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How cognitive biases can affect data management

Anyone who has ever taken an intro level course on psych (or just reads a lot) has probably encountered the concept of cognitive biases. In a nutshell, a cognitive bias is a mental shortcut, or heuristic, for helping humans make decisions. Cognitive biases are not inherently bad, but they can cause problems, especially when used during decision making processes.

Below are three cognitive biases that I see very commonly when discussing data management or data management systems (i.e., AMSes) with my clients, and how you might avoid the trap they can often set.

Confirmation bias: This bias is probably the most common bias among all humans. Simply put, confirmation bias is a tendency to search for, interpret, focus on and remember information in a way that confirms one’s preconceptions.* In other words, I’m looking for information that will confirm what I already believe. The problem is that I may ignore information that contradicts what I believe. I see this often during AMS system selection, when someone has decided “I’m familiar with this product and therefore I like it/don’t like it.”

The way to avoid confirmation bias, or minimize its effect, is to acknowledge that you have these beliefs, and then actively seek data that contradicts your belief. Finding countervailing evidence will, hopefully, help you balance this bias and see a clearer picture.

Anchoring is another bias that I see in play fairly often. Anchoring is the tendency to rely too heavily, or “anchor,” on one trait or piece of information when making decisions (usually the first piece of information acquired on the subject). I see this very commonly with clients when searching for AMS software. And it’s why I strongly recommend not actually looking at software until you’ve completed your needs analysis and can objectively state your functional needs. That way you’re not overawed by the shiny new object that is the first AMS software you see.

I also see this in data management, and how staff perceives the quality of data. Many people “anchor” their perception to one specific event, rather than measuring data quality over a period of time. For example, I’ve worked with many clients over the years who will tell me their data is bad, and when I asked for an example, they give me a single example of a board list pulled from the database that had an error in it…from four years ago. Ever since that moment, they’ve anchored in their mind that the data is bad.

How to beat the anchoring effect? Like confirmation bias above, find data that contradicts your position. Seek out information that directly contradicts your belief and test it to see if it holds up. Your “anchor” may still be correct, but it’s certainly worth testing to be sure.

Availability heuristic: This is one of my favorites because I see it so frequently, and it’s often easy to debunk. This one is a mental shortcut that relies on immediate examples that come to one’s mind when evaluating a specific topic, concept, method or decision. Where do I see this most often? When asking people to evaluate the quality of their data. If someone says their data is “bad” and you ask for examples, they’ll almost always point to something that just happened. “Just last week we pulled a list of members and the count was wrong.”

This is a natural reaction to any question, but the problem is that often just because it happened recently does not mean it’s happening frequently. In fact, I usually follow that statement with the question: “And how regularly does this happen?” Often, the answer is “I don’t know.”

The way to avoid the availability heuristic is to make sure you have plenty of data, over a good amount of time, to answer any question that requires data. For example, associations always struggle with knowing “what’s on our members’ minds.” One of the best ways to answer this question is to capture interactions with your members in your AMS. When a member calls or emails with a specific question related to your industry or profession, capture that information in your AMS, and categorize its type/topic. Over time you’ll be able to easily determine the trend of questions and topics you’re receiving from your members, and you won’t have to base your answer on simply the most recent conversation you’ve had (the availability heuristic!).

Cognitive biases are a natural human phenomena and the are not inherently bad. (In fact, some biases can save your life!) But understanding the biases above, and how to counteract them, can help you from making poor or ill-informed decisions. Being aware of them is the first step toward dealing with them.

*(All definitions courtesy of Wikipedia.)