Most manufacturers don’t choose to end up with technical debt. It just happens over time.
You layer fixes on top of fixes, hang onto old systems a little longer than planned, and before you know it, every small change starts to feel like a big project.
What used to be “good enough” slowly turns into a real problem.
As plants try to improve visibility, connect equipment, or use analytics, those old systems start dragging everything down.
At that point, technical debt isn’t just an IT issue. It affects production, profitability, and how fast you can take on new opportunities.
In this article, we address how technical debt forms, how it affects day-to-day operations, and the practical steps teams can take to reduce it.
Technical debt shows up long before a system fails. It reveals itself in the small friction points that accumulate across your operations. The impact usually tends to surface in three areas:
Teams move slower because every change carries risk.
A simple workflow update can trigger weeks of testing. A new data requirement might require custom scripts and manual workarounds. This delay compounds and ultimately constrains growth.
McKinsey estimated that 20 to 40 percent of a company’s technology value is tied up in technical debt.
A lot of IT teams spend most of their time maintaining outdated software instead of helping the business move forward. In the long run, companies that delay modernization often pay a lot more just to keep old systems running.
Legacy systems don’t connect well, which makes it harder to adopt things like real-time analytics, quality automation, or machine data collection. You get stuck with half-finished projects or tools that can’t scale.
In simple terms, technical debt quietly pulls time, budget, and energy away from activities that actually drive improvement.
Technical debt doesn’t show up in just one form. It can be a quick workaround that never got fixed, a legacy system your team is scared to touch, or a deeper architectural problem that slows everything down.
A simple way to think about it is this: Some debt happens on purpose, some by accident.
Some comes from careful trade-offs, and some comes from rushed decisions that weren’t well thought out.
Reckless vs. careful: Did the team take on the debt with a clear reason, or did it happen because of shortcuts or poor choices?
Intentional vs. unintentional: Did everyone understand they were creating debt, or did it slip in without much awareness?
After understanding those traits, it helps to look at the most common types manufacturers face:
This is when the foundation of a system can’t support where the business needs to go.
Monolithic designs, tightly connected components, and outdated frameworks make updates slow and risky. When a small change requires touching three or four other systems, that’s architectural debt at work.
Code debt usually comes from rushing or cutting corners.
Maybe someone copied and pasted logic instead of building it properly, or skipped documentation because they were trying to hit a deadline. These shortcuts add up and make debugging or adding new features way harder than it should be.
This shows up when deployment processes, servers, or CI/CD pipelines are behind the times.
Teams end up doing manual steps that should be automated, dealing with broken pipelines, or struggling to update dependencies. Old infrastructure makes everything slower, from releases to testing to troubleshooting.
Sometimes the problem isn’t the technology, it’s how people work together.
Poor communication, inconsistent workflows, unclear ownership, or missing documentation all create drag. This type of debt shows up when onboarding takes too long, backlogs balloon, or teams struggle to track work efficiently.
Security debt builds up when patches are delayed, outdated authentication stays in place, or no one regularly checks for vulnerabilities. These gaps don’t always cause immediate problems, but they create serious risks over time, especially in regulated industries.
Each type stacks on top of the others, and manufacturers usually deal with several at once. Understanding the mix makes it easier to figure out where to start and what will deliver the biggest impact.
Once you can spot the different types of technical debt, the next step is figuring out how it formed in the first place. Most of the time, it isn’t one big mistake—it’s years of decisions that made sense at the time.
Most manufacturers didn’t take shortcuts on purpose.
Technical debt builds up for a mix of reasons:
Many operations still depend on systems installed decades ago. After years of patches and one-off fixes, they become fragile. Even a simple change feels risky, so teams avoid touching them, which only makes the debt grow.
Older systems often got heavily customized to match how the plant worked at the time. Those customizations make upgrades difficult now. What solved a short-term problem years ago can lock you in today.
The people who originally built or understood these systems may have retired or moved on. Newer teams usually inherit systems they didn’t design and don’t have documentation for. That leads to more patches and quick fixes, which add even more debt.
Upgrades get postponed because they seem costly or disruptive. Over time, these delays stack up. What was once a routine update becomes a major project, making modernization harder and more expensive the longer it waits.
Some manufacturers invest so much time and money in one monolithic system that replacing it feels impossible. This kind of vendor lock-in forces teams to work around the system instead of improving it. They add extra tools, build side processes, and create more workarounds just to keep things moving. Over time, all those add-ons pile up and the technical debt grows even faster.
Knowing why the debt exists is helpful, but you still need a clear way to measure it. Technical debt becomes a lot easier to manage when you can see it in numbers instead of guessing.
Technical debt becomes much easier to manage when you can actually see it.
Here are a few ways manufacturers measure its impact:
If most of the IT or engineering workload is spent maintaining old systems rather than building new capabilities, technical debt is consuming operational capacity. Trends in this ratio reveal whether modernization is creating measurable impact.
Track how long it takes to introduce updates, add product specifications, or implement new compliance rules. Slower cycle times often reflect structural debt buried in workflows, integrations, or data models.
Systems that are multiple versions behind or past end-of-life represent quantifiable risk. Each skipped upgrade represents principal. Each workaround represents interest.
TCO includes maintenance labor, downtime, workarounds, infrastructure, validation overhead, and integration complexity. When all costs are tallied, legacy systems often carry significantly higher TCO than their modern counterparts.
Putting numbers behind technical debt helps shift the conversation from guesswork to actual business decisions.
Now that you have made technical debt visible, you can start building a plan to fix it.
There’s no magic switch to get rid of technical debt, but manufacturers can chip away at it with a steady, focused plan.
Start by identifying where the debt is hiding. Look at legacy systems, custom code, old components, and any process that constantly breaks. Include input from operations, not just IT.
Not every problem needs to be solved right away. Focus first on systems that slow down production, block compliance, or limit strategic goals. Create a roadmap that spreads modernization over time.
Technical debt needs ongoing attention. Set clear KPIs, review them regularly, and make sure someone is responsible for driving improvements. Even dedicating a small percentage of development time each cycle can make a real difference.
Big system overhauls are risky. Instead, make smaller upgrades or replace systems piece by piece. Favor platforms that are configurable and easier to update so you don’t recreate the same problems later. Look for tools with open APIs and modular designs, since they reduce the amount of new debt created.
The goal is to make continuous improvement normal, not something teams only think about once every ten years.
Every manufacturer carries technical debt. What separates the leaders from everyone else is how they handle it. You can let it keep slowing you down, or you can treat it as something worth fixing little by little.
Modernizing your stack opens the door to better data, faster change, smoother compliance, and more confident decisions. Once the debt becomes visible and manageable, you gain the flexibility to improve without the fear of breaking what already works.
If your systems didn’t hold you back, what would you change first?
Technical debt is the accumulated cost of using outdated systems, quick fixes, and temporary workarounds instead of long-term solutions. Over time, these choices slow down upgrades, increase manual work, and limit how fast a plant can adapt.
Technical debt slows down updates, increases manual work, and makes every improvement riskier than it should be.
This shows up in delays, fragile integrations, and growing maintenance needs, which pull time and resources away from more valuable work.
Manufacturers typically face architectural, code, infrastructure, process, and security debt. Each type creates different problems, but all of them add friction and slow down system changes.
Common categories include:
Technical debt builds up from years of quick fixes, outdated systems, and postponed modernization efforts. Most factories inherit legacy software, over-customized solutions, or knowledge gaps from turnover, which makes the debt grow without anyone noticing.
Common signs include slow updates, frequent workarounds, fragile integrations, and systems that are far behind on upgrades. Technical debt usually becomes visible through everyday pain points such as:
You measure technical debt by tracking maintenance workload, lead time for changes, upgrade gaps, and total cost of ownership. These metrics reveal how much time and money is spent maintaining old systems instead of improving them.
Effective indicators include:
The most effective path is steady, incremental progress:
Map the debt across systems and processes
Prioritize high-risk, high-impact issues
Assign ownership and measure progress
Modernize in small steps instead of one big overhaul
This approach reduces risk and makes upgrades manageable.
No, most technical debt can be reduced through incremental upgrades rather than a full system replacement.
Many plants modernize gradually by updating modules, improving integrations, or shifting to configurable platforms that reduce complexity over time.
Vendor lock-in often forces manufacturers to keep systems long past their useful life. Instead of replacing them, teams add more tools and workarounds, which increases complexity and drives even more technical debt.
Faster updates, lower operating costs, cleaner integrations, fewer surprises, easier audits, stronger security, and more freedom to innovate. Reducing technical debt is ultimately about restoring flexibility and unlocking sustainable profit.
MASS Group, Inc. is a trusted provider of cloud-based manufacturing and asset management software that helps organizations achieve real-time visibility, traceability, and operational control.
For over 25 years, MASS Group has successfully implemented secure, configurable, and scalable solutions to organizations across variety of highly regulated industries like aerospace & defense, semiconductor, and industrial manufacturing.
You can schedule a demo or email us directly at sales@massgroup.com