Despite the fact technical debt affects most modern organizations, it is an often misunderstood concept. Is technical debt analogous to financial debt? Is the name just a metaphor, or does it literally refer to the debts incurred by purchasing expensive technology? How much damage can unchecked technical debt do?
If you are an organization with an IT department, it’s likely that you’re currently dealing with at least some measure of technical debt. It’s critical to understand how it impacts your business, and proactively attack this debt. In fact, it’s one of the most important things you can do to protect the long-term success of your company.
What Is Technical Debt?
Technical debt is a metaphor used to explain the negative impact that choosing short-term software solutions can have, at the expense of the long-term benefit of the enterprise. The term, first coined by programmer Ward Cunningham in 1992, was used to describe what happens when programmers settle for a stop-gap, okay-for-now software solutions and inevitably have to pay the price down the line—plus interest.
Like financial debt, accruing technical debt is often the result of a series of small decisions, rather than one big one. Most enterprises willingly take on technical debt as a calculated risk. For example, development teams faced with small budgets and tight deadlines might find themselves knowingly accruing technical debt so they can get new features to market in time. If you leave the technical debt to grow without tending to it regularly, there comes a point where development on the app will get to a screeching halt. Every feature takes a very long time to bring to market—and involves some kind of a pain. This is when people start saying that they need to do a big refactor— or,even worse, a rewrite of the whole code base.
When speed to market isn’t a factor, technical debt is most common in enterprises that lack infrastructure to support practices that would improve code quality, like a team dedicated solely to testing code.
The truth is that all enterprises deal with a certain amount of technical debt, so much so that it’s considered a necessary cost of doing business. They can even think of it as the cost of innovating. However, having any amount of technical debt can get expensive very quickly.
Breaking Down the Costs of Technical Debt
Technical debt in enterprise businesses can hinder agility and innovation, slowing down the development and deployment of new features or products. This accumulated backlog of suboptimal code and infrastructure can lead to increased maintenance costs and a higher risk of system failures, impacting overall operational efficiency. Moreover, tech debt may impede the ability to respond swiftly to market changes, diminishing a company’s competitive edge and potentially affecting customer satisfaction.
The costs of technical debt manifest in many ways, most notably maintenance costs. According to “The Cost of Poor Quality Software in the US”, a report published in 2022 by the Consortium for IT Software Quality, the cost of poor software quality has grown to at least $2.41 trillion. The accumulated software technical debt (TD) has grown to ~$1.52 trillion. That number did not include the cost of future technical debt. This data indicates why software developers spend 42% of their time fixing bugs, and why a whopping 80% of IT budgets go toward doing so.
How To Measure Technical Debt
Measuring technical debt is a complex task, requiring you to assess various aspects of software development, including code quality, system architecture, testing practices, and documentation.
While there is no universally accepted set of key indices and ratios, here are ten commonly used metrics and ratios that organizations often consider when evaluating technical debt:
- Technical Debt Ratio (TDR): This ratio represents the amount of technical debt in the codebase relative to the size of the codebase. It is calculated as the sum of technical debt items (e.g., code issues, architectural concerns) divided by the total lines of code. (Remediation Cost ÷ Development Cost) × 100 = TDR can be measured in both monetary and time value – whichever is more beneficial for particular goals. A lower technical debt ratio indicates a healthier codebase.
- Code Smells Density: Code smells are indicators of potential issues in the code. The code smells density measures the number of code smells per unit of code (e.g., per 1,000 lines of code). A higher density suggests a higher level of technical debt.
- Cyclomatic Complexity: Cyclomatic complexity is a measure of the complexity of a program’s control flow. Higher complexity can indicate a higher likelihood of defects and increased difficulty in maintaining the code. Monitoring cyclomatic complexity can help manage technical debt related to code complexity.
- Test Coverage: Test coverage is the percentage of the codebase covered by automated tests. Low test coverage indicates areas where defects may go undetected, contributing to technical debt. The goal is to have high test coverage to ensure a robust codebase.
- Duplicated Code Percentage: Duplicated code can lead to inconsistencies and maintenance challenges. The duplicated code percentage measures the proportion of duplicated code in the overall codebase. Higher percentages suggest a need for refactoring to reduce redundancy.
- Code Churn: Code churn measures the frequency of code changes. High code churn may indicate instability and ongoing development challenges. Monitoring code churn helps identify areas that may contribute to technical debt.
- Architectural Debt Index: This index assesses the architectural quality of the system. It considers factors such as adherence to design principles, modularity, and coupling. A higher architectural debt index indicates more architectural issues that may contribute to technical debt.
- Documentation Debt Index: This index evaluates the quality and completeness of documentation. It includes factors such as the presence of code comments, up-to-date system documentation, and knowledge transfer practices. A higher documentation debt index suggests documentation-related technical debt.
- Bug Density: Bug density measures the number of bugs or defects per unit of code. Monitoring bug density helps identify areas of the codebase that may contribute to technical debt, requiring additional attention and refinement.
- Technical Debt Pay-down Rate: This rate represents the speed at which technical debt is being addressed or “paid down” over time. It is calculated as the reduction in technical debt over a specific period. A higher paydown rate indicates proactive efforts to manage and reduce technical debt.
Technical Debt Impact on Business
Technical debt also directly contributes to an enterprise’s legal costs in the form of fines, compliance penalties, and even lawsuits. HIPAA and PCI violations alone can each cost up to $1.5 million. When you add in technical debt, a vicious cycle ensues.
When enterprises have a lot of technical debt, it’s harder for them to fix software errors quickly, which results in time-based fines. Outstanding fines continue to increase until they are paid, which leads to more debt, and so on. In addition, data breaches due to faulty code can cost as much as $8.9 million in lost business, legal fees, and other costs associated with a publicly damaged reputation.
Two other major costs of technical debt—opportunity costs and talent—are harder to quantify, but they still add up.
Opportunity costs refer to the loss of potential gain when you choose one option over another. Enterprises with technical debt perpetually struggle with this dilemma because IT companies have finite resources—which is compounded by the ongoing IT skills shortage—and every operational decision will be informed by that debt. Every minute spent on maintenance due to technical debt is a lost opportunity for innovation or value-adding work.
Technical debt has human costs as well. Outdated technologies are hard to maintain, and it’s even harder to find software developers who can and are willing to work with these technologies. Enterprises with technical debt also experience higher turnover because talented developers are less inclined to stay at a company where they spend so much of their day fixing legacy code. This can have expensive consequences. Studies estimate it costs 6 to 9 months of annual salary to replace the average salaried employee, and even more for high-earning or executive-level employees.
When companies think about it this way, the most effective (and extreme) way to reduce technical debt once and for all is to stop all other projects to focus on addressing the problem. But the fact of the matter is that doing so is simply not realistic for traditional development teams. The opportunity cost of halting all other projects is too high, which is why companies have no choice but to tackle it in small chunks—and inevitably get trapped in a continuous cycle as debt compounds.
How Codeless Development Can Help Reduce Technical Debt
So far, we’ve only scratched the surface. The above costs don’t even include direct loss of revenue from software glitches or the customers lost when vital services go offline. With these crippling costs in mind, it’s time to modernize, integrate your legacy systems into new technologies, and free your organization from technical debt.
Codeless application development offers a cost-effective way to move away from legacy systems that were built on shortcuts. The most obvious way that codeless reduces or eliminates technical debt is by removing code altogether (unlike low-code/no-code platforms. That’s because the Unqork platform doesn’t generate any legacy code—because it doesn’t generate code at all.
But as we discussed above, there are a few other costs associated with technical debt that make it such a burden. Once a codebase is removed from the equation, codeless continues to tackle some of the secondary costs associated with technical debt.
By building in enterprise-grade security features from the ground up, the Unqork platform ensures that your applications are compliant with any audits. By removing your organization’s reliance on code in one fell swoop, your team is immediately freed up to work on your project backlog—avoiding any opportunity costs typically associated with paying off technical debt.
And finally, by empowering your employees with an intuitive tool to build complex applications, codeless can hopefully help you avoid turnover and increase employee satisfaction. Unqork can be seamlessly integrated with existing technology, which means no more struggling to configure a system you no longer use in order to unlock valuable data. It may not be possible to be 100% free of technical debt, but building apps with no code goes a long way in decreasing your balance.
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