In Arthur Conan Doyle’s book “A Scandal in Bohemia”, Holmes refers to the misconception of impulsive actions arguing that “It is a capital mistake to theorise before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.” 

The increasing digitalisation in all aspects of our lives has resulted in the production of a plethora of data. The amounts of information produced everyday are growing exponentially and allow us to create theories for interpreting every simple or complex fact. At the same time, a brand new terminology has entered into our everyday life.

Big data refers to large amounts of data produced with high velocity from a number of sources of different types. Big data analytics aim at the identification of efficiencies applicable to a wide range of sectors, leading to innovative new products and services, greater competiveness and, in turn, economic growth. Data science, a very popular term as well, offers an umbrella term describing the interdisciplinary field of all the processes and systems extracting knowledge and insights from data.

At policy level, the October 2013 European Council’s conclusions focused on digital economy, innovation and services as drivers of growth and job openings; while it called for action in the provision of a framework for a single market in big data and cloud computing[i]. In 2014 the European Commission respectively adopted a new strategy promoting the data-driven economy in the EU.

How Big Data affect the economy?

Source: European Commission, Final results of the European Data Market study measuring the size and trends of the EU data economy

Big data applications can foster management and resources efficiency for both the public and private sector. In fact, recent studies suggest that companies that adopt big data analytics can increase their productivity by 5% to 10% in comparison with companies that do not[ii].

Big data are expected to have a remarkable impact on the growth of the economy. In particular, the EU economy is expected by 2020 to grow by 1.9%[iii] thanks to big and open data. According to the McKinsey Global Institute, in the US by 2020, big data analytics will foster an accumulative GDP increase of 325 billion dollars just in retail and manufacturing. Nevertheless, to achieve economic value through the massive amount of data a new way of thinking, certain skills sets and operating models are required.

Big data: the new driver in job opportunities

Big data are expected to bring about significant new job opportunities. Along with cloud technology they have been characterised by World Economic Forum as the two main drivers of change in the employment landscape, with particularly strong impact on Information and Communication Technology, Financial Services and Professional Services[iv].The European Commission suggests that 100,000 new data-related jobs will be created in Europe by 2020[v]. Hence, there are huge opportunities to be deployed from the digitalisation of European industries[vi]. In the US, a shortage of 190,000 data scientists, and 1.5 million managers and analysts skilled enough to extract meaningful insights from the big data overflow are expected for 2018[vii]

The industries which will mostly be affected by the new era of data revolution in terms of change in the context of work, increasing productivity, and job growth include Insurance and Financial Services, Wholesale and Retail Trade, Real Estate and Professional Services, Manufacturing and Mining, Healthcare and Telecommunications. In fact, according to Cedefop’ s employment forecast[viii], between 2015 and 2025, the industries of Insurance and Financial Services and Real Estate and Professional Services sectors will experience the highest employment growth for all the Member States.

Developing the new skills set

The skills implications for the EU are manifold: the need for data workers can be described as a pyramid, with a substantial portion of “lower end” vacancies (related to data clearing and data quality), narrowing up to smaller segments of more focused roles and culminating in the major role of chief data officer. There is a new range of skills that need to be adopted alongside with data-centric operating models for employees to adapt to the labour market’s needs. The required skills regard several technical disciplines: IT-related, data manipulation, statistics and real-time analytics, business analytics, visualisation etc. For example see the Skills Panorama Analytical Highlight for ICT technicians[ix].

To overcome foreseen skill shortages as well as skill gaps, more forthcoming graduates need to be attracted and trained to data-relevant disciplines. Higher education should then play a critical role in cultivating the more sophisticated skills following a data science domain. In fact, there is a burst of new Bachelor and Master programmes in either business analytics or data science at various universities across Europe; extra data science courses have been also added in existing degrees such as statistics/business/economics/law, expanding rapidly in the past three years.

"I think data culture will continue to grow, even among people who aren't data scientists. This means that within lots of companies, you will begin to see people whose job titles don't say "data scientist," but they will be doing very similar things. I do believe that data gives people the power to make better decisions, so the more people who have access to it, the better."

Hiraly Mason - Data scientist, Founder of technology start-up Fast Forward Labs

At the same time, the data culture is been spread among people whose job is not dedicated to data science but have access to data for their daily decisions. However, in 2015, 37% of the EU labour force had an insufficient level of digital skills while 13% had no digital skills and was not using the internet at all[x]. A first step towards developing this new skillset would be for schools to provide basic data-related skills to younger people; while adult training opportunities can broaden learners’ understanding of data handling for everyday life. For active employees, there is a surmounting need for training on data-relevant skills from in–company trainers or external providers.

“Data! Data! Data!” Holmes cried impatiently. “I can’t make bricks without clay.”

The Adventure of the Speckled Band

 

References


[i] European Commission, (2014), Communication on data-driven economy

[ii] European Parliament, Think Tank, (2016),  Big data and data analytics

[iii] European Commission, (2014), Fact Sheet Data cPPP

[v] European Commission, (2014), Press Release

[vi] The European Data Science Academy is an EU Horizon 2020 funded program providing useful information related to the skills requirements and job openings in this field.

[viii] Find more about the Cedefop Skills Forecast here

[ix] Skills Panorama, (2016), ICT technicians: skills opportunities and challenges. Analytical highlights series. Available at http://skillspanorama.cedefop.europa.eu/en/analytical_highligths/ict-technicians-skills-opportunities-and-challenges

[x] European Commission, (2016), Commission Staff Working Document, Europe's Digital Progress Report 2016, Brussels