Data has become a fundamental tool in decision making for big businesses. Data analysis, along with the entire process that moves it and shapes it, has become a strategic asset that helps improve and evolve large organizations 

Publicada el 5 de Julio de 2019

I firmly believe in the power of data. I believe in its unquestionable impact and influence on the strategic decision-making process, when based on empirical evidence. But I question its influence on business transformation when more importance is attached to data per se than to the processes for guiding and governing it and transforming it into knowledge. 

There are success stories that show how brave companies understood data as a strategic asset and created the necessary ecosystem to ensure that it was governed and guided to its full extent. These are companies that revolutionized their industries, turning conventional wisdom on its head and leaving other companies that were incapable of seeing that everything had changed in the dust. 

Netflix is a case in point. It’s obviously a classic, but it’s nonetheless a clear case of how a company that was in the business of renting DVDs by mail saw that the conditions were ripe (digital screens, bandwidth, streaming technology) to transform the TV industry, and it became a giant in the world communications industry. All of this started from an age-old principle that is deceptively simple: “You must understand your customers.” 

 An image of the head of a virtual human being with many points plotted as a data union. City background

think that the key to Netflix’s success was not only its ability to acquire, integrate, and analyze all sorts of data related to how its customers use its platform. They succeeded by taking data as the starting point, focusing on governing it, and developing processes to turn it into knowledge. I can’t ignore its latest move into interactive content, where the user chooses the plot of a chapter in a series. That is simply brilliant. Did they create this interactive content to satisfy the user, or is it a way of extracting more data from the user while entertaining them at the same time? I have no doubt what the answer is: it is a new way of gaining deeper insights into user tastes and preferences focused on ad hoc content creation. 

This dynamic strategy denotes a high degree of maturity

During my career, I have had the good fortune to work in a range of industries. In recent years, my current company, Ferrovial Services — which operates in infrastructure and services for cities — has developed a range of projects and initiatives in the area of data analytics, some based on traditional statistical methods, others on new analytical techniques such as artificial intelligenceAll these endeavors had a clear goal: to promote data-based management, so as to reduce energy costs  in building maintenanceunderstand the dynamics of a city through urban data, optimize routes and propose dynamic approaches to waste collection, keep our workers safe, perform predictive maintenance for assets, and use image recognition techniques to analyze the status of critical infrastructures.

Two smartphones found simulate exchanging large amounts of data. A city in the background and two hands that support them

Generally, based on my experience, I believe that if you want to incorporate data-based management into a company, you have to start with a diagnosis. In particular, a company that does not have data in its DNA must calibrate its transformation in terms of its actual ability to adopt and change. It’s like the process by which a child moves from solving basic jigsaw puzzles up to completing ones with thousands of pieces: 

When a 3-year-old starts with jigsaws, they use a trial and error method that involves trying out every single piece until they find one that fits. Little by little, they develop simple strategies that enable them to group pieces by color or picture and, in this way, they can build fragments of the puzzle — little victories that keep up their morale and enable them to advance towards new challenges. 

As the puzzles become more complex, the old techniques no longer work. There comes a time when new strategies are needed, based on more complex methodologies. This happens because, as the child plays with jigsaws, they mature cognitively. They develop problem-solving abilities, learn to draw up strategies and follow them, and acquire spatial and visual skills. 

  • The key to success:being able to identify the child’s degree of maturity throughout the process of playing and learning. This way, when we see the need, we can introduce the most appropriate techniques and methodologies for addressing more complex challenges so that the child can move toward the final goal: having fun and finishing the puzzle. 
  • Learning: if we get ahead of ourselves and adopt a strategy that is too advanced, that curtails the learning mechanisms and demoralizes the child, eliminating the dimension of play and fun. On the other hand, if we are not capable of gradually elevating the maturity level of the child’s game with new techniques and methodologies, there will come a time when they cannot solve complex puzzles and, as a result, will feel frustrated and lose interest in the game. 

Image of a puzzle piece fitting in with the rest, simulating the learning that big data implies

An organization must ensure that it constructs and uses processes and methodologies for guiding and governing data that are in line with its degree of maturity. Ferrovial Services, a multinational company, is addressing the challenges arising from the complexity and variety of data in its business units and the services it operates. In recent years, we have acquired skills and honed our abilities, supported by implementing scalable, sustainable data analytics projects.  

If we extend the previous analogy, we face a global, multi-dimensional jigsaw puzzle. To this end, we have equipped ourselves with a strategic data plan and a program to promote data-based management of the business. Ultimately, the goal is to ensure that, at all times, appropriate processes are applied to guide the business on this journey, which seeks to transform data into knowledge, and that knowledge into decisions. Decisions that are better informed, and often more judicious. 

Prior experience in industries where data-based knowledge is already a reality shows that there is no one formula, no predefined path. This shows us the power of data to its fullest extent. A power that has transformed industries while sinking companies that failed to appreciate it. A power that must be used and cannot be ignored. A power that will exist only if the right processes, at any given time, are created to guide and manage data. 

 

Written by Sergio San Martín the 5 de Julio de 2019

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