The eternal fight of Data and Intuition

The interest for analytics professional is far from decreasing. Today, we are all familiar with the concept of data scientists, though often we are confused about it.

Businesses aim to become more data driven. People with analytical mindset and the right skills are needed to help companies grow efficiently. That also mean, for those who hadn’t the luck to study statistics or computer science, to be left behind.

Or that is, at least, what one could think when looking at numbers. Until now, the demand for data scientists grew and this seems not to stop. Anyways, hiring expert data scientists will come to a cost. As business owner, those are skills you want to pay good, and at the same time you can’t wait to see results.

Don’t we pretend too much from data?

I came to this question, being a developmental coach and also a reporting analyst. You can assume that I am divided between two different worlds: one where the most human skills are required to empower others, and another where logic and mathematics are a must to succeed. It could not be that far from truth!

We imagine coaching as an art. In truth, good coaching is, by all means, scientific. When I think of coaching skills, knowing and using a model is just the beginning. Every coach taps into a peculiar skill set. Sure, many tap too much into what they call intuition. I rather think of: observation, non-verbal analysis, critical thinking, effective communications, emotional intelligence. That means not just practicing, but studying at least the foundations of these forms of knowledge.

For the same reason, we might think of data scientists as some mad doctors, or guys that see code as real things: much like the post-apocalyptic humans of the Matrix trilogy. Besides, there is too much crap around about what data science truly is. Many job descriptions actually are for data analysts. However, companies call for data scientists, because it is more attractive. In turn, people that really studied data science may be over-skilled for those jobs. Also, they will not experience big data engineering and algorithms as they thought.

Anyways, this is still a starting point for people like, me who had a crash course in statistics at university and managed to capitalize knowledge on tools and learning, often provided directly by the employer. I won’t lie when I say that much is given by experience, but I would not progress without what we call intuition. Especially without the righteous academic education.

So, what’s exactly intuition?

To quote the American Psychological Association, intuition is “immediate insight or perception, as contrasted with conscious reasoning or reflection”. In other words, intuition is that cognitive skill that looks into what we define tacit knowledge: something we know, but we are unable to explain.

We form tacit knowledge through life, it is what makes us taking decisions automatically. It is not perfect, being especially built on experience, so it is influenced by the many biases we develop in our life. Yet, this implicit, quasi-subconscious form of wisdom can be revised through mindfulness, self-awareness and continuing to learn.

Back to business…

We now start to get a bigger picture. Since we look for more data driven solutions, we pretend that gut feeling is becoming obsolete.

I think that if we look at this type of intuition by its definition (cleansed of mysticism and metaphysics, to be clear), we can agree that it is a very powerful skill we have, and that cannot be replaced by numbers. Otherwise, we risk to look at data without knowing the context, most of which is absorbed indirectly, and whose quality depends by our situational awareness, observation, and memory. When we fail to understand the context we produce disasters instead than accurate predictions. And that is, above all, in fields where there is no exact science.

It is through intuition, driven by laser-focused attention and deep work, that I can connect the dots analytically and be good enough in a data-driven job. So I do also analyze the situation by non-verbal patterns, gestures, facial expressions recorded in my memory, to grasp emotions and better empathize during a coaching session.

It’s a matter of fact, that the most human skills and pure science can coexist and bring impressive results. It is not an eternal fight, but a well-dosed balance.

Published by Andrea Paviglianiti

I practice coaching, I love reading, and I work as a data scientist. I also recharge my batteries with meditation, martial arts, and video games. I perform career and skills coaching – thus I define myself as a “cognitive” coach: I help people improve their learning experience to succeed where they want. My method is based on behavioral analysis, psychology of learning, philosophy of dialogue, and classic literature. I write about how to get better at learning, the best books I read, and my personal philosophy of coaching. And I will not lie to you – I can get verbose at times! I’d be happy if you stick around and read more of what I have to share!

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