Companies that wish to stay competitive and relevant must adopt data strategies and artificial intelligence (AI). These technologies not only optimize operations, but also open new growth and innovation opportunities. To talk about it, Byte Ti, together with Qlik, organized a meeting that was attended by Carlos MirandaFerrovial ciio; Esperanza SánchezCio & cdo in Securitas Security Spain; Manel MirandaDirector of Innovation of FCC; Fernando de PabloGeneral Director of the Digital Office in Madrid City Council; David GurumetaExecutive of Qlik; Cristina HoneyResponsible for BBVA Corporate Bank fraud; Emilio Martín, Senior Data Science of Repsol; Francisco Borja EscalonaChief Data Office of Carrefour and Joaquín García de FranceEnterprise Sales Director of Qlik
Mass data collection and analysis allow organizations to obtain valuable data on a countless number of elements. Transforming a company into an organization based on the data encourages reported decision making at all levels of the company.
The AI, on the other hand, enhances process automation, improves customer experience and facilitates the prediction of future trends. Technologies such as automatic learning and natural language processing can be applied in areas such as customer service, inventory management and fraud detection. To make the most of these technologies, companies must invest in adequate infrastructure, train their staff in digital skills and promote a continuous innovation mentality. In addition, it is crucial to address the ethical and privacy challenges associated with the use of data and IA.
How the organizations’ data strategy is defined
The data strategy of each company varies according to the needs of your business. For example, Esperanza Sánchez, Cio & Cdo in Securitas Security Spain explained that in his case “we have a comprehensive plan that has made us become a Data Driven. Around the data the plan has been forged. We have been working on different models for years and around them the objective we pursue is self -service, so that all models can serve the fact”.
In this sense, David Gurumeta, Sales Executive de Qlik, considered that “self -service has a risk that is the part of governance because the government in this case has its risks.”
Cristina Mielgo, head of corporate banking fraud in BBVA, however, considered that “self -service has its risks but it gives a lot A misuse ”.
On the subject of self -service, David Gurumeta explained that “Qlik is an analytical company, but since 2018 we are a more end to end company. The issue of self -service is part of our DNA and we have seen that self -service has to be focused on giving autonomy to the user, but with adequate governance.”
Main challenges
Companies have different challenges ahead when managing the data. Many of those challenges have surpassed them. For example, Francisco Borja Escalona, Chief Data Officer of Carrefour explained that “our challenge is that we can now tell business that the silos have been broken and that they can use the data. Self -service is fundamental, but the information flows need to occur continuously.
In this sense, Fernando de Pablo, general director of the Digital Office in Madrid City Council, explained that “it is responsible for the areas that have an exact knowledge of what each data means. The benefits of self -service must be reversed for the benefit of the organization.”
Cristina Mielgo considered that the key is that “we must not go through an authorization for everything, or give freedom for everything. It will depend on the type of data. If you go to a complete authorization model or complete freedom, then we will have a negative experience.”
Companies that wish to stay competitive and relevant must adopt data strategies and artificial intelligence
Challenges to implement data culture
Implementing a culture that revolves around data is an increasingly widespread strategy among organizations. That culture must permeate almost all the departments that make up the organization. In this regard, Carlos Miranda de Ferrovial, Ciio de Ferrovial, explained that “we come from a very physical world and for the company a very important part is all the extraction of data that occurs, for example in a work, and we have the constant feeling that we are leaving many things outside. In the end we believe that we lack that real need with which the real person knows that everything that does generate data and information important. Applications and then are not used.
The spokeswoman for Securitas Security explained that “we change the CRM and after that a lot of training was done so that people analyze the data and clean. Copilot has now arrived and we see that users say it does not work and do not know that the problem is the data.”
Regarding this, Fernando de Pablo, stressed that “it is important to train people because sometimes I have the feeling that they ask us to do things that we are not able to do. That is why training is very important.”
Manel Miranda, director of Innovation of FCC, on the other hand, considered that “the management of change at different levels, especially in intermediates, is important. But we must also keep in mind that we deal with people and that information must be managed efficiently.” Miranda added that “in the case of Copilot we have started with very simple and simple projects. That is why I think the strategy must start through simpler tools for employees to take confidence.”
Emilio Martín, Senior Data Science of Repsol believes that “one of the challenges is that the businesses perceive value and this we have tried suppliers to innovate and try. ”
David Gurumeta believes that the most important section “is the government government. But so is the quality of the data because, for example, if there is no good fact, the AI does not make sense. And then, another of the most important challenges is in the catalog of data domains, that is, the dispersion of the data, and that is known where each data is and what it is for”.
Fernando de Pablo stressed that “the quality of information is one of the most important sections. There are government issues that have nothing to do with the latest technologies. The Tax Agency, for example, already worked 30 years ago. The quality of the data, we still have to get it. Give it to spend resources on quality is fundamental and sometimes it is not done. It is true that, today, all make decisions based on data, so it is mandatory You don’t have these entities, how are you going to AI, for example? ”
For Francisco Borja Escalona, ”in sectors that have narrow margins, data quality is much more important. These narrow margins make companies that work in this context, have a culture of quality of the data much greater than other types of companies.”
David Gurumeta explained that “we have clients that thanks to a more effective use, they have increased the margin of what they sell. There are tools that help improve your financial situation, simply analyzing data that show you that in a certain aspect you are working badly.”
The role of artificial intelligence
AI will have an increasingly important role in the business and evolution of companies. But for this, the data is fundamental. As Cristina Mielgo described, “AI without the data is not useful, but the data without the AI, yes. In the end you have to strive to have the data worked because it is what will allow you to do interesting things.”
For Joaquín García de France, Enterprise Sales Director of Qlik, “Decision making based on data, with the passage to AI, can lead to having to develop your own AI. We already had the Big Data boom and now we are with the AI that seems more complex and that was an element that already cost to develop it”.
For Carrefour spokesman, “the big difference is that AI has impacted the whole society and is something that does not have to pilot only from the IT area. IA modifies the relationship with customers and who knows about the relationship with customers? The client’s area. And it is the one that would have to decide, not it. Thus with the rest of the organization’s departments”
Finally Esperanza Sánchez explained that “the AI helps the analytics, is throughout the chain of the analytics, but I think it is important to hook it with the responsible AI, and this is a point that you have to take into account already the one that has a long way to go. It is that the income that currently produces you are not so relevant. ”
