Cognitive biases in foundation analysis can distort our ability to balance contradictory data, as discussed in a previous blog (Synthesis of the Data). To make accurate assessments, we need to regularly reassess our conclusions and actively minimize these biases. This often involves holding multiple conflicting ideas simultaneously while evaluating the data.

Human biases, or heuristic shortcuts, are ingrained in our nature. Historically, they helped our ancestors make quick decisions, such as determining a friend from a foe or choosing flight over fight. However, these shortcuts are less effective in today’s complex, data-driven environments. 

While our instincts can be hard to override, it’s crucial to recognize and manage these biases to ensure a more accurate foundation analysis.

The Peer Review Process Helps Minimize Biases

One of the best ways to combat cognitive biases in foundation analysis is through peer review. By getting input from others, we often catch things we would’ve missed on our own. It’s a crucial part of the scientific process—think defending a thesis or publishing peer-reviewed articles.

Personally, I’ve found that discussing projects with others helps me understand the data better, especially when it’s complex or contradictory. Having multiple perspectives really makes a difference. In past office debates, we’ve gone back and forth on issues and usually ended up with better results because of it.

But sometimes, the data is too inconclusive to arrive at a supportable position. When that happens, we need to gather more data. Below, I’ve outlined some common cognitive biases to watch out for. I’ll dive deeper into each of these in future posts with real-life examples from my own projects.

A Summary of Cognitive Biases that Can Interfere with Foundation Diagnoses

Anchoring

We often “judge a book by its cover,” and this applies not just to people but to ideas as well. Sometimes, the first impression we form about something isn’t the right one.

I’ve walked through many homes, observed the surroundings, and quickly formed an opinion. Later, when more information came in that contradicted my initial judgment, I found it difficult to change my mind. This happens especially when the initial data is visually striking, like severe damage. That’s why we always have multiple people review each report—to avoid fooling ourselves. (Noe)

What we can do: Deliberately challenge ourselves to consider alternative explanations.

Availability Heuristic

This happens when we have limited information and jump to an easy conclusion. Maybe we’ve recently seen something similar, or we’re influenced by a pattern of results that led to the same conclusion.

It’s one of the most common mistakes in evaluating foundation performance. For example, it’s easy to see a sloping floor and immediately assume the lower perimeter is settling when in reality, the opposite could be true. (Craig Smith)

What we can do: Get into the habit of holding off on conclusions until we have all the data in front of us. Always consider alternative viewpoints.

Confirmation Bias

This is similar to anchoring but goes a step further. It’s when we focus on information that supports our existing beliefs and ignore anything that contradicts them.

I’ve found myself resisting a change in my interpretation of damage, even when new data clearly suggests otherwise. For example, an out-of-square door usually indicates footing movement. But sometimes, because the door frame rests on the floor slab, the issue might be caused by slab movement, pointing to slab heave rather than footing settlement. 

These “rules of thumb” often have exceptions, which is why we always have multiple people review each report. Just like in science, peer review helps us avoid confirmation bias. (Craig Smith)

What we can do: Look for data that purposefully contradicts our current hypotheses.

Belief Bias

This is an extension of confirmation bias. Once a general belief is formed, we tend to dismiss any opposing facts without even considering them. For example, if someone believes all foundation problems are caused by water infiltrating the footing, they might ignore any other data, regardless of its validity.

This is why we invest in continual education and learning through organizations like the National Foundation Repair Association and the Foundation Performance Association—to challenge our existing belief systems and stay open to new information.

What we can do: Work hard at not holding unchallengeable beliefs. Be grateful to overturn paradigms in your mind as an opportunity to learn.

Dunning-Kruger Effect

The more you know, the less certain you tend to be about your conclusions. The reverse is also true—the less you know, the more confident you might be. In other words, you don’t know what you don’t know.

This is often seen with engineers who speak in terms of probability and possibility, versus foundation salespeople or so-called “experts” who confidently claim they have the exclusive skills to understand foundation mechanics.

If we actively avoid anchoring, confirmation bias, and belief bias, and stay mindful of our tendency toward lazy thinking, we can avoid being overly confident in areas where we might be wrong. We encourage everyone to keep their egos in check—sometimes the least experienced person turns out to be right. (Belvile)

What we can do: Realize this bias in discussions with others who make claims, and try not to fall victim to our own built-up perception of our knowledge.

Backfire Effect

This is our natural reaction to resist information that challenges our beliefs. When someone questions my position, my initial instinct is to get defensive and argue back. I see this happen on Facebook all the time—the more evidence someone presents against my view, the more I dig in. This can be especially risky when my interpretation is wrong, particularly if it concerns someone else’s foundation problem.

What we can do: When challenged, despite the emotions at the time, cool off and try to look at things from many angles before making statements that paint us into a corner.

Reactance

Similar to the backfire effect, reactance is the tendency to resist any kind of change, often pushing us to do the opposite of what we’re being told. We saw this happen during the Covid pandemic.

We aim to bring together team members who don’t instinctively go against the team’s direction once the evidence is clear.

What we can do: Try not to be obstinate.

In Group Bias

This is the tendency to favor the ideas of those we see as part of our “in group,” whether that’s based on nationality, political beliefs, religion, or even workplace roles.

For example, within a company, engineers might discount the insights of field workers or sales consultants, and vice versa. But we’ve learned that great ideas can come from anywhere. The more open-minded we are, the better results we achieve for both our team and our customers. It’s easy to label people as “in” or “out,” but this can lead to rigid opinions about their ideas and contributions.

What we can do: Focus on identifying with the larger team rather than smaller, exclusive groups.

Groupthink

This happens when we prioritize harmony over independent thinking and end up agreeing with the group just to avoid conflict.

As a team, it’s easy to fall into this trap—especially when we’re busy and just want to move forward. But this can lead to poor decisions in the long run.

What we can do: Assign a “red team” or a “devil’s advocate” to challenge ideas and keep us from falling into groupthink.

Curse of Knowledge

This happens when we assume that what we know is obvious to everyone else—even to our past selves.

Forensic foundation mechanics aren’t commonly understood, and the jargon and thought processes we use daily can leave those unfamiliar feeling lost and overwhelmed. It’s easy to forget this when we’re deep in the subject.

What we can do: Take a step back, listen, and ask for feedback. Remember, hubris is unbecoming.

The McNamara Fallacy

This fallacy involves relying too heavily on easily obtained data, without digging deeper. A classic example is during the Vietnam War, when enemy body counts were used as a measure of success, ignoring the broader context.

In cognitive biases in foundation analysis, certain metrics can be helpful for gauging severity, but they shouldn’t be the sole basis for conclusions. Some of these metrics are still under debate, and engineering judgment is crucial in these cases.

False Cause

The false cause fallacy happens when we mistake correlation for causation. Humans have evolved by making associations to better navigate an unpredictable world—like using the position of the sun and stars to predict the seasons. However, correlation doesn’t always mean causation. Just because two things happen together doesn’t mean one caused the other.

Key Takeaway

Each of these common normal human biases can interfere with our best judgment. Having others peer review our conclusions can help minimize their effects on us. 

In the upcoming blogs, we will explore each of these cognitive biases in foundation analysis with real-world examples to show how they can impact foundation repair diagnoses.