Creating Value from Data

Interview with Prof. Marco Brambilla, EIT Digital Professional School, Politechnico di Milano

The amount of data is growing as we speak, creating more opportunities for medium-sized and large businesses and more risks for small businesses. ‘Companies need to innovate their business models’, says Marco Brambilla, Professor of Data Engineering and the Data Science Lab Leader at Politecnico di Milano. Marco, who also teaches the EIT Digital professional course, Data Science for Business Innovation, further stresses that ‘business is about who has the data and who doesn't.’ 

Data Science Lab @ Politecnico di Milano

The Data Science Lab of Politecnico di Milano works on data sciences projects with special attention to application-oriented problems. These can be physical industry-oriented business challenges like industry 4.0, which relate to industrial plant monitoring and anomaly detections, or smaller scale specific applications, such as studying brand reputation online.  

In addition, the lab has a share of problems coming from industrial companies via joint projects or consultancy activities, researching techniques and methods for optimising language models. In a recent Large-Scale Analysis of Online Conversation about vaccines before COVID-19, Brambilla investigated the impact of disinformation on vaccination with his team. This research found a correlation between the dynamics of social media shares on fake, unreliable, partial, or biased news about vaccination and vaccination trends. The researchers also try to detect how to tackle fake accounts, fake bots, and social media bots that generate misinformation. 

Most of the projects the lab conducts come from European or national public institutions or research grants. For example, Brambilla's team is a research partner within the European research consortium PERISCOPE, running from November 2020 until October 2023, which investigates the socio-economic and behavioural impacts of the COVID-19 pandemic.

Data and the new business opportunities

As the volume of data keeps growing, the Global DataSphere Forecast of market intelligence provider IDC estimates that the amount of data created over the next three years will exceed the one created over the past 30 years. Brambilla foresees that this growth can help society and business in the long term by triggering a quicker reaction to changes and optimisation problems. ‘We already started to see automatic notification of changes in services. For instance, at the travel level, you get automatically redirected if disruptions happen. Notifications could come from crowdsourced information, meaning that people detect disruptions and notify a system. When this becomes a standard process, it becomes another source of information and enters the processing of data science flow.’ 

More data creates new business opportunities and innovations. ‘Companies will be able to exploit data integration, data availability and improve a lot on the level of cost of cross-selling, cross-marketing, or cross-platform devices. Companies start collecting information on customers' behaviour and use it to improve the customer experience on a large scale. As a result, businesses consistently increase their scope of action towards and with the users.’ 

Data Divide

Small companies have difficulties keeping the pace of Data Science developments. This is what Brambilla calls the Data Divide. ‘It is the modern evolution of the digital divide. Data divide is about who has the data and who doesn't, who can or cannot access or process it. This divide is critical, even at a societal and economic level. It will impact a lot, like market models and so on. A large quantity of data within large companies such as Amazon creates huge potential business opportunities.  

This is challenging as small businesses may not be able to keep up with this pace and assuming that smaller businesses have the power to leverage this significantly, is too optimistic. In the long run, the quantitative trend may kill all the small competitors.’

Small business strategy

The challenge for small businesses is at the strategic level. ‘Small businesses could try to benefit as much as possible by using some existing platforms applied to their small amount of data and see what they can get out of it.  

Another way to go could be to build a federation of small businesses. So, the data is not just collected by one hairdresser or one bakery but within a network of small businesses. This network shares information for optimising the quality of life and business in the cities.’ 

A third option Brambilla suggests is creating alliances between small and big entities to counteract the dynamics of big companies pushing small companies out of business. Building mechanisms for creating partnerships or cooperation between small and big entities could work if both get benefits. For instance, Italy installed a regulation for large malls to be closed on the weekends. Consequently, people somehow rediscovered the advantage of small shops in the city centres. An alliance between big and small businesses could leverage a combined data-driven valuation. It is impossible to compete in terms of pricing with the big players. You need to use the value you have.’ 

That brings up another option: working more closely together in the value chain. ‘One could try to integrate the provider and clients in one value chain. Small stores buy things from big warehouses or even directly from the producer. A pasta producer or car producer might be interested in building a stronger alliance with their sales channel and maybe deliver some type of data-driven platforms along the pipeline.’ 

(Mis)use of data

‘As the growth is not going to stop’, says Brambilla, the data collection practices will just get more and more widespread and cover all aspects of life around us. We are going to see more refined data descriptions for each person, object, and business. Our life will be described by the data we produce. And that opens possibilities. Today, we can capture data all the time from all kinds of sources. We can analyse it and transform it into actionable values, for instance, to improve business processes. As a result, data science can exploit benefits for individuals and society.  

Nevertheless, there are also risks in misusing data, like the one we see in identity theft. Data Science should therefore also be about preventing or fighting against possible misuse of data.’ 

Be ready for change

All companies should rethink their strategies. Staying ignorant of the impact of data science on your business is not an option. ‘You become marginal on the market. You must be ready for a change. If you want to scale up your business, you need a data-driven mindset focused on the business objective. This could be “I want to become more cost effective” or “I want to become more efficient in reaching out to our customers”.  

The EIT Digital course Data Science for Business Innovation has this very objective, to demonstrate how to implement change in your data strategy to meet your business and customer needs.’

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