Technical debt is one of those technology terms that business leaders hear constantly but do not always get a clear explanation about. It sounds like a problem belonging to developers and IT departments, yet its consequences can reach far beyond the technology team. Slower systems, bad data, incorrect reports, expensive upgrades, delayed projects, difficult integrations, rising maintenance demands, and limited ability to adopt new technology can all be connected to technical debt.
In this article, we’ll talk about what technical debt actually means, how it develops inside business systems, why it matters to business leaders, how to recognize the warning signs, and what organizations can do to manage it before it becomes a larger operational problem.
What Is Technical Debt and How Does It Develop?
Technical debt is essentially the future cost created when a technology decision provides a short term advantage but makes future work more difficult, expensive, or time consuming.
The Software Engineering Institute describes technical debt as an approach that is expedient in the short term but creates a technical context where the same work can cost more to complete later. (SEI)
The financial debt comparison is useful because it explains the basic idea. A company can choose the faster option today, but the decision can create additional work later. That additional work is the interest.
Technical debt can exist in software code, system architecture, integrations, databases, documentation, configurations, workflows, and other technical decisions. It can also accumulate gradually as business requirements change.
Technical Debt Is Not Simply Bad Code
One of the most important misconceptions about technical debt is that it means poorly written code.
That is not always the case.
Technical debt can result from deliberate decisions made to meet an immediate business requirement. A development team might implement a temporary solution because a customer needs a capability immediately. An organization might postpone a larger architectural change because the business cannot afford the disruption at that moment. A company might customize a system because its processes are unique.
Those decisions can make perfect business sense.
The problem comes when the temporary solution becomes permanent and nobody revisits it. Or the perfect solution 5 years ago no longer fits the business.
That means business leaders should not approach technical debt as a blame exercise. The better question is:
What technology decisions are creating future costs or limiting our ability to change?
That question turns technical debt from a technical criticism into a business management issue.
How Technical Debt Accumulates
Technical debt rarely appears as one enormous problem.
It usually accumulates in small pieces.
A custom workflow is created for a process that needs to happen quickly. A year later, another workflow was added because the process has changed. An integration is built to connect two systems. Later, a third system needs access to the same information. A script is created to automate a repetitive task. Another script is added to handle an exception.
Individually, each decision may be reasonable.
Over several years, however, the environment can become increasingly complicated.
Documentation may no longer accurately describe how everything works. Employees who created certain automations may leave. New teams may inherit systems they did not design. Business processes may change while the underlying technology remains.
The result is a technology environment where making one change can require understanding many other components first.
Technical Debt Can Exist in Mature Systems
A common misconception is that only old or poorly maintained systems have technical debt.
In reality, technical debt can develop in relatively modern environments too.
Every technology environment evolves. Business requirements change. Vendors introduce new capabilities. Integrations expand. Regulations change. Companies acquire other organizations. Teams change. New applications are introduced.
Even a carefully designed system can develop technical debt as its surrounding environment changes.
This is particularly relevant for mature ERP environments. An ERP system can be operating successfully while carrying years of customizations, scripts, workflows, integrations, reports, and configurations.
The system may not be broken.
It may simply be more complicated than it needs to be.
That distinction matters because technical debt management is not necessarily about replacing a system. In many cases, the better strategy is to understand the environment, identify the highest impact problems, and prioritize improvements.
Why Should Business Leaders Care About Technical Debt?
Technical debt becomes a business issue when technology complexity starts affecting the organization’s ability to operate, grow, change, and innovate.
Sources have noted that unmanaged technical debt can make integrating new products and capabilities more expensive, create unexpected project risks, and consume technology resources that could otherwise be used for innovation.
That makes technical debt particularly important for executives who are responsible for growth and transformation.
Technical Debt Can Increase the Cost of Change
Imagine that a company wants to introduce a new automation.
The business case looks simple. The technology team estimates the project based on the desired functionality.
Then the team discovers that the existing system contains several dependencies that were not documented clearly. One workflow interacts with another process. An older integration depends on a specific data structure. A custom script modifies records before another automation processes them.
The project becomes larger.
This is one of the practical consequences of technical debt. The company is not necessarily paying more because the new feature itself is complicated. It is paying more because the existing environment makes change more complicated.
For business leaders, this means technical debt can directly affect the speed at which the organization can respond to customers, competitors, regulations, and market opportunities.
Technical Debt Can Consume Valuable IT Resources
IT teams do not have unlimited time.
Every hour spent investigating an undocumented customization, troubleshooting an unexpected dependency, or maintaining redundant automation is an hour that cannot be spent on another initiative.
A source has reported that technical debt can divert technology resources away from new products and capabilities. In one survey cited by the firm, 30 percent of CIOs said more than 20 percent of their technical budget intended for new products was being diverted to technical debt related issues. (McKinsey & Company)
That does not mean every organization experiences the same percentage.
The broader lesson is more useful: technical debt has an opportunity cost.
The cost is not limited to the money required to fix the problem.
It is also the innovation that gets delayed because the team is busy maintaining complexity.
Technical Debt Can Limit Digital Transformation
Businesses increasingly want to implement AI, IoT, automation, advanced analytics, and connected operational systems.
But these technologies still depend on underlying systems and data.
If information is fragmented, processes are poorly documented, integrations are fragile, or system behavior is difficult to understand, implementing new technology can become significantly harder.
This is why technical debt should be considered during digital transformation planning.
A company does not necessarily need to eliminate every piece of technical debt before adopting new technology. That would often be unrealistic.
Instead, leadership should understand where technical debt exists, how much risk it creates, and which areas could interfere with strategic initiatives.
10 Warning Signs Your Business May Have Technical Debt
Technical debt is often difficult to see because the business can continue operating while it accumulates.
The following signs can help leadership teams identify when technology complexity deserves closer attention.
1. Simple Changes Take Surprisingly Long
If a seemingly small system change repeatedly turns into a major project, investigate why.
The issue may not be the requested change itself. It may be the number of dependencies surrounding the process.
2. Nobody Knows Exactly What an Automation Does
This is a major warning sign.
If employees rely on scripts, workflows, integrations, or automated processes but cannot clearly explain what they do, why they exist, or what other processes depend on them, the organization has an information problem.
That information problem can become a technical risk.
3. Upgrades Create Anxiety
Upgrades should involve planning, testing, and change management.
They should not feel like an organization is gambling with its operations.
If every major system upgrade requires extensive investigation because nobody is completely sure what might break, technical debt may be part of the reason.
4. The Same Problems Keep Returning
Recurring performance issues, recurring errors, repeated manual workarounds, and repeated troubleshooting can indicate that teams are treating symptoms instead of addressing underlying causes.
5. Your IT Team Spends Too Much Time Maintaining Old Customizations
Customization is not automatically bad.
In many industries, customization is necessary because businesses have specialized requirements.
The problem is maintaining customizations that are no longer providing meaningful value or that have become unnecessarily difficult to support.
6. Documentation Is Missing or Outdated
Documentation is often one of the first things sacrificed when teams are under deadline pressure.
Years later, that missing information can become expensive.
When the people who built a system are no longer available, undocumented technical decisions become much harder to understand.
7. Integrations Are Becoming Difficult to Manage
As businesses add applications, integrations can multiply.
If every new system requires another custom connection or workaround, the technology environment can become increasingly fragile.
8. Employees Create Manual Workarounds
When users repeatedly export data to spreadsheets, reenter information, manually reconcile records, or bypass system processes, leadership should ask why.
Sometimes the problem is training.
Sometimes it is a process issue.
Sometimes it is a technology limitation created by accumulated technical debt.
9. AI Projects Are Harder Than Expected
AI initiatives require usable data, accessible systems, and clearly understood processes.
If teams spend more time preparing fragmented information than using AI to generate insights, the organization may have foundational technology issues that need attention first.
10. Nobody Has a Prioritized Technology Cleanup Plan
This may be the biggest warning sign.
Knowing that technical debt exists is not enough.
Leadership needs to know which problems matter most, what they affect, what they could cost, and what should be addressed first.
How Can Businesses Manage Technical Debt?
Technical debt does not need to be eliminated all at once.
In fact, trying to eliminate everything immediately can create unnecessary disruption.
The more practical approach is to make the debt visible, understand its impact, prioritize it, and create a realistic plan.
Start With Visibility
You cannot effectively manage what you cannot see.
The first step is understanding what exists inside the environment.
That can include applications, customizations, scripts, workflows, integrations, dependencies, data flows, and processes.
The important point is that technical analysis should produce understanding, not simply more data.
Prioritize by Business Impact
Not every technical issue deserves immediate attention.
A minor issue that rarely affects users may be less important than a customization that affects a critical order processing workflow.
A useful prioritization framework can consider:
- Business criticality
- Performance impact
- Operational risk
- Frequency of use
- Dependency complexity
- Maintenance effort
- Security or compliance implications
- Impact on future projects
- Cost of remediation
This allows leadership to focus resources where they can create the greatest business value.
Technical debt management becomes much more useful when technology teams and business leaders share the same prioritization framework.
Use Technology to Understand Complex Environments
Modern organizations can use automation and AI to accelerate parts of the technical assessment process.
This is particularly useful when environments contain large numbers of scripts, workflows, customizations, or integrations that would take significant manual effort to review.
Epiphany has developed Epiphany Lens around this specific challenge.
Lens uses AI to analyze a business environment and help identify areas such as redundant or outdated scripts, performance bottlenecks, dependencies, and other potential sources of technical complexity. The goal is not simply to produce a technical inventory. It is to turn a complex environment into understandable findings and a prioritized action plan.
That distinction is important.
A business leader does not necessarily need a report containing hundreds of technical observations.
They need to understand:
What is happening?
Why does it matter?
What should we fix first?
What can wait?
How could this affect our next major initiative?
That is where an AI assisted technical assessment can become useful.
Why Technical Debt Matters More in the Age of AI
AI is changing the technology conversation for business leaders.
Organizations are looking at AI for automation, analytics, customer service, forecasting, maintenance, procurement, contract management, and operational decision making.
But AI does not remove the need for strong technology foundations.
In many cases, it makes those foundations more important.
AI Needs Accessible and Reliable Information
AI systems are only as useful as the information and processes they can work with.
If business data is fragmented across systems, if important workflows are poorly understood, or if integrations are unreliable, AI initiatives may produce less value than expected.
This is one reason technical debt should be considered before large scale AI initiatives.
The goal is not to create a perfect technology environment.
The goal is to understand the environment well enough to make intelligent decisions about where AI can create value.
AI Can Help Organizations Analyze Complexity
AI can also become part of the solution.
Instead of asking people to manually review every component of a large technology environment, AI can assist with classification, explanation, pattern identification, and prioritization.
For example, Epiphany Lens is designed to help analyze scripts and technical components at scale, explain their function in more accessible language, identify potential duplication and dependencies, and help organizations determine where attention should be focused.
For businesses with mature ERP environments, that can provide a starting point for a much more informed modernization conversation.
Modernization Should Be Tied to Business Outcomes
The ultimate objective is not to have a cleaner technology environment simply for the sake of cleanliness.
Technology exists to support the business.
A technical cleanup project should therefore connect back to outcomes such as:
- Faster operations
- Lower maintenance effort
- Better system performance
- Reduced operational risk
- Easier upgrades
- Faster implementation of new capabilities
- Better visibility
- More efficient use of IT resources
- Greater ability to adopt AI and automation
That is why technical debt belongs in the executive conversation.
It is ultimately about the organization’s ability to move forward.
How Epiphany Helps Businesses Address Technology Complexity
Technical debt can be difficult to manage when technology analysis is separated from the business processes the technology supports.
Epiphany approaches technology through an operational lens.
The company has more than two decades of experience helping service, repair, and aftermarket organizations modernize their operations, with a particular focus on MRO environments and integrated solutions. Epiphany’s platform and expertise connect areas such as equipment management, service operations, inventory, and ERP workflows.
For organizations using NetSuite, Epiphany has developed Epiphany Lens – designed to highlight where the technical debt is so that a plan can be created to reduce/eliminate it. Learn more here https://www.youtube.com/watch?v=-GDgflVMpqc
That experience matters because technical decisions rarely exist in isolation.
A script may affect a work order.
A customization may affect inventory.
An integration may affect service operations.
A system limitation may affect how quickly a repair can be processed.
Understanding the technology in relation to the business process is therefore critical.
Epiphany Lens adds another layer to that approach by using AI to help organizations understand technical complexity and identify areas that deserve attention.
The result should not be technology for technology’s sake.
It should be a clearer path toward a more maintainable, understandable, and strategically useful technology environment.
Wrapping Up – Technical Debt Is a Business Decision
Technical debt is not something business leaders can simply hand over to IT and forget about.
It affects how quickly a company can change, how much it costs to maintain systems, how confidently it can undertake upgrades, how effectively it can adopt new technology, and how much of its technology budget is consumed by maintaining yesterday’s decisions.
The answer is not to eliminate every customization or replace every legacy system.
The answer is to understand the environment.
Know what exists.
Know what matters.
Know what creates risk.
Know what is slowing the organization down.
Then prioritize the work based on business value.
For companies preparing for AI initiatives, ERP modernization, MRO transformation, or major operational changes, that visibility becomes even more important.
Epiphany helps organizations connect technology with the operational realities of their business. Technical debt may have started as a technology problem but managing it is a business responsibility.
Sources
- Software Engineering Institute, Managing Technical Debt in Complex Software Systems. (SEI)
- Software Engineering Institute, Managing the Consequences of Technical Debt. (SEI)
- McKinsey, Tech Debt: Reclaiming Tech Equity. (McKinsey & Company)
- McKinsey, Demystifying Digital Dark Matter: A New Standard to Tame Technical Debt. (McKinsey & Company)
- McKinsey, Tame Tech Debt to Modernize Your Business. (McKinsey & Company)
- IBM, What Is Technical Debt? (IBM)
- Martin Fowler, Technical Debt Quadrant. (martinfowler.com)
- Oracle NetSuite, Optimizing SuiteScript Performance. (Oracle Docs)
- Oracle NetSuite, Application Performance Management for SuiteCloud Platform. (Oracle Docs)
- Oracle NetSuite, Analyzing Scripts. (Oracle Docs)