MOVING TOWARDS THE EUROPEAN DATA-AGILE ECONOMY The ...

The European Data Market Monitoring Tool Report

15th May 2020

MOVING TOWARDS THE EUROPEAN DATA-AGILE ECONOMY

UPDATE OF THE EUROPEAN DATA MARKET STUDY

SMART 2016/0063

D2.8 FINAL REPORT ON POLICY

CONCLUSIONS

IDC Italia S.r.l (Milan, IT) The Lisbon Council (Brussels, BE)

Prepared for:

Katalin IMREI

Policy Officer

European Commission – DG CONNECT

Unit G1 – Data Policy & Innovation

15th May 2020

Author(s) Gabriella Cattaneo, Giorgio Micheletti,Carla La Croce, Cristina Pepato, Alessandra Massaro, Irene Magnani (IDC)

Deliverable D2.8 Final Report on Policy Conclusions update

Date of delivery 15.05.2020

Version 2.1

Addressee officer Katalin IMREI

Policy Officer

European Commission, DG CONNECT

Unit G1 — Data Policy and Innovation

EUFO 1/265, L-2557 Luxembourg/Gasperich

[email protected]

Contract ref. N- 30-CE-0835309/00-96

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Table of Contents

1. Introduction .................................................................................................................. 7

Considerations on COVID-19 Impact ............................................................................................. 8

2. THE EU DATA MARKET GROWTH IN 2019 .................................................................... 9

3. THE EU DATA MARKET AND ECONOMY POST-COVID SCENARIO ............................... 12

3.1 Introduction .......................................................................................................................... 12

3.2 The EU27 Data Market Post-COVID ...................................................................................... 12

3.3 The impact of COVID-19 on industries ................................................................................. 14

3.4 The EU27 Data Economy post-Covid .................................................................................... 15

4. THREE SCENARIOS FOR THE EUROPEAN DATA ECONOMY ......................................... 19

4.1 Baseline Scenario (Pre-COVID) ............................................................................................. 24

4.2 High-Growth Scenario (Pre-Covid) ........................................................................................ 27

4.3 Challenge Scenario (Pre-Covid) ............................................................................................. 30

5. A CHANGE OF PACE IN DATA POLICIES ....................................................................... 33

5.1 The new Data Policies and the EDM Monitoring Tool .......................................................... 33

5.2 The evolution of Data Ethics ................................................................................................. 35

5.3 Big Data as the lifeblood of the next innovation waves like AI ............................................. 36

5.3.1 AI paving the way for the Cognitive Revolution across European Utilities ........................ 36

5.3.2 Health Data and Data-driven Innovation in the European Healthcare Industry ................ 40

6. THE ROLE OF THE U.K. IN THE EUROPEAN DATA ECONOMY ...................................... 45

6.1 The U.K. - A Leading European Data Economy ...................................................................... 47

6.2 After Brexit: An initial policy perspective .............................................................................. 48

7. THE EU DATA POLICY AND THE INTERNATIONAL DIMENSION ................................... 51

7.1 The International Indicators and the EU in 2019 .................................................................. 51

7.2 What the International Indicators really say ......................................................................... 54

7.3 Europe on the international scene: looking for a recovered confidence ............................. 55

8. CONCLUSIONS ............................................................................................................ 56

8.1 Overview ............................................................................................................................... 56

8.2 Data Professionals ................................................................................................................ 57

8.3 Data Companies .................................................................................................................... 58

8.4 Data Market and Data Economy........................................................................................... 58

8.5 Concluding remarks .............................................................................................................. 60

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Table of Figures Figure 1: The European Data Market Monitoring Tool ........................................................................... 8

Figure 2 Top three use case for AI among European healthcare providers ......................................... 41

Figure 3 Digital Economy and Society Index (DESI) – 2019 Ranking ..................................................... 45

Figure 4 IMG World Digital Competitiveness Ranking 2019 ................................................................. 46

Figure 5 Data Professionals, Data Professionals’ Skills Gap, Data Suppliers and Data Users in the U.K.

(2019; 2025, 3 scenarios) ...................................................................................................................... 47

Figure 6 Data Suppliers’ Revenues, Data Market Value, Data Economy Value in the U.K. (2025, 3

scenarios) .............................................................................................................................................. 48

Figure 7 Adequacy vs. No-Deal ............................................................................................................. 50

Figure 8: The European Data Market Monitoring Tool: Interrelated Indicators and Building Blocks .. 56

Table of Tables Table 1 ICT spending by segment, 2019 and forecast 2020 ................................................................. 13

Table 2 Industries with the highest negative impact on IT spending from COVID-19, 2020 ................ 13

Table 3 EU27 Data Market, Post-Covid scenario, 2020 and 2025, 3 scenarios (€M)............................ 14

Table 4 EU27 Data Economy, Post-Covid Scenario, value and impact on GDP, 2019, 2020, 2025 (€

Million; %) ............................................................................................................................................. 16

Table 5 EU27 Data Economy, Post-Covid Forecast 2020 by type of impact (M€, %) ........................... 17

Table 6 EU27 Data Economy, Post-Covid Baseline scenario 2025, value and shares by type of impact

(€ Million; %) ......................................................................................................................................... 17

Table 7: Macroeconomic Assumptions ................................................................................................. 20

Table 8: Policy-Regulatory Assumptions ............................................................................................... 20

Table 9: Data Market Assumptions ....................................................................................................... 22

Table 10: Global Trends ........................................................................................................................ 23

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1. Introduction

Since 2013, the European Data Market Monitoring tool has traced the fast development of data-driven

innovation and its gradual diffusion across industries and user constituencies. What started as a

technology trend mostly relevant for business IT managers has quickly become a transformation

process of deep social as well as economic relevance, witnessed by the over 400 €B of value reached

by the European Data Economy in 2019, corresponding to 2.8% of the EU28 GDP. 2019 was also the

year when the emergence of Artificial Intelligence and related technologies became visible outside

the technology world. This created a new awareness about the power of data enabling all kinds of AI-

enabled decision-support systems, digital helpers in the work environment, robots, and drones,

generating new cultural as well as ethical and organizational challenges.

Today, in 2020, a more mature understanding of the complexity of the multi-dimensional

transformation driven by Big Data and AI has crystallised. The digital policy strategies presented in

February 2020 by the new Commission led by Ursula Von der Leyen recognize this and represent a

change of pace in data policies, both in breadth and boldness. The new European Data Strategy is a

cornerstone of the new Europe’s Digital Strategy and underline the ambition for Europe to become a

leading role model for a society empowered by data to make better decisions in business and the

public sector. A renewed ambition for Europe to become a global leader in the data-agile economy is

accompanied by the need to achieve “technological sovereignty” based on a resilient and independent

data infrastructure. The White Paper on Artificial Intelligence presented the same day suggests several

policy options to develop AI ecosystems of excellence and trust, reflecting the understanding of the

systemic impacts of technological innovation always promoted by this study.

As the centrality of data for European competitiveness is recognized at the highest level of the EU, the

results of the European Data Market (EDM) Monitoring Tool, presented in this report, provide relevant

insights and suggestions for the potential consequences of policy choices in the next years. The EDM

Monitoring Tool was designed by IDC, in collaboration with the Lisbon Council, to provide the

European Commission with a comprehensive view of the data-driven economy, through annual

reports. The methodology provides a unique perspective of the development of the data ecosystem

in Europe, through 6 main indicators measuring its key components (see Figure 1): the skills (the

number of data professionals and the gap between demand and supply of data skills); the enterprises

and their roles (both data suppliers and data user companies); the demand-side value (the market)

and the supply-side value (the data suppliers revenues); and finally the overall impacts on the

economic system, through the estimate of the European Data Economy as a share of EU GDP. This

report presents the main indicators for the year 2019 and the potential development paths of the

EU27 Data Market and Data Economy to 2025 under the three updated scenarios presented in the

Third Report on Facts and Figures1: Baseline scenario, High Growth scenario, and Challenge scenario.

These scenarios provide a snapshot of the range of magnitude of the potential economic gains or

missed opportunities facing the Data Economy.

Finally, the EDM Monitoring Tool measures a more limited set of indicators for three other

international economies, the U.S., Brazil and Japan. The report presents a snapshot of the indicators

and looks more closely at the U.S., examining the competitiveness implications. The full set of

indicators is available in the “Facts and Figures” report. Further results of the study are published on

the website www.datalandscape.eu.

1 Update of the European Data Market Study, SMART 2016/0063, D2.7 Third Report on Facts and Figures

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Considerations on COVID-19 Impact

As this report was being finalised in February 2020, the COVID-19 pandemic started its rampage across

the globe, endangering people and livelihoods, forcing governments to implement measures to

contain the virus, with unprecedented impacts on the European economy as well as the technology

market. While the EDM Monitoring tool data and analysis until 2019 remain valid, clearly our

estimates for 2020 are now off the mark and all forecasts to 2025 would need to be revised. Based on

IDC research carried out in March-April 2020, we provide an additional post-Covid-impact scenario

with estimates on the likely Data Market and Data Economy decline in 2020 and potential rebound

and impacts on the 2025 scenarios for the EU27. These estimates should be taken with caution

because of the extremely high level of uncertainty about the current damages to the economy and

the potential recovery paths. Unfortunately, there is insufficient evidence and time to revise the

estimate of all the other indicators of the EDM Monitoring too for 2020.

According to our post-COVID scenario estimates, the European Data Market should decrease by 7.1%

to 54 €B in 2020 (compared to 58 €B in 2019) and the Data Economy by 5.5% to 307 €B (compared to

325 €B in 2019). In our view, the powerful negative impact of the slow-down in 2020 will be followed

by a rebound and a likely return on the growth path in the next years. Many of the powerful drivers

of data-driven innovation are likely to prove resilient in the next years, particularly the willingness to

invest in digital technologies in order to re-launch services and create new products to stimulate

demand.

By 2025, the post-Covid Baseline scenario foresees strong growth rates resulting in a value of 80 €B

for the European Data Market (compared to 82.5 €B in the pre-Covid scenario) and 516 €B for the

Data Economy (compared to 550 €B in the pre-Covid scenario). However, the incidence of the

European Data Economy on the EU27 GDP will slightly increase from 4% (Pre-Covid scenario) to 4.04%

(post-Covid scenario) because GDP is also affected by the recession. The Challenge and High Growth

scenarios remain broadly valid, even though their degree of likeliness change; the Challenge scenario

is marginally more likely (if the recovery does not take off as hoped) while the High Growth scenario

assumptions, based on hyper-growth thanks to technology investments, seem now quite remote.

Figure 1: The European Data Market Monitoring Tool

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2. THE EU DATA MARKET GROWTH IN 2019

The value of the Data Economy, which measures the overall impacts of the Data Market on the

economy as a whole, exceeded the threshold of 400 Billion Euro in 2019 for the EU27 plus the United

Kingdom2, with a growth of 7.6% over the previous year. The positive trend in the growth of the Data

Economy is confirmed by the Data Market value in 2019 for the EU27+U.K., which is displaying a

growth rate above the one exhibited by the total IT spending, at 4.9% year-on-year, reaching 75 Billion

Euro. The size of the Data Market by Member State still correlates closely with the overall economic

strength of each country, as well as with their national spending on ICT - the U.K, Germany, France,

Italy, the Netherlands and Spain account for approximately three quarters of the Data Market for the

EU27+U.K. in 2019. Smaller economies, however, display higher-than-average shares of Data Market

on ICT Spending. This is notably the case of Estonia, and, to a lesser extent, Cyprus, Latvia and Lithuania

that have all fully embraced the process of digital transformation for some time. Aside from the

outliers, the spread of share of ICT spending taken by the Data Market is fairly narrow across most

Member States with the 16 middle Member States having a share between 10% and 13%.

As far as supply and demand are concerned, data suppliers are estimated at more than 290,000 units

in the EU27+U.K. for 2019, exhibiting a year-on-year growth of 2.3%. Data users, instead, remained

stable in 2019, amounting to nearly 716,000 units and registering a growth of 0.6% over the previous

year. Following increasing growth rates over the prior four years, these figures show a picture of

consolidation of data companies in the EU.

Revenues generated by data suppliers increased by 9% to reach almost 84 Billion Euro in the

EU27+U.K., with the U.K., still in the leading position, Germany, France and Italy showing the highest

share of data revenues per country - together accounting for two thirds (66%) of data revenues in the

European Union plus the U.K.

According to the latest estimates, the number of data professionals in the EU27+U.K. reached 7.6 €

million in 2019, corresponding to 3.6% of the total workforce, with an increase of 5.5% over the

previous year. However, the EDM Monitoring Tool continues to register an imbalance between the

demand and the supply of data skills in Europe as the estimated gap reached approximately 459,000

unfilled positions in the EU27+U.K., corresponding to 5.7% of total demand. The data skills gap is

forecast to continue in all the forecast scenarios as demand will continue to outpace supply.

2 Since Brexit is now definitive (as of May 2020), the authors provided an overview of data for EU27+U.K. until 2019, and for the remaining months data are displayed for EU27.

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Source: EDM Monitoring Tool, IDC 2020

The European Data Market Monitoring Tool – Key Numbers 2019 for EU27

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The European Data Market Monitoring Tool – Key Numbers 2019 for EU27 + U.K.

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3. THE EU DATA MARKET AND ECONOMY POST-COVID SCENARIO

3.1 Introduction

This section presents revised estimates of the EU27 Data Market and Data Economy value in 2020,

based on IDC revised ICT market estimates3 developed in the period March-April 2020, as well as a

forecast of the implications of these changes for the 2025 Baseline scenario. An analysis of the current

impacts by industry and the potential for rebound is also included. However, these estimates should

be considered with caution given the unprecedented nature of this pandemic and its economic impacts

and the high level of uncertainty about the potential consequences.

As COVID-19 sweeps across the globe, endangering people and livelihoods, forcing governments to

implement measures to contain the virus, Europe is facing a significant impact on people, the

economy, business, and investments. The impact of COVID-19 across European industries is significant

and is creating uncertainty in the technology market, with overall negative consequences ranging from

decreased customer demand and technology investment delays to supply-chain failures. Although

essential to contain the virus, lockdowns and restrictions on mobility are extracting a sizable toll on

economic activity.

As the IMF highlighted in the latest World Economic Outlook (April 2020), this crisis is like no other for

three main reasons: the first is that the shock is large, with an output loss that likely dwarfs the losses

that triggered the global financial crisis. Second, there is continued severe uncertainty about the

duration and intensity of the shock, similarly to what happens during a war or a political crisis. Third,

there is a very different role for economic policy, as differently that in normal crises, where

policymakers try to encourage economic activity in this case, the crisis is to a large extent the

consequence of needed containment measures. A partial recovery is projected for 2021, but the level

of GDP is likely to remain below the pre-virus forecast, also due to the considerable uncertainty about

the strength of the rebound.

3.2 The EU27 Data Market Post-COVID

The economic impact of the COVID-19 slow-down started to be understood only in March. IDC carries

out ongoing research and analysis of the impacts on ICT spending by industry, which is influenced by

contrasting trends: industries providing digitally-enabled (telecom, media) and critical services

(healthcare, government) are holding on or even growing, while others (tourism, transport services,

retail) are in free fall. This is clearly illustrated by Table 1 about forecasts of ICT spending by segment

in 2020, showing growth for infrastructures and software spending and reductions for devices and IT

services (correlated with business spending). The impact on the Data Market however is not identical,

because of the different mix of ICT components.

3 https://www.idc.com/misc/covid19

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Table 1 ICT spending by segment, 2019 and forecast 2020

Year on year growth (%)

2019 2020 2021

Devices 0.9% -8.8%

Infrastructure 8.8% 5.3%

Software 10.0% 1.7%

IT Services 3.9% -2.0%

Telecom Spending

1.0% 0.5% 1.0%

ICT Spending 3.5% -1.6% 3.4%

Source: IDC Worldwide ICT spending forecast Post-Covid, 21-Apr-2020

Industries see different effects on their ICT spending depending on their necessity to support the

population through the corona virus, and the industry’s interaction with workers. Some Member

States have imposed a lockdown, where the population must remain home in self isolation, but key

industry workers are exempt from this. Industries whose workers must be present at the workplace

are most affected, particularly consumer service industries, while the industries where remote work

is possible have been less impacted by the lockdown. While the Data Market is based on digital

technologies, many of the leading Big Data user industries are service industries severely affected by

the lockdown (e.g., Transport, Manufacturing, Retail and Wholesale). Table 2 shows the top industries

with the biggest revenues decline anticipated in 2020.

Table 2 Industries with the highest negative impact on IT spending from COVID-19, 2020

2019 2020 2021

Transport and Storage 4.7% -8.4% 0.0%

Mining, Manufacturing 5.6% -6.8% 0.4%

Home -0.1% -4.0% 0.1%

Retail & Wholesale 5.1% -3.3% 0.7%

Source: IDC Worldwide ICT spending forecast Post-Covid, 21-Apr-2020

All industries – except for Healthcare – are expected to decline in 2020, but most should return to

growth by 2021. According to IDC forecasts, several industries (Communications, Manufacturing,

Professional Services, and Retail) are likely to experience significant rebound in 2021, but not all

industries are expected to bounce back at the same rate, because of the disruption to the value chains

and the uncertainty about consumer and end user demand perspectives.

The estimated impact of Covid-19 on forecast growth in the European Data Market for 2019, and 2020,

is shown in Table 3. The turnaround in the market is dramatic: instead of a growth of +6.9% a fall of

7.1% in revenues. The four industries listed in Table 2 (Transport, Manufacturing, Retail and Home

consumer) account for nearly 90 percent of this fall.

However, as soon as the economy will start recovering, we expect the Data Market to pick up its

growth again. For example, Big Data and AI technologies have proven their value in managing the

COVID-19 pandemic and will likely continue to play a strong role in healthcare but also in many other

industries. Online interactions in education, remote working and media have increased and reached

new users as never before, hopefully overcoming once and for all old cultural barriers.

Overall, we estimate the cumulative average growth rate from 2020 to 2025 to increase from 5.8%

(pre-COVID baseline scenario) to 8.1% (post-COVID baseline scenario) leading the EU27 Data Market

to reach a value of 80 €B (Table 3). Even with this faster growth rate, the EU Data Market will not

reach the same value expected in the pre-COVID scenario but will be only slightly smaller, losing only

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3%. Symmetrically, this means that without this acceleration of growth it will not be possible to

recover the value burnt by the 2020 recession.

Extrapolating the same rationale to the other 2025 scenarios, we consider the Challenge scenario as

still valid in absolute terms, with a higher cumulative growth rate compared to the pre-Covid scenario,

because of a limited rebound effect. On the other hand, we consider the High Growth scenario post-

Covid as less likely, because of the difficulty to achieve very fast growth, and lower in value than the

pre-Covid estimate by 2%. In conclusion, based on these considerations, the most likely scenario

remains the Baseline, with the Challenge scenario as a possible alternative.

Table 3 EU27 Data Market, Post-Covid scenario, 2020 and 2025, 3 scenarios (€M)

EU27 Data Market

2019 2020 Forecast Growth rate 2020/2019

Baseline Scenario 2025

Forecast CAGR 2025/ 2020

Challenge Scenario 2025


High Growth Scenario

2025


Pre-COVID forecast

58,214 62,244 6.9% 82,564 5.8% 72,329 3.0% 107,139 11.5%

Post-COVID forecast

58,214 54,081 -7.1% 79,965 8.1% 72,329 6.0% 104,783 14.1%

Forecast variation

-8,163

-2,599

0

-2,355

% Variation -13%

-3%

0%

-2%

Variation on 2019

-4,133

% Variation -7%

Source: IDC European Data Monitoring Tool, April 2020

3.3 The impact of COVID-19 on industries

The impact of COVID-19 across European industries is significant and is creating uncertainty in the

technology market, with overall negative consequences ranging from decreased customer demand

and technology investment delays to supply-chain failures. IDC believes the IT spending pattern will

generally follow the direction of GDP, with some potential exceptions.

European industries that are the most negatively affected by the outbreak in terms of cash-flow and

overall business impact in this first phase are consumer facing, including transport and leisure and

retail. Moreover, severe challenges raised in the manufacturing space (lack of labour, supply chain,

and eventually demand) and oil and gas (demand, pricing).

Public sector organizations are in a special situation - they are under incredible duress but are also

expected to see more monetary support. The healthcare sector is expected to receive additional

emergency funding in many countries to cope with hospitalizations. Some of that funding will find its

way into ICT technologies in the mid-term.

If the overall impact on industries is negative, there are also some important "bright spots" for specific

solutions and use cases, through which technology can help make the difference and help businesses

and societies deal with the COVID-19 disruption. They are all enabled by data-driven innovation and

anticipate trends which are likely to drive the Data Market and the Data Economy back to growth.

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AI Enabled Solutions Will Support Healthcare Systems in Proactively Managing Outbreaks

Healthcare is the sector where organizations look at technology to predict the spread of disease more

accurately, and to proactively manage the pandemic. At this time, IT investments might undergo an

immediate increase, with hospitals expanding their digital infrastructure supporting ICUs and a surge

in capacity. But investments in population health analytics, AI-enabled solutions, remote patient

monitoring, and telemedicine will be also key in the broader response to the outbreak. The use of big

data and artificial intelligence were applied "to strengthen contact tracing and the management of

priority populations." Researchers have been starting to use deep learning techniques to support

COVID-19 detection when analysing CT scans and patient records. Remote health monitoring systems

can be used to observe and check the progress of less critical COVID-19 patients, and at the same time

keep the pressure off hospitals by managing patients affected by other pathologies at home or in other

care settings. IDC believes some of these patterns, albeit at a smaller scale, are already taking place in

Europe as well.

Online Shopping Triggering More Cloud Infrastructure Consumption

With restrictions and social distancing in place, online shopping is even more popular and consumers

who haven't relied on ecommerce, have been more likely to move online to buy food and household

items to avoid busy stores. These platforms and online marketplaces are experiencing an increase in

demand that could also be significant. In turn, this will increase cloud infrastructure consumption in

the short term.

Digital Advertising Will Help the Public Sector Raise COVID-19 Awareness

Safeguarding citizens' health will be among the top priorities for the public sector during these hard

times. Digital ads and social media campaigns to provide trusted, localized information to residents

regarding the spread and development of the outbreak are key to help societies in the fight against

the virus.

Chatbots Will Help Self-Isolating Customers Get Support

With stay-at-home measures in place, face-to-face customer support might be challenged, especially

for highly customer-facing industries such as finance, retail, and telecoms. These companies might

look at alternative ways to provide their customers the support they need without physical human

interaction needed. We see an increase of adoption of virtual assistants or digital customer service

agents (chatbots) to maintain customer relationships without human contact. Since these projects

require some incubation, IDC maintains that spending might take months or quarters to follow.

Intelligent Supply Chain Will Help Businesses Minimize Disruption

Another area that is deeply affected and is experiencing delays or shortages is the supply chain. This

is impacting many European automotive manufacturers as they are experiencing difficulties in

sourcing components from Chinese suppliers. In this scenario, manufacturing companies are looking

at use cases relying on artificial intelligence (AI) to minimize supply chain disruption. Intelligent supply

chain solutions might see an increase in demand as companies look at automation to improve visibility

of inventories, supply prediction, and adaption in order to minimize disruption. Backend changes

require long timeframes for implementation, so spending will take a quarter to follow.

3.4 The EU27 Data Economy post-Covid

This section presents our post-Covid scenario forecast for the Data Economy, building on the revised

estimates of the EU27 Data Market and on macroeconomic and industrial trends. To understand this

forecast it is important to remember the three main components of the Data Economy:

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• The direct impacts, which is the value of the goods and services sold in the Data Market;

• The indirect impacts, backwards (on the supply chain: gains made by industries providing

goods and services to data users) and forwards: revenues gained by user industries thanks to

data innovation;

• The induced impacts on the general economy, thanks to additional spending and consumption

driven by the value of the direct and indirect impacts.

Therefore, the post-COVID Data Economy reflects the decline of the Data Market, the fall in revenues

of the industries affected by the lock-down, and the steep decrease of consumer demand and overall

consumption.

As shown in Table 4, according to our new estimates the EU27 Data Economy is expected to decrease

by 5.5% in 2020, contrasting with a healthy growth of 7.7% in 2019. This means a reduction of 18 €B

on the previous year and a loss of 48 €B of potential growth, compared with the pre-Covid forecast

for the 2020 Data Economy. The value of the Data Economy as a share of GDP is stable compared to

2019 because the EU GDP is decreasing sharply too.

Table 4 EU27 Data Economy, Post-Covid Scenario, value and impact on GDP, 2019, 2020, 2025 (€ Million; %)

EU 27 Data Economy

2019 Impact on GDP

2019

2020 Forecast Growth rate 2020/2019

Impact on GDP

2020

Baseline Scenario

2025

CAGR 2025/2020

Impact on GDP 2025

Pre-COVID forecast

324,858 2.60% 355,109 9.30% 2.80% 549,783 9.10% 4.00%

Post-COVID forecast

324,858 2.60% 306,926 -5.50% 2.60% 509,851 10.70% 3.90%

Forecast variation

0.0% -48,183 -15% -0.20% -39,932 2% -0.10%

% Variation

-13.6%

-7.3%

Variation on 2019

-17,932

% Variation

-5.5%


Breaking down the type of impacts provides new light on the dynamics of this fall of the Data Economy

(Table 5). The direct impacts decrease by 7% compared to the previous year, on a par with the Data

Market. The indirect impacts decrease only by 3% and therefore represent a higher share of the Data

Economy. As explained above, the indirect impacts are the B2B component of the Data Economy,

which is suffering from the disruption of value chains but is also more resilient, since some critical

industries remained active during lockdown and others such as healthcare see spending going up, not

down. Digital supply chains were disrupted, but less so than physical supply chains: consider for

example online shopping which during lockdown is increasing, even if facing delivery problems for

physical goods. Finally, the biggest loss concerns the induced impacts, a decrease of 8.5% on 2019,

reflecting the steep drop of consumer spending, tight financial conditions, and the rise of

unemployment. These effects lead to a decrease in the share of induced impacts from 33% in 2019 to

32% in 2020.

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Table 5 EU27 Data Economy, Post-Covid Forecast 2020 by type of impact (M€, %)

EU27 Data Economy, 2019-2020

Direct

Impacts Share of total %

Indirect Impacts

Share of total %

Induced Impacts

Share of total %

Values 2019 58,214 17.92% 158,586 48.8% 108,058 33%

Post-COVID forecast 2020 54,081 17.60% 153,992 50.20% 98,853 32.20%

Variation 2020 on 2019 -4,133 -0.3% -4,594 1.4% -9,205 -1.1%

% Variation 2020 on 2019 -7% -2% -3% 3% -8.5% -3%

Pre-COVID forecast 2020 62,244 17.50% 170,753 48.10% 122,113 34.40%


Finally, in the post-COVID baseline scenario the EU27 Data Economy is expected to reach 516 €B by

2025, corresponding to 4% of GDP, same share as in the pre-COVID scenario. This means we expect

similar growth dynamics for the Data Economy and GDP. As already observed concerning the Data

Market, the recovery is expected to be quick, with the Data Economy returning to a healthy growth

rate already from 2021. However, because of the 2020 decline, the value by 2025 is estimated to be

33 €B lower than in the previous forecast. In the new forecast we expect direct and indirect impacts

to recover faster than induced impacts (Table 6) because the damages to consumer demand and the

labour market will take longer to be overcome.

Unfortunately, we are unable to present post-COVID revised estimates for the Data Economy

Challenge and High Growth scenarios. These scenarios rely on alternative assumptions on industry

revenues, consumer consumption and GDP dynamics and we do not feel able in the present

uncertainty to elaborate such assumptions, beyond the Baseline scenario. However, as discussed for

the European Data Market, we believe that the forecast estimates remain broadly valid with the

Challenge scenario relatively more likely than before the COVID pandemics.

Table 6 EU27 Data Economy, Post-Covid Baseline scenario 2025, value and shares by type of impact (€ Million; %)

EU27 Data Economy, Baseline scenario, 2025

Direct Impacts Share of total %

Indirect Impacts

Share of total %

Induced Impacts

Share of total %

Pre-COVID forecast 2025

82,564 15% 235,613 42.90% 231,606 42.10%

Post-COVID forecast 2025

79,965 15.50% 220,915 42.80% 214,992 41.70%

Variation Forecast

-2,599 0.5% -14,698 -0.1% -16,685 -0.4%

% Variation Forecast

-3% -6.2% -7.2%


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Baseline Scenario

High Growth Scenario

Challenge Scenario


4 Unfortunately, we are unable to present post-COVID revised estimates for the Data Economy Challenge and High Growth scenarios. These scenarios rely on alternative assumptions on industry revenues, consumer consumption and GDP dynamics and we do not feel able in the present uncertainty to elaborate such assumptions, beyond the Baseline scenario. However, as discussed for the European Data Market, we believe that the forecast estimates remain broadly valid with the Challenge scenario relatively more likely than before the COVID pandemics.

The European Data Market Monitoring Tool – Post-Covid Scenarios 2020-2025 for EU27 (€M)

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4. THREE SCENARIOS FOR THE EUROPEAN DATA ECONOMY

The new European Data strategy outlines the ambition for Europe to become a leading role model for

a society empowered by data to make better decisions in business and the public sector and a global

leader in the data-agile economy. Our 2025 scenarios outline different pathways of evolution of the

European Data Market (EDM) and Data Economy in the next years, exploring the different mix of

factors and policy choices which may lead to achieve this ambition or instead to fail it. In the past years

we have monitored the fast growth of the Data Market and Data Economy and have witnessed the

evolution of supply and demand dynamics in Europe. Today, as we look at the main driving trends for

the next years, we notice that the role of policies has increased in relevance: as data-driven innovation

has become widespread across all industry sectors and user constituencies, the scope of the

regulations and framework conditions to be adapted has considerably grown. At the same time, the

emergence of disruptive technologies such as AI has increased the need for policy intervention to

manage emerging social, economic and ethical risks. Therefore, the 2025 scenario presented in this

report are strongly influenced by multiple policy assumptions shaped by the Data Strategy and

European Digital Strategy recently published by the new Commission.

Given this context, we have updated the description of the two main focal issues (axes) around which

we have developed our 2025 scenarios, as follows:

• the high or low pace of diffusion of data-driven innovation, driven by demand-supply

dynamics, and its impact on economic growth. This year we add to this perspective the pace

of multiple innovation adoption, where data is at the core of a multiple technology

environment powered by AI.

• the social and economic data governance model enabling a fair and competitive economy,

as indicated by the new European Data Strategy. Today the term “data governance” has grown

from its original narrow definition as an approach to data management, to a much broader

concept of a policy and conceptual framework establishing the norms, practices and principles

covering all aspects of data dynamics in the society and the economy. Essentially, the data

governance framework which is the first pillar of the new European Data Strategy recognizes

the need to deal with data as a strategic asset influencing power dynamics in the socio-

economic system.

At one extreme, we foresee a society where a few actors, such as leading online platforms,

governments, large businesses, dominate the main data assets and therefore capture a

disproportionately high share of data innovation benefits, increasing social inequality (highly

centralized model). The polar opposite of this scenario would be a society characterised by an open,

transparent and participatory approach to data governance, where both citizens and organisations

are able to control and extract value from their data. This would result in a wider social distribution of

data innovation benefits, decreasing social inequality. Trustworthiness and respect of data ethics

principles are other important characteristics of this ideal model.

This analysis highlights the critical turning points to be faced in the next years by governments,

businesses and social actors in the development of the European Data Economy. The combination of

alternative social and economic trends results in the following scenarios:

• The Baseline scenario is characterised by a healthy growth of data innovation, a moderate

concentration of power by dominant data owners with a data governance model protecting

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personal data rights, and an uneven but rather wide distribution of data innovation benefits in the

society. This is considered the most likely scenario.

• The High Growth scenario is characterised by a high level of data innovation, low data power

concentration, an open and transparent data governance model with high data sharing, and a

wide distribution of the benefits of data innovation in the society;

• The Challenge scenario is characterised by a low level of data innovation, a moderate level of data

power concentration due to digital markets fragmentation, and an uneven distribution of data

innovation benefits in the society.

The scenarios explore the drivers and framework conditions which may lead to maximise the benefits

of a balanced Data Economy and to avoid the risks of an unbalanced one, highlighting the

consequences of policy actions.

Table 7: Macroeconomic Assumptions

MACROECONOMIC

ASSUMPTIONS Baseline Scenario High Growth Scenario Challenge Scenario

Economy trends Moderate GDP growth

trends under 2% continue

after a slow down in 2020

Moderate GDP growth in

2020-2021 gradually

accelerates to healthy

growth by the end of the

forecast period.

Trade wars, political conflicts, and

unexpected events such as the

Coronavirus pandemic reduce

cumulative GDP growth rates over the

period to 1%

EU27 GDP growth CAGR 2019-

2025 1.5% 2.0% 1.0%

EU27 ICT spending growth CAGR

2019-2025 1.7% 2.2% 1.2%

EU27 Data Market CAGR 2019-

2025 6.0% 10.7% 3.7%

EU27 Data Market as a share of

ICT spending,2025 14.3% 18.0% 12.9%

Source: European Data Market Monitoring Tool, IDC February 2020

Table 8: Policy-Regulatory Assumptions

POLICY-REGULATORY

ASSUMPTIONS

Baseline Scenario High Growth Scenario Challenge Scenario

Digital Strategy/ Achieving

European technological

sovereignty

Europe makes progress in the

development of data

infrastructures and digital

resources, plays a strong role in

shaping global digital

governance rules building on

GDPR but does not quite

dominate AI-led developments

Strong investments and MS

cooperation help Europe to

develop fully independent data

infrastructures and digital

resources, to shape global digital

governance rules with EU values,

becoming a leader in the Big

Data-AI space

Uneven development of

European data infrastructures

and digital resources, continuing

dependency from global

platforms, fails in taking the lead

in global digital governance,

Europe struggles to keep up with

competition particularly for AI

Data Strategy-make

Europe a global leader in

the data-agile economy

The EU's gradually builds a single

market for data and attracts a

growing share of the global Data

Economy

The EU's share of the global Data

Economy well on the way to

become equal to its economic

weight by 2030 thanks to a

genuine single market for data

The EU market for data remains

fragmented with uneven data

sharing and the EU share of the

global Data Economy does not

grow on a par of its economy

Data Strategy -

Development of an

effective data governance

framework

Progress in the development of

the new regulatory framework

enhance data access and sharing

in time but main effects

deployed at the end of the

forecast period, the single

Fast progress with new Data Act,

Digital Services and Competition

framework enhance data access,

sharing and re-use, achieve fair

playing field and contribute to

effective single market for data

EU efforts to renew the digital

services and data governance

regulation fail or achieve only

minimal changes, barriers and

stakeholder’s reluctance to data

sharing remain high, only high

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market for data gradually

emerges

performing enterprises and

regions make progress

Data Strategy-

empowering individuals-

data and privacy

protection

GDPR implementation continues

successfully but further progress

on personal data portability and

control is slow and unevenly

applied across Europe, slow

progress in sharing data for

social good

GDPR and new measures ensure

people control of their data,

improve willingness to share

data for social good (healthcare),

barriers to data sharing removed

GDPR compliance only formal -

many Europeans become

careless about it and enterprises

learn to get around it - this

hinders the willingness to share

and reuse personal and non-

personal data for social good

Data Strategy/ investments

in EU data capabilities,

infrastructures,

standardization and

interoperability

EU High impact projects make

progress in the development of

data sharing and interoperable

architectures. Gradual

deployment of an EU cloud

infrastructure and cloud services

marketplace

EU High impact projects

successfully catalyse private

investment to develop data

sharing and interoperable

architectures. Successful

deployment of an EU cloud

infrastructure and cloud services

marketplace satisfies industry/

SMEs needs

EU High Impact projects

insufficient to catalyse

investments in EU data

infrastructures, European cloud

offerings grow but remain

marginal in the market and do

not break the dominance of

foreign suppliers-

Data Strategy/ developing

the skills for the Data

Economy

DEP programme5 slow to start

but delivers boost to

development of advanced digital

and data skills - uneven

distribution across the EU of

skills supply

DEP programme delivers boost

to development of advanced

digital and data skills - revised

Digital Education act drives

digital skills for digital

transformation

DEP Programme slow to start

with low impacts on advanced

digital skills supply, while

demand is hindered by weak

economic growth

Data strategy (Common

European data spaces

The development of common EU

data spaces is faster and more

successful in some sectors with

strong innovation demand

(manufacturing, agriculture) but

meets with barriers and low

demand in others failing to

achieve economies of scale.

Improvement of the single Data

Market and of data exploitation

by EU industries.

Successful development of

common EU data spaces

achieves economies of scale and

delivers strong boost to data

single market and data

exploitation by EU industries

The development of common EU

data spaces is slow and does not

deliver the expected boost to

industries across Europe, failing

to generate economies of scale

and therefore to fight the Data

Market fragmentation.

Data strategy and Digital

Strategy/ Europe as a

global player

EU makes progress towards a

Global Digital Cooperation

strategy and promoting the EU

digital transformation approach

- EU more proactive in

development and adoption of

standards and interoperable

technologies with mixed success

on the global scene

EU develops successfully a

Global Digital Cooperation

strategy becoming a leader in

promoting the EU digital

transformation approach -

defends and successfully

promotes EU standards and

interoperability choices

The EU fails in developing an

effective Global Digital

Cooperation strategy and

remains strongly dependent

from international standards and

interoperability choices

Digital Strategy/

Development of a

legislative framework for

trustworthy AI

The EU makes progress in

defining requirements for high-

risk AI particularly for training

data, human oversight, specific

applications such as remote

biometric identification (face

recognition) but fails to lead in

overall AI development

regulation

Europe develops a flexible

legislation based on the risk

management principle not

hindering technology progress

and becomes a successful global

leader of AI governance

principles

Fast AI technology progress in

other world regions supersedes

EU legislative proposals forcing

EU to revise its approach or risk

to weaken EU industry

competitiveness

White Paper on AI/ Development of an ecosystem of excellence for AI

Slow but secure improvement of EU AI research and innovation capabilities through HE, DEP and CEF2 programmes

HE, DEP and CEF2 programmes deliver a strong boost to European AI research and innovation capabilities building an ecosystem capable of global leadership

Slow start of HE, DEP and CEF2 programmes and insufficient investments hinder the development of European AI capabilities and research-innovation ecosystem

5 DE: Digital Europe Programme, HE: Horizon Europe Programme, CEF2: Connecting Europe Facility.

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Digital strategy/ European Cybersecurity, Gigabit connectivity, interoperability and standardization, Quantum. Blockchain and HPC

Increased investments accelerate deployment of 5G and blockchain infrastructures, provide basis for fast innovation adoption, progress accelerates at the end of the forecast period

Strong investment and MS collaboration drives boost to data infrastructures also providing basis for fast adoption of AI

Insufficient investments and difficulty in solving technology challenges hinder the development of EU digital capabilities and infrastructures

Digital Strategy/ Develop fair and effective regulation for the digital economy (competition, taxation, digital finance, consumer empowerment...)

Progress towards creating favourable conditions for the digital economy fighting new power imbalances

Fast progress in the adaptation of the market regulatory framework creating a fair playing field especially for SMEs and traditional industries

Insufficient progress towards creating favourable conditions for the digital economy - new power imbalances remain creating difficulties for SMEs and many traditional industries

Digital Strategy/ Develop a sustainable Data Economy

Partially successful policy initiatives supporting the ICT and electronic industry transition to fully climate-neutral, sustainability and energy efficiency

Successful policy initiatives supporting the ICT and electronic industry transition to fully climate-neutral, sustainability and energy efficiency

Policy initiatives fail to drive the ICT and electronic industry fully towards climate neutrality and sustainability by the end of the period


Table 9: Data Market Assumptions

DATA MARKET

ASSUMPTIONS

Baseline Scenario High Growth Scenario Challenge Scenario

Data technologies

supply-demand

dynamics

Data industry drives technology

innovation, lower costs, data

holders gradually increase demand.

The adoption of big data

technologies spreads beyond

pioneers to mainstream users; a

fully developed data ecosystem

powers a positive demand-supply

growth cycle – boost by the DEP

European innovation forces

become lost in a maze of digital

barriers (incomplete Digital Single

Market). Only the best

enterprises and the richest regions

keep pace with the technology

race

Development of the

data ecosystem in

Europe

Emergence of multiple vertical/

horizontal industrial and personal

data platforms providing secure

data sharing and trading

environments for data industry and

data owners

The industrial and personal data

platforms converge in

interoperable EU infrastructures

with clear governance models,

fostering participation of SMEs

Insufficient development of the

data ecosystem, limited diffusion

of data sharing platforms

Rate of diffusion of

digital

transformation and

data-driven

business models

Fast adoption by large companies

and innovative SMEs; public sector

gradually catches up during the

period; slower adoption by

traditional SMEs

Widespread diffusion of digital

transformation, EU SMEs learn to

adopt data monetization

solutions; successful impact of

DEP and other policies supporting

fast digital transformation

Slower adoption of digital

transformation and data-driven

business models hindered by

lower private investments, lower

expectation of take-up of

innovative services, lack of trust

and confidence in data sharing

Managing data ethics and AI business risks

Guidelines and data ethics principles multiply – enterprises need time to find a balance between business interests and ethics but eventually succeed – in some areas European enterprises able to use their ethics as a competitive advantage

Europe develops a coherent system of data ethics guidelines balancing EU values and business interests which becomes a global reference point and a competitive advantage for EU businesses

Guidelines and data ethics principles multiply – European enterprises struggle to develop skills and capability to manage risks – many enterprises refrain from data-driven innovation for fear of business risks

Deployment of 5G

infrastructures

Commercial deployment starts

around 2020, uneven diffusion

across Europe

5G networks and services

deployment accelerated and fully

interoperable across Europe by

2025

Slow deployment of 5G networks

and services undermine IoT/

advanced services diffusion


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Table 10: Global Trends

Global Trends Baseline Scenario High Growth Scenario Challenge Scenario

Multiple innovation:

enterprise ability to

adopt and combine

multiple technologies

enabled by data

Fast diffusion of technologies

drives multiple innovation, for

example leveraging AI software

for technology and process

innovation. By 2025 the take-up

of AI, Big Data, IoT, and

robotics reach over 60% of

medium-large EU enterprises.

But SMEs and enterprises from

traditional industries in some

regions (where for example 5G

diffusion is slower) struggle to

keep pace.

Take-up of multiple technologies and

multiple innovation grow even faster

than in the baseline scenario including

a large share of SMEs and all EU

regions.

Only leading enterprises succeed in

adopting multiple innovation, many

enterprises lag behind suffering from

insufficient investments in digital

infrastructures (missing 5G for

example) resources and skills

Rise of the platform

economy

(collaborative

connected, data-

centric environments

used to develop

multiple innovation) at

various levels: global

(mega platforms),

applications-specific or

industry specific.

European industries develop

industry platforms to harness

multiplied innovation and build

ecosystem-based value. For

example, by 2025 the majority

of manufacturers will use IoT

platforms with digital innovation

platforms to operate networks

of asset, product, and process

digital twins for a 25% reduction

in cost of quality.

European industries exploit platforms

to combine data with AI and machine

learning, spreading intelligence from

the core to the edge of their networks

turning data into action and action

into value.

European industries struggle to adapt

to the platform economy and to

develop cross-border ecosystems.

Markets fragmentation, data-sharing

obstacles. Insufficient interoperability

and standardization hinder

collaboration and innovation.

Deep transformation

of the work

environment

Driven by demographic and

technology trends, European

enterprises multiply the use of

"digital co-workers" (using

intelligent process automation

and AR/VR to

support/complement human

workers) reducing repetitive

tasks, improving productivity

and security and managing

digital transformation.

Besides automation, enterprises

engage in "augmentation" of human

resources providing technologies

enhancing their physical and

intelligence capabilities.

Technology-driven automation and

augmentation are badly managed and

create a negative reaction by the

human workforce slowing down

acceptance and digital transformation.

Emergence of new work culture and contracting models to create and manage an agile, borderless and reconfigurable workforce.

Organizations improve their capability to manage, retrain and upskill the existing workforce but they face problems of digital skills gap, resistance and need to access new talent sources. Change management and HR management are critical success factors. But substantial groups of workers are unhappy or displaced by the new way of working.

Organizations succeed in managing the transformation of the work culture for digital transformation through a combination of incentives, intensive training investments, identifying appropriate job roles and tasks in open ecosystems.

European organizations struggle to adapt to the new work environment and to motivate the workforce. Fragmented ecosystems and insufficient investments in re-training and re-skilling increase the skills gap and slow down digital transformation, while leaving many workers unhappy or displaced

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4.1 Baseline Scenario (Pre-COVID)

This scenario predicts a healthy growth of data-driven innovation and increase of investments in the

new wave of digital technologies, pioneered by the most advanced, competitive and innovative

enterprises, medium and large (both as technology providers and users) with a share of competitive

SMEs, savvy in the use of ICTs. By 2025 we expect the take-up of AI, Big Data, IoT, and robotics to

reach over 60% of medium-large EU enterprises (IDC survey on Advanced Technologies for Industry,

2019), while other technologies such as 5G, AR/VR, blockchain, new materials and industrial

biotechnologies will also make strong progress. This will force enterprises to engage in multiple

innovation, adopting and combining multiple technologies: this convergence is enabled and powered

by data and intelligence. A key driver of innovation will be the interplay and convergence between

cloud-enabled AI, Robotics and 5G, extensively supported by edge computing, which will require deep

re-organization and restructuring of business processes and value chains. In this scenario, competition

is powered by platforms and ecosystems where network effects and innovations feed off themselves.

In this scenario, the EU27 GDP cumulative growth average in the period 2019-2025 (+1.5%) will sustain

the investments in the digital economy and consumer willingness to spend. As a result, the Data

Market is forecast to reach 82.5 billion Euro in the EU27, with a compound annual growth rate of 5.8%.

The Data Economy will grow faster than the Data Market, because the investments in data

technologies have direct and indirect impacts on the economy with a multiplier effect, reaching a

value of 550 billion Euro in the EU27, with a steep increase of its incidence on EU from 2.6% in 2019

to 4% in 2025. Enterprises will add 3.2 € million data professionals’ positions between 2019 and 2025,

bringing the total to 9.3 € million jobs. However, this will increase the potential data professionals’

skills gap to approximately 759,000 unfilled positions in the EU27, corresponding to 8.2% of total data

skills demand. The lack of skills may become a bottleneck for some enterprises or regions, creating

competition between enterprises for the most skilled professionals. In this scenario, Europe makes

progress in the investment and deployment of independent data infrastructures and digital resources,

also leveraging the new Horizon Europe and Digital Europe Programs. This means Europe reaches a

better, but not quite complete, technological sovereignty. We expect Europe to play a strong role in

shaping global digital governance rules building on GDPR, but without quite dominating AI-led

developments. There is a good chance that Europe will play an important role in defining requirements

for high-risk AI, particularly for training data and human oversight. However, since this will take some

time, it will be difficult to bring under control ex-ante specific applications such as remote biometric

identification (facial recognition) which are already in the market. We foresee a scenario where

Europe will bring ex post some order and respect of ethical principles to applications such as facial

recognition.

The new digital policy strategies will empower Europe to play a stronger role in the global scene,

leveraging the GDPR success as a global standard. Not only Europe, but also many other international

governments are now conscious of the downside and risks of global platforms dominance and control

of global data flows and will work together towards achieving a more balanced playing field. Progress

will be made in terms of fair and effective regulation of competition in the digital economy, digital

finance and consumer empowerment. This scenario therefore is positioned between the two

extremes of high and low concentration of power and data control. The development of an effective

regulatory framework of data governance, as foreseen by the Data strategy, will enhance

stakeholders’ willingness and capability to manage data sharing and improves data access and re-use,

even though the main effects are seen at the end of the forecast period. The single market for data

gradually emerges as fragmentation is overcome, and this enables Europe to attract a growing share

of the global Data Economy, in terms of capability of data processing and management. The

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development of common EU data spaces is faster and more successful in some sectors with strong

innovation demand (manufacturing, agriculture) but meets with barriers and low demand in others,

failing to achieve economies of scale.

The rise of the platform economy (collaborative connected, data-centric environments used to

develop multiple innovation) at various levels: global (mega platforms), applications-specific or

industry specific will reshape the competitive environment. European industries will develop industry

platforms to harness multiplied innovation and build ecosystem-based value. For example, by 2025

the majority of manufacturers will use IoT platforms with digital innovation platforms to operate

networks of asset, product, and process digital twins for a 25% reduction in cost of quality. The market

is not yet mature and because of the arising of a new wave of innovation driven by the exploitation of

data by AI and Machine learning technologies, the dominant model is still technology push and so will

be for a few years more.

To enable digital transformation, this scenario is accompanied by the emergence of new work culture

and contracting models to create and manage an agile, borderless and reconfigurable workforce.

Driven by demographic and technology trends, European enterprises multiply the use of "digital co-

workers" (using intelligent process automation and AR/VR to support/complement human workers)

reducing repetitive tasks, improving productivity and security. To achieve this, European organizations

improve their capability to manage, retrain and upskill the workforce but also face problems of

motivation and resistance. A substantial minority of workers however may be unhappy or displaced.

Europe will make progress towards a sustainable Data Economy, with policy initiatives promoting the

ICT and electronic industry full transformation to climate-neutral and energy efficiency practices. In

this scenario we foresee progress towards a Global Digital Cooperation strategy led by the EU and a

more proactive European role in the development and adoption of standards and interoperable

technologies on the global scene, leveraging the power of the single internal market.

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The European Data Market Monitoring Tool – Baseline Scenario 2025 for EU27

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4.2 High-Growth Scenario (Pre-Covid)

This scenario foresees a faster growth trajectory of the Data Market and economy, boosted by

favourable economic conditions, by strong investment, proactive policies, and effective collaboration

between the MS at the EU level. By 2025 we expect a higher take-up of multiple technologies than in

the baseline scenario (AI, Big Data, IoT, robotics, 5G, new materials, blockchain…) with European

enterprises fully embracing multiple innovation and the power of data. In this scenario, business

competitiveness is enabled by platforms and ecosystems where innovation and network effects (each

additional user multiplies benefits for all users, increasing the attractiveness of the platform) create a

positive feedback loop, reinforcing the positive impacts. All industries will keep pace, also the public

sector, even though the intensity of data innovation will grow faster in Finance, Manufacturing,

Professional services, ICT and Media. European industries will exploit platforms to combine data with

AI and machine learning, spreading intelligence from the core to the edge of their networks, turning

data into action and action into value. The supply-demand dynamics will become more balanced

between technology-push and demand pull, with a fully developed ecosystem generating positive

feed-back loops between data companies and users. Horizon Europe, Digital Europe and Connecting

Europe Facility programmes deliver a strong boost to European AI research and innovation capabilities

building an ecosystem capable of global leadership. To achieve the benefits of this scenario, Europe

must fully capture the AI opportunity.

In this scenario, the EU27 GDP compound annual growth rate in the period 2019-2025 (+2.0%) will be

1.5 times higher than in the Challenge scenario and 40% higher than in the Baseline scenario. This will

accelerate the investments in the digital economy and consumer willingness to spend. In the European

Union public and private investments will accelerate in Artificial Intelligence, advanced robotics,

automation as well as new skills. As a result, the Data Market is forecast to reach 107 billion Euro in

the EU27, with a compound annual growth rate of 10.7% between 2019 and 2025. The Data Economy

will grow faster than the Data Market, reaching a value of 827 billion Euro in the EU27, with an

incidence on EU GDP of 5.9%, against the 4.0% of the Baseline scenario. Enterprises will add 4.8 €

million data professionals’ positions between 2019 and 2025 (compared to 3.2 € million in the

previous scenario).

Given the acceleration of technology trends, this scenario foresees a deep transformation of business

processes and the work culture, where change management and HR management become critical

success factors. As in the Baseline scenario, European enterprises multiply the use of "digital co-

workers" (using intelligent process automation and AR/VR to support/complement human workers)

reducing repetitive tasks, improving productivity and security and managing digital transformation.

Besides automation, enterprises engage in "augmentation" of human resources providing

technologies enhancing their physical and intelligence capabilities. Organizations succeed in managing

the transformation of the work culture for digital transformation through a combination of incentives,

intensive training investments, identifying appropriate job roles and tasks in open ecosystems. On the

other hand, initiatives to develop digital skills are successful: the Digital Europe Programmes delivers

a boost to the supply of advanced digital and data skills, the revised Digital Education act helps to

improve digital learning, and the networks of Digital Innovation Hubs play their role in providing

internships, training and experimental spaces for companies to learn about new technologies.

In this scenario, strong investments and MS cooperation help Europe to develop fully independent

data infrastructures and digital resources, to shape global digital governance rules with EU values,

becoming a leader in the Big Data-AI space. As foreseen by the digital and data strategies, Europe

succeeds in achieving technological sovereignty. Europe’s share of the global Data Economy is well on

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the way to become equal to its economic weight by 2030 thanks to a successful single market for data.

The new Horizon Europe and Digital Europe Programmes as well as the EU High impact projects

successfully catalyze private investment to develop data sharing and interoperable architectures. The

successful deployment of an EU cloud infrastructure and cloud services marketplace satisfies industry

and SMEs needs. The successful development of common EU data spaces in most sectors achieves

economies of scale and supports the rise of the platform economy, enabling companies to deal with

multiple innovation.

By developing a flexible legislation based on the risk management principle, but not hindering

technology progress. Europe becomes a successful global leader of trustworthy AI governance.

However, since this will take some time, it will be difficult to bring under control ex-ante specific

applications such as remote biometric identification (facial recognition) which are already in the

market. We foresee a scenario where Europe will bring ex post some order and respect of ethical

principles to applications such as facial recognition. Fast progress with a new Data Act, Digital Services

and Competition framework enhance data access, sharing and re-use, achieve fair playing field and

build the basis for the effective single market for data.

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The European Data Market Monitoring Tool – High Growth Scenario 2025 for EU27

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4.3 Challenge Scenario (Pre-Covid)

In the Challenge scenario, a combination of economic, social and technology threats overcome

European innovation forces, which become lost in a maze of barriers, resulting in much slower Data

Market and Data Economy growth. This scenario examines the main fault points and critical issues

which may drag down Europe’s potential for innovation and growth, to be able to anticipate and fight

them.

The first threat is lower GDP growth, estimated at a compound annual growth rate in the period 2019-

2025 of 1%, substantially lower than in the other scenarios. Trade wars, political conflicts, and

unexpected events such as the Coronavirus pandemic are the main drivers of this growth slow-down.

Lower GDP growth means lower overall investments and consumers’ willingness to spend. Even

though research and innovation investments are partially countercyclical and in a low-interest rate

world, so that public investments are easier to make, in this scenario governments have many other

demands on their budgets and private enterprises have less resources. So, investments inevitably slow

down.

The second main threat is if the digital Europe and data strategies are not implemented successfully

and fail to achieve many of their objectives. This may happen if a combination of insufficient

investments and lack of collaboration at EU level lead to an uneven development of data

infrastructures and digital resources. Without an effective data governance framework and incentives

for stakeholders to increase data sharing, there is a risk that the Data Market will remain fragmented.

Europe fails to achieve technological sovereignty and the lack of widespread European cloud

infrastructures and services results in dependency of EU industries, particularly SMEs, on global

platforms, with the risk to have low control of European datasets. In this scenario it is possible that,

notwithstanding the GDPR, many Europeans have no visibility and very little control on the use of their

personal data: this hinders the willingness to share and reuse personal and non- personal data for

social good. If the development of common data spaces is slow and does not deliver the expected

boost to industries across Europe, this may hinder the rise of the platform economy, miss the

development of economies of scale and reduce the incentives to fight market fragmentation for

innovative services.

In this context and missing public support, European enterprises struggle to manage multiple

innovation and adapt to the platform economy, losing competitiveness in the global market.

Guidelines and data ethics principles multiply, but European enterprises struggle to develop skills and

capability to manage risks and in many cases refrain from data-driven innovation for fear of business

risks. Insufficient interoperability and standardization hinder collaboration and innovation. European

organizations struggle to adapt to the new work environment and to motivate the workforce.

Fragmented ecosystems and insufficient investments in re-training and re-skilling increase the skills

gap and slow down digital transformation, while leaving many workers unhappy or displaced.

Technology-driven automation and augmentation are badly managed and create a negative reaction

by the human workforce slowing down acceptance and digital transformation.

This scenario foresees a negative self-reinforcing circle, where less positive global economic conditions

discourage investments and weaken global demand with a negative impact on European growth. A

slower pace of digital innovation deprives the economy of the boost to growth potentially given by

data-driven services and products, while enterprises find competing in international markets more

difficult.

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As a result, in this scenario the Data Market is forecast to reach 72 billion Euro in the EU27 with a

compound annual growth rate of 3.7% between 2019 and 2025. In the same context, the Data

Economy will reach a value of 432 billion Euro in the EU27 with an incidence on GDP of 3.3%, compared

to 4% in the Baseline scenario 2025.

The number of data professionals will still increase to 8.4 € million in the EU27 by 2025, adding 2.4 €

million data professionals’ positions in the period 2019-2025. We estimate a potential data skills gap

of approximately 484,000 unfilled positions in the EU27 by 2025, corresponding to 5.7% of total

demand, as demand will still grow faster than supply. The lower supply will be due mainly to lower

market entries from other careers and less upskilling-retraining initiatives, because of the lower

attractiveness of the Data Market. The uneven diffusion of data innovation will result in a mismatch

between demand and supply by geographical area across the Union, with unemployment in some

regions and unsatisfied demand in others.

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The European Data Market Monitoring Tool – Challenge Scenario 2025 for EU27


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5. A CHANGE OF PACE IN DATA POLICIES

5.1 The new Data Policies and the EDM Monitoring Tool

The digital policy package presented in February 20206 by the new Commission led by Ursula Von der

Leyen widens considerably the scope and breadth of data policies, reflecting the new policy awareness

about the critical role of data for the competitiveness of the European economy. Only a few years ago

Big Data was a topic of interest mainly to the ICT industry, while today there is a widespread awareness

of the social and economic impacts of data-driven innovation. One of the key turning point was the

Facebook-Cambridge Analytica scandal in early 2018, when people discovered that the British firm

had illegally harvested the personal data of millions of people's Facebook profiles without their

consent and used it for political advertising purposes. The timely implementation of the GDPR in May

2018 was also a call to arms, forcing both consumers and all data owner organizations not only to be

aware of, but also to take action on personal data privacy protection. But 2019 was the year when

Artificial Intelligence became a household word with accompanying concerns and endless debates

about potential risks of discrimination, weakening of democracy, and lack of transparency. All these

strands of debate are today collected and considered in the comprehensive digital strategy package

published in February 2020. We review here the main components of these policies, how they can be

monitored by the EDM indicators and how their potential achievement and degree of success can

shape the Data Economy forecast scenarios (described in chapter 3).

In the “Political guidelines of the Commission 2019-2024”7, the development of a Digital Europe is

indicated as one of the six main priorities of the new Commission, recognizing its capability to support

the achievement of other high-profile policy goals, such as a climate-neutral continent and a fair and

open society. The transformation potential of data technologies is clearly recognized in von der

Leyen’s political agenda, as well as the need to understand and manage the whole range of data

positive and negative impacts, with a specific attention to data ethics and the development of

trustworthy Artificial Intelligence (AI).

The Communication “Shaping Europe’s digital future”8 is articulated in four main action areas,

covering all the framework and enabling conditions to develop “a digital society based on European

values and rules” (Technology for people, A fair and competitive economy, An open, democratic and

sustainable society and Europe as a global leader). The Data Strategy is a key component of the

economy action area together with actions to update competition rules and develop an industrial

strategy, among others. This matches very well the rationale of the EDM scenarios for the

development of a balanced European Data Economy, which have long posed as a key enabling

condition the adaptation of the overall economic and regulatory framework (not limited to ICT or

R&D).

The European Strategy for Data’s four main pillars also mirror the priorities highlighted by the EDM

Monitoring Tool for the development of the Data Economy. The Pillar A on the development of “A

cross-sectoral governance framework for data access and re-use” brings together several initiatives to

enable and stimulate data sharing, but at the same time ensure a fair playing field for all organizations.

This recognizes the need to deal with data as a strategic asset influencing power dynamics in the socio-

economic system. Europe’s ability to achieve this goal is a major differentiating factor between the

three alternative scenarios of the Data Economy presented in this report. The Data Strategy’s Pillar B

6 https://www.orgalim.eu/news/commissions-digital-package-roadmap-towards-europes-digital-future 7 https://ec.europa.eu/commission/sites/beta-political/files/political-guidelines-next-commission_en.pdf 8 https://ec.europa.eu/info/sites/info/files/communication-shaping-europes-digital-future-feb2020_en_4.pdf

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on Enablers (Investments in data and strengthening Europe’s capabilities and infrastructures for

hosting, processing and using data, interoperability) and Pillar C on Competences (Empowering

individuals, investing in skills and in SMEs) cover the needs for investments, interoperability,

standardization and infrastructures as well as skills. The EDM’s indicators on the numbers and

penetration of Data Users and Data Companies, as well as Data Professionals and the Data Skills Gap,

can help monitoring the development and achievement of these policies.

Finally, the Data Strategy Pillar D for “Common European data spaces in strategic sectors and domains

of public interest” is driven by the need to accelerate data sharing and make B2B data sets actionable

for data-driven innovation, a priority often underlined by this study analyses. The EDM Monitoring

Tool indicators on data innovation diffusion by industry are also useful to provide a baseline for this

policy area. We have also produced several in-depth stories based on original case studies about the

state of the art and the dynamics of data-driven innovation and data sharing in strategic sectors: two

of them (about utilities and healthcare) are illustrated in the following paragraphs.

Concerning Europe’s international role, the Digital strategy for the first time highlights as a priority the

achievement of “technological sovereignty”, defined as “ensuring the integrity and resilience of our

data infrastructure, networks and communications” and creating the conditions to “reducing our

dependency on other parts of the globe for the most crucial technologies”. This is a relevant change

of policy, even though the Communication clarifies that this “sovereignty” is defined positively to

achieve independence rather than against anyone else. From the point of view of data infrastructures,

there is a strong concern about cloud computing, since the public cloud computing market is highly

concentrated in the hands of a few global providers from the US (Amazon AWS and Microsoft). In this

field, the EDM’s international indicators provide useful intelligence about the comparative

development of the EU Data Market and Data Economy with the USA, Brazil and Japan, as illustrated

in the chapter 6 of this report.

Another key component of the digital strategy is the “White Paper on Artificial Intelligence” which

presented policy options for public consultation and a “Commission Report on safety and liability

implications of AI, the Internet of Things and Robotics”, providing background information on the

type of risks that the White Paper proposes to deal with (to be followed by legislation proposals in the

4th quarter of 2020). The White Paper is organized around two main goals, the creation of an

“ecosystem of excellence” to build European capabilities for AI and an “ecosystem of trust”, to make

sure that the legislative system is updated to deal with new challenges, based on the choice to develop

a risk-based approach where only technologies and solutions with high potential risks for human rights

and social welfare are managed through regulation or other tools. This approach will be finalised and

completed based on the feedback from public consultation. In our scenarios, we consider different

assumptions about the final deployment and effectiveness of this approach, including the potential

timing: considering the need to build consensus and proceed with the agreement of all Member

States, there is a risk that the European decisions will be late to influence the AI global market as

strongly as GDPR did on privacy protection.

To conclude, it is useful considering how the different policy visions of the Data Economy are being

shaped in different socio-economic systems, specifically the US, China and Europe. According to a

recent special report by the Economist9 , there are three main models or visions of the Data Economy,

mirroring the three main metaphors used for data and three different ways to extract its value, but

none of them is fully coherent with reality.

9 The Data Economy, the Economist, February 22, 2020

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The first is “data as oil”, data as the fuel of the economy: this rings true because of the efforts and

investments needed to extract and exploit data, but the analogy breaks down because of the difficulty

to trade data and use it as a corporate asset. The second metaphor is “data as sunlight”, because like

solar rays, data is everywhere and can be re-used indefinitely: this is the main rationale of the open

data movement and the motivation to use data for social good. Nevertheless, this type of Data

Economy also finds objective obstacles in reality, because not all data can be open and shared (due

e.g. to personal data protection) and because generating data is expensive and requires investments

which must have a return. The third approach explored by the Economist is “data as infrastructure”:

a kind of digital twins to physical roads, requiring public investments and new institutions to manage

them. Many different typologies of “data roads” can be designed, local or global, and different kinds

of new organizations will arise to manage them, private or public or a mix of the two, like data trusts,

data cooperatives, personal data stores.

The “data as infrastructure” model is the type of Data Economy which most closely reflects the

ambitions of the European policies, building on collaborative efforts and a common approach to data

governance. This is different from the US, where the dominating trend is the “data as oil” approach

(whoever extracts data owns it and exploits it); while in China data is considered a public good and

directly controlled by the government. This illuminating analysis is very useful to understand the

potential pros and cons of the different visions of the Data Economy, always considering that the three

ways to exploit data, as oil, sunlight or infrastructure, will be present in each socio-economic system

in different combinations and with different prevalent models.

5.2 The evolution of Data Ethics

The debate on the social and ethical challenges of Big Data is not new, but the emergence of AI has

added a whole new range of challenges to be managed, and this in turn has created what is now

defined as the “data ethics”. Data Ethics today encompasses the ethics of handling personal data

(including, but not limited to, privacy protection as defined by the GDPR), but also non-personal data

(as may be generated by IoT systems and often inextricably linked with personal data) and of course

the ethics of data-driven technologies such as algorithmic systems powering AI-supported decision

systems. There is a multiplication of guidelines particularly on AI, starting with those published by the

OECD, the EC High-Level Expert Group on Artificial Intelligence (AI HLEG), as well as the human-centred

principles for AI adopted by the G20 in June 2019. Initiatives and position papers around data ethics,

usually in the context of AI strategies, have been published by several governments, including France,

Germany, Denmark, Norway, Portugal, Czechia. Several leading vendors have also published their data

ethics principles, including Microsoft, Google, IBM and Workday, while Amazon characteristically

sustains that technologies are ethically neutral but will take action if it discovers that customers use

its technologies for illegal purposes including the violation of human rights. This multiplication of

principles and guidelines is to some extent bewildering for businesses, particularly for SMEs. An EC

intervention would be useful to provide some clarity and guiding principles.

Initially, most of the data ethics debate focused around a defensive approach, how to manage and

defuse potential negative impacts. Today, there is an increasing attention towards a proactive

approach, that is how to use data for ethical objectives. For example, the German Data Ethics

Commission in its opinion issued in October 201910 highlighted the potential imperative to use data

for social good, and therefore the need to balance personal data protection with social welfare, a

perspective of primary relevance for government decision makers. For a balanced and socially positive

use of data-driven innovation, governments must deal with legal issues (comply with existing

10 https://datenethikkommission.de/wp-content/uploads/DEK_Gutachten_engl_bf_200121.pdf

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regulation but still find ways to use data), social issues (understand and manage the potential risks of

discrimination and social exclusion) and ethical issues (respect the fundamental rights of citizens but

also employ data for social good).

Perhaps the most compelling example of these potential benefits and challenges is the case of the

current COVID-19 (coronavirus) epidemic. The Chinese government applied extensively AI and data

analytics to provide a quick and effective response to the emergency. As reported by WHO11: "China

has capitalized on the use of technology, big data and AI for COVID-19 preparedness, readiness and

response. Authoritative and reliable information, medical guidance, access to online services, provision

of educational tools and remote work tools have been developed in and used across China. These

services have increased accessibility to health services, reduced misinformation and minimized the

impact of fake news." However, it was very clear that this use of technology was decided by the

government without any concern for the privacy or willingness of citizens, as is normal in authoritarian

social systems.

South Korea too is using smartphones to help track citizens movement and particularly those placed

in lockdown to slow down the epidemic12, over 30,000 citizens so far. However, this seems to happen

with the consensus of citizens and under greater transparency than in China. At the time of writing

this report, a flurry of smartphone applications for contact tracing are being developed in Europe but

taking into account the principles of personal data protection, concerns remain. 13 There has been a

strong acceleration in the use of Big Data and AI technologies to fight the pandemic and this is likely

to make a strong impact in the healthcare and government ways to use technologies for social good

in the next years14.

5.3 Big Data as the lifeblood of the next innovation waves like AI

As pointed out in the previous part of this report and, indeed, throughout this European Data Market

update study, data as such, their affordability and availability, their capability to be exchanged and

shared, together with the possibility to perform sophisticated analysis through Big Data and Analytics

techniques constitute the very basis of the fruitful application of innovative technologies across the

European industry. The following pages summarize the key policy elements that we found while

analyzing the use of data and data-driven technologies in different sectors, such as the Utility industry

and the Healthcare industry in Europe.

5.3.1 AI paving the way for the Cognitive Revolution across European Utilities

Utilities face some of the strongest headwinds in their century-old history. Energy technology is

changing how energy and resources are generated and consumed, reducing demand and making the

energy system more complex and less predictable. Digital technology has raised the bar for utilities

customer service while at the same time lowering the sector’s barriers to entry. The industry is

determined to use data as a compass to address this change, leveraging data technology like analytics

and artificial intelligence (AI) to excel in operations, improve customer satisfaction and create new

revenue streams and business models. The EU’s policy ambition in decarbonizing and unbundling the

11 https://www.who.int/docs/default-source/coronaviruse/who-china-joint-mission-on-covid-19-final-report.pdf

12 https://www.technologyreview.com/s/615329/coronavirus-south-korea-smartphone-app-quarantine/

13 https://www.politico.eu/article/how-to-choose-a-coronavirus-tracking-app-wisely/ 14 https://www.idc.com/getdoc.jsp?containerId=EUR146202420 “Preparing for COVID-19 Phase2: adopting contact tracing”

https://www.who.int/docs/default-source/coronaviruse/who-china-joint-mission-on-covid-19-final-report.pdf

https://www.idc.com/getdoc.jsp?containerId=EUR146202420

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energy value chain and creating a competitive energy market has made European utilities among the

most innovative in the world, and this extends to pioneering use of AI.

Lying at the core of the Europe’s economic system, European utilities are undergoing some of the

most significant and structural changes ever in decades. From an operational perspective, the power

system is shifting from centralized generation and predictable demand to complex grid that integrates

growing amounts of variable and distributed renewable generation, making it much harder to match

predicted demand and planned supply; In business terms, stagnating demand is reducing the value

generated by energy production to the benefit of downstream segments in the value chain, thus

forcing utilities to search and create new revenue streams and/or look for new business models in the

first place.

Faced with these challenges, European utilities are increasingly turning to data-driven technologies to

excel in operations, improve customer service satisfaction and create new revenue streams and

business models. Indeed, Big Data technologies, smart meter solutions and the increasing deployment

of the Internet of Things (IoT), are fuelling an operational and technological revolution in European

utilities and leading to the rapid introduction of Artificial Intelligence (AI). In turn, AI is starting to

emerge as the technology game changer for the industry, helping utilities make operation more cost

effective while ensuring optimal utilization of infrastructure and resources to balance supply and

demand safety and reliability.

The utilities industry sits at the core of the European economic system. Energy utilities were the main

driving force behind the EU’s progress towards its 2020 targets on climate change and energy15 and

will continue to be amongst the primary contributors to Europe’s energy ambitions going forward.

The new EU 2030 climate and energy framework16 – progressively enabled through the Clean Energy

for All Europeans package – is a testament to Europe’s role as leader of the global clean energy

transition. It builds and expands on more than 20 years of EU-wide reform of the energy industry,

which started from the first liberalization directives of the second half of the 1990s and continued

through the Third Package for Electricity & Gas markets of 2007. The overarching objective of these

reforms is to improve the functioning of national energy markets by strengthening their competitive

foundations and laying the groundwork for their integration into an energy union with a common

governance, energy security and climate strategy. This two-decade long process has made the

European energy system, along with the utilities that operate in it, one the most competitive and

innovative in the world.

15 The primary objectives of Europe 2020 are a 20% reduction in greenhouse gas emissions compared with 1990 levels, a 20 % share of

renewable energy in gross final energy consumption, and a 20 % cut in energy consumption compared to a 2020 business-as-usual

projection (https://ec.europa.eu/clima/policies/strategies/2020_en)

16 The 2030 climate and energy framework includes EU-wide baseline targets and policy objectives for the 2021-2030 period, including at

least a 40% cut in greenhouse gas emissions (from 1990 levels), at least 32% share for renewable energy, and at least 32.5% improvement

in energy efficiency. (https://ec.europa.eu/clima/policies/strategies/2030_en)

https://ec.europa.eu/clima/policies/strategies/2020_en

https://ec.europa.eu/clima/policies/strategies/2030_en

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To better understand how AI and data-driven technologies are impacting utilities industries, we

carried out six case studies which are briefly summarized in the table below:

Company Business Challenge Area of AI Deployment Specific Benefits of AI Wider impact

Atos Cost and efficiency of energy theft detection and claim processing

• Non-technical loss (NTL) pattern detection and case management

• Robotics claim process automation

• Improvement of hit rate of NTL inspections from 5% to 30% over the first two algorithm runs. Project-specific ROI of under 12 months

• 75% reduction in the NTL claim management process

• Improved energy recovery rates and network safety

• Redeployment of resources to other areas of revenue protection (e.g., engagement with local authorities, subcontractor education, etc.)

Enel Green Power

Cost of PV (Photovoltaic) plant inspection and process efficiency from fault detection to maintenance execution

Real-time PV fault recognition onboard in-flight drones and automated work order creation

• More efficient plant inspections and more accurate fault detection

• Reduction of the detection-to-repair process from days to hours

• Plant production improvement by extension

• Possibility to automate the inspection process across plant fleet

E.ON Effectiveness of fault detection and efficiency of maintenance on the medium-voltage grid

Fault prediction through data inconsistency and pattern recognition

• Overall, 30% improvement over conventional maintenance

• 100% to 200% increase in accuracy of defect prediction after nine months of training the algorithm

• Improvement of distribution reliability and security of supply

• Better maintenance and grid development planning

• Horizontal and vertical extension of the solution to cover other assets

Innogy • Consistent handling of mass-market customer inquiries

• Efficient management of external service providers and service quality

Automatic identification and pre-sorting of customer inquiries through self-learning content analysis and data extraction

• 97% of customer inquiry cases identified and classified correctly on an ongoing basis

• Automatic case routing to appropriate staff through CRM system

• Automatic proactive customer updates (including tariff quotes) through process management service

• Automated performance (volumes and quality) reporting

Fortum • Heat consumption optimization for utility customers

• Efficient and sustainable production and supply of district heat for utilities

Heat consumption pattern prediction using weather, behavioural and energy flow data

• Reduction in district heating costs by 10% to 20% and lower carbon footprint for customers

• Decrease or shift in peak hot water demand and related load

• Better indoor air quality through

• Dynamic heat pricing

• Ability to buy back heat from customers

• Possibility of using heating as energy storage systems to balance variable wind power production

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smoother temperature and humidity profiles

E.ON Machine uptime improvement, production, quality and energy optimization for large industrial energy customers

Root cause, optimization, and predictive analytics based on an integrated energy and process digital twin

• Up to 40% lower energy costs 30% lower carbon footprint on average across more than 5,000 customer sites using energy analytics only

• Better energy usage visibility and awareness

• Behavioural change through custom energy efficiency guidelines

• Energy usage optimization and efficiency investment

The case studies have shown that AI deployments across European utilities have not only helped to

successfully address a variety of business and operational challenges but, more importantly, have also

produced quantifiable specific benefits for the utilities themselves often leading to more general

positive impacts not directly attributable to AI. When looking at the case studies in some more details,

we could argue that:

• The case studies outlined in this research do not represent the mainstream reality for now but their significance – in both “traditional” data-driven use cases (such as those of predictive maintenance, fieldwork optimization and fraud detection) as well as in more innovative realities (such as automated customer service, flexibility, and grid balancing) – is expected to grow remarkedly over the next few years.

• The importance of the AI implementation and of the subsequent “cognitive revolution” in the Utilities industry is also destined to increase as a direct consequence of Europe’s legacy of early energy market liberalization and leadership in energy system transformation and climate initiatives. In other words, European utilities (especially those operating in the energy market) are on average more advanced than their peers elsewhere and this constitutes a fertile ground for further and more beneficial implementations of AI and data-driven technologies in the sector, thus reinforcing Europe’s leading position vis-à-vis other regions of the world.

• Yet, there is room for policy initiatives at both European and national level as uneven energy

market guidelines and regulatory incentives are still at play across the Member States. Some

use cases, for example, have been pursued successfully and systematically in some European

countries but not in others. To achieve the benefits of a truly European level-playing field and

of a truthfully harmonised energy market, more policy guidance would be beneficial.

• The increasingly accurate information produced by AI, and their associated potential on the

renewable energy production, are likely to spark higher investments from businesses and

augment the willingness of individuals to invest in renewables. For this to concretely

accelerate the energy transition towards renewable energy sources and the factual

contribution to the EU’s long-term strategy for a climate neutral economy, more help (also in

the form of funding or financial help otherwise) is likely to be needed, especially for SMEs

and individuals.

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5.3.2 Health Data and Data-driven Innovation in the European Healthcare Industry

A growing number of European Healthcare Systems are embarking on long-term reforms to improve

outcomes and foster innovation with the ultimate goal of benefiting patients, while, at the same time,

ensuring long-term sustainability of healthcare services provision. An un-locked potential is clearly

there as recent evidence has highlighted that the majority of healthcare providers (59%) has not

adopted a Digital Transformation roadmap yet and only the 6% has established a unique roadmap for

Digital Transformation and general business strategy17.

This unexplored potential of the use of Big Data and Analytics (BDA) in healthcare is eliciting a new

wave of interest in data-driven value creation, which, in the medium to long run, will enable to reward

performance rather than just volume. According to the IDC DX Sentiment survey 201818, over 60% of

the European healthcare providers reported that developing data management is a priority. Indeed,

being able to analyse and use data for process automation and decision support, in a granular,

accurate, safe and context-relevant way, is key to long-term competitiveness and sustainability.

AI is still in its infancy and only the 30% of European healthcare providers are already using/testing or

have immediate plans for the technology, adding to another 23% evaluating AI use cases 19. The top

three BDA use cases that European healthcare providers are working are Clinical decision support

(16%), Illness progression (15%) and Patient engagement (14%)20. Patient engagement is a key

priority for almost 40% of European healthcare providers, particularly among countries that are

experimenting with value-based reimbursement models structured around patient experience and

outcomes, while the most significant AI use cases that European healthcare providers are working on

are: Personalization of clinical pathway (10%) Clinical decision support (9%) and Patient risk (9%)21 .

The most significant AI use cases that European healthcare providers are working on are:

• Personalization of clinical pathway. As PHM is transforming the traditional hospital focused approach into a value care to deliver more efficient outcome using fewer resources, AI and machine learning algorithms can derive actionable insights from the untapped datasets essential for population health programs. AI can, for example, elaborate real-time data to pinpoint specific demographics where health issues exists and target them precisely with ad-hoc treatment program.

• Clinical decision support. A machine learning system can provide a high level of clinical accuracy and a coverage of a broad range of conditions. Symptoms can be entered via natural language and can be used to drive diagnoses and the level of care direction.

• Patient risk. AI can predict the future of patient's health with better accuracy, as the risk of contracting specific diseases. AI system can predict the outcomes of hospital visits to prevent readmissions and shorten the amount of time patients are kept in hospitals.

• Compliance check. The healthcare industry is highly regulated but maintaining compliance within evolving patchworks of national and regional regulations can be strain on providers'

17 Source: IDC DX Executive Sentiment Survey, May 2018 (n=66) 18 Source: IDC DX Executive Sentiment Survey, May 2018 (n=66) 19 The IDC European Vertical Markets Survey is an annual landmark study of IT solutions, investment priorities, and emerging technologies. In the 2018-2019 version, the sample covers over 77% of the European economy (in terms of GDP of the 40 countries). Respondents are distributed across Western Europe (UK, France, Germany, Italy, Spain, Netherlands, the Nordics) and Central & East Europe (Russia, Poland, and Czech Republic). The survey was conducted in the native language of each country, using either telephone interviewing (CATI) or web interviewing (CAWI) systems. Eligible respondents are individuals primarily involved in IT and/or business decisions at their companies and ranked director level or above. Results are analysed by vertical market and company size and represent a basis for a series of demand-side reports published by IDC. 20 Data retrieved from IDC European Vertical Markets Survey, 2018–2019 (n= 290 [WE = 232, CEE = 58])

21 ibidem

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limited resources. The adoption of AI in this area optimize administrative procedures and frees experienced caregivers from routine tasks.

• Optimization of resource utilization. Machine learning and AI have the potential to provide the front line with the real time wisdom to improve the speed and the quality of the hundreds of decisions they make each day in order to improve the flow of patients through the various clinical services involved in delivering appropriate care.

Figure 2 Top three use case for AI among European healthcare providers

Source: IDC European Vertical Markets Survey, 2018–2019 (n= 290 [WE = 232, CEE = 58])

We analyse four different case studies (see table below):

• The Secondary Use of Data in Finland - in the health and social welfare sector there has been

an extensive work between the public and private sectors to promote the secondary use of

health and well-being data, which has led the creation of a new ecosystem through a national

development project, leading to the development of a ground-breaking new legislation and

the establishment of a permit authority for secondary use of health data. Interviews

conducted with Jaana Sinipuro, Hannu Hämäläinen e Antti Kivelä (SITRA).

• The Health Data Hub in France - In 2018, president Macron launched this initiative to establish a nationwide data platform. The project is today strongly pushed forward from the French Health Act "Ma Santé 2022", approved last July, and including the creation of the "Espace Numérique de Santé" (ENS – e-health personal space) with the aim to establish a more efficient and patient oriented healthcare system by leveraging the power of data and artificial intelligence. The project goal is to enrich and enhance the National Health Data System (SNDS - Système National des Données de Santé) by including the wider French heritage of health data in one place, for open use by researchers, healthcare professionals, care institutions, start-ups, insurers, etc.

• The development of Data Policies in Portugal - In August 2019, the Portugal Health Ministry has made available the strategic document "From big Data to smart data: putting data to work for the public's health", that outlines the vision, key areas and principles for secondary use of data, advanced analytics and artificial intelligence to improve Portuguese population´s health. There are several initiatives and pilot projects, that are testing the capabilities of AI and providing evidence to support the development of new data management and governance policy.

• ARIA’s Health Data Warehouse and Business Intelligence Competency Center (Italy) – In July 2019, Regione Lombardia (Lombardy Region, Italy), has established a new Regional

company called ARIA (Agency for Innovation and Procurement) from the merge of ARCA

(regional agency for procurement) and Lombardia Informatica (the regional in-house digital

company). Within its mandate, ARIA has the specific aim to enhance the value of all regional

health data assets. Interviews conducted with Giuseppe Preziosi (Aria)

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Country Challenges/ business needs

Key initiatives and application areas for secondary use of health data

Benefits (current or expected)

Output to date

Finland • Making use of the huge amount of health and social care data collected from different sources and registers

• Offering to researchers and organizations looking to leverage health data for innovation, a coherent, and simple environment for accessing and using the data in a legally compliant way

• Maintaining public trust in government capability to manage data towards common good and respect of individual rights

• Creation of a data access permit authority and the related organizational, infrastructural, and legal conditions

• Key application areas: innovation in clinical and public health research, as well as in the private sector (pharma and life sciences) R&D to promote economic growth

• Simple yet comprehensive permit procedure to get access to data for R&D scopes

• Strong knowledge base and experience on managing a complex ecosystem of stakeholders, sometimes with conflicting interests, and to enable sustainable cooperation

• Establishment of a single authority that work as a one stop shop for permits regarding several registers

Sitra launched 8 pre-production projects, whose lesson learned, and outcomes have been then integrated into an action plan for the new permit authority once in operation.

France • Fragmentation of the healthcare ecosystem

• The need for a secure governance framework enabling the ethical use of data for analysis and research

• The need for establishing a regulated platform for data access and use as well for facilitating the interaction of multiple stakeholders (collecting, producing and using data)

• Establishment of a Health Data Hub (HDH) to manage a large number of data sources with harmonized rules for data access, and use.

• Key application areas for secondary use of research include the development of RWE research, support to clinical trials, development of precision and personalized medicine, predictive clinical decision support solutions

• A harmonized standard of data access at national and international level

• Patients/citizens access and control over the use of their data

• Accelerated innovation and personalized services

19 pilot projects have been launched projects with various focuses ranging from breast cancer to health surveillance, using predictive tools enabling predictions and insights able to drive decision making

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Portugal • The need to transform the National Health Service into an intelligent, data driven NHS to drive efficiency and better patient outcomes

• The need to define a framework for the secure collection, storage and reuse of health data

• Establishment of a national strategy for health data management and for secondary use

• Funding of AI enabled research programs and projects aimed at the development of clinical decision support; personalization of clinical pathways; patient risk management; optimization of resources utilization

Creation of

• A data infrastructure that supports population health management

• Predictive solution aimed at reducing skin cancer mortality

• Predictive solution aimed at optimizing the delivery of emergency services

There are several initiatives and pilot projects, that are testing the capabilities of AI and providing evidence to support the development of new data management and governance policy.

Italy (Lombardy region)

• Need to integrate and use >10 years of collected health data in the regional Data Warehouse

• Development of infrastructural, organizational and policy framework for the use of and access to data

Predictive BDA models and Data health hub

• Patient risk

• Population risk management

• Illness progression and clinical decision support

• RWE driven research

• Enablement of new data driven research streams and collaboration at national and international level

• Establishment of a PoC framework to predict cardiovascular risk with accuracy between 96,22% and 97,96%

• Launch of a pilot determining the clinical best next action for Alzheimer patients

Several Initiatives to support the regional healthcare service in areas such as: planning and management, costs rationalization, evaluation of safety and efficiency of clinical pathways and integrated patient journeys, as well as health risk prevention

In terms of the triggering challenges, security and data privacy concerns are on top, due to the

highly regulated environment of the healthcare industry. However, the common theme emerging

from the case studies are threefold:

• The establishment of a regulatory framework for the use of and access to data. This involves multiple players in the public and private healthcare arena to establish partnerships and create a collaborative environment. It requires all stakeholders to agree on the value of data as a shared asset, and to actively promote initiatives where common standards and a one-stop-shop approach to data access are brought forward. This is the case of Portugal, where the Health Ministry authority is seeking to establish a new healthcare ecosystem based on a data-driven approach towards the delivery of healthcare services across the nation.

• The collection, processing, storing and access of complex data coming from different structured (e.g. National health records) and unstructured (e.g. wearables) sources, along with semantic, geographical and time complexities. This is the case of ARIA and its collection of over 10 years of healthcare data stored in different locations, as well as Sitra's project working at establishing a common framework and developing metadata descriptions. Additionally, data collected require intelligent solutions, capabilities and skills to extract value from data and provide actionable areas for the deployment of information (i.e. population risk stratification, clinical decision support, personalization of clinical pathways, etc.).

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• Maintaining trust and ensuring security. The high sensitiveness of healthcare data requires an attentive approach to identifying and enforcing regulatory frameworks and solutions that ensure information is treated in compliance with regional and country-specific policies. The adoption of GDPR strengthens and unifies data protection for individuals within the EU, regulating how data integration happen safely. It gives individuals key control over the usage, processing and transfer of their personal data held by healthcare organizations. The transition to a VBHC model, in which care plans should be personalized and stakeholders should integrate their activities, must be underpinned by consistent information management governance that enables patient data integration across providers, processes and IT systems. GDPR is expected to provide a patient-centric ecosystem. In addition, authorities need to establish a high level of public trust for the ethical and secure use of healthcare and social population data for the public good. In this example, Finnish citizens are informed about how their data are used for secondary purposes out of primary care.

The case studies presented in this research highlight several benefits obtained by the organizations

adopting AI/ML and BDA technologies:

• The easy and convenient access to intelligent solutions for clinicians and patients offers more opportunities to advance decision making and enhance clinical process efficiency at the point of care. Portugal skin cancer screening solution is an example of how technology supports a clinical collaborative framework and enables the integration of information to serve population health management,

• More advanced predictive capabilities, allowing greater control over disease-specific variables impacting health outcomes, as well as costs and resources utilization associated with care. This approach enables to more efficiently target population segments at risk of developing chronic and long-term conditions by putting in place initiatives aimed at promoting health and preventing or delaying the development of risk factors. Predictive BDA by ARIA is an example of development of a predictive model able to effectively target cardiovascular conditions and offer an accurate estimate of the number of future cases in a specific geographical area.

• The adoption of BDA as part of their business intelligence strategy, help healthcare providers to improve the overall operational efficiency. Advanced predictive analytics model supports the definition of admission rates along with attrition rate to help with staff allocation. In Finland, for example, the new Act on secondary use of data is expected also to support the planning and the reporting duties of authorities. The aim is to reduce the healthcare costs and focus more resources on the delivery of better healthcare.

• Big data can help in uncovering unknown correlations, hidden patterns, and insights by examining large sets of data. By applying machine learning, big data can study human genomes and find the correct treatment or drugs to treat cancer or other rare disease. Clinical studies are long and expensive to implement. They provide results on the drug administration in a specific controlled frame that is not real-life conditions. Moreover, it can be difficult to compare results between different clinical studies (indirect comparison of different new treatments). Real World Data (RWD) analysis could provide exhaustive and real-life analysis. Aware of RWD potential, health authorities are developing new evaluation frames with RWE and artificial intelligence. The HDH in France is an example of how a secure and a regulated environment offer the access to relevant data for health actors but also to the means needed to analyse these data, facilitating clinical trials initiatives.

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6. THE ROLE OF THE U.K. IN THE EUROPEAN DATA ECONOMY

On 31st January 2020, the withdrawal agreement concluded between the European Union and the

United Kingdom entered into force, marking the start of a transition period due to last until 31st

December 2020. The transition period aims at allowing the U.K. and the EU to negotiate their future

partnership while ensuring the continuity of their current relations. During the transition period the

U.K. is no longer a member of the EU but continues to be subject to EU rules and remains a member

of the single market and customs union. Following the decision adopted by the European Council of

Ministers on 25th February 2020, negotiations on the future partnership between the EU and the U.K.

have started in March 2020.

As the U.K. government declared to not seek to extend the transition period beyond 31st December

202022, the time span to reach an agreement appears to be very tight, thus surrounding the future

relationship between the U.K. and the EU with uncertainty and concern of a no-deal potential

implications.

Undoubtedly, this represents an important element to take into consideration when drawing the

conclusions about Europe’s Data Market and Data Economy. As in the Second Report on Policy

Conclusions (D2.5), this chapter introduces a selected set of indicators for the U.K. and presents some

considerations about the potential consequences of Brexit on the EU Data Market and Data Economy.

The U.K. remains at the forefront of the European data-driven economy, confirming its prominent role

described in the previous reports. According to the 2019 Digital Economy and Society Index (DESI)23

tracking the progress made by EU Member States in terms of their digitisation process, the United

Kingdom ranks 5th out of 28 EU Member States (see Figure 3 below). Its score increased with respect

to 2018 (7th) due to an improved performance in all of the DESI dimensions. While performing well in

most indicators, a very high rate of regular internet use and a strong uptake of a wide variety of online

services puts the U.K. at the leading edge particularly in terms of Use of internet services. In other

domains, such as Human capital, the strong demand for ICT specialists has led to supply shortages;

measures put in place to combat this have not yet had a significant impact.

Figure 3 Digital Economy and Society Index (DESI) – 2019 Ranking

The prominence of the U.K. in the European Data Economy is confirmed by the 2019 IMD World Digital

Competitiveness Ranking (WDCR)24, which measures the capacity and readiness of 63 economies to

adopt and explore digital technologies as a key driver for economic transformation in business,

22 http://www.legislation.gov.uk/ukpga/2020/1/enacted/data.pdf 23 https://ec.europa.eu/digital-single-market/en/scoreboard/united-kingdom 24 https://www.imd.org/wcc/world-competitiveness-center-rankings/world-digital-competitiveness-rankings-2019/

http://www.legislation.gov.uk/ukpga/2020/1/enacted/data.pdf

https://ec.europa.eu/digital-single-market/en/scoreboard/united-kingdom

https://www.imd.org/wcc/world-competitiveness-center-rankings/world-digital-competitiveness-rankings-2019/

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government and wider society (see Figure 4 below). Featuring 15th in the global ranking, the U.K.

confirms the 5th place when considering the EU Member states. The report also gives some

justification about the U.K. decline from 10th to 15th. WDCR, in consistency with DESI, identifies in the

human capital context the reason of the decline. The U.K. performance has been affected by negative

perceptions about the country attractiveness for overseas highly skilled personnel and the availability

of managers with international experience and digital/technological skills.

Figure 4 IMG World Digital Competitiveness Ranking 2019

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6.1 The U.K. - A Leading European Data Economy

In line with the findings of the Second report on Policy Conclusions, the U.K.’s leadership on the overall

Data Economy in Europe is confirmed when looking at data professionals (both in terms of units as

well as in terms of skills gap) and at the role that data companies play across the Channel (see Figure

below).

Figure 5 Data Professionals, Data Professionals’ Skills Gap, Data Suppliers and Data Users in the U.K. (2019; 2025, 3 scenarios)

Source: European Data Market Monitoring Tool, IDC 2020

The U.K. holds the highest number of workers in the Data Economy with more than 1.6 € million data

professionals in 2019, projected at 2.3 € million in 2025 under the High-Growth scenario (being

overtaken only by Germany with 2.6 € million professionals), with all the other Member States well

behind in this respect. Similarly, the lack of data professionals measured as the gap between data

professionals’ demand and data professionals’ supply, in the U.K. in 2019 accounts for approximately

74 thousand units – a relatively high gap but still slightly lower than the gap of 114 thousand units

measured in Germany, the EU’s largest Data Economy. The U.K.’s data professional’s skills gap is

expected to decrease in 2025 in the Challenge scenario but to increase in 2025 under Baseline and

Growth scenarios. It is also projected to remain below the gaps measured in the three other largest

data economies in the EU - France, Germany and Italy.

The distribution of data companies confirms U.K.’s centrality in the European Data Market, as shown

in Figure 5. A total of 141 thousand data supplier companies to the U.K. has been estimated in 2019,

representing the 49% of the overall number of data suppliers in the EU28 in the same year. Britain’s

leading role on the European data suppliers’ scene is confirmed by the high penetration level of data

suppliers in data-intense sectors in the U.K. Indicator 2.2 – share of data supplier companies –

measures the percentage share of data suppliers on the total companies in the ICT and Professional

services industries. In 2019 this share amounts to 15% on average in the EU28. In the U.K., though,

the same indicator arrives at 23.1%, second only to another boosting Data Economy – Ireland,

registering 23.6%. A similar picture emerges when considering the number of data users which are

estimated at more 181 thousand units in 2019 and expected to reach the threshold of 218 thousand

in 2025 under the High-Growth scenarios. These estimates confirm the trend registered in the

previous reports and, if correct, forecast an absolute U.K.’s predominance on the data demand scene,

well ahead of all the other principal European data economies.

Figure 6 also displays an undiscussed U.K. primacy across the EU when looking at indicators measuring

the revenues and spending in terms of data suppliers’, Data Market and the Data Economy.

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Figure 6 Data Suppliers’ Revenues, Data Market Value, Data Economy Value in the U.K. (2025, 3 scenarios)

The revenues generated by data supplier companies in the U.K. amounted to more than 19 billion

Euro in 2019 and may reach 45.4 billion in 2025 under the most favourable scenario, above Germany

and the other traditional EU data economies.

The overall market of data-driven products and services is estimated at about 75.3 billion Euro in 2019

in the EU28. Of this, the U.K. generates 17 billion Euro, ahead of Germany (16.3 billion Euro), France

(9.5 billion Euro) and Italy (5.6 billion Euro). The U.K. captures therefore the largest share of the Data

Market value according to our most recent estimates with a relative portion of 22.7% of Europe’s Data

Market value. This percentage is expected to remain stable in 2020 and in 2025 – with only minor

variations by scenario. The British economy, as a result, will continue to represent almost one fourth

of the European Data Market in the next few years.

The latest release of the Data Market Monitoring Tool confirms the U.K. at the forefront of the

European scene when considering the Data Market impact on the economy as a whole (the “Data

Economy”). With 82 billion Euros of combined direct, indirect and induced impacts measured in 2019,

U.K. ranked second only after Germany with 100 billion Euros, thus representing more than one fifth

of the EU28 Data Economy in this year. The U.K.’s economy keeps high also as a portion of the

country’s GDP, significantly above the EU28 average: in 2019 it measured 3.7% - up 0.2 percentage

points from the previous year versus 2.8% in 2019 and 2.6% in 2018 in the EU28.

6.2 After Brexit: An initial policy perspective

Data flows underpin the modern economy and are vital for businesses both in the EU and the U.K.

With the withdrawal agreement put in place on 31st January 2020, the United Kingdom left the

European Union. Both the EU and the U.K. declared the aim to establish a future partnership which

reflects their political and geographical proximity and economic inter-dependence. Given the central

role played by the U.K. in the European Data Economy, reaching an agreement on data flow appears

to be of crucial importance.

In recent years, the EU has put in place a series of regulations issuing guidance on the management of

personal and non-personal data. The General Data Protection Regulation (2016/679) lays down a set

of rules for the free movement and portability of personal data in the EU. The Regulation on a


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framework for the free flow of non-personal data in the European Union (2018/1807) allows data to

be stored and processed in the entire EU without unjustified restrictions.

To comply with the EU framework of data protection laws, the U.K. fully implemented GDPR via the

U.K.’s own Data Protection Action in 2018. However, despite the U.K. Government published a plan

for technical amendments to this legislation to ensure it continues to apply in the U.K. in case of a no

deal with the EU, the ongoing negotiations on a future partnership show a much more complex

situation.

The position of the U.K. after 31st December 2020 will be the one of a ‘third country’ and, as such,

subject to an analysis and determination of adequacy to the EU data protection laws if an agreement

on an international treaty is not reached. In January 2020, the EU published a decision setting out the

road to an adequacy agreement and stating the need for the U.K. to fully respect EU data protection

rules25. On the other hand, the U.K. government appeared to be favoring a control-driven approach

to set his own agenda, instead simply of seeking an adequacy decision from the EU; in this respect

declaring the intention to develop separate and independent policies in a range of fields, including

data protection26. Furthermore, on 12 February 2020 the European Parliament adopted a resolution

in which expressed concerns about the U.K. data protection framework claiming that the U.K. does

not currently meet the conditions for adequacy27.

A deal on data would be of crucial importance for U.K. businesses. 75% of the U.K.’s international data

flows are with the EU, and a good deal of the U.K. economic activity depends on these flows. For

example, 46% of U.K. exports are to the EU, and services account for 40% of these exports28.

Should the United Kingdom leave the European Union after the transition period without a ratified

agreement establishing a future partnership, it is very likely that this will have significant, disruptive

consequences for relations between the U.K. and the EU. In this event, preparing for a no-deal appears

to concern not just national authorities but especially small businesses, which would probably be the

most affected by the related consequences.

Already in August 2019, a study conducted by the University College London29 analysed how the

disruption to EU-U.K. data flows would be unprecedented and extremely damaging for business and

the U.K. economy. In case the U.K. would not get a positive adequacy decision or in case of a no-deal

Brexit, data flows between EU and U.K. could still occur, but they will require individual organisation

to set up legal arrangements to facilitate them. Several consequences might then raise from this

situation, namely the threat for small businesses to be absorbed by larger firms, the risk of severe

fines from the EU (see figure below). In this context, the U.K. is likely to become a data protection rule-

taker and no longer a rule-maker.

25 https://www.consilium.europa.eu/media/42736/st05870-ad01re03-en20.pdf 26 https://www.parliament.uk/business/publications/written-questions-answers-statements/written-statement/Commons/2020-02-03/HCWS86/ 27 https://www.europarl.europa.eu/doceo/document/TA-9-2020-0033_EN.html 28 https://www.techuk.org/insights/news/item/15910-explaining-adequacy-personal-data-transfers-to-the-eea-under-no-deal 29 https://www.ucl.ac.uk/european-institute/sites/european-institute/files/eu-uk_data_flows_brexit_and_no-deal.pdf

https://www.consilium.europa.eu/media/42736/st05870-ad01re03-en20.pdf

https://www.parliament.uk/business/publications/written-questions-answers-statements/written-statement/Commons/2020-02-03/HCWS86/

https://www.parliament.uk/business/publications/written-questions-answers-statements/written-statement/Commons/2020-02-03/HCWS86/

https://www.europarl.europa.eu/doceo/document/TA-9-2020-0033_EN.html

https://www.techuk.org/insights/news/item/15910-explaining-adequacy-personal-data-transfers-to-the-eea-under-no-deal

https://www.ucl.ac.uk/european-institute/sites/european-institute/files/eu-uk_data_flows_brexit_and_no-deal.pdf

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Figure 7 Adequacy vs. No-Deal

As a matter of fact, the U.K. Information Commissioner’s Office (ICO), acting as the lead supervisory

authority for businesses and organisations operating in the U.K., recognized businesses concern about

the flow of personal data. For this reason, ICO published a guidance for SMEs and large enterprises on

how to prepare for a no-deal Brexit30. The guidance claims U.K.’s commitment to maintain high

standards of the GDPR and advise organizations to review their privacy information and

documentation to identify any changes that might need to take place after Brexit. More importantly,

ICO strongly recommends businesses to immediately comply with the GDPR, thus recognizing the

strength of the EU data protection system.

The ongoing EU-U.K. discussion on free flow of data and data protection is even more important when

looking at the new EU data strategy31, released by the European Commission on 19 February 2020.

Acknowledging the changing economic and societal circumstances introduced by digital

transformation, the European strategy for data aims at creating a single market for data and ensure

Europe’s global competitiveness and data sovereignty. The restoration of full sovereign control over

data protection is on the other hand the position the U.K. government seems to have assumed in this

first round of negotiations, thus confirming the interest of both parties to focus on their respective

territories.

30 https://ico.org.uk/for-organisations/data-protection-and-brexit/data-protection-and-brexit-for-small-organisations/ 31 https://ec.europa.eu/info/sites/info/files/communication-european-strategy-data-19feb2020_en.pdf

https://ico.org.uk/for-organisations/data-protection-and-brexit/data-protection-and-brexit-for-small-organisations/

https://ec.europa.eu/info/sites/info/files/communication-european-strategy-data-19feb2020_en.pdf

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7. THE EU DATA POLICY AND THE INTERNATIONAL DIMENSION

7.1 The International Indicators and the EU in 2019

According to the third and final round of measurements of the European Data Market Monitoring

Tool, providing an overview of the key indicators for the U.S., Japan and Brazil (the three extra-

European countries analysed in the framework of the Update to the European Data Market Study),

the EU27+U.K. continue to represent the second-largest Data Economy worldwide after the U.S. even

though it slips to last place in growth. The value of the Data Economy (direct and backward indirect

impacts only) in 2019 is estimated in fact at 363 billion Euro in the U.S., which is followed by the

EU27+U.K. (79 billion Euro), the EU27 (61 billion Euro), Japan (34 billion Euro) and Brazil (8.3 billion

Euro). In terms of incidence of the Data Economy on total GDP, however, both the EU27 (0.49%) and

the EU27+U.K. (0.55%) lag behind the U.S. (1.19%) and Japan (1.09%) and are better only than Brazil

(0.23%).

The positive development of the U.S.’ Data Economy is confirmed by a solid year-on-year growth of

the main indicators monitored, including the overall Data Market, with more than 184 billion Euro in

size and a buoyant year-on-year growth rate of 12.7% in 2019 over the previous year. The EU27+U.K.

positions itself as the only regional market able to challenge the U.S.’ leading position, even though

its Data Market is less than 40% that of the U.S. The value of the Data Market for the EU27+U.K. in

2019 is in fact estimated at 75 billion Euro in size (58 billion Euro in the EU27), followed by Japan (32

billion Euro) and Brazil (7 billion Euro).

The U.S. also confirm their leadership in the number of data professionals with an estimate of more

than 14 million, although year-on-year growth slowed again to just 1.7% in 2019. Europe continues to

lead in terms of growth, with a year-on-year growth rate of 6% for the EU27+U.K. and 5.4% for the

EU27. Japan follows with a rate of 2.9%, while Brazil consistently shows the lowest growth in the

number of data professionals at a rate of 0.9%. This is mainly linked to economic issues in the country

reducing industrial and business growth and having negative impact on the digital economy as well.

In terms of data suppliers, the EU27 and the EU27 plus the U.K both exhibit higher growth than the

U.S. in 2019. As a matter of fact, while in the EU growth rates are close to 2.4%, the U.S. show a year-

on-year growth of 1% over the same period, even lower than Brazil and Japan, both registering a rate

of 1.6%. The EU, in addition, continues to boast the second-largest number of data suppliers (290 €

million in the EU27+U.K. and almost 149 € million in the EU27), preceded only by the U.S. (312 million)

and followed by Japan (almost 107 million) and Brazil (38 million).

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The European Data Market Monitoring Tool – The International Indicators and the EU27

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The European Data Market Monitoring Tool – The International Indicators and the EU27 + U.K.

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7.2 What the International Indicators really say

Our latest measurement of the European Data Market Monitoring Tool reveals a substantially

unchanged picture when comparing the EU indicators to those that have been developed for some of

the key international partners of the EU. While confirming its vitality, the EU continues to significantly

lag behind the U.S in terms of both size and growth of the Data Market. Even when focusing on the

EU27+U.K., Europe generates a Data Market value in 2019 that is still approximately 2.5 times smaller

than the one produced in the U.S. (72.3 billion Euro in the EU vs. almost 185 billion Euro in the U.S.)

in the same year. The pace of this development is even less flattering as year-on-year growth for the

Data Market in the U.S. is almost three times as faster than in the EU in 2019 (12.7% in the U.S. vs.

4.9% in the EU). The same pattern applies when comparing the EU performance to the US

performance in terms of the Data Economy32: even if confined to direct and backward indirect impacts,

the U.S. Data Economy represents a share in terms of GDP that is more than double the one of the EU

(1.2% vs. 0.5%) in 2019 with a year-on-year growth that, again, is twice as much than in the EU (6.8%

in 2019 over 2018 in the U.S. vs. 3.4% in the EU).

This is certainly not surprising given that the U.S. economy continued to exhibit a very heathy picture

in 2019 with GDP increasing 2.1% in the fourth quarter of 2019, according to the “second” estimate

released by the Bureau of Economic Analysis33, bringing the value for the whole year at a very positive

2.2%. What is more, the U.S. endures a leading role in the development and application of advanced

technologies, holding more than 50% of all patents related to blockchain technologies as well as

dominating shares of global spending on IoT and public cloud computing. Even more relevant for our

analysis is that the country accounts for more than 70% of the market capitalization value of the

world’s 70 largest digital platforms. According to the UNCTAD Digital Economy Report of 2019,

Europe’s share is around 4% and Africa and Latin America’s together is only 1%. 34. Five “super

platforms” - Microsoft, followed by Apple, Amazon, Google, Facebook, − account for almost two thirds

of the total market value. Thus, in many digital technological developments, the dominance of the

U.S. remains uncontested.

When it comes to Japan - EU’s second biggest trading partner in Asia (after China) - its Data Market is

similar to the European one in terms of growth and investment, but it still represents less than half

the size of the EU’s. In fact, the Japanese economy shrank 1.8 % in the last quarter of 2019, compared

to the preliminary estimate of a 1.6 % contraction.35. Nevertheless, Japan’s digital economy is catching

up with the EU’s Data Market and Data Economy and displays higher growth rates in both the Data

Market and the Data Economy in 2019 than the ones performed in Europe. Japan’s Data Economy, in

particular, continues to have a stronger impact on GDP than Europe’s with the sum of direct and

backward indirect impacts totalling 1% of share of GDP in 2019 (vs. 0.5% in the EU).

Brazil’s economic situation and outlook continue to be moderately positive. The country’s

expansionary monetary policy with inflation more and more under control, the gradual increase in

consumer confidence, the recent approval of the social security reform, among other factors, have

32 The Data Economy for Brazil, Japan and U.S. has been measured in terms of direct and indirect impacts only due to lack of comparable and consistent statistical sources for all these three countries. This is consistent with what has been presented throughout all duration of this update study (SMART 2016/0063) as well as the original European Data Market Study (SMART 2013/0063). 33 https://www.bea.gov/news/glance 34 https://unctad.org/en/PublicationsLibrary/der2019_overview_en.pdf 35 https://tradingeconomics.com/articles/05202019002225.htm

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secured the gradual recovery of the Brazilian economy and are expected to generate positive effects

in 2020 and 2021. After having grown around 1.1% in 2019, GDP is expected to expand 1.9% in 2020

and 2.0% in 2021, when it will finally reach the level exhibited before the severe crisis of 2015-1636.

This encouraging picture is expected to exert a beneficial impact on the country’s digital economy over

the next few years. The growth of Brazil’s Data Market in 2019 over the previous here has already

registered a very positive 7.2% year on year vs. a 4.9% of the EU28; likewise, the impact of the Data

Economy on the country’s GDP, while still limited in terms of share, has marked a considerable 8.8%

growth in 2019 – a remarkable performance when considering that the share of the Data Economy on

the EU28 GDP has grown only 3.4% in the same year.

7.3 Europe on the international scene: looking for a recovered confidence

The new European Digital Strategy recently unveiled by the European Commission37 appears to design

a new, confident role for Europe as a global player. Realizing that the European model has proved to

be an inspiration for many other partners worldwide, the strategy calls for the EU to strengthen its

commitment towards the setting global standards for emerging technologies and to remain the most

open region for trade and investment in the world. In terms of standards, in particular, the EU has

paved the way for the setting of global standards for 5G and the IoT and is now committed to leading

the standardisation process of a number of additional advanced and new generation technologies

such as blockchain, quantum computing, supercomputing – all technologies that lie behind and allow

data sharing and data usage and that, as a straight consequence, are directly linked to the further

development of a well-functioning Data Economy.

This proactive international role in the standardisation process is accompanied by a robust

commitment on trade and investments on the international scene to ensure a collaborative approach

on several technology-related topics including data flows and the possibility to pool available and

relevant high-quality data together. This move is indeed in line with the “data-as-infrastructure”

approach to the Data Economy (see paragraph 4.1 above) which aims at a negotiated, common data

governance setting between the EU and like-minded partners. This approach, however, will have to

be put in place while safeguarding Europe’s “technology sovereignty”, that is by making sure that

Europe reduces its level of dependency on other parts of the globe for most of the crucial technologies

and effectively protects the integrity and resilience of its data, networks and communication

infrastructures. As noted above, this marks a considerable distance from previous policy stances on

the international scene. Yes, “sovereignty” is defined positively and is not directed against anyone.

Nevertheless, this renewed confidence on the international scene may indicate that Europe will

gradually abandon a merely reactive role to embrace a more dynamic and enterprising stance vis-à-

vis a number of trading partners at worldwide.

36 https://www.bbvaresearch.com/en/publicaciones/brazil-economic-outlook-first-quarter-of-2020/ 37 https://ec.europa.eu/digital-single-market/en/content/european-digital-strategy

https://www.bbvaresearch.com/en/publicaciones/brazil-economic-outlook-first-quarter-of-2020/

https://ec.europa.eu/digital-single-market/en/content/european-digital-strategy

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8. CONCLUSIONS

8.1 Overview

Both the European Data Market and Data Economy have achieved a remarkable growth development

since 2013, when we started tracking their value. The EU27+U.K. Data Market doubled in value from

47 €B in 2013 to 80 €B in 2019. The EU27+U.K. Data Economy almost doubled from 247 €B in 2013 to

406 €B in 2019: each Euro spent in the Data Market generated more than 5 Euros in the Data Economy,

showing the multiplier value of data technologies. In the same period, the Data Economy grew faster

than the EU27+U.K. GDP, with an incidence growing from 2% in 2013 to 2.6% in 2019. Most of the

indicators of the EDM Monitoring Tool have shown consistent growth rates in this same period.

Unfortunately, 2020 saw the negative impact of the Covid-19 pandemics. Based on IDC research

carried out in March-April 2020, we provided for this report additional post-Covid estimates of the

EU27 Data Market and Data Economy in 2020, and potential implications for the Baseline scenarios in

2025. These estimates should be taken with caution, given the high level of uncertainty of the socio-

economic environment and the still-evolving Covid pandemic, but they provide a timely perspective

of the possible consequences of this dramatic event.

Figure 8: The European Data Market Monitoring Tool: Interrelated Indicators and Building Blocks


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The six interrelated indicators apprehending Europe’s Data Economy in 2019, and through the year

2025, can be seen holistically along four main building blocks (Figure 8):

• The data professional area measuring the workers employed by data companies actively

participating to the building of the Data Economy;

• The data companies’ area measuring both the suppliers as well as the demand of data-driven

products and services;

• The Data Market area representing the actual market where data-driven products and services

are exchanged;

• The Data Economy area measuring the overall impacts of the Data Market on the economy as a

whole.

8.2 Data Professionals

According to this third round of measurements of the European Market Monitoring Tool, data

professionals are estimated at a total of 6.0 € million in EU27 and at 7.6 € million in EU27 plus U.K in

2019, thus marking a continuing increase in 2019 over the previous year (6.1% and 5.5% year-on-year

respectively). More interestingly, the employment share and the intensity share components of the

data professionals’ indicator are also expected to improve in 2019 and 2020 if compared to our

previous estimates (now estimated at 3.3% and 3.5% in 2019 and 2020 in EU27 and 3.6% and 3.8% for

the same years in EU27 plus U.K). As underlined in the Final Report on Facts & Figures (D2.4), this

increase confirms the positive evolution of the workforce involved in data-related professions over

the period under consideration.

The number of data professionals in both EU27 and EU27+U.K. is forecast to grow significantly under

all the three scenarios out to 2025 as the use of data-driven innovation is expected to grow even under

the less economically favorable scenario. Under the Baseline scenario, data professionals are expected

to amount to 9.3 € million in EU27 and 11.3 € million in EU27+U.K. by 2025. In the Challenge and High

Growth scenarios, data professionals are forecast to reach more than 8.4 € million and 10.8 € million

in EU27 and 10.2 € millionand 13.1 € million in EU27 + U.K. respectively.

Since the demand of data professionals continues to grow faster than supply, in 2019 the data skills

gap amounted to approximately 459,000 unfilled positions in the EU27+U.K.(399,000 without the

U.K.), corresponding to 6.2% of total demand (5.7% without the U.K.).

For the next years, the absolute size of the potential data skills gap is estimated to be considerable,

up to 759,000 unfilled positions by 2025 in the EU27 Baseline scenario, corresponding to 8.2% of

potential demand. The forecast gap remains in all scenarios, ranging from 5.7% of demand in the

Challenge scenario to 10.5% in the High Growth (EU27).

The EDM monitoring tool has consistently measured a data skills gap since 2013, due to a structural

imbalance between demand and supply of data skills. In the last years we have witnessed an increased

awareness of the risk of lack of skills as a development bottleneck, resulting in proactive supply-side

policies for high technology skills in the education and training sector, as well as efforts by

governments and the ICT industry to drive more young people to STEM education paths. On the

demand side, the labour market has proven its ability to deal with the skills gap in the short term, as

employers have learnt to provide more incentives and/or more training, attracting skilled resources

from other careers. Until now, lack of skills has not slowed down noticeably the growth capability of

the European data industry. Skill policies have helped to reduce the data skills gap but have not solved

the problem, as demand is expected to continue to outpace supply for demographic (a smaller number

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of young people) and higher education (insufficient number of teachers) trends. As Europe moves

towards widespread data-driven innovation and enterprises deal with a new wave of innovation led

by AI technologies, the demand of data skills will necessarily increase. European digital policies

recognize this, and the development of high technology skills for the digital economy is a key priority

of the forthcoming Digital Europe Programme 2021-2027 and of the new Data strategy presented in

February 2020. The successful implementation of these policies and of initiatives such as the Digital

Innovation Hubs is a critical factor to avoid the risks of an increasing data skills gap highlighted by our

scenarios.

8.3 Data Companies

As far as data companies are concerned, the number of data suppliers continue to grow at a faster

pace than the number of data users in the longer term – out to 2025. Data suppliers are estimated at

almost 149,000 in the EU27 and 290,000 units in the EU27+U.K. for 2019, thus exhibiting a year-on-

year growth of 2.4% and 2.3% respectively. Data users, instead, are projected to grow at 0.6% in 2019,

amounting to nearly 535,000 in the EU27 and to nearly 716,000 units in the EU27+U.K.

This consolidation is reflected in the slow but consistent increase in the share of data companies over

the total number of companies in Europe. The share of data suppliers on total companies in the ICT

and Professional services industries is estimated at 11.5% in the EU27 and 15.2% in the EU27+U.K. for

2019, a slight improvement with respect to an adjusted 2018. The data users’ penetration rate (i.e.

the share of data users on total companies in the EU) is also stable with a fractional percentage point

increase in 2019 to 5.9%. According to our definition, data users are the companies using data in a

strategic way to inform their decision making, and they are the leaders of the Data Market.

Data companies’ revenues in 2019 increased by 9% to over 64 €B in EU27 , corresponding to an

increasing share of 3.6% of the total revenues in the ICT and Professional services sectors. This means

that data companies performed better than other companies in the same industries.

Forecasting the EU27 data companies’ revenues shows an expected annual growth rate out to 2025

of 6.8%, easily outpacing the growth of the total ICT market over the same period. The smaller

Member States show the highest long-term growth as they start from a smaller base, but the larger

Member States will make the biggest overall contribution to the Data Economy out to 2025.

In the period since 2013 European both data suppliers and data user companies increased

substantially in number and revenues, fuelling the growth of the Data Market. On the supply side, the

EU27 data industry saw its revenues multiply from 38 €B in 2013 to 64 €B in 2019. The dynamism and

innovation capability of the EU data industry is one of the key drivers of the overall development of

the Data Economy. We expect the data industry to overcome the recession caused by COVID-19 in

2020 and to start growing again fast already from 2021.

8.4 Data Market and Data Economy

Pre-Covid data

In 2019 the European Data Market continued to show a healthy growth rate of 4.9% to a value of 58

€B in the EU27 (75 €B including the U.K.). Manufacturing, Financial services and Professional services,

industries were data-driven innovation plays a relevant role, remain the top 3 industries in value and

for adoption of data technologies and tools. The fastest growing industries are Transport and Storage,

and Information and communications, with growth at 6.7% and 6.2% respectively. The largest

spenders – Manufacturing, Financial, and Professional Services – all show moderate growth in 2019,

but manufacturing is a little below average for the whole of the EU.

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The value of the Data Economy, which measures the overall impacts of the Data Market on the

economy as a whole, exceeded the threshold of 400 Billion Euro in 2019 for the EU27+U.K., with a

growth of 7.6% over the previous year. The EU27+U.K. Data Economy grew faster than the EU GDP,

with an incidence of 2.8% in 2019 compared to 2.6% in the previous year.

A screenshot of the Data Economy by industry shows that the Financial sector, the Manufacturing

industry and the realm of Professional services continue to represent the vertical markets in which

the impacts of the Data Economy are most strongly felt.

Thanks to the significant diffusion of data-related technologies, these industries exhibit high levels of

forward and backward impacts and can convey effects at an induced level more quickly and more

effectively than other industries.

Their IoT diffusion and the usage of Cloud Computing, as well as the usage of mobile and social technologies, coupled with the ongoing process of digital transformation, make these industries particularly reactive to induced effects. Emerging technologies such as Artificial Intelligence and blockchain applications, are also gaining momentum in these industries, thus reinforcing the impact of indirect and induced impacts in these sectors.

Post-Covid data

Unfortunately, our 2020 estimates have been superseded by the Covid-19 pandemic. Based on

updated research, we estimate that the EU27 Data Market (without the U.K.) will decrease by

approximately 7.1% in 2020 to 54 €B. We also estimate that already by 2021 both the Data Market

and the Data Economy will return to growth and by 2025 their value will be close to that of the pre-

Covid forecast scenarios presented in this report. The incidence of the European Data Economy on the

EU27 GDP in the Baseline scenario will slightly increase from 4% (Pre-Covid scenario) to 4.04% (post-

Covid scenario) because GDP is also affected by the recession.

However, the scenarios perspectives will change; we still see the Baseline as the most likely scenario,

but the Challenge scenario is relatively more likely (if the recovery does not take off as hoped) while

the positive feed-back loop and hyper-growth supporting the High Growth scenario seem now quite

unlikely. Unfortunately, there is insufficient evidence and time to revise the estimate of all the other

indicators of the EDM Monitoring too for 2020.

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8.5 Concluding remarks

The European Data Market (EDM) Monitoring tool has monitored since 2013 the evolution of the Data

Economy, providing insights and quantitative evidence about its diffusion by industry and by region,

contributing substantially to the evolution of European policy strategies in this field. Since the first

intuition of the potential disruptive impacts of Big Data, this monitoring effort and analysis has

documented the social and economic relevance of the deep transformation process enabled by data-

driven innovation. Today this process is accelerated by the emergence of Artificial Intelligence tools

and services powered by data.

As most recently described by the Economist, there is no more doubt that the next years economic

and social development model will be deeply influenced by choices about the governance of data and

the use of data assets. The new European Data strategy outlines the ambition for Europe to become

a leading role model for a society empowered by data to make better decisions in business and the

public sector and a global leader in the data-agile economy. According to the Economist, Europe is

moving towards a “data as infrastructure” model: a governance model where data is considered as a

public asset, and data infrastructures work as a kind of “digital twins” to physical roads, requiring

public investments and new institutions to manage them. This model allows for many different

typologies of “data roads”, local or global, leaves freedom for private initiative but tries to maintain a

balance between private and public interests, to be managed through new kinds of organizations,

private or public or a mix of the two, like data trusts, data cooperatives, personal data stores.

Our indicators framework and 2025 scenarios are consistent with the “data as infrastructure”

approach, as they consider choices about data governance models as a key differentiating factor and

explore the different mix of factors and policy choices which may lead to achieve this ambition or

instead to fail it. Today, as we look at the main driving trends for the next years, we notice that the

role of policies has increased in relevance: as data-driven innovation has become widespread across

all industry sectors and user constituencies, the scope of the regulations and framework conditions to

be adapted has considerably grown. At the same time, the emergence of disruptive technologies such

as AI has increased the need for policy intervention to manage emerging social, economic and ethical

risks. The EDM monitoring tool provides a consistent and solid framework to assess and estimate the

potential consequences of policy choices to be made in the next years.

Even the disruption caused by the Covid-19 pandemic has not undermined the value of the EDM

monitoring tool indicators and analysis. As we argue in our post-Covid scenario estimates, the main

drivers of data-driven innovation are still powerful, the Data Market and the Data Economy are likely

to start growing again already from 2021 and by 2025 may have recovered much of the ground lost in

2020. The pandemic has shown new ways in which digital technologies can help to adapt to a new

post-Covid environment, manage health risks and accelerate the economic recovery. Now as never

before proactive innovation policies and technology investments are needed to support the European

social and economic recovery.

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