Logical vs Emotional Decision Making: A Conceptual Dilemma

Do we in the business intelligence community need to be careful what we wish for? Are we ushering in an age during which our own insight and value will be made obsolete? Will there come a time when our work as “data apostles” is no longer necessary?

I felt compelled to write this post after spending time thinking about something many would consider scary or even dangerous: the ’Autonomous Corporation.’ With the advancement of machine learning and AI, it is not too preposterous to conceive of the ultimate data-driven organization: one where algorithms drive all decision-making processes independent of human intervention.

We are already laying the foundation of a world built around AI. Google’s Nest is quietly gathering data on how we like to control our home’s climate, and Amazon’s Alexa makes suggestions on what we might enjoy based on algorithms that are constantly being refined. If we allow the intrusion of machine intelligence so easily into our private lives, why would we expect that corporations be immune to the same?

What would an autonomous organization look like? Could it really function purely on data without any human experience to guide it? Why does imagining this possible future inspire fear?

Answering these deep questions may lie outside the scope of a mere blog post, but this train of thought led me to contemplate questions on the basic drivers for decision making: what is the role of logical and emotional processes in our decision making? Are we building ourselves a gallows by exalting ‘logic’ above all else?

Brain Vs Heart

One of the main barriers to achieving the data-driven organization is our internal desire to follow our instincts/intuition. When I say intuition, I mean the sum of our experience that we internalize and use as the subconscious driver of our decision-making process. This entails our entire life experience including work, education, cultural values, moral codes, etc. While trying to implement a data culture we are often still drawn into our own intuition that implores us to listen to our ‘heart’ rather than our ‘brain’.

Reliance on intuition vexes us in the business intelligence community because it is so often the source of misguided decisions. A great starting point to understand the depth of this issue is to watch this phenomenal lecture by Dan Ariely. Scholarship on decision-making and rationality has consistently shown us that our belief in our own decision-making process as logical is misguided.  No one makes this point better than him.

If data is the key to rational informed decisions, we need to find the force to step away from a self-assured belief in our own rationality; time and time again we are proven to fall victim to cognitive illusions.

But should we divorce ourselves entirely from intuitive or emotionally based decisions? How do we quantify their value? Why do we hold so strongly to a mode of thinking that is proven to be insufficient so frequently? When I ask myself these questions, I cannot help but come back to the concept of trust.

Human decisions are built around experiences spanning an individuals entire life. When we attack the validity of intuitive decisions, we are calling into question all the education and work experience an individual has relied upon in the past. Of course people are going to “trust their instincts;” their instincts are built on years of internalized experiences. From an evolutionary perspective, our brains have developed over millions of years run on these intuitions.

Data-driven decisions, on the other hand, are entirely logical. Entirely transparent. And entirely novel. No wonder so many people, when faced with an unsuccessful data system implementation, are quick to claim “garbage in, garbage out.” We are asking people to place trust in systems in which they have no experience operating.

We can understand the conflict between these two schools of thought by looking at “the HR dilemma” as a good easy to grasp example. Think of a well-liked, hardworking, intelligent employee that simply under performs when subjected to data analysis: A sales person that might be a great team player, receive overwhelmingly positive feedback from customers, and generally be viewed as an asset to the organization. Despite all this, they just can’t seem to reach their sales numbers.

Intuition will tell us to keep training the employee, keep investing until they perform at the level we believe they are capable of. A data-reliant perspective will implore us to let the employee go. To disregard our feelings and trust in the numbers. So our heart will encourage us to keep them on the job but our brain will suggest to point them to a new career path.

Which path should we follow?

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