The Information and Communications Technology (ICT) sector is directly responsible for 5 % of European GDP, with a market value
of 660 billion euros annually; it also contributes significantly to overall productivity growth (20 % directly from the ICT sector and 30 % from ICT investments). Big data solutions can contribute to increase European competitiveness by delivering value adding tools, applications, and services. One estimate for 2020 puts the potential of big and open data to improve the European GDP by 1.9 %, an equivalent of one full year of economic growth in the EU (Buchholtz et al. 2014). International Data Corporation (IDC) forecasts that the big data technology and services market will grow at a 27 % compound annual growth rate (CAGR) to $32.4 billion through 2017 (Vesset et al. 2013).
The European Commission launched in March 2010 the Europe 2020 Strategy (European Commission 2010) to exit the crisis and prepare the EU economy for the next challenges in terms of productivity, economy, and social cohesion. The Digital Agenda
for Europe is one of the seven flagship initiatives of the Europe 2020 Strategy; it defines the key enabling role that the use of ICT will have to play if Europe wants to succeed in its ambitions for 2020. The paramount importance of big data was recognized by including a specific topic in the Digital Agenda to get maximum benefit from existing data and specifically the need to open up public data resources for re-use. As then EU Commissioner Kroes stated, “Big Data is the new Oil” that can be managed, manipulated, and used like never before thanks to high-performance digital tools, making big data the fuel for innovation.
1.3.1 Transformation of Industry Sectors
The potential for big data is expected to impact all sectors, from healthcare to media, from energy to retail (Manyika et al. 2011). The positive transformational potential has already been identified in a number of key sectors.
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Healthcare: In the early twenty-first century, Europe is an ageing society that places significant demands on its healthcare
infrastructure. There is an urgent need for improvement in efficiency of the current healthcare system to make it more sustainable. The application of big data has significant potential in the sector with estimated savings in expenditure at 90 billion euros from national healthcare budgets in the EU (Manyika et al. 2011). Clinical applications of big data range from comparative effectiveness research where the clinical and financial effectiveness of interventions is compared to the next generation of clinical decision support systems that make use of comprehensive heterogeneous health datasets as well as advanced analytics of clinical operations. Healthcare R&D applications include predictive modelling, statistical tools, and algorithms to improve clinical trial design, personalized medicine, and analysing disease patterns.
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Public Sector: Europe’s public sector
accounts for almost half of GDP and can benefit significantly from big data to gain efficiency in administrative processes. Big data could reduce the costs of administrative activities by 15–20 %, creating the equivalent of 150 billion euros to 300 billion euros in new value (OECD 2013). Potential benefits in the public sector include improved transparency via open government and open data
, improved public procurement, enhanced allocation of funding into programmes, higher quality services, increased public sector accountability, and a better-informed citizen. Crucial to the future is the definition of policies to share data across government agencies and to inform citizens about the trade-offs between the privacy and security risks of sharing data
and the benefits they can gain. Big data will also change the relationship between citizens and government by empowering citizens to understand political and social issues in new transparent ways, enabling them to engage with local, regional, national, and global issues through participation.
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Finance and Insurance
: There are a number of ways for financial service companies to achieve business advantages by mining and analysing data. These include enhanced retail customer service, detection of fraud, and improvement of operational efficiencies. Big data can be used to identify exposure in real time across a range of sophisticated financial instruments like derivatives. Predictive analysis of both internal and external data results in better, proactive management of a wide range of issues from credit and operational risk (e.g. fraud and reputational risk) to customer loyalty and profitability. A challenge for the financial sector is how to use the breadth and depth of data available to satisfy more demanding regulators while also providing personalized services for their customers.
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Telecom, Media, and Entertainment: Big data analysis and visualization techniques can enable the effective discovery and delivery of media content enabling users to dynamically interact with new media and content across multiple platforms. The domain of personal location data offers the potential for new value creation with applications, including location-based content delivery for individuals, smart personalized content routing, automotive telematics, mobile location-based services, and geo-targeted advertising.
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Retail
: Significant opportunities for using big data technologies reside in the interactions between retailers and consumers
. Data is playing an increasing role as consumers search, research, compare, buy, and obtain support online and the products sold by retailers increasingly generate their own data footprints. Big data can increase productivity and efficiency resulting in a potential 60 % increase in retailers’ operating margins (Manyika et al. 2011). Big data can impact retail in areas such as marketing: cross-selling, location-based marketing, in-store behaviour analysis, customer micro-segmentation, customer sentiment analysis, enhancement of multi-channel consumer experience; merchandizing: assortment optimization, pricing optimization, placement and design optimization; operations: performance transparency, labour inputs optimization; supply chain: inventory management, distribution and logistics optimization, informing supplier negotiations; new business models: price comparison services, web-based markets.
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Manufacturing: The manufacturing
sector was an early adopter of IT to design, build, and distribute products. The next-generation of smart factories with intelligent and networked machinery (i.e. Internet of Things
, Industry 4.0) will see further efficiency improvement in design, production, and product quality. Big data will enable fulfilment of customer needs through precisely targeted products and effective distribution. In addition to efficiency gains and predictive maintenance, big data will enable entirely new business models in the area of mass production of individualized products.
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Energy and Transport
: Big data will open up new opportunities for innovative ways to monitor and control transportation and logistics networks using a variety of data sources and the Internet of Things. The potential for big data in the transport sector is estimated at USD 500 billion worldwide in the form of time and fuel savings, with the avoidance of 380 megatonnes of CO2 emissions
(OECD 2013). The digitization of energy systems enables the acquisition of real-time, high-resolution data via smart metres
that can be leveraged within advanced analytics to improve the levels of efficiency within both the demand and supply sides of energy networks. Smart buildings
and smart cities
will be key drivers of enhanced efficiency in the energy sectors. Big data technology in the utilities sectors has the potential to reduce CO2 emissions by more than 2 gigatonnes, equivalent to 79 billion euros (OECD 2013).
A successful data ecosystem
would “bring together data owners, data analytics companies, skilled data professionals, cloud service providers, companies from the user industries, venture capitalists, entrepreneurs, research institutes and universities” (DG Connect 2013). A successful data ecosystem, which is a prominent feature of the data-driven economy
, would see these stakeholders interact seamlessly within a Digital Single Market
, leading to business opportunities, easier access to knowledge, and capital (European Commission 2014). “The Commission can contribute to this by bringing the relevant players together and by steering the available financial resources that facilitate collaboration among the various stakeholders in the European data economy
” (DG Connect 2013).
Big data offers tremendous untapped potential value for many sectors; however, there is no coherent data ecosystem in Europe. As Commissioner Kroes explained, “The fragmentation concerns sectors, languages, as well as differences in laws and policy practices between EU countries” (European Commission 2013; Kroes 2013). During the ICT 2013 Conference, Commissioner Kroes called for a European public–private partnership
on big data to create a coherent European data ecosystem
that stimulates research and innovation around data, as well as the uptake of cross-sector, cross-lingual, and cross-border data services and products. She also noted the need for ensuring privacy
“Mastering big data means mastering privacy too” (Kroes 2013). In order for this to occur, an interdisciplinary approach is required to create an optimal business environment for big data that will accelerate adoption within Europe.