Technical debt and its impact on IT budgets
In this article
Summary
Technical debt refers to the mounting costs, over time, of maintaining software systems built using shortcuts and workarounds to quickly deliver products to market. The money made by taking a product to market fast, however, is soon greatly overshadowed by the crippling impact of tech debt on a company’s IT budget—with around 40% of the average IT department’s spend getting lost to the maintenance of technical debt. Get ahead of technical debt today and mitigate its impact on your IT budget with this article.
Introduction: Technical debt is devouring your IT budget and stifling your team’s productivity
Despite the fact that up to 71% of the value derived from business transformations depends entirely on technology, there is an often-overlooked ‘spanner in the works’ directly responsible for minimizing that value. The culprit? Technical debt; otherwise known as “the silent company killer.”
Technical debt eats IT budgets and profit margins for breakfast, undermines productivity, and delays time to market at lunch, and come dinner time has incrementally compounded your software maintenance costs to such a degree that around 40% of your IT budget is spent solely dealing with the tech debt fallout.
Chief Technical Officers (CTOs) and their IT teams have enough on their plates without having to deal with the limiting effects of technical debt on their IT budget, efficiency, productivity, and reputation.
At Software Improvement Group (SIG), we help IT leaders quantify and reduce technical debt. In this article, we break down what technical debt is, how it impacts IT budgets, and how you can proactively manage it.
What is technical debt?
Technical debt refers to the past decisions taken while developing software, which includes shortcuts and compromises on code quality, for the sake of shortening time-to-market while increasing the long-term cost of software maintenance.
We call tech debt ‘debt’ because it acts in the same way a loan does. The difference between tech debt and a traditional cash loan, however, is that whilst anyone who takes out a loan understands the interest they will later have to pay, technical debt is often entered into unknowingly, and the long-term interest on the debt is left hidden until it is too late and already paid multiple times over.
Here’s an analogy to help better explain what technical debt is and where it comes from:
Imagine building a race car, if the priority of the engineering department is to get the car over the line the fastest, then they’re likely to take anything that adds weight to the car, such as the safety cage. This would arguably be an acceptable approach to engineering, provided that the car (your software) only ever needed to get over the finish line (or get to market) once and you assume everything goes well.
Of course, in reality, software must continue to go round and round our proverbial track for many years, even decades. Like our race car, as software continues around the track, maintenance becomes increasingly more time-consuming because the system was initially built for time-to-market speed and not long-term usability, safety, or performance. In this analogy, technical debt manifests as the high costs of repeatedly pulling the car (your software) into the pit for repairs.
Types of technical debt
We’ve written a separate article detailing the five key types of technical debt most commonly overlooked by CTOs and IT departments. Let’s briefly recap those types of technical debt here:
- Code-level tech debt: Code debt refers to the costs of fixing, modifying, or maintaining poorly crafted code.
- Architectural tech debt: Architecture debt refers to the costs of maintaining unnecessarily complex architectures (like circular dependency ‘spaghetti architecture’). According to Gartner, 80% of technical debt will be architectural by 2026.
- Process-level tech debt: Process debt occurs when software testing stages are skipped, leaving expensive bugs and errors in the code, or documentation of coding practices is insufficient for future engineers to efficiently modify and maintain the system.
- Data-level tech debt: Data debt, particularly relevant in the AI era, refers to a build-up of incomplete and low-quality data or outdated data models and datasets that cost more to run than more modern, efficient substitutes.
- Legacy-level tech debt: Legacy debt refers to obsolescent and/or redundant code that few engineers know how to work with anymore, making maintenance of legacy software even more complex and costly.
Exploring the causes of technical debt
Technical debt arises in software portfolios and tech stacks because of shortcuts taken during development. Let’s take a look at some of the more common types of shortcuts taken, among other root causes of technical debt.
- Time: Perhaps the most common cause of technical debt is time constraints—for example when stakeholders put pressure on a development team to release an app or update before their competitors do. When time is tight, engineers may take shortcuts to meet their deadlines, compromising code quality and generating long-term debt.
- Budget: Similarly, budgetary constraints can cause technical debt to arise in the same way by limiting an IT team’s resources. For example, a smaller engineering team with a larger scope of work may be forced to take shortcuts.
- Negligence: Technical debt is also commonly created by a lack of maintenance and modernization, leaving IT departments with software-turned-legacy which is much slower and more difficult to work with.
- Insufficient Governance and Quality Assurance: When there is a lack of governance or quality assurance processes baked into the software development lifecycle (SDLC), technical debt goes easily unnoticed, its costs compounding over time.
- No documentation: Similarly, a lack of proper documentation practices tied to the SDLC leaves future engineers poorly equipped to properly understand the codebase, thus taking them more time—and costing them more money—to maintain it.
- Manual testing: Similar to the previous two points, a lack of automated testing or use of sub-standard testing methods in the SDCL can leave a debt of bugs and errors which will require fixing further down the line (at far greater expense than if they were fixed early).
- Job security: Software engineers may sometimes purposefully neglect to improve the code or documentation in order to secure their job. So, that the company continues to rely on their “unique skills and understanding”. This is called ‘job security through obscurity.’
How technical debt impacts IT budgets
Now to the crux of our article: How tech debt impacts your IT budget.
Impact 1) Technical debt leads to higher maintenance costs
The principal impact of technical debt on IT budgets is, without a doubt, higher maintenance costs and effort. Simply put, the worse a software system’s codebase and architecture are, the harder and therefore more expensive it is to maintain over time.
What might surprise you to learn, however, is just how expensive those maintenance costs can be. A recent article by Forbes showed that if software bugs are addressed early in the SDLC, such as in the planning stage, they can cost as little as say, $100 to fix. However, if that same bug is left in the system as technical debt, the cost to fix it soon escalates until, further down the line, it can cost one hundred times that amount (or $10,000, in this example).
Impact 2) Technical debt leads to lower productivity
Less obviously financial, but equally as costly is the impact technical debt has on your IT team’s productivity—if not your company’s productivity as a whole. In businesses with lots of technical debt (and bear in mind, the average tech stack is made up of 20-40% pure technical debt), engineers are forced to spend most of their working hours making the software work, which means maintaining and fixing poorly made software. This drastically reduces the amount of time engineers have for value-creating tasks like innovation and design.
Productivity may be further lowered by the oft-reported burnout experienced by software developers working in low-quality code environments. Engineers are quickly drained of motivation and job satisfaction when asked to work round-the-clock to keep a slapdash product up and running. On the flip side, had code quality been prioritized from the outset, the product would contain upwards of 15 times fewer defects and would be five times faster to modify—improving overall team output and decreasing burnout.
Impact 3) Technical debt impacts time-to-market
This may be one of the most important takeaways from this article:
Despite the fact that it is time-to-market prioritization which mainly creates the circumstances for technical debt to arise in the first place, over time that same technical debt is going to severely disrupt and delay your delivery cycle.
As engineers become increasingly tangled up in the maintenance of low-quality code, whilst new technical debt continues to pile up behind them, they have less and less capacity to work on new products, let alone get them to market by the deadline.
Impact 4) Technical debt is the cause for hidden costs
The most visible impacts of technical debt on a company’s IT budget are those we’ve just discussed: higher maintenance costs, reduced productivity, and prolonged time-to-market negatively affecting revenue.
But those aren’t the only ways technical debt can dangerously eat into your budget—there are a number of hidden costs and invisible risks which must also be considered.
- Higher development costs: McKinsey found that, on average, 10-20% of IT budgets intended for the development of new products are instead redirected to dealing with technical debt. In other words, without an effective tech debt management strategy, each new product you decide to engineer will cost 10-20% more than you think.
- Delayed ROI: With demanding maintenance of shoddy code delaying time-to-market for any new product, software ROI is also delayed, proving a problem for both a company’s accounts and its reputation with stakeholders.
- Security risks: Lower-quality code leads to a higher number of vulnerabilities, as our independent research has shown.
Get ahead of technical debt
The best way to deal with technical debt is to minimize its creation in the first place. Our Landscape Scan helps businesses like yours easily uncover and quantify their technical debt, ensuring they can efficiently minimize it whilst avoiding the impacts on their IT budget.
Technical debt is the silent company killer, consuming up to 40% of a business’s entire IT budget on average. Most often, technical debt arises because time-to-market was prioritized in lieu of software quality, and can manifest as any number of engineering nightmares: from complex architectures to legacy systems, garbage code, and redundant data sets.
If CTOs and IT leadership fail to take technical debt seriously, the relatively small costs of addressing bugs early in the software development lifecycle (SDLC) can rapidly escalate into enormous financial burdens. What might have been a quick fix in the initial stages can grow into a complex, deeply embedded issue sometimes costing up to 100 times more.
Proactively managing technical debt starts with visibility. SIG’s Landscape Scan enables IT leaders to uncover hidden risks, quantify debt, and prioritize improvements. Get started today.
