ABCs of Decision-Making Biases – Part 2

In Part 1 we looked at some of the biases that introduce themselves when generating potential solutions to be decided on later. There are also a number of decision-making biases that rear their ugly heads when it’s time to evaluate the proposed options and decide. This post will focus on just four of these biases.

So, let’s assume we’ve addressed all of the scary biases in the first stage of the decision making process, we’ve got our potential solutions in front of us bias free (congratulations!), and now it’s time to make the decision.

Not so fast! Let’s work on getting an understanding of some of the decision-making biases that introduce themselves during the all important decision-making stage. For now, let’s dive into four big ones, and we’ll tackle some of the others in future posts.

Decision-Making Biases

Distinction Bias

Oftentimes, when deciding between options, we compare them side by side. This only seems natural, right? As kids, selecting a toy from the shelf was a painstaking process of side by side comparisons, looking for that small edge. Our eyes shift back and forth between options, magnifying any slight difference that was enough to make us comfortable with our decision.

Now, as important members of our respective organizations, we do the same with options that have much greater implications than entertainment on a rainy day. Still, we do these side by side (or side by side by side and so on) comparisons to bring slight differences to light. This magnifying of slight or nearly non-existent differences that occurs during side by side comparisons is the Distinction Bias.

This is a tricky one because it seems like it would be a good thing to find these slight differences. However, let’s imagine that we’re a team of Venture Capitalists that after much due diligence reduced the list of prospects to two companies. Our job is to make the best investment, whether that’s providing funding for one company, neither of the companies, or both companies.

Both of the companies are very similar in terms of the way they match up to our decision making criteria. Had we compared them in series, we would have concluded that both of these companies were either good or bad investments. However, we compared each piece of our decision making criteria side by side, finding differences where they hardly existed, and decided to fund one of the companies and not the other based on these small differences. Turns out, they were both winners, and the best decision would have been to fund both of these companies.

Statistical Bias

As mentioned in a previous post, we human beings are a busy bunch in this global and technological age. When it comes to making decisions it is common to either make little effort to gather relevant data, or to skim the data to help us feel more comfortable with the gut decision we’re about to make.

This makes sense! Statistical analysis is often time consuming and difficult to interpret, adding to our already demanding cognitive load. This avoidance of statistical analysis in our decision-making process is the Statistical Bias.

Luckily, great business intelligence technologies are being released all of the time, helping us take advantage of data by making it easy to generate and interpret. For example, a few button clicks by your teammates and yourself could generate a wealth of useful data that is then interpreted and visualized in such a way that the best decision becomes obvious at a glance. This is some of the stuff that we get REALLY excited about here at Decision.io, so I’ll stop myself here and just say this topic will headline a number of posts!

Bandwagon Effect

This is similar to “group think”. Basically, it’s our tendency to do or believe things simply because others are doing and believing those same things. We are social animals after all, and so this stems from our need to belong to the group.

Unfortunately, great decisions are rarely the product of everyone falling in line, but rather everyone bringing their special sauce to the decision-making table. Once we have all of these different perspectives and opinions together, efforts need to be made to ensure that the final decision reflects all of the information available.

We all know that it doesn’t always happen this way. Often, it’s the most senior or persuasive person’s decision that spreads like wild fire throughout the group, resulting in the Bandwagon Effect.

The perfect recipe for the Bandwagon Effect is a dash of the hectic times we live in, a sprinkle of our distaste for large sets of data to be statistically analyzed, and a bunch of co-decision makers crammed into a boardroom with the goal of making a decision. Everyone in the room has obligations that require time and energy outside of the events in the boardroom, and so it’s important that this process be efficient.

So, we forego or skim the data when possible if it isn’t generated and presented in a way that values our time and sanity. With ten different personalities in the room, giving each perspective equal airtime seems inefficient, so the most experienced or persuasive individuals dominate the room. As a result, we’re suddenly down to two or three perspectives out of ten with little in the way of due diligence.

The session wears on, we become cognizant of every tick of the clock, we pick up subtle and not so subtle cues from the others in the room, and one by one we start to lean towards a particular option. Eventually, a small group that agrees on something within the larger and still fragmented group begins to form. We can choose to feel excluded and stick to our guns while wasting a lot of time, or we can do what it takes to convince ourselves to join the growing group.

Like water, we take the path of least resistance and join the group. Notice it was being conscious of the time the decision-making process is taking, the social cues, and our need to be included in the group that led us to this decision and NOT the information available. That’s trouble! This movement towards consensus based on the fact that others have chosen to do or believe something is the Bandwagon Effect.

Hyperbolic Discounting

Given the choice between a reward now or the same reward later, we choose the reward right now. This makes sense because why would we wait for something when we can have that same thing immediately? However, given the choice between a reward now or a slightly bigger reward later, we will still often choose the smaller reward now.

We appear to discount the value of rewards that we could receive in the future. Perhaps this is related to the fact that we struggle to predict the future and account for all of the variables that allow the future to materialize the way it will. It seems like in addition to the passage of time, it will take more things going “right” between now and then to actually receive that future reward. So, unless that big score in the distant future is far bigger than what we stand to gain right now, we take the little prize now and never look back. This tendency to prefer a reward that arrives sooner rather than later due to our discounting the value of future rewards is Hyperbolic Discounting.

If we don’t have a well structured collective decision-making process, we may fall into this tendency to prefer options that will provide a reward sooner rather than later. Without structure, it is unlikely that our team will collectively choose to forego the reward in the near future for the larger reward in the distant future.

The best way to negate this bias is to firstly acknowledge it, and secondly structure our decision-making process in such a way that requires our team to consider future rewards. For Hyperbolic Discounting, we could create criteria categories to be considered by a review team, and then assign some weighted value to the “future rewards” category to account for the fact that the team will probably discount these potential future rewards in favour of more immediate rewards. This can get messy if we’re putting pen to paper of course, but it’s a breeze when we leverage the technology of today.

Closing Thoughts

Between Part 1 and now Part 2, we should at least be on the same page and realize that biases are real and rampant in our organization’s decision-making process. This has by no means been a complete coverage of the epidemic that is decision-making biases, but rather a small taste. Hopefully you agree that biases taste as sour as we think they do here at Decision.io!

Biases do not have to prevail, there is hope! Easy to use submission management and group decision-making software are becoming available at a favourable price point for organizations of all sizes and in many different industries. These solutions can help you structure your organization’s decision-making process and make it painless to use data and statistical analysis as a cornerstone for decision making. They can also help you keep all of the wonderful things that come with bringing a diverse group of decision makers together while avoiding the many pitfalls that are inherent in our human condition and team dynamics. We’ll take a look at how business intelligence, more specifically business intelligence 2.0, can support collective decision-making while avoiding some of the biases as well in our next post. Stay tuned!

Let’s hear from you!

Perhaps some of you are already addressing biases in your organization’s decision-making process. I’ve only listed a small fraction of the many biases out there. What are some other biases you’ve detected? How are you dealing with them?

For many of you, this is the first you’ve really thought about biases in the context of your organization’s decision making. What steps are you going to take/currently taking as a result of visiting us here at the Decision.io blog?

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