Technical Debt Assessment: A Guide for Business Leaders and Acquirers

A technical debt assessment is a structured review that identifies the shortcuts, outdated components and deferred work in a company's software and infrastructure, and estimates what each one costs in money, speed and risk. The output is a debt register: a ranked list of items, each with a business impact, a cost to fix and a recommended order. Leaders use it to decide what to fix, what to live with and, in a transaction, what to price.

This guide, first published in 2023 and updated for 2026, explains technical debt in business terms, how to measure it without reading code yourself, and how acquirers assess and price it during due diligence. If you need an independent read on your own systems or on a target's, a Sphere code audit produces exactly this kind of register.

What Is Technical Debt?

Technical debt is the future cost of decisions made to ship faster today. Like financial debt, it is not always bad: borrowing time to hit a launch can be the right call. The problem is the interest. Every shortcut left in place makes later changes slower, riskier and more expensive, and the interest compounds when nobody tracks it.

Debt usually takes one of five forms:

1. Design debt. Rushed architectural decisions that make new features or technologies harder to add with every release.
2. Code debt. Corners cut in the code itself, which raise maintenance effort, lower quality and slow development.
3. Testing debt. Too little automated testing, so bugs reach customers and every release carries more risk.
4. Documentation debt. Knowledge that lives in people's heads, which slows onboarding and makes the business dependent on a few individuals.
5. Infrastructure debt. Outdated servers, platforms or versions that cost more to run, perform worse and open security gaps.

A newer form has grown quickly since 2024: code produced with AI assistants and merged faster than anyone reviewed it. It can look tidy while carrying weak tests and logic nobody on the team fully understands. Our conversation on how AI is changing technical debt covers both sides: AI adding to debt and AI helping to pay it down.

How Does Technical Debt Affect the Business?

• Slower innovation. Engineers spend more time on fixes and workarounds and less on new capability.
• Higher costs. Maintenance, incidents and eventual rework compete with every other budget line.
• Longer time to market. Simple changes take weeks, and market windows close before releases ship.
• Talent loss. Strong engineers rarely stay long in codebases they cannot improve.
• Customer experience. Bugs, outages and slow performance reach customers and damage the brand.
• Valuation. In a sale or funding round, buyers and investors look for debt and take its cost off the price.

How Do You Measure Technical Debt?

There is no single number for technical debt, but a handful of indicators show whether it is growing. None of them requires a technical background to follow:

• Maintenance share: the portion of engineering time spent on fixes, patches and workarounds rather than new capability. A rising share is the clearest sign that interest is compounding.
• Lead time for change: how long a small, approved change takes to reach customers.
• Failure and repeat-incident rate: how often releases cause problems, and how often the same problems come back.
• End-of-support exposure: how many critical components run on versions their vendor or community no longer patches.
• Key-person concentration: how many systems only one or two people can safely change.
• Test coverage where it matters: not overall coverage, which is easy to pad, but coverage on the paths where a failure costs money.

Track them every quarter. The trend tells you whether the team is paying debt down faster than it adds new debt, which matters more than any single reading.

How Do You Run a Technical Debt Assessment?

1. Inventory the systems. List what runs revenue, operations and reporting, with each system's age, owner and support status.
2. Follow the symptoms. Ask where delivery is slow, which changes the team avoids and where incidents keep recurring. Symptoms point to debt faster than any tool.
3. Inspect the code. Have engineers who did not write it review the architecture, dependencies and tests. Automated analysis is a starting point, not a verdict.
4. Price each item. Estimate the one-time cost to fix it, the ongoing cost of leaving it, and the risk it carries.
5. Decide. For each item, choose to fix it now, schedule it, accept it, or retire the system that carries it.

How Do Acquirers Assess and Price Technical Debt?

In a transaction, technical debt stops being an internal engineering topic and becomes a number in the deal model. Buyers look for it because it changes what the business will cost to run and grow after close, and they probe it with pointed technical due diligence questions about maintenance load, unsupported components and the modules nobody wants to touch. A well-built technical due diligence report then presents the debt as a costed register, so the deal team can decide where each item lands:

When Betr evaluated a sports-technology acquisition, Sphere tested whether the target could handle five times its load without a ground-up rewrite, and assessed its technical debt both for severity and for how well the target managed it. The report gave a clear scalability verdict and a prioritized debt register, which let Betr's deal team model post-acquisition engineering costs.

Two details matter most to buyers. The first is whether the debt is known: a target that keeps its own register, with owners and dates, is lower risk than one with less debt that nobody has written down. The second is whether the debt blocks the plan the buyer is paying for. Debt in a system the buyer will retire matters little; the same debt in the platform meant to carry growth can move the price. Codebases built heavily with AI tools need an extra look here, covered in our guide to due diligence on AI-generated code.

What Should Owners Do Before a Sale or Investment?

If a transaction is on the horizon, assess your own debt before a buyer does. Fixing the cheap items and documenting the rest turns the buyer's discovery into your disclosure, which is a far stronger position in negotiation. Our guide to preparing for sell-side technical due diligence covers how founders get ready.

How Should You Pay Down Technical Debt?

1. Make it visible. Keep a register and make it safe for engineers to add to it. Debt that is hidden cannot be managed.
2. Prioritize by business impact. Not all debt is equal. Fix first what slows revenue work, threatens security or blocks the growth plan.
3. Budget for it. Reserve a steady share of engineering capacity for debt instead of waiting for a crisis to fund a rewrite.
4. Tie it to strategy. Invest in the systems the strategy depends on, and retire rather than repair the ones you plan to replace.
5. Guard new code. Hold every change to the same review and testing standard, including code written with AI tools.

For how a technical debt assessment fits alongside code audits and full due diligence, see our guide to technical due diligence and code audits.