Traps in Decision-Making: How Decision Intelligence Helps You Prevent Bias
In the complex landscape of decision-making, the siren call of bias can be alluring. If unperceived, bias creeps into our decisions, shaping our strategies, and influencing our outcomes. So let’s talk about how Decision Intelligence can guide us through the treacherous waters of cognitive bias and help us navigate towards more objective, effective decisions.
What is Bias in Decision-Making?
Before we dive into the role of Decision Intelligence in combating bias, let’s understand what bias is in the context of decision-making. Bias is the systematic deviation from objective, rational, and logical decision processes. It’s the ghost in the machine, lurking in our minds and influencing the choices we make.
In the world of behavioural sciences, bias is not a new phenomenon. It’s a product of our brain’s attempt to simplify the overwhelming amount of information it encounters daily. Our brains rely on shortcuts and heuristics to make decisions quickly, but these mental shortcuts, while efficient, can lead to systematic errors in judgment.
Common Types of Bias, traps in Decision-Making and Strategy
The biases that infiltrate our decision-making processes are more common than we might think, so let’s look at the ones that I think appear the most:
Confirmation Bias
Confirmation bias is probably the most famous one of all, and it refers to the tendency to search for, interpret, and remember information in a way that confirms our preconceptions. When we fall victim to confirmation bias, we cherry-pick evidence that aligns with our beliefs while ignoring or dismissing information that challenges them.
In case you want to dig deeper, a lot of research has explored confirmation bias, such as “Motivated Skepticism in the Evaluation of Political Beliefs” by Charles Taber and Milton Lodge, revealing how individuals tend to accept information that aligns with their political beliefs.
Sunk-Cost Fallacy
The sunk-cost fallacy is our tendency to continue investing in a decision or project because we’ve already invested resources (time, money, effort) into it, even when it’s clear that the best course of action is to cut our losses and move on.
Numerous experiments, including the “Concorde Fallacy” study by Arkes and Blumer, have demonstrated the prevalence of the sunk-cost fallacy. They show how individuals are reluctant to abandon investments, even when doing so would be the rational choice. To visualize it better, I personally like this example from thedecisionlab.com:
Imagine that you bought a concert ticket a few weeks ago for $50. On the day of the concert, you feel sick, and it’s raining outside. You know that traffic will be worse because of the rain and that you risk getting sicker by going to the concert. Although it seems that the current drawbacks outweigh the benefits, why are you still likely to choose to go to the concert?
Cognitive Dissonance: The Clash of Beliefs
This bias occurs when individuals are confronted with conflicting beliefs or ideas that challenge their existing views or decisions. To alleviate the discomfort of holding contradictory beliefs, people often engage in a process of almost mental gymnastics — they rationalize, justify, or even distort information to align with their preconceived notions.
In the realm of decision-making and strategy, cognitive dissonance can be particularly problematic because it can lead individuals and organizations to stick stubbornly to a failing course of action, putting more resources into doomed projects or investments simply to avoid the discomfort of admitting an error.
When people feel a strong connection to a political party, leader, ideology, or belief, they are more likely to let that allegiance do their thinking for them and distort or ignore the evidence that challenges those loyalties. — Social psychologists Elliot Aronson and Carol Tavris
The Framing Effect
The way a problem (or solution) is framed can significantly influence the choices we make. Different ways of framing information can establish different status quos and lead us down distinct decision paths. For example, consider the difference between offering a product with a 95% success rate versus one with a 5% failure rate. The framing shapes our perception of risk and potential gain, and for some specific audience they are going to take one version better than the other.
Research on framing effects is pretty extensive, but I would say studies such as “Prospect Theory: An Analysis of Decision under Risk” by Kahneman and Tversky can help you understand how different framings can significantly alter decision-making outcomes.
How to Prevent and Educate Yourself in Identifying Bias
But the question is, how can we shield ourselves from their seductive grasp and make more objective decisions? Education and awareness are our first lines of defence, nothing can replace domain knowledge and self awareness.
Seek Out Education
Understanding the types of bias that can influence your decisions is the first step. Consider taking courses on behavioural economics or reading introductory books like Daniel Kahneman’s “Thinking, Fast and Slow” to start to build your knowledge of cognitive biases. That is what I love about behavioural science, you always have different alternatives and views to take on and learn.
Challenge Your Assumptions
Regularly question your own assumptions and beliefs by actively seeking out information that contradicts your views, and stay open to changing your mind when presented with compelling evidence. This practice will help counter confirmation bias, which is the base concept for multiple other types.
Embrace Scepticism
Maintain a healthy level of scepticism, especially when evaluating information that aligns with your preconceived opinions. Ask critical questions and check the quality of evidence, even with trusted sources or people you know for a long time. You will always face bias, but if you are sceptical to some point, you might solve them faster.
Bridging the Gap Between Data Science and Behavioural Science
In our realm of Data Science, the focus is often on algorithms, models, and data collection. While these technical aspects are crucial, one integral element often takes a backseat: the human element. The intricate web of biases, heuristics, and cognitive shortcuts that shape our decisions is frequently neglected in traditional data science simply because most people don’t have this knowledge. And this oversight can have big consequences, leading to bad choices, missed opportunities, and costly mistakes.
Behavioural science, a field dedicated to understanding human behaviour and decision-making processes, offers a wealth of insights that data science can no longer afford to ignore. It uncovers the dance between the rational and irrational facets of our minds, clarifying why we make the decisions we do. Yet, behavioural science often exists in parallel to data science, rarely integrated into the decision-making processes of organizations.
This separation between them creates a void — a chasm where bias thrives and optimal decision-making withers. And that is why I talk about Decision Intelligence, it can bridge this gap by harmonizing the analytical efforts of data science with the understanding of human behaviour and going beyond the data.
Decision Intelligence: The Confluence of Data Science and Behavioural Science
Decision Intelligence, in my opinion, represents the evolution of data science — a paradigm shift that recognizes the critical importance of integrating behavioural science into the decision-making of organizations.
In the world of Decision Intelligence, data is not just about numbers, it’s about everything behind it, such as people, politics, economics. It acknowledges that decisions are not made in a vacuum but within the web of biases, emotions, and cognitive processes that define us as human beings. Decision Intelligence embraces the teachings of behavioural science and applies them in practical, real-world scenarios.
If you want to know more, I would recommend the article Decision Intelligence, except this time it’s not complicated.
Are you ready to face your biases?
Thanks for reading! Follow me to continue with the series — Vinícius A. R. Z.
I’m a Senior Data Analyst and when people ask me what do I work with, I always say “I work with decision intelligence” because I try not to limit myself to data! It’s like they say, you have to be smart as a fox… 🦊
