Why You Still Need Business Intuition in the Era of Big Data

Artificial intelligence is coming for your job, right? Not so fast. Despite what doomsday enthusiasts predict, machines are a long way off from becoming dangerously sentient. Instead, machines are taking over areas where humans just aren’t that great, freeing up human labor to do what we do best, create, build relationships, and problem solve.

So no, AI isn’t coming for your job. It’s not even coming for your most valuable asset, your gut. There are a few different ways that big data and AI can complement your gut feelings about business, putting that intuitive skill to better use than in years past.

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Why AI And Intuition Are Good Friends

Big data can validate some basic hunches you have about your market, but it can also up-end some long-held beliefs about it too. The piece to remember is that data and intuition aren’t adversarial. Breaking those silos opens up an entirely new perspective on massive data and its role in your organization.

Data Versus Intuition Is False Dilemma

Basing your business entirely on your gut feelings will end in disappointment because humans just aren’t capable of processing the large amounts of data businesses receive daily. We can typically make pretty good intuition-based decisions for situations in which we are familiar, but our intuition can’t help us with the unfamiliar.

Data, on the other hand, is neutral, but the machines processing data don’t have an understanding of what they’re processing. The data is only an imprint. It may be able to identify which shows you’d prefer to watch next on Netflix, but it can’t tell you why.

The intersection of these two areas, the what and the why, are critical ways in which data and intuition work together. Data can reveal market trends, and your gut analysis of the solution can reveal factors contributing to that conclusion.

Both Data and Intuition Reflect Our Biases

Bias can also inform how we build our data collection and processing algorithms. Relying solely on the data accepts the idea that humans are incapable of influencing data outcomes regardless.

A hybrid decision-making approach can help mitigate the biases we experience both from data and intuition. In the hiring process, we are notably predisposed to hiring certain types of people, but a machine can quickly strip away the internal biases we have and present us with a list of truly qualified candidates.

The other side of this is a blind trust in the conclusions of data. For example, data conclusions often run without the addition of outliers, but our gut responses can tell us a lot about why those outliers exist, helping paint a broader picture. Also, predicting trends is a compelling part of big data, but your business experience can also tell you when your data is experiencing a confounding variable.

It’s A Fine Line To Decision Paralysis

Humans are notoriously bad at visualizing at the macro scale. For us to make decisions from the sheer amount of data we have access to, we have to make it smaller for our consumption. One of the most critical aspects of data science is the presentation, knowing how to visualize outcomes without oversimplifying, muddying, outright lying, or misinterpreting.

More information doesn’t always lead to more confident decisions. In some cases, more information clarifies the message and prevents an organization from moving forward with an ill-hatched plan. However, the line from there to decision paralysis is a fine one.

Using Intuition to Guide Data Exploration

The big draw here for your business intuition is to help lead your team through a series of decisions about your data. First, you’ll have to know when enough data is enough. Again, half-baked plans aren’t great, but the right decision is never the result of perfectly complete data. Instead, it’s a balance between too little and too much.

Second, you’ll need to have an innate understanding of when big data isn’t necessary. Not every decision needs to be overcomplicated with deep learning algorithms. Knowing enough about data science to lead your team logically through which problems are data science related and which aren’t is key here.

Finally (though not exhaustive), knowing what questions to ask in the first place requires a certain amount of business intuition. The data is only an impression of the question; the wrong ones lead you astray. The right ones glean that critical insight.

Build A Relationship Between Data And Your Gut

Data doesn’t detract from a well-timed gut feeling. Instead, data can provide your intuition with well-documented and logical paths, satisfying both shareholders and employees. Data makes it easier to establish a history and makes your organization less reliant on the gut feelings of one individual.

Intuition humanizes your data. It allows you to analyze without reaching decision paralysis or fatigue. It identifies and contextualizes data in ways that machines still aren’t able to. Using both to your advantage in a way that embraces their strengths and forgoes the adversarial relationship. Intuition is essentially your body’s own version of the big data process. Back it up with real numbers.