Europe needs a data-driven economy - ten ways to achieve it


Picture of Elena Alfaro Martinez
Elena Alfaro Martinez

Global Head of Data & Advanced Analytics, Client Solutions at BBVA and 2013 European Young Leader (EYL40)

How should Europe’s digital skills, labour market and regulatory framework evolve?

Elena Alfaro Martinez is Chief Executive Officer of BBVA Data & Analytics and European Young Leader (EYL40)

The policymaking implications of the so-called 4th Industrial Revolution – the fusion of technologies that is blurring the lines between the physical, digital and biological spheres – are hard to measure.

What steps must we take to enhance transatlantic cooperation? How should Europe’s digital skills, labour market and regulatory framework evolve? And what must we do to encourage this change?

The success of digital companies is based on how they use data to create and improve services. Their products are data engines or algorithms surrounded by a great customer experience. These algorithms are fuelled by data in an iterative process: the more customers they have, the better their algorithms get. This continuous learning circle makes the companies’ products better and better.

Amazon is a prime example of a digital success story. It may seem that their success is based on selling their own products, together with those of other retailers, in a logistically smart way. But it was the company’s algorithm, recommending what customers may be interested in buying next, that made sales grow. Amazon keeps evolving its algorithm and has started to offer loans to its retailers. A new business model is born, thanks to digitalisation.

Digital means data-driven: not only for digital native companies, but for any company or sector that wants to survive

Another example is Netflix. You might imagine you log on to see movies or series that you want to watch, but the truth is that 85% of the content people watch is based on the suggestions made by the company’s recommendation engine.

LinkedIn, with its ‘people you may know’ algorithm, has made its networks grow at a faster pace than ever before. Again, sets of algorithms are driving successful businesses.

So, from my point of view, digital means data-driven: not only for digital native companies, but for any company or sector that wants to survive into the near future. Data-driven, in a nutshell, means using data either to support decision-making or eliminate it through process automation. Every company should now consider how they use data engines in their products and processes. As your business becomes data-driven, transactions costs tend to zero and virtually anyone can play in your field.

But to allow the data-driven economy flourish in Europe, we need to deal with data innovation and data protection in a coordinated way, without giving up either of the two.

There are ten aspects that I think require particular focus:

1. Data literacy for citizens: today we have a situation where people give away their data without control but at the same time complain about data use that might be beneficial for the societies, like investigating health data.

2. Transparency: there is a need for more transparency from companies and governments in how they use data. This should be promoted and seen as a business advantage, and not just a subject for legal compliance.

3. Data security research coordination: we need global standards that guarantee protection against cybercrime, such as using blockchain technologies for distributed identity and data management.

4. Data flow and data storage: a good effort has been made with the European Union’s free data flow initiative, but still we experience many delays when using cloud storage and cloud tools.

5. Algorithm protection and interpretability: investments in algorithm development are high and the companies should be able to decide whether they want to protect them or open them up. Interpretability of algorithms is also mandatory in the EU’s General Data Protection Regulation (GDPR) but further discussions are needed so that the industries can work on explaining complex models that work better than the traditional ones.

6. The use of anonymised and aggregated data: there are many opportunities in the use of this kind of non-personal data, both for companies and for society as a whole. However, it is still unclear in which cases using this type of data is allowed.

7. Promoting open data policies: this is essential, and not only for the public sector. Today a company that opens its data faces many more risks than rewards. This is why only a few companies are actually doing this.

8. Data portability: the right to data portability in all sectors is a way to promote fair competition and innovation in data services. Data portability will be mandatory in 2018 for the financial sector according to the Directive on payment services, but not for other sectors, although the GDPR introduces it as an important aspect of data innovation.

9. Harmonisation of data laws: this should take place across the EU so that digital businesses can operate in all of them without frontiers.

10. Artificial intelligence: we need to examine the impact of AI on labour markets and what we can do to help them adapt as fast as possible.
This list is far from exhaustive, but it includes several regulatory, cultural and educational factors that, in my view, need to be considered by the EU, its member states and the companies if Europe is to make the most of the opportunities presented by the 4th Industrial Revolution.

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