How does Big Data help in companies? Today I would like to share with you another debate of the “Café con Talento” channel, in which we deal with the topic of Big Data.
Andrea Lacoma, (CEO and Co-founder of Blipol HR Analytics, a start-up from the University of Zaragoza specialized in Big Dataand data mining in the field of Human Resources) and Tomás Ramos, (Plant Manager at ArcelorMittal, A professional who has been working in the automotive world for more than 30 years and focuses on managing people in different positions of responsibility. We are hearing more and more frequently that Big Data helps to better adapt to changing environments and the imperative need for customer knowledge.
However, information and data have long been sought and analyzed to learn more about people’s needs, tastes, trends, and opinions.
What is Big Data in companies?
Why is it so important?
So what is the main difference between analytics and management applications and new Big Data concepts?
The fundamental differences have to do with the three ‘Vs’ of Big Data: Volume, Variety and Speed (3Vs).
On the other hand, taking into account the previous experience of pioneering companies in this concept, two other ‘Vs’ are now added with two new characteristics: Veracity and Data Value (5Vs).
In reality, it is Big Data when the volume of information exceeds the capacity of a usual software to be handled and managed.
The idea of variety refers to including other types of data sources different from those used in a traditional way, (information from social networks, in the increasing number of connected electronic devices, the exploitation of sensors that allow us to know movements and lifestyle habits, external information from various sources, etc.).
What is Big Data?
How is it applied in companies?
According to Andrea, it is a concept that encompasses a large amount of data.
Experts usually define it in the 5 V’s: Volume, (large amount of data), Speed, Variety, (due to the different format that this data has), Veracity, (the data has to be correct) and Value (because of the value it has for companies).
According to Tomás, it consists of managing the data that you are accumulating in a massive way and that you get online and ontime.
In the company, it means considering the data that you store at a given time, which will later allow you to predict processes or be able to make decisions through algorithms on data that you have stored from other times.
The data collected in companies has been analysed for a long time, so what are the fundamental differences now with Big Data?
Tomás believes that before the databases that were handled, the problem they had is that when they wanted to be used they had already become obsolete or were only useful to make an exposition of what had happened the previous week.
Nowadays in industry you need information to be able to make decisions immediately.
If you decide with data from a week ago, it is quite likely that you may be making mistakes.
That is why Big Data in companies helps us to make quick decisions with very good predictions, with fewer errors.
Andres comments that Eric Schmidt, who was CEO of Google, said that the data that is currently generated in two days is the same volume as that that which was generated previously from the beginning of our days until 2003.
Tomás comments that it is not enough to have data, to store it, but it is essential to have an efficient way of analyzing it.
In this data collection and processing, how do you see the aspect of transparency, ethics and privacy of this personal data in Big Data?
To begin with, what we have to see is that algorithms are created based on historical data, so if that data is biased, for example with racist or sexist criteria, the algorithm and the predictions will also be biased.
Earlier we talked about Amazon’s predictive model in personnel selection processes some time ago.
An initial screening was carried out automatically in the job selection processes.
Historical data were taken in which men were promoted faster and more frequently than women.
Therefore, what the algorithm did was simply model that fact and candidates were positioned better simply because they were men.
For this reason, Amazon had to acknowledge it and apologize and modify the algorithm so that they did not have biased criteria.
Is there legislation at national and international level on limits to the application of Big Data in companies or does it depend on the criteria of companies?
In terms of data protection, there is European legislation that unifies the criteria in this regard and is quite robust, especially on the subject of personal data.
Companies have to take measures, especially in the face of hackers, to protect this information with “firewalls” that allow third parties to block access to this information.
What phases are there in organizations so that they know how to apply Big Data?
The first thing is that it is important that the data that can be used is collected, that the company is prepared to capture the data throughout the process and that it can then be processed, with easy-to-use intelligent data management programs to be able to visualize it as a user in a simple way.
Capture, process and make it easy to make decisions in Big Data in companies.
That the data can be sifted through useful information to make decisions.
That you are clear about what you want to have as information, what results you are looking for, that they are really relevant.
In relation to this, the concept of “matching learning” also arises, where machines use their own data to improve their own processes.
How important is collaboration for the best application of Big Data?
It is very important to collaborate with suppliers, as well as customers, as well as between companies.
Sometimes in order to make correct use of data you need to have suppliers, for example, to be able to make decisions and that implies opening companies to external parties or suppliers to access your data.
The demand for Big Data professionals in companies has also increased, data scientists is a profession that is increasingly in demand.
How does Spain position itself in the application of Big Data?
This type of technology is hunting us down and catches us unprepared, we are not delving well due to the lack of professional experts in the field or because it is going very fast.
4 days ago we were talking about technology 4.0, it was a boom and it is almost not yet implemented in companies, it is being worked on but at the same time for some processes it is still working on an “Excel” sheet. Big Data has entered above all in Marketing departments, then it has been consolidated in the areas of Human Resources, also in the areas of Production, to improve processes, but we have to go a step further and make it more strategic, more global in organizations.
In addition, Smart Data is the intelligence of data.
To have the data to be able to learn, to predict, to have a clear purpose.
What are the main resistances of companies to the application of Big Data?
One of the difficulties is that companies must “open up” in order to apply it efficiently.
You can’t take advantage of it 100% autonomously and you have to open yourself up to third parties, so that they can work with the data and for that you have to trust and be willing to do so.
The risks could perhaps be being more exposed to a possible cyberattack.
In any case, the benefits are many and Big Data in companies can help us a lot to make better decisions, with fewer risks, fewer costs and adapting faster to changes. And you, what do you think about the application of Big Data in companies?
