 Hello, how are you doing? Hey, we told this what's going to be interactive. Hello. How are you doing? Now we will use the laser points for interaction. I hope you are all having a great experience during today's event, and I hope you are getting the best out of big things. This is the last session and we will try to make it a little bit more different, a little bit more fun, a little bit more interactive. First of all, thank you very much to Paradigma, which gave us the opportunity to come here and give this speech to you. And thank you very much to all the sponsors that facilitate all these things happening. But also, and that's very important, thank you very much to you all. I don't know if you realize, but you represent the big data community. And as you will see during this presentation, being the big data community is a very relevant thing in the Spanish continent, and I presume worldwide. But before starting, let me present myself. I am Carlos Bellarain, head of the development, service development department at Minsai, and you will say, what is service development? Service development is about adding a layer of service among all the solutions that Minsai is providing to the clients. But today we are not going to speak about service layers, we are going to speak about data. But I'm sorry, I don't know anything about data. The fact is that I know anything about data. That's why here is Nacho, which is the one that knows about data. Nacho, may you present yourself? Thank you. My name is Nacho Álvaro, I am the responsible of the data and analytics business unit at Minsai, and today I'm the voice of the expert. Great, so he's the one that's going to speak. Okay, any questions to him? Okay, and today we're going to present this. We're going to present the conclusions of this report. That's why I'm here. I'm here because I've been leading this effort within Minsai. We have been spending some time in developing this report. This report is about trying to understand how are the big corporations tackling big data? How are they approaching, what are they doing? In which initiatives they are having success, in which initiatives they are failing? And perhaps what's more important, how are they approaching the big data strategies, what they are using them for? Some data. We have interviewed above 100 companies. We have spent more than six months doing the report. The companies that are in this report represent about 20% of the Spanish economy. And we have analyzed in-depth with them all their investments in big data, order tactics, order strategies. So perhaps we are the company in Spain that have a more global vision about how big corporations are approaching big data. But before telling you the conclusions of the report, why don't you tell us what's the methodology we have followed? Good. When Carlos presented us this challenge, because it was kind of a challenge, we organized a small group of very multidisciplinary and talented people. So we can cover all the different areas of our report, of our research. We divided the research in three main blocks, digital enablers, those basic capabilities in order to be prepared to be data-driven, such as strategy, governance, talents and culture, and technology. We have another second part that we call intelligence, which are those advanced skills, let's say, to manage data life cycle. Listening, capturing information from any source and any format. Learning, transform all this raw data into information and actioning, which is transform the information into decision. Both human-based decision or fully automated decision. And the last part of the research is what we call a digital dimension, which is how to apply all these capabilities to different areas of the business, innovation, customers, operations and security. So through this report, you can find how are the Spanish corporations attacking all these issues. How much money they are investing on listening, on learning, on acting, what their structures they are building, what's the technology they are building, how much money they are investing in culture, in talent, in systems, in organization, which are the main use cases they are developing, which ones they are failing, which ones they are having success, all within here. This is a 150 pages report. We have 30 minutes. It's going to be boring if just I come here and tell you the conclusions. So let's make it a little bit more interactive. Let's play a game. This is the last session. Let's play a game all together. And for playing this game, I need you to be interact. So take your laser points and let's try to check if you are able to aim here. At my report, come on, here are only three or four laser points. I can see many. Let's try another thing. Can you aim to systematic? The blue zone. Right. It's working. So now we know how to vote. So the game is going to work this way. I'm going to present different approaches for three topics. All the Spanish corporations are classified in these three different approaches. Okay. But before telling you what are the corporations doing, you are going to tell me which is the best solution. You are the big data community. So you are the opinion, the knowledge of the big data community. And you are going to tell which is the right answer. And then we will compare it with the reality of the Spanish market to see what comes. Okay. Let's play the game. Yes. Okay. Let's go for the first. No. Let's go for the first. Yes. Let's go for the first. The key. So first question. How to optimize a force to generate greater business impact through data driven? Wow. What a question. Let's see which are the alternatives. During our work, we have found the Spanish corporations investing money in very different approaches. There are companies that are not invested much money on the enablers. That means they are not investing money on the technology, nor on the talent, nor on the organization or building the study. They are neither investing money on the intelligence. That means they are not investing money in collecting data or making the analysis. But they are investing their money in the business dimension. So they are mostly investing all the money on the use cases directly without enabling or building the intelligence behind. And there is a group of Spanish corporations in Group A. There is a second group of corporations, which is Group B, establish the basis to perform the business. Are those corporations that are investing first the money on the enablers, on getting prepared with the technology, with the systems, with the talent. Then they are investing the money on the intelligence, gathering the data, analyzing it, and only afterwards doing their best to take the usage of that investment on the business dimensions. There is a third group of companies that are investing the money on the enablers, getting prepared and directly on the use cases, for getting about, getting the data or analyzing it. Third group. And fourth group, there are some companies that are just investing the money on preparing. And they are eternally preparing themselves, building better systems which is a mass, capturing, enhancing the culture, or preparing themselves with a great study but not really doing anything. And so, the question for the big data community, which is you, which one do you think is the most adequate approach for the big corporations? It looks like it's B. Yeah, we agree? Great. So you think the big data community represented in this room thinks that the B is the adequate solution. In case the lesser bonds were broken, I made this survey to the global big data community through email over the last two weeks. And the global community also thinks that B is the adequate solution. So it's clear, you all agree, big data community in this room thinks that that's the way to approach this problem. What does it mean, I think? Well, in our opinion, this is the way to go. Establish the foundations of your strategy or your technology base or platform will help us to develop all the use cases that you will develop at the current time or in the future. So I think, in my opinion, in our opinion, it makes much sense to many organizations to act like this. Okay, this is going to be easy. If everybody agrees this is the adequate solution, I'm sure 100% of the Spanish corporations will be there. No? Let's see. Two of the Spanish corporations are following the A-path. They are not investing money in enabling anything. They are not investing money in collecting the data nor analyzing anything. But they are investing tons of money in building use cases. Without getting prepared and without the information. But they invest money on big data just on building the use cases. Only 13% of the corporations are really getting prepared and building the intelligence in order to use it. And the rest, you know, is minor. But I'm not technical. I don't understand anything about this. How can this be related? Well, in our opinion, many companies are under a lot of pressure to demonstrate results. So it's quite logical that they put the focus on use cases. The point is that maybe they are losing their bigger picture because they will end up with a list of POCs or unconnected initiatives. So they can be losing some big opportunities. Okay, great. Thanks for the participation. Let's go for the second question. Intelligence, the key to generate added value. How to invest on such capabilities? Again, four different options. Corporations in the Spanish market are following four different paths. There is a group of corporations that are investing money in collecting information. They are also investing money in analyzing that information. And they are also investing money in making the decisions with that information. That's what we call, don't be shy, put analytics at work. There is a second group of corporations that don't invest money in capturing anything. Don't invest money on analyzing anything, but they invest money on making things happen. First group, they invest money in capturing information. They invest money on analyzing only after analyzing the capture information. Then they start thinking about which should be the use cases and how to put in value that information. Third group of companies. Fourth group of companies, people that invest tons of money in capturing tons of information. Everything that we can collect, we collect it. And we have in our legs, in our computers, in our data rooms. We don't know what was the uses for that, but in the future I'm sure that's going to be critical. And they save everything and they don't do anything with that information. Fourth group of companies. Again, is your time to participate, which is the best approach for the corporations? What do you think, Carlos? Maybe the first one. I think it's A, your opinion. Many people are on C. Something between A and C. Okay, what's your insight opinion? Well, our opinion is, in this case, I would prefer. I agree with the community that maybe there are two options that may be closed. But I agree that the first option is the one to go. Okay? Why? It must be challenging to develop at the same pace your decision capabilities. While you are developing as well your listening or your learning capabilities. But it's the only way to demonstrate value and to test your decisions in the real world. The world is changing very quickly. So you may lose some feedback for your customers or from your business. If you don't activate those algorithms in the real world. Okay, so you global big data community here at the room think that A is the best option. A or C? Means I agree. Yes. Through the email, through the Shun Vive, the big data community, global big data community also agrees. Let's see what are the corporations really doing. Some emotion. Sorry to say that 50% of the corporations are choosing for strategy number B. They are not investing anything on collecting new information. They are not investing anything on making any single analysis. They are just investing some money on the decision making process. Only 9% of the companies goes for A, 22% of the companies goes for the most equilibrated strategy. What does it mean I think about these results? Well, I guess that many corporations are still using traditional business intelligence solutions and approaches to take decisions or even they are using intuition. So it's quite logical having these results. Great. Let's go for the third question. Became a data-driven organization which is the best approach. In the path to build the data-driven organizations, corporations are following completely different approach in their thinking process. Some corporations think this way. The first thing I'm going to do is I'm going to surround myself with partners that enhance my data capabilities. One, having built this digital ecosystem, they build the adequate technology. Afterwards, they build a governance system in order to ensure that everything was perfect and then they start with all these capabilities to work on the use cases. Approach number one. Second approach. Some companies think, no, the adequate approach is let's first think on the client. What does the client needs? What does the client want? Let's understand the client deeply. And once we understand the client and once we understand what can we deliver to them, let's think about the operations. How can we enhance the operations to deliver that service to the client? And therefore, let's securitize those process and let's innovate with all the data in order to provide the best service to the client. Approach number two. Approach number three. This is the core transform and this is about data. So they say, hey, let's think about data. The first thing is to ensure that the data is protected, that we understand which is the adequate data. It's about building an adequate data governance strategy within the company. Then we build a data culture because we can set the rules. We need everybody, all employees to understand the value data. Third, then we have to add the adequate technology in order to ensure this culture. And fourth, we make all the analysis and the governance in order to ensure that they put in value this data. So the third approach is everything goes around the data and the value behind the data. Fourth approach. The followers. The ones that say, hey, I don't want to say anything to anyone. I just securitize myself and I look and I wait. And I don't invest a single euro on anything because everybody's speaking about big data, but everybody's investing tons of money on this and losing tons of money. I don't have much money. I just wait. And once someone comes here and demonstrates me that there is a profitable investment, then I do it. So it's about waiting and seeing. Wait and see. And I will decide once I go for sure. So followers. So big data community, what do you think is the most adequate approach? Can you say something, Carlos? Yes, I can say something. No one is a follower. Thank you very much. The only clear thing here is the follower strategy is not the adequate strategy. Let's check what has through the survive, what's the opinion of the global big data community? More like you. Everybody say the only thing we have clear is being a follower is not adequate. If big data is about building a competitive advantage, we have to move forward. We have to step on top of the others. What's the insight opinion about this? Well, I can see that the community is divided into these three top options. But if I have to choose one, I must confess that the visionary one is the one I will choose. Why? Well, I think that we think that maybe competing today in this big data world must be very complex. So you will need the help of many companies or many partners, the startup ecosystem, and you can also collaborate with other industries. So you build up with this digital ecosystem while you are concentrating on transforming your business, your core business, where you probably are the master of what you want to do. At this time, I presume corporations should be somewhere between A, B, and C. I hope. I'm not sure. I'm sorry. Almost half of the Spanish corporations are just followers explicitly waiting for what are the others doing. That means they don't recognize any competitive advantage. They just wait for the others to invest, to give a head, and to go forward. What do we think about this? Well, our research covers more than 100 enterprises. So it's logical to have some of them, the big ones, the visionaries acting as the leaders. And many other companies just seeing what is going on with these companies that are more advanced. In fact, one of the outcomes of our research is some industries are more advanced, such as telco or banking. So I assume that many other sectors, they are just looking and waiting to learn something from this success or the failure of the others. Okay. That was about with the game. I hope you have learned one thing. I hope you have learned that despite we do think as technicians, we do think that there is a right approach for the problems. Corporations has a completely different point of view. The reality is absolutely different from our reality. And I think that is the main conclusion or one of the main conclusions of the report we have been doing. But having a global look at the report, which could be the great highlights we have come while doing it? Well, it's clear that the main highlight is that companies, Spanish companies are still far away of being data driven. For instance, they are applying intelligence and data in the more obvious areas of their business, such as security, fraud or compliance. But they are not applying intelligence in some core capabilities, such as customer relationship. Only less than 20% of the companies are using analytics to monitor customer experience, which is one of their priorities. Only regarding intelligence, only 12% of the companies enrich their internal vision with external data, which seems amazing for me because there are a lot of information in this digital world that may be missing. And even if they can capture complex data and complex and social data, only a fraction of them are using to take decisions. But it's not all bad news. I guess the good news is that almost any company, 56% of the companies has already a strategy regarding data. And those companies that are later on this evolution path don't have a strategy, but they are thinking on putting this big data analytics, AI or machine learning on top of their priorities for these coming years. Okay, that's about it on the report. There is one single additional conclusion we have come while building this report. There is, in fact, only one thing on which all the 100 corporations have agreed on. 108 corporations we have interviewed and 108 corporations agree on which is the biggest problem they face in order to develop their big data strategies. And that problem, all of them agree, is talent. To capture the talented people, to capture the adequate people in order to develop their strategies is the most critical point in order to have success in building any approach. So the good thing here is that you, big data community, you are the critical ones in this equation. So congratulations. You are critical. Thank you very much. Thank you.