new development.
Technical debt can exist without being the most valuable thing to work on next. Evidence that supports continued feature delivery is a useful outcome too.
2. Problems are spreading
A broader intervention becomes more credible when comparable changes are getting harder, complexity is rising across several areas and maintenance demand is increasing. Look for sustained trends rather than a single disappointing measurement.
A stable but imperfect codebase presents a different investment problem from one that is becoming steadily harder to change. Define the scope and review point before committing a larger share of capacity.
3. One area is causing most of the friction
An otherwise healthy product may contain a customer-facing component that repeatedly makes features expensive. Increasing maintenance across every team would spread effort too thinly.
Target the affected component, identify the roadmap work it supports and let development elsewhere continue. The intervention should be as specific as the evidence.
4. The evidence is unclear
Short-term and long-term trends may disagree. An apparent deterioration may be marginal or reflect a change in measurement. Acting immediately creates a cost of its own.
Record the concern, shorten the review period and agree what would trigger action. Monitoring is a deliberate decision when it has an owner and a review date.
Five questions before you increase the allocation
- Is the problem getting worse, or is it stable?
- Is it spread across the estate or concentrated in a few areas?
- How often do engineers change the affected code?
- Which customer outcomes and roadmap commitments depend on it?
- What would we stop building to make room for the intervention?
The last question puts maintenance on the same footing as other investments. A technical improvement may be worthwhile and still be less valuable than the work it would displace.
Allocate for value, then review
The objective is to put engineering capacity where it creates the greatest value. That may mean a larger maintenance programme, a focused intervention, closer monitoring or continued feature development.
Choose an allocation for a defined period. Explain the outcome it should achieve and revisit it using the same evidence. You will have a stronger basis for the next decision than a percentage inherited from last year’s planning process.
Make the next engineering decision with better evidence.
Code Tuner analyses technical debt, complexity and codebase health to support engineering judgement and investment decisions. Explore how Code Tuner can help your team.