In a world where data abounds, organizations face the challenge of being able to separate the signal from the noise, that is, being able to convert the data into relevant information. The goal is none other than making the right decisions. Use the information to progress, pulling algorithm and good food.
But no, it's not that simple. Abandoning the "here it has always been done like this" or as Shakira would say "those of intuition" is a great challenge, among other things because this step implies a new way of thinking and acting. Help.
Changes are good. True sentence. The changes are traumatic. Truest sentence. Resistance to change is one of the main enemies of progress. Absolute truth. And then what do we do with the bad(blessed) data?
Let's take a practical and everyday example: how much attention do you pay to the GPS when the path is obvious and it shows you a street that is not the usual one? I'm sorry to remind you of the last time he was right and you found the road blocked. Those data that you went unnoticed were online, meeting a need that you yourself had generated and that you later decided not to attend to.
We are as afraid of not controlling the result as the process that leads us to it. Not understanding, not being a part, not taking communion sometimes leads us to mistrust. It is normal, we are human and, therefore, distrustful. We weren't the best species, we thrived on that continual alert. But we also did it thanks to the mass. We were much weaker physically than other animals, but we managed to develop thinking, that's why we achieved things that the rest had no chance.
Thinking is still important. Very important. But it is better to let computers do the work they do best and ask them to make decisions with them. In medicine they have it very clear. Oncologists and radiologists have already accepted that the imaging diagnosis made by a mathematical model cannot be done by them, they have understood that there are oncological lesions that are alien to the human eye. They have accepted that their job is to interpret the data, diagnose and treat.
Now we need the rest of the professionals to accept that although life is not what we are putting at stake, the improvement is infinite, like the data. Our mission is to exploit them, not guess them.
