What does data-driven mean?
Data management for efficient decision-making
The use of data by organizations to improve efficiency and drive innovation is nothing new. Since the beginning of the 20th century, companies have been incorporating data management techniques. However, new tools and technologies have emerged in the last decade, such as big data and AI, which have turned information into the most important asset for ensuring sustainable and inclusive economic growth.
What do we mean by data-driven?
Data-driven is a way of making decisions based on the analysis and interpretation of data stored from digital sources.
This methodology enables companies to make better strategic decisions as it's based on real data obtained from different business areas.
The data-driven approach offers a number of advantages to organizations, in particular the following:
Without proper training, it's not easy for company professionals to get the maximum potential from the large amounts of data they handle. Therefore, it's important to create a data-driven culture that includes the study of the technical terminology related to this discipline and the different methodological application areas.
Data-driven decision-making (DDDM) is defined as the use of continuously optimized data, analysis, and software to guide strategic business decisions. In order for this methodology to be successful, this source of information must be made available to all members of the organization so that they can make the right decisions at any given moment.
Data-driven design is the use of data analysis in the design and development of products and services. In general, it consists of shaping data regarding what the goals of the business and the digital environments are (apps or websites), who the users are, and how the strategy will be measured to design successful services and user experiences (UX). By using data analysis in the design process, it allows us to create tailored, more efficient, and sustainable products.
Data-driven companies make decisions that are always based on data with the aim of improving their agility and efficiency. These companies undergo a deep digital transformation to incorporate the necessary technologies that allow them to make the most of the data obtained from the different information sources they manage. A characteristic of these data-driven companies is their ability to capture, organize, and share information among all members of the organization, which facilitates collaborative work and innovation.
Data-driven marketing is the set of marketing decisions or strategies designed after analyzing, processing, and using the large amount of data obtained from users and their preferences. These large volumes of data are collected through interactions with consumers and are used for mapping predictions of their future behaviors. The aim of this methodology is to understand consumer habits in order to design more precise and results-oriented digital marketing initiatives. Decisions supported by big data enable companies to anticipate customer needs, mitigate risks, and offer more relevant products and personalized services.
Despite their growing digtalization, many organizations waste the large amount of data they generate, often due to lack of practical knowledge or the tools necessary to make the most of it. Therefore, it's important to develop a data culture or data-driven mindset that is cross-company in order to become a data-driven company that places data analysis at the center of its decisions. A data-driven mindset doesn't exclusively consist of the incorporation of new digital technologies. It involves the creation of a data architecture that articulates the entire value chain, from the operating systems to the management solutions, analysis tools, and people and culture of the company.
"Our AI products enable us to promote a data-driven culture."
Oscar CampilloExpert in digital technologies
The data-driven economy in Spain
Over the last 20 years, successive Spanish governments have been developing digital advancement programs, in line with European digital agendas, which have provided a framework for promoting a process of business and technological ecosystem and infrastructure deployment. As such, a major public and private investment effort in this area has been led by the Info XXI Plan, the España.es Program, the Avanza Plan, the España Digital 2025 agenda, and the Spanish R&D&I Strategy in Artificial Intelligence in order to boost Spain's leadership in the data economy and digital transformation.
At Repsol, in our commitment to the energy transition and sustainability, we are opting for digitalization to achieve our goal of net zero emissions by 2050. We rely on different solutions such as big data, AI, the internet of things (IoT), omnichannel, robotization, digital twins, and blockchain technology to design new digital products and services that bring added value to our customers.
While focusing on this goal, we have transformed ourselves into a data-driven company that uses the most advanced technology to offer a personalized and sustainable offering based on data. Therefore, our Data&Analytics hub has developed ARiA, a big data and artificial intelligence cloud platform that centralizes all of the company's data to develop analytical models and algorithms that improve processes and decision-making. One of the advantages of this tool is that everyone can use it autonomously, whether or not they have analytical knowledge, and access more valuable information
ARiA has promoted hundreds of digital initiatives that are being carried out in different business areas such as RAIP (Repsol AI Products), a catalog of AI modular solutions that allows us to develop an true data-driven culture throughout the entire company.