Human Error vs Technical Error

Imagine you're in the middle of a complex project with tight deadlines, and everything seems to be going well. Then, suddenly, a mistake happens — a misplaced decimal, an overlooked email, or a glitch in the software. The fallout is immediate, and you wonder: Was this due to human error, or was it a technical error?

At first glance, these two types of errors seem straightforward, but in reality, they blur into one another in ways that can significantly impact outcomes. When you delve deeper, you realize that both human errors and technical errors are part of a larger ecosystem of decision-making and automation, each with its own triggers, complexities, and consequences. The dividing line between them isn’t always clear, but understanding these two types of errors is critical for avoiding costly mistakes and improving processes.

So, why does it matter? Let’s dive into the core differences, the consequences, and most importantly, how you can mitigate these risks to make your projects bulletproof.

The Shocking Domino Effect of Human Error

Human error is often the culprit behind some of the most catastrophic failures, both in business and technology. It could be as simple as a typing mistake or as monumental as misjudging the safety of a multi-million-dollar decision. But these errors don’t exist in isolation. They start a chain reaction, sometimes causing irreversible damage.

Take, for example, the infamous Chernobyl disaster. While a lot of attention is given to the technical faults of the reactor, the underlying issue was a series of human errors, bad judgment calls, and poor communication that triggered the event. Human beings — with their emotions, stress levels, and subjective thinking — are prone to making mistakes, especially when under pressure.

But here’s the kicker: most human errors occur not because of lack of knowledge but due to overconfidence, fatigue, or distractions. These errors often seem trivial but can amplify when combined with other factors.

Types of Human Errors:

1. Slips: These are unconscious mistakes, like mistyping a word or clicking the wrong button. They usually happen when you’re on autopilot.
2. Lapses: Forgetting to complete a task or missing out on a detail, often due to distractions or multitasking.
3. Mistakes: These happen when you make the wrong decision, thinking it's the right one — the result of overconfidence or lack of understanding.
4. Violations: Sometimes, people deliberately break the rules, whether to save time or avoid perceived hassle, leading to mistakes that could've been avoided.

The Stealthy Nature of Technical Error

On the other hand, technical errors arise from faults in equipment, software glitches, or improper configurations. Unlike human errors, these are typically unintentional malfunctions that occur despite correct human input. You can configure the system perfectly, but if a piece of software crashes or a machine component breaks down, it can grind everything to a halt.

Here’s a surprising fact: Technical errors are often the result of human oversight in design or testing. For example, a software bug that wasn’t caught in the development phase can cause massive disruptions once it hits production. A good example of this is the Knight Capital trading glitch, where a faulty software update led to $440 million in losses within just 45 minutes.

Types of Technical Errors:

1. Hardware Failures: Physical devices malfunctioning or breaking, like a hard drive crash.
2. Software Bugs: Faulty code, untested scenarios, or misconfigurations that cause unexpected behavior.
3. Network Issues: Connectivity problems that disrupt communication between systems or cause data loss.
4. System Overload: A system’s failure to handle excessive load due to poor scaling or inadequate resources.

The Fine Line Between Human and Technical Error

One of the most intriguing aspects of this topic is how intertwined human and technical errors often are. Consider an air traffic control system that relies on both human operators and sophisticated technology. A technical glitch may cause the radar to show incorrect data, but a human error — failing to cross-check the information — can lead to disaster.

In reality, technical errors can stem from earlier human errors in the design, maintenance, or testing phases. Conversely, a human error can be mitigated or worsened by the technical tools in place. That’s why companies like Tesla have invested so heavily in automation. By reducing human involvement, they aim to minimize human error. But even the most advanced automation systems can experience bugs or require human intervention at critical moments.

How to Reduce Human and Technical Errors

To effectively manage and reduce both types of errors, you need a multi-pronged strategy. Simply focusing on one while ignoring the other is like trying to fix a leaking boat by plugging only one hole. Here are practical steps that can help minimize both human and technical errors in your workflow:

1. Automation: Automate repetitive tasks wherever possible to reduce the likelihood of human errors. Machine learning algorithms and automation scripts can handle these tasks more efficiently and without emotional interference.

2. Redundancy: Implement fail-safes and redundancy systems to catch and correct errors. This can be as simple as having a second pair of eyes review important documents or as complex as automatic rollback systems that activate when software bugs are detected.

3. Training: Continuous training for employees to recognize potential pitfalls, stress management techniques, and proper technology usage can drastically reduce human error. People who are aware of their own limitations are more likely to take the necessary precautions.

4. Testing: For technical errors, rigorous testing in diverse environments can expose bugs before they occur in real-world scenarios. Unit tests, integration tests, and load tests are critical for avoiding software glitches.

5. Clear Communication Channels: Many human errors stem from poor communication. Use clear, concise, and standardized communication protocols to ensure that everyone is on the same page.

Real-World Case Studies: When Things Go Wrong

Let’s look at a few real-world examples to better understand how human and technical errors play out in practice.

Case Study 1: The 2013 Facebook Outage

In 2013, a Facebook engineer accidentally triggered a bug during routine maintenance, causing an hour-long outage that affected millions of users. This was a classic example of a human error that led to a technical error, illustrating how one small mistake can escalate into a massive issue. Facebook responded by implementing better automation and more rigorous testing protocols.

Case Study 2: Mars Climate Orbiter

In 1999, NASA lost the Mars Climate Orbiter due to a mix-up between metric and imperial units. The spacecraft was lost because engineers at Lockheed Martin used English units of measurement, while NASA’s team was using metric units. This simple human error — a miscommunication — resulted in a technical error that caused the mission’s failure.

Case Study 3: The Knight Capital Group Trading Glitch

In 2012, Knight Capital Group’s trading system experienced a technical glitch due to a faulty software deployment. The glitch went undetected for 45 minutes, causing erroneous trades worth $440 million. Although the glitch was a technical issue, human error played a role in failing to properly test the software before it was deployed.

Final Thoughts

The interplay between human and technical errors is complex but manageable. By understanding how they interact, we can design better systems, train our teams more effectively, and minimize the risk of catastrophic failures. It's not just about fixing the error after it occurs but about building systems that are robust enough to prevent these errors from happening in the first place.

In conclusion, whether you’re a project manager, a developer, or an executive, the key takeaway is this: Both human and technical errors are inevitable, but they are also preventable. It’s all about the systems you build, the training you provide, and the testing you conduct. With the right approach, you can significantly reduce the risk of errors, creating a safer, more reliable workflow for everyone involved.