Beyond Blame: A Smarter Approach to Reducing Human Error

In the fast-paced world of pharmaceutical manufacturing, precision is everything. Every batch, every process, and every quality control check must meet the highest standards. But despite the best efforts, mistakes still happen. A misplaced decimal, a skipped verification, a misread label—small human errors that can lead to costly deviations, regulatory citations, and even risks to patient safety.

For years, the default response to human error has been blame. A deviation report is filed, an investigation is launched, and the conclusion is often the same: operator error. The corrective action? Retrain the individual and remind them to be more careful next time. But does that really solve the problem? Or is it just treating the symptom while ignoring the underlying disease?

Blaming human error is easy. It’s clean. It feels like an explanation. But in reality, human error is often a symptom of deeper, systemic problems. If an employee enters the wrong lot number, is it truly because they were careless? Or is it because the labeling system is confusing, the SOP is unclear, or the workload is overwhelming? Research into human factors shows that errors occur not just because of individuals, but because of the environments, processes, and systems they work within. In highly regulated industries like pharmaceuticals, where compliance is strict and processes are complex, reducing human error requires a shift in mindset—moving from blame to prevention.

To understand how to reduce errors, we first need to understand why they happen. Human mistakes are not random; they follow predictable patterns. Some errors occur because of cognitive overload—when employees must remember too many steps, numbers, or variables at once. In a high-pressure setting, our brains prioritize speed over accuracy, increasing the risk of mistakes. Other errors stem from process complexity. If a standard operating procedure (SOP) is too detailed, too ambiguous, or too difficult to follow, employees will either make mistakes or create their own shortcuts—both of which can lead to compliance issues. Then there are environmental factors: distractions, fatigue, poor lighting, multitasking, or a lack of proper tools. A technician trying to manually enter data while also overseeing a production line is far more likely to make a mistake than someone who can focus on a single task.

When human error occurs, the go-to corrective action is often retraining. The logic is simple: if someone made a mistake, they must not understand the procedure well enough. But this approach assumes that knowledge alone prevents mistakes—and that’s simply not true. Imagine a trained pilot making a navigation error due to poorly designed flight controls. The solution isn’t just more training; it’s fixing the system that contributed to the error. In pharmaceuticals, the same principle applies. If mistakes keep happening despite repeated training, the problem isn’t the employee—it’s the process. Instead of over-relying on retraining, companies need to look deeper: Is the process designed to be error-resistant? Are there fail-safes in place? Are procedures easy to follow, even under stress?

Reducing human error doesn’t mean eliminating mistakes completely—that’s impossible. But it does mean building systems that make mistakes less likely and less impactful. One of the most powerful tools for this is error-proofing. This strategy, widely used in industries like automotive manufacturing and aviation, focuses on designing processes in a way that makes mistakes physically or procedurally impossible. For example, in pharmaceutical packaging, using barcode scanning instead of manual data entry ensures that the correct lot number is always recorded—eliminating a common source of human error. Similarly, color-coded labeling, standardized checklists, and automation can significantly reduce mistakes in formulation, batch records, and quality control.

Not all mistakes are the same, and not all require the same solutions. A technician misplacing a decimal point in a calculation is a different type of error than a manufacturing worker skipping a procedural step. Understanding the category of error is key to applying the right corrective action. The Grifols framework classifies human errors into six main types: application errors, decision errors, learning gaps, memory lapses, omissions, and inconsistencies. By categorizing errors, companies can move beyond generic "operator error" conclusions and implement corrective actions that actually prevent future mistakes.

Regulatory agencies like the FDA and EMA recognize that human error should not be the default explanation for deviations. In fact, investigators expect companies to demonstrate that all systemic causes have been ruled out before attributing an issue to human error. Shifting to a human performance culture means designing processes and equipment that minimize opportunities for error, moving beyond retraining to structural fixes that address error-prone procedures, encouraging open reporting of near-misses without fear of punishment, and applying automation, checklists, and error-proofing strategies to critical processes.

Instead of focusing solely on the individual, organizations must look at the system. What conditions allow errors to happen? How can they be prevented at the design level? Human error is not just a problem to be fixed—it’s a signal that something in the system needs attention. If companies keep seeing the same types of errors over and over, it’s time to stop blaming individuals and start redesigning the process.

The pharmaceutical industry has made incredible advancements in technology, automation, and quality control. Yet, when it comes to human error, many organizations still rely on outdated approaches—blame, retraining, and documentation fixes that don’t address the root cause. By adopting a data-driven, human-centered approach, companies can reduce deviations, improve compliance, and ultimately create a safer, more efficient work environment.

Human error is not an excuse—it’s an opportunity. If companies stop seeing mistakes as failures and start treating them as insights, they will unlock new ways to improve processes, enhance reliability, and ensure long-term success. Instead of just correcting errors, companies must focus on designing better systems that prevent them in the first place. Reducing human error is not just about improving efficiency—it is about ensuring patient safety, regulatory compliance, and long-term operational success.