The power of data to create efficient transport systems

The power of data to create efficient transport systems

The boom of the digital era and the data inherent to the nature of computers, has resulted in the creation of large volumes of data, in many places and expressed very heterogeneously. In 2011 this paradigm was named “Big Data”. It generated a lot of interest from the outset due to its contribution to gaining a better knowledge of organisations and people, to thus improve the decision making process and performance in many dimensions. Over the course of these years we have not stopped asking ourselves how it could affect our daily lives.

There are three elements that are encouraging Big Data and making its adoption exponential. Firstly, computing has become cheaper. We now have sensors and computers everywhere in our society. Secondly, the automation of society and its digitalisation. We encode an increasing number of social behaviours and expressions in objects that are connected to the Internet. And, thirdly, we live in the era of social networks. As we are more connected and communicate with one another more quickly, we produce more data.

Therefore, it is not that we now have computing abilities that we didn´t have before, but rather, we now have much more data, produced at a much greater speed, and with a variety of formats. This means that we need a new paradigm for the storage, processing and valuing of data. We have named this Big Data. The digitalisation of society, which enables us to be capable of measuring all human behaviour, has brought us a new field of possibility of working with data.

Thus, neither technology, nor the availability of data, nor the economic factor are limiting. What we need are data entrepreneurs, who are able to ask the right questions of data, and we will thus be able to contribute to business management and strategy via the extraction of intelligence and the value of data. Within the mobility sector specifically, which features in this blog, this is precisely the approach needed to be able to activate data and generate value based on them.

You will surely be wondering how we can optimise our transport systems using data. Well, basically by entering something that we did not have before: precise data on the day to day behaviour of a person. In daily life, ultimately we all end up doing the same things: we travel to work, we purchase products and services, we socialise, we consume content, etc. If I am able to understand the preferences of people for these vital events, I am naturally obtaining information that expresses a lot in order to find out where citizens in a city are and what they will do. And thus, in doing so, appropriately size the transport networks. 

Does anyone wonder why Google Maps is free? It is a very useful tool that we apparently do not pay money for. But we do pay with data. Enter into your browser in order to see everything that Google knows about you. What do you think they will use it for? Google offers us this data (on an aggregate and anonymous basis, naturally) through an API (application programming interface). And what about when we put our credit cards through a POS? The same idea: digitalized data, data that can be exploited. We also make calls, that telecom operators record. And we exchange messages on social networks and instant messaging tools, some of which are free. How do we pay for them? With the data about what we like and who we interact with. These examples, as you can imagine, are numerous and practically endless.

As we said at the beginning, the variety of the data is one of the characteristics of this paradigm of Big Data. If I am able to gather together all the data that we described in the previous paragraph, I will be able to create a model of knowledge about the mobility of citizens. If I was previously able to find out about a citizen through surveys with questions that tried to understand what they liked, I now have the finer details about their preferences and interests. Thus, not only will transport networks be efficient, but I will also be able to offer the chance to personalise the services demanded not just by that person, but by everyone who has the same profile.

The modern practice of data analysis, which is popularly and often wrongly known as “Big Data”, is based on “Data Science”. It is a decision making approach based on data that transcends traditional methods and immerses us in an era where the ability to handle data will be at the core of organisations. And, on the other hand, an era where the opportunities to provide added value will be about realising that we are not facing a paradigm that has brought tools for (only) analysing data, but rather a paradigm for beginning to look for new frameworks of action that offer more efficient answers.

Naturally, with all the above, ethics and values now need to be at the centre of decision making more than ever. Having a detailed knowledge of what citizens do as trustees of data: that is to say, only to aid them, and never taking advantage of their ignorance in relation to the data that we have obtained. 

Big Data is a paradigm that is here to stay.

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