By Duane Newman, Chief Product Officer, Accuris
There is a familiar logic behind the decision to keep a legacy system running. It works. The team knows it. Replacing it takes time, money, and risk no one has the appetite for. And so the system stays. Quarter after quarter, year after year.
That logic made sense once. It no longer does. What felt like stability has become a structural drag, and in industries where engineering decisions carry real consequences, the gap between what legacy systems can do and what modern operations require is now wide enough to matter.
The evidence is no longer subtle. 62% of organizations are still running critical workloads on outdated platforms. According to Gartner, companies spend 40% of their IT budgets managing technical debt. That is not an investment, it’s overhead. And it compounds every year that an organization delays the decision to modernize.
The visible cost and the one that actually matters
Most organizations understand, at some level, that legacy systems are expensive to maintain. Server costs, licensing fees, specialist contractors, and security patches. Those costs are visible and quantifiable.
The cost that rarely gets quantified is what those systems do to the people who work inside them.
When information is siloed, difficult to search, and disconnected from the tools where decisions are made, workers spend an outsized portion of their time not doing their jobs. Research from McKinsey found that employees spend nearly two hours every day searching for and gathering information. IDC puts it even higher, at 2.5 hours per day for knowledge workers. Either way, the math is damaging. A team of fifty professionals losing even one hour a day to information friction is the equivalent of six full-time employees doing nothing useful.
In engineering contexts, that friction has sharper edges. Engineers working on technical decisions are not just losing productivity. They are losing the time they need to do the work correctly. Time spent searching is time not spent analyzing, validating, or applying judgment. And in regulated environments, that tradeoff has real consequences.
The Building Safety Act in the UK is a concrete illustration. When new compliance and traceability requirements were introduced across building projects, teams relying on manual standards management had no reliable way to quickly determine which projects, specifications, or certifications were affected. Individual engineers managing revision histories in spreadsheets spent weeks reconstructing compliance evidence that a connected system would have surfaced in hours. The regulatory deadline did not move. The scramble was the cost.
Why inaction is not the cautious choice
There is a tendency in large organizations to treat the status quo as low risk. It is not. Staying on a legacy system is a decision, and like any decision, it carries consequences.
The most frequently overlooked consequence is what it does to decision quality. Legacy systems were not designed for the speed or complexity of modern engineering and compliance workflows. They were built when information was less dense, change cycles were slower, and teams were smaller. Running those systems today means running workflows that were not designed for today’s demands, and accepting the errors and delays that follow.
The consequences follow recognizable patterns: an engineer working from a version of a safety standard that was superseded months ago, without knowing it. An audit preparation that takes three weeks of manual document reconstruction rather than three days. In medical devices, document control deficiencies remain among the most frequently cited observations in FDA quality system inspections year after year. Not because engineers are careless, but because the systems they depend on were not built to manage change at scale.
Gartner has projected that 85% of enterprises that rely heavily on legacy systems will struggle to fully execute their digital strategies. That is not a future risk. For many organizations, it is already the current state. Transformation programs stall, and AI initiatives cannot get off the ground because the underlying data infrastructure is too fragmented. Integration projects cost three times the original estimate because the legacy systems were never designed to connect with anything.
Meanwhile, digital transformation leaders achieve up to 55% higher productivity compared to those still operating on legacy infrastructure. The gap is not closing; it is widening.
What modern systems actually enable
The argument for modernization is often framed as a technology upgrade. That framing understates it.
What modern systems provide is not just faster processing or better interfaces. They provide a fundamentally different relationship between information and the people who need to use it. Answers instead of documents. Insights in context rather than raw content scattered across repositories. Traceability that connects every decision back to its source without manual effort.
For engineering teams, this distinction matters in ways that show up on the balance sheet. A global materials testing and certification organization, responsible for validating products against standards across dozens of jurisdictions, documented a reduction in standards research time that translated to over £165,000 in recovered engineering capacity in a single year. The same engineers, the same scope of work, and different tools.
The downstream effects extend further, with fewer requirements missed, less rework, and stronger audit readiness. These are not aspirational outcomes. They are the practical result of giving teams information they can actually use, at the speed at which they need it.
The decision that organizations keep deferring
The modernization conversation tends to get stuck in the same place: cost and disruption. Both are real, but neither is as prohibitive as organizations tend to assume when weighed against the alternative.
A 2024 IDC report found that enterprises maintaining legacy systems spend up to 42% more on operational overhead than those that have modernized. That premium is paid every year the decision is deferred. It is not a one-time cost of staying put, but a recurring one.
The more useful question is not whether modernization is disruptive, but whether the disruption of modernizing is larger than the disruption being absorbed every day inside legacy systems. For most engineering-led organizations, it is not. The daily friction, the missed updates, the manual work that should not be manual, the decisions made on incomplete information: these are already disruptive. They are just disruptions that have been normalized.
The organizations that move forward are not the ones with the easiest modernization path. They are the ones that stopped treating the status quo as safe.
The case for moving now
Every quarter spent on a legacy system is a quarter in which the gap between current capability and competitive requirement grows. The organizations best positioned for the next five years are not the ones that waited until the risk became unavoidable. They are the ones that recognized earlier that waiting was itself the risk.
Modern systems that deliver instant answers, clear traceability, and real-time insight do not just make teams faster. They make better decisions possible. In engineering environments, where the cost of a wrong decision can propagate through an entire product lifecycle, that is not a marginal improvement. It is a structural one.
The question organizations need to ask is not whether they can afford to modernize. It is whether they can afford to keep absorbing the cost of not doing so.
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ABOUT THE AUTHOR
Duane Newman is Chief Product Officer at Accuris, an Engineering Intelligence platform that helps technical teams find, interpret, and act on standards and technical content across the product lifecycle.
