Cognitive bias gets in the way of good decision-making. For the most part, bias is largely subconscious – in business and in everyday life. But that doesn’t mean bias can’t have a big impact on the way you view the world (and the data) around you. Research suggests that the best line of defense against cognitive bias is awareness. Simply knowing that you’re prone to take mental shortcuts in the decision making process can help you avoid them. Awareness might not be the only solution to avoid cognitive bias, but it’s definitely a step in the right direction.
What is cognitive bias?
Whether you’re picking out new furniture or looking for ways to improve your organization’s customer retention rates, cognitive bias can creep in and skew your otherwise objective point of view. But simply knowing this isn’t enough for your brain to slam on the bias brakes. You need something else, something that – no matter how you slice it – is truly objective. This is where data comes in.
When used properly, data can be an effective tool against some of the most common forms of cognitive bias. Whether you’re analyzing or presenting data, knowing how to use it increase objectivity is invaluable. Here’s how:
Combating Confirmation Bias
Succumbing to confirmation bias is very common. In the simplest terms, confirmation bias happens when people tend to interpret new evidence as support for their already existing ideas. Fortunately, avoiding it is a breeze if you have the right information backing up your decision.
Let’s say you want to know why student retention rates are down at a specific university. If you’re already aware that state funding recently cut financial aid for all students, you might be inclined to stop looking for further evidence and assume that’s the “why” behind your data. You might be so convinced that you don’t bother to notice that a similar school recently lowered its tuition rates, convincing a number of students to transfer to a new university.
In the example above, confirmation bias could easily mislead you into thinking that the issue you already know about is the only factor influencing your data. To avoid situations like this, be aware of your own confirmation bias and dig deeper into the data you have, looking for additional possibilities.
Seeing Past Clustering Illusions
“Clustering illusion” occurs when your brain starts to draw connections between random pieces of information in a sample set. This particular cognitive bias is tricky because it often occurs simultaneously with confirmation bias. If you’re viewing a set of random data, don’t jump to conclusions until you actually have enough information to draw parallels where they really exist.
Instead of confirming your own bias, take a second look at the data and assume your first inclination is false. How does your interpretation of the data change? Additionally, make sure your sample size is large enough. The more information you have, the hard it is for your brain to manufacture false connections.
Choosing to Ignore Selection Bias
Sometimes called “cherry picking,” selection bias has a somewhat nefarious reputation in the data visualization world. Whether conscious or inadvertent, selection bias occurs when someone – without actually changing the data – presents certain metrics or groups of metrics because they support a theory, while ignoring metrics that do not.
Much like confirmation bias, selection bias favors information that supports your preconceived ideas about a subject. To avoid it, carefully consider all data that pertains to your decision making. Make sure that the scales on your charts have a zero baseline. Play devil’s advocate. Most importantly, don’t be afraid of data that might change your mind. In the end, objectivity can help you avoid unseen roadblocks that could’ve arisen as a result of your original bias.
Read next: How to Spot and Stop Bad Data
Leave the Ostrich Effect for the Birds
The Ostrich Effect bias is often seen in the financial sector. In short, it happens when an individual (such as an investor) tries to avoid negative information by pretending it doesn’t exist. If you’re like most people, your immediate thought is “I would never!” But remember: Cognitive bias is largely subconscious. To avoid ignoring negative data, consider the following:
- Are there any data sets that don’t support your theory? Pay extra attention to them.
- Find “negative” data and troubleshoot your ideas. Does your theory still stand?
- Scrutinize even small pieces of data that don’t support your idea. Your subconscious might try to minimize them!
- Remember that “negative” data isn’t really negative at all because it will help you make better, positive decisions in the long run.
Don’t Ignore Hyperbolic Discounting
In a sense, hyperbolic discounting is a fancy term for “instant gratification.” This cognitive bias refers to the human tendency to choose smaller rewards if we know they will happen sooner – opposed to waiting for larger rewards that are farther out on the horizon. The principal arises from the simple fact that humans are impatient; we want positive outcomes now. In fact, we want immediacy even more than we want a better reward in the future.
Hyperbolic discounting is a unique cognitive bias because you can actually use it to defeat it. How? Determine your organization’s goals. While a small but immediate return on your data investment might seem appealing, your data has much more to offer. To avoid getting stuck with a near-sighted perspective of your information, establish a bigger but more-difficult-to-obtain goal and break it down into bite-sized goals.
This way, you’re using data to reach a better endgame without sacrificing the immediate, smaller payoff. By doing so, you can constantly revisit your data to determine if you’re still on track to reach the organization’s final, bigger goal.
Don’t Get Used to the Status Quo Bias
It goes without saying that the status quo bias is the most boring of all biases. This is because it refers to people’s natural aversion to change. We can get stuck in ruts, because we like things to stay the same by doing nothing. In fact, we won’t change things without a good reason. “The devil you know is better than the one you don’t,” the saying goes. While status quo bias can easily hid under the guise of “cautious” and “prudent” decision making, it can also cripple your organization from making the progress it needs to stay ahead of the curve.
Combating status quo bias is easy when you have the right data. With data storytelling, you can demonstrate not only why things need to change, but the best way to change. Additionally, you can provide actual evidence supporting your theory and use predictive data to demonstrate how positive change will influence your organization in the long run.
Bias is a part of cognition, and is a constant factor in interpersonal relations and decision-making. While we are all susceptible to bias, we don’t need to be ruled by it. Armed with a little knowledge and a healthy amount of data, you’ll be prepared to fight your own biases on the path towards better decision-making.