Time Is Money: How Poor Code Management Drains the Factory Floor

ReadStats & TrendsBest PracticesInfographic

Sep 18

Manufacturing downtime has long been seen as a costly enemy of productivity. In 2025, it remains “one of the most significant threats to profitability and operational stability” for industrial companies. When production lines stop unexpectedly, the losses pile up faster than many realize, and recent data from Copia Automation shows the scale of the problem is even greater than anticipated. This report dives into the staggering cost of downtime, why much of it is not due to mechanical failures as commonly assumed, and how the hidden world of industrial software (“industrial code”) is emerging as a major factor. The goal is to bring awareness to this often overlooked aspect of downtime, especially as factories evolve into software-defined, digitally driven operations.

The Staggering Costs of Downtime in 2025

Unplanned downtime is extremely expensive, more so than many would guess. According to Copia Automation in their 2025 State of DevOps Report, the average cost of downtime is about $3.63 million per hour. C-Suite executives, who tend to have a broader view of business impact, estimate even higher losses, around $4.29 million per hour on average. This figure is roughly 50% higher than what operational managers report, indicating top leaders factor in not just lost production, but also indirect costs like supply chain disruptions, missed orders, and reputational damage. In other words, a single hour of downtime for a large manufacturer can cost several million dollars, once you account for the cascade of consequences across the business.

It’s worth noting that this reported cost actually decreased from 2024 (when it was ~$4.18M/hour), potentially due to resilience investments paying off. But at $3–4 million per hour, the cost today is still astonishingly high. Most plant managers typically think of direct losses, idle workers, scrap material, overtime to catch up, when calculating downtime cost. However, the “hidden” impacts (like late delivery penalties and lost customer trust) often dwarf the obvious ones. This helps explain why the C-suite’s downtime estimates are so large: they see downtime as a far-reaching business threat, not just a momentary nuisance on the factory floor. The takeaway is clear: downtime is a multi-million dollar problem, and even a few minutes of stoppage can burn a hole in the bottom line. (As one industry expert bluntly put it, “In a world where minutes cost millions, unified visibility is the new competitive currency”.)

Software Failures: A Major (and Unexpected) Culprit

When asked what causes these costly stoppages, many would reflexively blame physical equipment problems, a jammed conveyor, a broken machine, a power outage, etc. Surprisingly, nearly half of all downtime is actually attributed to software and automation code issues. In the 2025 survey, respondents said 45% of their total downtime (planned and unplanned) was caused by issues related to industrial code. This “industrial code” refers to the software that runs production processes, including PLC programs, robotics code, HMIs, SCADA systems, and so on – essentially the digital brain of modern factories. That figure (45%) is higher than most people would expect; it means software-related glitches are on par with, if not more frequent than, mechanical breakdowns as a source of downtime.

Even more eye-opening: for the largest and most complex organizations, the share of downtime caused by software is higher still. Companies with over $15 billion in revenue reported that fully 66% of their downtime incidents involved industrial code issues. Likewise, those running a very high number of automated devices (1000+ PLCs) saw about 60% of downtime tied to software problems. And among firms with the highest downtime costs (over $5 million per hour), roughly 70% of their stoppages were linked to code errors or malfunctions. Clearly, as operations scale up in size, complexity, and automation, software becomes an even larger Achilles’ heel. This is a wake-up call: industrial software failures are a massive contributor to plant downtime, even though many in the industry might not immediately think of “software bugs” when a line goes down.

Why are so many outages attributed to code? Part of the answer may lie in how “industrial code” is defined. It encompasses a broad range of digital control logic, not just traditional programming bugs, but also things like incorrect PLC configurations, version mismatches, communication faults between systems, and even changes made by engineers without proper testing. Essentially, any issue in the digital control layer can bring production to a halt. As factories modernize, this layer has grown in complexity. In fact, an average facility today runs on nearly 13 different software packages for operations technology (OT) and automation. This software sprawl means there are many points where a coding error, integration issue, or update glitch can trigger downtime. The survey data supports this: respondents noted that size and complexity are crippling large organizations’ OT environments, extending downtime and increasing attribution to code-related causes. In other words, the more complex the digital tapestry of a plant, the higher the chances that something in the code will go wrong and stop production.

Another reason is that management of industrial code has lagged behind. Unlike IT software, which typically benefits from robust version control, testing, and deployment practices, OT code has often been managed in an ad-hoc way. Many teams still rely on manual processes or fragmented tools to handle automation code changes. According to the report, 44% of companies use standard IT version control systems for some code, but an equal 40% are still using manual spreadsheets to track code changes in production equipment. Additionally, 27% admitted to informal practices like engineers saving code on local PCs or USB drives. This patchwork approach leads to poor visibility into what code is running where, and makes it easy for mistakes or conflicting changes to slip through. For example, a technician might quickly tweak a PLC program to fix a problem (“a quick fix”), but without documentation or testing, that change could inadvertently cause another issue later, a phenomenon sometimes summarized as “a quick fix adds value; a quick fix adds time,” meaning it fixes now but adds downtime later. Over time, these uncoordinated code changes accumulate as technical debt, eventually contributing to outages (when something finally breaks due to a buggy or inconsistent state). The report highlights that once an industrial code-related downtime event occurs, it takes on average 28 hours to fully resolve – over a full day of halted production. This prolonged recovery time underlines how tricky diagnosing and fixing software issues can be in an industrial setting, especially without proper tools in place.

Misconceptions: It’s Not Just Mechanical Issues

The dominance of software-related downtime runs counter to the common perception in manufacturing. If you ask a plant veteran what keeps them up at night, they might mention machine failures, wear and tear, or operator errors. Indeed, traditional causes like hardware malfunctions and human error are still significant – but data shows they are no longer the only major culprits. In the same report, when respondents identified the top causes of unplanned downtime in the past year, the results were striking: Cybersecurity breaches, hardware failures, and software (coding) issues were tied as the leading causes, each cited by a large share of respondents. In fact, cybersecurity attacks slightly edged out the others (47% of respondents experienced those), with hardware and software issues close behind (around 45% each). Meanwhile, human error was not far behind at roughly 43%. This means that people tend to think of downtime as a mechanical problem, like a jam or a broken part, but in reality, digital problems (software bugs or cyber-attacks) are just as likely to be the cause of an unexpected shutdown.

It’s also interesting to see how perceptions differ between front-line managers and senior executives on this issue. The report notes a major perception gap: managers on the factory floor tend to blame immediate, tangible issues like equipment failures or mistakes by operators, whereas senior leaders (C-suite) are more likely to point to systemic issues like software and cybersecurity as the root causes of downtime. For example, when ranking unplanned downtime causes, plant managers most frequently chose human error and hardware malfunction (each around 50% of managers surveyed cited those). In contrast, the C-suite respondents overwhelmingly flagged cybersecurity incidents as a top concern (45% of executives versus only 22% of managers), and they also recognize software issues as a key driver. This makes sense: managers see the immediate trigger (“the machine X broke” or “operator Y made a mistake”), while executives think about the underlying vulnerabilities (“why did our system allow this failure?” – often pointing to code, system integration, or security gaps). The consequence of this gap is that many organizations might overlook the software side of reliability if they go by only the traditional, ground-level view. The reality illuminated by the data is that mechanical reliability and digital reliability are now equally crucial to keeping factories running.

Preparing for a Software-Defined Manufacturing Future

These findings carry an important message: as manufacturing becomes more digitized and software-defined, companies must give as much attention to their code and digital systems as they do to their machines. Downtime is no longer just a maintenance issue; it’s also a software engineering and cybersecurity issue. The fact that industrial code issues account for nearly half of downtime cannot be ignored. It calls for a new mindset in plant management, one that treats PLC programs, robot control code, and automation scripts as critical assets that need disciplined lifecycle management. In practice, this means adopting some of the best practices from the IT world (where software reliability has long been a focus) into the OT world. For instance, Industrial DevOps is emerging as an approach to bridge that gap. Industrial DevOps involves applying modern DevOps principles (like version control, continuous integration/testing, and collaborative workflows) to industrial automation code. By doing so, manufacturers aim to reduce errors in code deployments, get better visibility into changes, and respond faster when issues arise.

Encouragingly, the industry is recognizing the need for better software and code management. 92% of surveyed organizations said they have invested or plan to invest in Industrial DevOps within the next 11 months. This includes implementing platforms for Industrial Code Lifecycle Management (ICLM), essentially systems to centrally manage all automation code versions, track changes, and secure backups of PLC and other device programs. The rationale is straightforward: if nearly half of downtime is due to code, then improving how we handle that code can directly improve uptime. A unified source of truth for industrial code changes can prevent the scenario where a simple programming mistake propagates into hours of lost production. As the report puts it, adopting a unified platform to manage the lifecycle of industrial code is now essential for protecting operations and ensuring efficiency. Simply relying on tribal knowledge or isolated quick fixes is no longer viable in the face of rising complexity and cyber threats.

In summary, the world of manufacturing is entering an era where software reliability is as important as mechanical reliability. Downtime statistics are higher than many would expect, both in cost and in the proportion attributable to software issues. While a jammed machine or broken pump might have been the archetypal cause of factory downtime in the past, today a bug in a PLC program or a network glitch can just as easily bring production to a standstill, and often for even longer, if the issue is hard to diagnose. This reality might be surprising, but it’s also an opportunity: by shining a light on the “hidden” world of industrial code, companies can address a whole new category of improvements. Reducing software-related downtime through better code management, testing, and cybersecurity hardening will directly translate into higher uptime and productivity. And with downtime costs as high as they are, every minute saved is literally millions saved. The manufacturing leaders who understand this dual nature of reliability, mechanical and digital, will be best positioned to thrive in our increasingly software-defined industrial future.