The boon of new technologies to those capable of navigating the sea of big data is a huge mass of information from a multitude of sources, ranging from statistics bureaux to public authorities, delivered via the internet. Indeed, even the most mundane details available on social media, if properly analyzed, could become a valuable tool for generating GDP and employment according to Euro Beinat. An expert in this field, Beinat, in the following interview with the Aspen Italia website team, conveys his firm belief that data science is capable of improving the efficiency of the some of the most important sectors of the Italian economy, starting with manufacturing and tourism.
How far has Italy progressed in the collection and use of big data? Rather than big data, I prefer to speak of data science, which is a vast field not confined to any particular geographical area and capable of yielding huge competitive advantages for those with the ability, skills and tools to exploit the data in question. In Italy, we see some activity in this field by firms with an international profile, forced as they are to use these tools to remain competitive, while on the institutional front we see a number of limitations. In general, there are no major physical infrastructure problems: the optimal use of such data is related to the capacity for innovation. Italy is a few steps behind the United States and other countries in Northern Europe in this regard, but this is not necessarily bad news. Indeed, there are still plenty of opportunities to exploit.
Can you give us some examples? I have worked on what is one of the key sectors for the Italian economy with my research group at the University of Salzburg – namely, tourism. It is an industry of particular interest not just because it accounts for a sizeable chunk of Italian GDP – in the order of 10% – but also because it is marked by fragmentation of supply and a lack of coordination, making efficiency gains a very attractive prospect. Many urban areas, for instance, continue to be managed with fragmented data which becomes available months or years after the phenomenon it describes, is too aggregated to be useful, and almost never predicts the future. It only describes the past and therefore does not ensure adequate visibility for flows of what we call the transient tourist population. In the absence of detail on the phenomenon they seek to influence, and without evidence that such influence is effective, tourism promotional strategies often prove useless. It is therefore better to place a stronger emphasis on analyzing available data and utilizing new data. Indeed, in such a scenario of structural inefficiency, even a small improvement could translate into a GDP increase and more jobs.
What areas could Italy invest in to improve the efficiency of its tourism sector? The study we conducted in Salzburg, although experimental, shows that the data required to examine national tourist population flows are generally available. Through social networks, blogs, and large aggregations of telephone and banking data, we were able to piece together not only where tourists go and what they visit, but also what they subsequently say of their experiences in Italy. Pulling together such data is no simple feat, but nor does it require prohibitively high levels of investment, and it can be accomplished within a short time.
In addition to tourism, are there other areas that could benefit from the use of data science? Given the pervasiveness of technology, there is a wide range of areas to which data analysis could be applied. Aside from tourism, however, the management and control of industrial sectors could reap the greatest benefits, with positive effects on distribution, but also on manufacturing. In fact, data analysis enables significant improvements in logistics, an area in which the large conglomerates of the sector are developing predictive models that allow business to be structured in a forward-looking rather than backward-looking manner. Furthermore, another area of great interest is the health sector. In this case, however, certain advanced applications – such as the implantation into the human body of devices that transmit patient data – are giving rise to legal disputes over who owns the data.
So are there risks associated with the use of this huge mass of data? If so, how can they be reduced? There are risks and we must not forget that the development of data science does not just involve technology, but also rules. Unfortunately, however, privacy is an issue that is still taken too lightly and superficially. During a course on data ethics that I run in Salzburg, I usually give my students a questionnaire. The vast majority of them are concerned about the use made of personal data, but very few are able to say what sensitive data they have passed on and who holds it. Truth be known, this is made even more difficult by data protection procedures, whereby data is collected by certain people but then aggregated and disseminated by others, by means of a chain that is not particularly transparent and which is difficult to control. Let’s not forget, however, that the analysis of large aggregates of data is a growing phenomenon which, although calling for caution, should not make us lose sight of the great opportunities that exist in terms of growth and innovation.
Euro Beinat is Professor of Geoinformatics and Data Science at the University of Salzburg, and is Vice President at Zebra Technologies Corporation, a listed company based in Chicago, tasked with heading up strategy for the development of Internet of Things platform technologies. As an expert in these areas, he serves as an advisor to government agencies and businesses on strategic matters and the long-term implications of the growing diffusion of the Internet of Things. He is also a member of Aspen Institute Italia’s “Italian talent abroad” group.
