Why Human Error Still Dominates Root Cause Analysis Findings

Even with the shift towards digital transformation in plants today, human error still makes up a large proportion of audit findings on the manufacturing floor.

Why is this the case?

As with many manufacturing problems, the issue is more complex than it would seem at first glance.

In this article, we explore some of the biggest reasons human error remains a top cause of nonconformances, and what it reveals about gaps in quality processes today.

Dig deeper into manufacturing nonconformances by downloading your free Root Cause Analysis Guidebook

Surface-Level Root Cause Analysis

In many cases when problems are attributed to human error, it’s because root cause analysis didn’t go deep enough.

The problem is that when you accept surface-level conclusions, you risk the same problem recurring with another operator, another line, or another shift. A 5 Whys exercise, for instance, should dig a level below operator error to ask why the process allowed the error to occur in the first place.

Consider a safety example where an auditor flags an extension cord in the work cell as a trip hazard, noting that the operator was using a plug-in drill rather than a battery-powered drill as required.

On the surface, reminding the operator to use a battery-powered drill would seem like an appropriate corrective measure. When you drill down further, however, you discover the reason the operator was using the extension cord was that the battery-powered drill was significantly heavier.

Here, the real solution was installing an overhead balancer so the correct tool could be used comfortably and safely.

Key takeaway: Without direct observation and engaging operators on the plant floor, root cause analysis may miss why doing it the wrong way made sense to the person doing the work.

Underlying Process Issues

Oftentimes, nonconformances are attributed to human error when in reality they are symptoms of underlying process issues.

One way this tends to show up is in undocumented workarounds, also known as hidden factory processes, which operators develop to compensate for unstable processes or flawed equipment.

Let’s look at a couple of examples to see how this happens:

• Operators were observed manually bending mounting tabs on injection-molded coolant overflow bottles. Investigation revealed that broken injector pins in the mold were causing the bottles to eject improperly. Rather than causing the problem in this case, operators were keeping production running in spite of it.
• A hose blew off a fitting despite having passed inspection using a pi tape. While it appeared to be an operator measurement error, the real failure was that engineering had specified a tool incapable of detecting ovality.
• Operators were supposed to mark screws yellow only once they installed them to make it visible that the correct number was present. After a defect that identified human error as the root cause, a bin of pre-marked screws was discovered at the workstation. This revealed that the underlying issue was that the operator wasn’t trained on why they were to mark the screws yellow.

Key takeaway: In mature quality cultures, leaders recognize that most defects stem from product or process design rather than individual mistakes.

Training and the Execution Gap

Training is by far the number one mitigation we see assigned after an audit nonconformance among our users. One question that plants should be asking is how the training process itself contributes to these issues.

The problem is that in many organizations, training is not part of a closed feedback loop that links directly to plant floor checks. There’s rarely a structured process for confirming whether the retraining actually changed behavior on the floor, or whether the same issue is happening on other shifts or lines.

On-the-job training tools designed specifically for identifying and correcting knowledge gaps can help close the loop by allowing teams to:

• Link audit findings directly to task-specific training resources like work instructions and demonstration videos
• Provide critical information right when a gap is identified, rather than when someone gets around to reviewing the procedure with the operator
• Add follow-up questions for plant floor checks to confirm the corrective action is held in place
• Document the entire process to demonstrate, internally and externally, how issues were prevented from recurring
• Turn mistakes into learning opportunities to drive continuous improvement

Key takeaway: When audit data and training systems operate separately, organizations are forced to rely on assumptions. When they operate together, they create visibility into whether corrective actions are truly reducing risk.

Despite rapid advances in digital transformation and AI, human error will always exist in manufacturing. What matters is whether teams use it as a crutch or a signal. Where humans do need retraining, it’s critical that teams connect root cause analysis, on-the-job training and verification in order to move past blame towards true prevention.