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Macarena Estévez is a partner at Deloitte and, as an expert in data analysis, she directs the Analytics & Cognitive area of the consulting firm. Throughout her professional career she has developed mathematical models and created solutions based on mathematics for companies of all types.
Additionally, in 2020 she was named Top Voice Linkedin , as well as one of the ten best entrepreneurs by Emprendedores magazine , thus recognizing her work as founder in 2007 of Conento , a company that she later integrated into Deloitte. Deserving of countless awards, professor at the Phone Number List main Business Schools and advisor to several business councils and committees, she tells in a talk with Economía 3 how she has achieved her success in the social work network par excellence, her work at Deloitte and the importance, benefits and risks of data.
What content do you reach people on Linkedin with?
I decided to do something a little different, because a lot of people share other posts and such. I decided to always publish a style of post, with the Deloitte brand. Although I started posting before being at Deloitte. But I always did the same, short slide with a clear message. And always the mathematical themes applied to the business world, Machine Learning... It's about doing something different, that characterizes you, persevering, not giving up...
I have some schedules. I post at least two posts, one at 8 and another at 11. In other words, it's a routine. I also try to stay up to date with what people are interested in. I also give it a personal touch. On Linkedin, people like it when you say what you think, I answer all the comments...
“It turns out that a neural network is a super simple thing!”
There are influencers who are dedicated to gastronomy, for example. With these topics it seems easier to reach people than with more technical issues. What's your trick?
I have my audience. Linkedin is a professional network where there are people who work in companies. And in companies, the topics of Machine Learning, artificial intelligence and Google Analytics are of increasing interest, because the future is supported by data, analysis and technology.
One of the things that characterizes me is that I make complicated things simple. My audience is not technicians. My audience is the people who are in companies, in the marketing, financial, and purchasing departments. Who know that this is the future, that they are immersed in a digital transformation and that when they see my posts they say: "Oh, look how complicated this seems, but how easy!" It turns out that a neural network is a super simple thing!
In certain sectors we see a lack of talent and talent retention. Does it happen in the area of data analysis?
I have always done applied mathematics. It was something that interested all companies because, in general, they did not have this type of profiles. Now, however, all companies have very large departments with lots of analysts. Although it is true that universities are now opening a lot of new degrees and master's degrees, the demand is immense and it is true that these types of profiles are lacking.
They steal from one company to another. Losing that talent is difficult for Deloitte. We want to make the people who work with us develop and be happy. So that they do not want to leave Deloitte even if someone offers them gold and silver.
«Companies are transforming from the inside, they are no longer the same»
How important is data analysis today? Is it an upward trend?
In companies there has always been data and analysis has always been done. The change now is that, with technology, which has developed a lot, one of the things it has allowed is that where before you had weekly sales data, you now have up-to-the-minute sales data. That means that you have millions of data and that implies that there is no longer an analyst that you are going to have there. He is an analyst surrounded by Artificial Intelligence, data algorithms... Companies are transforming from the inside, they are no longer the same.
There are two totally different companies. The companies that have already been born digital natives and the other reality, the traditional companies, but that know that they have to transform. Because the consumer is already accustomed to a different treatment. All companies have to transform and that means that profiles, cultures have to be transformed... It is a total transformation.
Where are the humans then? They have three clear positions in the companies of the future. First, at the top, leading strategic thinking, which is something that will never depend on machines. Then, even if the machines are connected, you have to have people who control the quality of the algorithm and that it is not making mistakes and the ethics of the algorithm. That you are not committing biases. Finally, humans will be in companies on small islands, innovating, inventing, creating, dreaming, visualizing the future... Humans will clearly have their positioning, but with companies fully connected.
"We are giving away our data, sometimes knowingly and sometimes without, which is the worst"
We have seen cases like Facebook with Cambridge Analytica... To what extent are we giving our personal information to these companies and these technological giants?
We are giving them a lot. Sometimes knowingly and sometimes without, which is the worst. We humans tend to think that this is not going to happen to me. But I am a person who trusts companies a lot. In companies there are people who are always trying to do things well. Although it is true that sometimes this gets out of control somewhere, someone in the company makes a mistake, what has to be done is to solve it. There are many regulations that protect us. When something happens, it is fixed, fines are imposed on companies...
So we don't have to be scared of having our cell phone listening to us?
You have to be cautious. I have a company cell phone but I have it super protected. You can't be ignorant. There are many tools and you can use technology safely.
"If I like bicycles and I always get bicycles, how likely is it that I think about skateboards?"
We have seen cases in which it has been possible to intervene in elections. Can data be used as a political or even geopolitical weapon?
I don't think the intention is necessarily bad. Human beings have this tendency to manipulate, instead of convincing. The border is narrow. Companies are all very concerned about making a difference and not manipulating people. Google engines are prepared to show us something that we will like. Google has no bad intentions , it wants to teach things that it believes each user is interested in.
But if I like bicycles and I always get bicycles, what is the probability that one day I will think about skateboards? So, I don't think the intentions are bad in almost any case, but it is true that the border between right and wrong... It is difficult.
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發表於 2023-11-29 14:53:17