Your engineers spend 40% of their time fighting old code
That number comes from Stripe's developer coefficient report, and it matches what we see at enterprise clients. Technical debt is the gap between what your code is and what it should be. It accumulates every time someone takes a shortcut, and compound interest is brutal.
The temptation is to schedule a "big rewrite" or a "tech debt sprint." Both fail. Rewrites take twice as long as estimated and deliver half the value. Dedicated sprints get canceled when the next urgent feature comes in.
A framework that actually works
We've helped enterprise clients reduce their tech debt while maintaining release velocity. The approach has three parts.
Measure it first. You can't reduce what you don't quantify. Track cycle time (how long from commit to production), defect density (bugs per feature), and developer satisfaction scores. These three metrics tell you where debt is worst.
The 20% rule. Allocate 20% of every sprint to debt reduction, not a separate sprint, just 20% of each one. Engineers pick the highest-impact items from a prioritized debt backlog. This is non-negotiable. Even when deadlines are tight. Especially when deadlines are tight.
Strangle, don't rewrite. When a component is too far gone, wrap it in a clean API and build the replacement alongside it. Route traffic gradually from old to new. We did this with a financial services client's transaction processing system. It took 8 months, happened entirely in production, and zero customers noticed the switch.
Where to start: the four types of debt
Architecture debt is the hardest and most expensive. Monolithic services that should be decomposed, databases with 500-column tables, synchronous calls that should be async. Fix these first because they constrain everything else.
Code debt is the most visible. Duplicated logic, no tests, functions that do 15 things. Engineers know where these are. Let them fix what irritates them most.
Infrastructure debt hides until it explodes. Manual deployments, no staging environment, production configs stored in someone's head. Automate these before they cause an outage.
Documentation debt slows onboarding. Every time a new developer takes two weeks to become productive instead of two days, you're paying for missing docs.
The ROI conversation
CFOs ask: "Why should I spend engineering time on code nobody sees?" Here's the answer in their language.
A client we worked with had 8 production incidents per month, each costing roughly $15K in engineer time and customer impact. After 6 months of systematic debt reduction, incidents dropped to 2 per month. That's $90K/month saved, or over $1M annually. The debt reduction work cost about $200K in engineering time.
Frequently asked questions
How do I convince leadership to invest in tech debt? Frame it as risk reduction and velocity improvement, not code quality. Show the data: deployment frequency, incident count, time-to-fix. Leadership responds to trends, not abstractions.
How long before we see results? Infrastructure and code debt improvements show within 2-3 months. Architecture debt takes 6-12 months but delivers the largest long-term gains.
Should we outsource tech debt work? For well-scoped refactoring, yes. An external team can focus on debt reduction while your team maintains feature velocity. That's one of the things we do best.