promotion of e-leadership skills in europe [scale] business,...

Promotion of e-Leadership Skills in Europe [SCALE]

Business, Industrial and Technological Trends Analysis and Impact on e-Leadership Skills

Prepared for the European Commission DG GROW

December 9, 2015

Prepared for the European Commission DG GROW 2


Table of Contents

EXECUTIVE SUMMARY ............................................................................................................... 7

1 INTRODUCTION .......................................................................................................... 13

1.1 BACKGROUND AND SCOPE .............................................................................................. 13

1.2 STRUCTURE OF THE REPORT .......................................................................................... 13

2 TOWARDS DIGITAL TRANSFORMATION ................................................................ 15

2.1 INTRODUCTION ............................................................................................................... 15

2.2 A DEFINITION OF DIGITAL TRANSFORMATION .................................................................... 16

2.3 REVIEW OF THE MAIN SOURCES ...................................................................................... 19

2.3.1 Accenture .................................................................................................................................. 20

2.3.2 McKinsey Global Institute ......................................................................................................... 21

2.3.3 IBM, Global Technology Outlook, 2015 ..................................................................................... 24

2.3.4 Automation and Robotics .......................................................................................................... 26

2.4 THE EFFECT OF NEW TECHNOLOGIES ON BUSINESS MODELS ........................................... 26

2.5 MAIN DISRUPTIVE SHIFTS IN THE COMING YEARS ............................................................. 28

3 OVERVIEW OF THE KEY ICT TRENDS AND SKILLS .............................................. 30

3.1 OVERVIEW ..................................................................................................................... 30

3.2 APPROACH TO THE ASSESSMENT OF IMPACT ON SKILLS ................................................... 31

4 MOBILITY AND MOBILE APPLICATIONS ................................................................ 34

4.1 MAIN TRENDS ................................................................................................................. 34

4.2 CURRENT AND FUTURE ADOPTION .................................................................................. 35

4.3 SKILLS IMPACT ............................................................................................................... 38

5 CLOUD COMPUTING ................................................................................................. 41

5.1 MAIN TRENDS ................................................................................................................. 41

5.1.1 Hybrid Cloud .............................................................................................................................. 42

5.1.2 Explosive Uptake of Applications .............................................................................................. 42

5.1.3 Cloud for Digital Transformation ............................................................................................... 42

5.2 CURRENT AND FUTURE ADOPTION: CLOUD COMPUTING ................................................... 43

5.2.1 Cloud Maturity ........................................................................................................................... 44

5.3 SKILLS IMPACT ............................................................................................................... 45

6 BIG DATA .................................................................................................................... 48

6.1 MAIN TRENDS ................................................................................................................ 48


6.3 SCENARIOS OF EVOLUTION OF THE EUROPEAN DATA MARKET .......................................... 50

6.4 SKILLS IMPACT ............................................................................................................... 54

7 SOCIAL BUSINESS .................................................................................................... 57


7.1 MAIN TRENDS ................................................................................................................ 57


7.3 SKILLS IMPACT ............................................................................................................... 59

8 THE INTERNET OF THINGS ...................................................................................... 62

8.1 MAIN TRENDS ................................................................................................................ 62


8.3 SKILLS IMPACT ............................................................................................................... 67

9 IT SECURITY ............................................................................................................... 69

9.1 MAIN TRENDS ................................................................................................................ 69


9.3 SKILLS IMPACT ............................................................................................................... 70

10 INNOVATION ACCELERATORS ............................................................................... 72

10.1 MAIN TRENDS ................................................................................................................ 72


10.2.1 Virtual/Augmented Reality........................................................................................................ 74

10.2.2 Wearables .................................................................................................................................. 76

10.2.3 3D Printing ................................................................................................................................ 77

10.2.4 Cognitive Systems ..................................................................................................................... 78

10.2.5 Robotics 79

10.2.6 The Intersection between Advanced Cognitive Systems and Robots ........................................ 80

10.3 SKILLS IMPACT ............................................................................................................... 82

11 MAIN KETS TRENDS .................................................................................................. 85

11.1 MAIN TRENDS ................................................................................................................ 85

11.2 DEMAND OF KETS SKILLS ............................................................................................... 86

11.3 MAIN KET'S COMPETENCES ........................................................................................... 87

11.4 SKILLS IMPACT ............................................................................................................... 88

12 GENERAL CONCLUSIONS ........................................................................................ 91

12.1 OVERVIEW OF MAIN INNOVATION TRENDS ....................................................................... 91

12.2 THE IMPACTS ON SKILLS DEMAND ................................................................................... 92

12.2.1 Impact of ICT Trends on Core Technical Skills .......................................................................... 93

12.2.2 Impact of ICT Trends on R&D Skills .......................................................................................... 93

12.2.3 Impact on Quality, Risk and Safety Skills .................................................................................. 94

12.2.4 Impact of ICT Trends on e-leadership skills .............................................................................. 95

12.2.5 Impact of KETs on ICT Skills ..................................................................................................... 96

12.2.6 Impact of KETs on e-Leadership skills ....................................................................................... 96


12.3 THE EXPERTS' OPINION .................................................................................................. 97

12.3.1 Profile of the sample ................................................................................................................. 97

12.3.2 Impacts of ICT Trends on Industry and Daily Life ..................................................................... 98

12.3.3 Impacts on the demand of ICT and e-Leadership skills .......................................................... 101

12.3.4 E-Leadership Demand: Main Challenges ................................................................................. 103

12.4 CONCLUSIONS .............................................................................................................. 105

ANNEX – MAIN REFERENCES ............................................................................................... 106

Table of Figures

Figure 1: European Digital Transformation Maturity Distribution across the Stages ............................ 18

Figure 2: Evolution of Main Trends in Accenture's Vision ..................................................................... 21

Figure 3: McKinsey's view of digital transformation .............................................................................. 23

Figure 4: Impact of technological automation based on 2,000 work activities ...................................... 24

Figure 5 The 3d Platform and Innovation Accelerators ......................................................................... 31

Figure 6: Western Europe Spending on Mobile Applications, 2015 and 2019 ($ Million) .................... 35

Figure 7: Mobile IT across Maturity Stages ........................................................................................... 36

Figure 8 : the Maturity of European Organisations in Mobility .............................................................. 37

Figure 9: IDC's Definition of Cloud Computing Deployment Models ..................................................... 41

Figure 10: Cloud Adoption and Plans in Western Europe, 2015........................................................... 43

Figure 11: Cloud Spending in the EU, 2015 and 2019 .......................................................................... 44

Figure 12: Cloud Maturity in Western Europe, 2015 ............................................................................. 45

Figure 13: Europe's Hadoop Adoption Trajectory, 2013–2015 ............................................................. 50

Figure 14 Value of the European Data Economy, 2014 ....................................................................... 51

Figure 15: Three Scenarios for the European Data Market in 2020 .................................................... 53

Figure 16: Social Business Experiences ............................................................................................... 57

Figure 17: Current and Planned European Social Business Initiatives ................................................. 59

Figure 18: Business Importance of IoT ................................................................................................. 62

Figure 19: Components of an Internet of Things Solution ..................................................................... 63

Figure 20: IoT EU Market Forecast, installed base of sensors and revenues, 2013-2020 ................... 64

Figure 21: Alternative IoT European market scenarios, revenues, 2014-2020 ..................................... 65

Figure 22: Smart Environments by IoT Spending Size and Growth ..................................................... 66

Figure 23: The importance of IT security improvements ....................................................................... 70

Figure 24: Major Innovation Accelerators in Europe ............................................................................. 73

Figure 25: Intersection of Major Innovation Accelerators in Europe ..................................................... 74


Figure 26: Future View of the Wearable Market (Western Europe Wearables Forecast, 2014–2019,

Units) .............................................................................................................................................. 76

Figure 27: Future View of 3D Printers Market (Western Europe, 3D Printer Shipment Forecast, units,

2013–2018) .................................................................................................................................... 78

Figure 28: Robotics and Cognitive Computing Future View of the Market ........................................... 81

Figure 29 the KETs Skills Box ............................................................................................................... 87

Figure 30 Survey sample by domain (% of respondents) ..................................................................... 98

Figure 31 Impact of Key ICT trends on Demand of Skills to 2020, % of Respondents by score .......... 99

Figure 32 ICT Trends Impacts on industry and Skills Demand, Average Scores, All Respondents ... 100

Figure 33 Impact of Key ICT trends on the Risks of Skills Gap in Europe, % of Respondents by score

...................................................................................................................................................... 103

Figure 34 Experts Opinions on e-Leadership Skills ............................................................................ 104

Table of Tables

Table 1: Twelve Potentially Economically Disruptive Technologies...................................................... 21

Table 2: Assessment Matrix of Trends Impacts on Skills Demand ....................................................... 33

Table 3: Mobility impacts on demand of new skills ............................................................................... 40

Table 4: Cloud Computing Impact on demand of new skills ................................................................. 47

Table 5: Big Data impact on demand of new skills ............................................................................... 55

Table 6: Business Impact and Skills Required ...................................................................................... 60

Table 7: Social Business Impact on demand of new skills .................................................................... 61

Table 8: IoT Impact on Skills Demand .................................................................................................. 68

Table 9: IT Security Impact on Skills Demand to 2020 ......................................................................... 71

Table 10: Innovation Accelerators Impact on Skills Demand ................................................................ 83

Table 11: Innovation Accelerators Impact on e-Leadership Skills Demand .......................................... 84

Table 12: Emerging Areas of Demand of skills in KETs field ................................................................ 89

Table 13 Demand of e-Leadership skills by KETs organizations .......................................................... 90

Table 14 Summary of ICT Trends Impacts on Demand of Skills to 2020 ............................................. 94

Table 15 Summary of ICT Trends Impacts on Demand of e-Leadership Skills to 2020 ....................... 95

Table 16 Summary of KET Trends Impacts on Demand of ICT and e-Leadership Skills to 2020 ........ 97

Table 17 ICT trends Impact on Industry (Share of "Very High" answers) ............................................. 99

Table 18 Impact of ICT Trends on Demand of Skills and Risks of Skills Gap (share of "Very High +

High" answers) ............................................................................................................................. 101

Table 19 Impact of ICT Trends on the Demand of technical and e-leadership skills, share of "Very

High" answers .............................................................................................................................. 102

Table 20 ICT Trends Impact on Risk of Skills Gap in 2020 (share of "Very High" answers) ............. 102


Executive Summary

Main Goals and Scope

This report "Business, Industrial & Technological Trends Analysis and Impact on e-Leadership skills"

was delivered by IDC on behalf of the project "Promotion of e-Leadership Skills in Europe (SCALE)".

This project is carried out by empirica GMBH in cooperation with Price Waterhouse Coopers (PwC),

IDC Europe and Carl Frey from the Oxford Martin School at Oxford University and is promoted by the

EASME/COSME program of the European Commission (contract n.2014/013).

The aim of the SCALE project is to promote e-leadership skills and provide Europe with a larger talent

pool of highly-skilled entrepreneurs, managers and professionals. This report presents a summary of

the main ICT and new technology trends affecting the demand of ICT and e-leadership skills in

Europe, today and for the period up to 2020. The report provides an assessment of the level of skills

demand, based on desk research and IDC data, as well as on the opinions of more than 700 e-skills

experts responding to a survey carried out by empirica in the fall of 20151.

Main Innovation Trends and their Impacts

According to IDC, in the next few years the four key technologies which have driven innovation in the

last few years (Mobile, Cloud Computing, Social business and Big Data) will combine with other

emerging trends, the so-called innovation accelerators, multiplying their transformative effects on the

economy. They include:

The Internet of Things (IoT) which enables objects sharing information with other

objects/members in the network, recognizing events and changes so to react autonomously

in an appropriate manner. The IoT therefore builds on communication between things

(machines, buildings, cars, animals etc.) that leads to action and value creation.

Virtual/augmented reality: Technology that allows immersive visual experience that

removes or complements external visual input and follows the user's head movement.

Wearables: Wearable devices with a microprocessor, that is capable of digitally processing

data.

3D printing: technology used for additive manufacturing, that is able to materialize all sorts of

physical things from digital blueprints — from food to clothing to eventually even living tissue

and organs.

Cognitive systems: Systems that observe, learn, analyse, offer suggestions, and even

create new ideas — dramatically reshaping every services industry. This includes artificial

intelligence (AI), machine learning, cognitive computing, and robotic process automation.

Robotics is the branch of technology that deals with the design, construction, operation, and

application of robots, as well as computer systems for their control, sensory feedback, and

information processing. A robot is a mechanical or virtual artificial agent, usually an electro-

mechanical machine that is guided by a computer program or electronic circuitry.

ICT innovation is complemented by KETs (Key Enabling Technologies) which are transforming the

European industry, as documented by PWC's analysis. They include:

Micro and Nano electronics providing the components for hardware and software advances;

Nanotechnologies, feeding into the development of sensors and components for IoT;

Industrial biotechnology, pushing to the market scientific breakthroughs in fields as different

as molecular biology, biochemistry, biophysics, genomics.

1 empirica: European and national e-leadership skills policies, initiatives and partnerships, challenges and

technology trends and their impact on digital leadership skills – empirical evidence and expert views (working document), January 2016 (forthcoming)


Advanced materials revolutionizing the very substance of new products;

Photonics enabling radical innovations in communication networks and computing;

Advanced manufacturing technologies complementing 3D printing and enabling additive

manufacturing;

According to IDC, Mobile, Cloud, Social business and Big Data already account for more than a

quarter of enterprise IT spending; one or more of innovation accelerator technologies have already

been adopted by approximately 12% of European enterprises with more than 10 employees, but

growth rates are expected to be very fast, as documented in the previous chapters.

The cumulative transformational impacts of these ICT trends are described by IDC as the

phenomenon of "Digital transformation", a continuous process of disruptive innovation experienced by

enterprises by leveraging digital competencies to innovate new business models, products, and

services that seamlessly blend digital and physical and business and customer experiences. Every

business will become a digital business, not in the sense that digital will become their core business,

but that in every organization digital processes will be deeply embedded with traditional processes.

According to IDC's European Digital Transformation maturity benchmark, only 5% of European

organisations can currently be termed digital disruptors while at the other end of the spectrum, one in

five can be characterised as digital laggards. Many European organisations are currently only laying

the groundwork in terms of establishing the enabling ICT environments that will allow them to

transform digitally, but this is expected to change rapidly in the next years.

The Impacts on the demand of ICT Technical Skills

The drivers of new demand of ICT and e-leadership skills have been considered separately for each

technology trend: even if the largest impacts come from their combination, each technology has some

specificity and therefore it was important to consider each of them in depth.

The following tables present a summary of the impact on demand of each category of skills for

comparison, based on a three steps semantic scale (high, medium and low increase of demand). This

is a qualitative assessment, since it was not possible to quantify the potential increase or decrease of

demand separately for each trend compared to an average benchmark.

Core technical skills are those needed to develop and implement innovation in the organization:

infrastructure skills concern the deployment, implementation and management of hardware or network

solutions, while applications skills, as the term says, concern the implementation and management of

software and applications. Based on IDC's analysis, Big Data and IoT trends will generate the highest

demand for both infrastructure and applications-related skills, because of the need to deploy and

implement complex systems solutions; also the other innovation accelerators (Virtual/Augmented

reality, 3D printing and Cognitive systems/Robotics) will drive a high increase of demand. Mobile,

Cloud and Social business technologies will generate high-medium demand of new skills, depending

on the trend.

Also, a fundamental impact of these trends will be to accelerate the reduction of demand for traditional

IT skills, including operational skills to manage and maintain corporate IT systems and maintenance

and support of legacy systems and applications.

R&D skills will be required to deal with the main research challenges driven by the ICT trends and to

design and develop new products and services based on these emerging technologies. The

innovation trends will have a high or medium impact on the increase of demand, because of their early

stage of development and the need for solving countless deployment and implementation problems.

Only mobile and cloud may have a low impact on the increase of demand of new R&D skills because

of their higher level of maturity in the market.


These new trends will pose new challenges in terms of new quality standards to be developed;

understanding of new typologies of risks and dealing with them with a comprehensive approach;

completely new safety challenges (think of automated cars, for example). Therefore they will require

new or updated skills in this area.

Summary of ICT Trends Impacts on Demand of Skills to 2020

TREND Technical Skills R&D

Quality, Risk and

Safety

Infrastructure Applications

Mobility M H L M

Cloud Computing H M L M

Big Data H H H H

Social Business L M M H

IoT H H H H

IT Security H M M H

Virtual/ Augmented reality H H H M

Wearables M M H M

3d Printing H H H M

Cognitive Systems/ Robotics H H H H

Source: IDC 2015 Legenda: H = High increase of demand M = Medium L = Low

E-leadership Skills are those required of an individual to initiate and achieve digital innovation,

including strategic leadership, digital savvy and business savvy. All ICT trends will generate a high or

medium level increase of demand. There are however relevant variations between trends. Big Data

and IoT for example will drive high demand of e-leadership in all its components: both data-driven

innovation and IoT systemic innovation require sophisticated leadership skills as well as digital and

business savvy and are starting to take-off in the market.

Finally, for the main innovation accelerators (Virtual/Augmented reality, Wearables, 3D printing and

Cognitive systems/ Robotics) we foresee high demand for all the components of e-leadership, since

these technologies will require strategic vision and a high degree of industry specific competences to

be implemented in the digitally transformed environment.


Summary of ICT Trends Impacts on Demand of e-Leadership Skills to 2020

E-Leadership Skills

Strategic Leadership Digital Savvy Business Savvy

Mobility M M M

Cloud Computing M M M

Big Data H H H

Social Business M M M

IoT H H H

IT Security M H H

Virtual/Augmented reality H H H

Wearables H H H

3d Printing H H H

Cognitive Systems/

Robotics H H H


Impact of KETs on e-leadership skills

KETs are technologies, not industry sectors. While they grow from different scientific domains, KETs

have in common a positioning at the basis of supply value chains (they develop basic components and

technologies for use by other industries) and a fast pace of evolution, driven by high R&D intensity.

KETs will generate medium-high demand of e-leadership skills, as illustrated in the following table.

Given the profile of these organizations, we expect them to require strategic e-leadership capabilities

in terms of a deep understanding of the role of innovative digital technologies in supporting KETs and

to share this vision with other managers and partners. We also expect them to require skills of

leveraging digital innovation to support each specific KET development (digital savvy); we foresee

lower demand of business savvy e-leadership skills, simply because the business and for-profit

activities of these organizations are less relevant.


Summary of KET Trends Impacts on Demand of ICT and e-Leadership Skills to 2020

KETs

ICT Skills E-Leadership Skills

Strategic

Leadership

Digital

Savvy

Business

Savvy

Micro and nano electronics L M M L

Nanotechnologies M H M L

Industrial biotechnologies M H M L

Advanced materials L M M L

Photonics M H M L

Advanced manufacturing technologies M H M L


Experts' Survey on Impacts on Skills

There is a broad consensus among the leading stakeholders surveyed by empirica that all major ICT

trends covered in this report will have a strong impact on industry and daily life in the next years to

2020. The survey collected over 400 answers from a group composed of policy makers, university and

research, e-skills experts. The majority of them belonged to the ICT domain (59%),

The majority of experts evaluate the impacts of ICT trends on the demand of skills as very high or

high, with shares ranging from 57% to over 80% for technical skills and from 63 to 75% for e-

leadership skills. The ranking of trends by level of impact sees IT security first, closely followed by Big

Data, IoT and Artificial Intelligence, while Mobile and Cloud are last. The impacts on the demand of

technical skills are expected to be slightly higher than those on the demand of e-leadership skills, but

differences are really minor. Finally, the opinion on the risks of a skills gap is universally shared: the

share of respondents believing this risk is high or very high is between 60-70% of the sample for all

trends, with a similar ranking of trends as for the impact on demand. Looking more closely, we notice

that almost twice as many experts think that the risk is very high for IT Security and Big Data than for

Mobile and Cloud.

These survey answers highlight the main pain points in sourcing skills now experienced in the market

and expected to become worse. These results are coherent with the analysis presented in this report

about the potential impacts of the main ICT trends and the disruptive nature of the combination IoT Big

Data and Cloud, which will pose the greater challenges in skills recruitment.


Experts' Opinions on the Impact of ICT Trends on Demand of Skills and Risks of Skills Gap

% of "Very High + High" answers

Impact on Technical Skills demand (%)

Impact on e-Leadership skills

demand (%)

Risk of Skills Gap (%)

TREND All Respondents All Respondents All Respondents

IT security 83.6 75.6 75.4

Big data 81.2 71.9 74.7

IoT 72.6 67.2 69.3

Artificial Intelligence 73.4 56.0 62.9

Mobile 62.3 64.0 60.8

Cloud 57.1 63.5 62.6

Source: empirica experts survey, 2015 (empirica 2016)

Conclusions

The innovation push of the main ICT trends and KETs will generate in the years to 2020 strong

transformational impacts on the EU economy and society, driving a strong increase of demand of ICT,

R&D but especially e-leadership skills. The demand of e-leadership skills varies by type of technology

trend and type of skills, but Big Data, the Internet of Things and the combination Cognitive

systems/Robotics are likely to generate the most disruptive impacts and drive the highest demand of

e-leadership skills. Both IDC research and the experts' opinions converge on these conclusions.

Approximately 70% of the experts surveyed agree that the increase of demand of skills will create a

very high risk of skills gaps in Europe.

However, experience says that complaints about the difficulty of sourcing skills do not necessarily

translate into a concrete increase of employment, if skills become available. There are all kinds of

mismatches between demand and supply which must be dealt with (from unrealistic expectations, to

wrong timing, to mismatched geographical location: supply in Europe is not always available where

demand is). Therefore, the demand of IT skills is more likely to translate into demand for training and

specialized certification for existing IT employees and managers than into the creation of new,

additional jobs.

Nevertheless, the innovative nature and technology profiles of some of these trends, particularly Big

Data and IoT, will definitely create demand for genuinely new skills and, thanks to the potential of

increasing business revenues, also the creation of new jobs.


1 Introduction

1.1 Background and Scope

This is the 1st release of the report "Business, Industrial & Technological Trends Analysis and Impact

on e-Leadership skills" carried out by IDC on behalf of the project "Promotion of e-Leadership Skills in

Europe (SCALE)". This project is carried out by empirica in cooperation with Price Waterhouse

Coopers (PwC), IDC Europe and Carl Frey from the Oxford Martin School at Oxford University and is

promoted by the EASME/COSME program of the European Commission (contract n.2014/013).

The European Commission sees the need to keep momentum relating to e-leadership skills going,

provide consolidation to these efforts in 2015-2016. The aim of the SCALE project is to promote e-

leadership skills and provide Europe with a larger talent pool of highly-skilled entrepreneurs, managers

and professionals. A comprehensive agenda (2016-2020) for e-leadership will be elaborated. The new

agenda is to take digital education and entrepreneurship policies fully into account, as well as

addressing labour market disruptions resulting from ICT developments and integrating new analyses

of leadership skills for liberal professions such as doctors and lawyers. The agenda is to be broad

enough to exploit synergy with emerging leadership skills requirements in businesses exploiting

Advanced Manufacturing Technologies and Key Enabling Technologies, and is to be explicitly

international in scope.

Within this context, the main objectives of this report are the following:

To summarize the current state of the art of knowledge about the main ICT and new

technology trends affecting the demand of ICT and e-leadership skills;

To provide data and evidence about the current and forecast diffusion of the main trends in

Europe;

To review the main drivers of change of the demand of ICT and e-leadership skills in Europe

and the main challenges;

To draw main conclusions about the main impacts of the demand of e-leadership skills and

the main challenges for the period up to 2020;

To draw on the expert survey carried out by empirica on the dynamic of ICT trends and on the

feedback of an expert workshop to finalize the main conclusions about the demand of e-

leadership skills in the period up to 2020.

1.2 Structure of the Report

The report is organized as follows:

Executive summary

Chapter 1 presents the background and main goals of the report;

Chapter 2 presents an overview of the main technology, business and industrial trends of

innovation, based on main sources, with a focus on the main drivers of transformation of

enterprises (Digital transformation) and the economy;

Chapter 3 presents an overview of the main ICT skills and the approach to the assessment of

their impact on the demand of ICT and e-leadership skills.

The following chapters present a detailed analysis of each main trend, the perspective evolution to

2020 and the estimated impacts on skills as follows:


Chapter 4 Mobility

Chapter 5 Cloud Computing

Chapter 6 Big Data

Chapter 7 Social Business

Chapter 8 The Internet of Things

Chapter 9 IT Security

Chapter 10 Innovation Accelerators (including Cognitive systems and robotics, 3D printing,

Virtual/augmented reality, Wearables)

Then the last two chapters are as follows:

Chapter 11 looks at the main KET trends and their impacts on the demand of skills, based on

PWC's leading study on the issue. This provides complementary evidence to the ICT trends

analysis.

Finally Chapter 12 draws general conclusions on the main trends and their perspective

impacts.

A list of the main reference sources is attached in Annex.


2 Towards Digital Transformation

2.1 Introduction

For most of the past decade, European organisations have been focused on how to get through the

financial crisis with much of the attention being directed internally towards increasing efficiencies and

cutting costs, wherever possible. However, in the past year or so, increasingly the attention has been

directed towards how to achieve top line growth, how to service customers and citizens better, how to

innovate products and services, and how to increase competitive positioning.

However, these overarching business trends are playing out in different ways in different industries.

Let us look at some examples.

Public Sector

The public sector across the EU is still under considerable budget pressure. At the same time, citizens

are increasingly seeing themselves as consumers of public services – and are expecting to be treated

as consumers with multi-channel access, online, self-services capabilities and the ability to

personalise the service that they receive from the public sector bodies. This brings the need for new

thinking and innovation in how services are delivered using digital technology. At the same time, in

most of the EU countries, governments also have to deal with growing populations – and ageing

populations as well with the fiscal challenges that both of these factors bring. Consequently, the public

sector is a good example of the dual demands of driving efficiencies while freeing up resources for

innovating service delivery.

Financial Services

After 2008, the financial services sector has come under intense scrutiny and has seen an impressive

amount of fines imposed for wrongdoings on a corporate scale but also because of actions of

individuals. This has partly led to new legislation, such as Basel III, Solvency II and new anti-money

laundering rules, but also to demands for better control functions and stricter risk management. In

addition to this, the financial services firms have in many cases to deal with ageing (and creaking)

core legacy IT systems that need modernization. Adding to these challenges are a whole raft of new

demands on the sector that are largely driven by the availability of new digital technologies. In

"Cleared for Takeoff"2, Deloitte has set out five such megatrends that will change the financial services

market:

Customer preferences are changing the face of the primary account providers in retail banking

The rise of a cashless world leading to massive changes in payment processes

The use of technologies to create distributed capital raising platforms

Use of robotics – or online tools – to provide a wider range of customers with tailored advice

for wealth management

Use of IoT and analytics to change the insurance industry, particularly automotive

It is clear that there is much to be done in the financial services sector. Some of this still involves

modernizations and efficiencies – but partly the longer-term savings from these undertakings will be

2 "Cleared for takeoff. Five megatrends that will change financial services", Deloitte, 2015


reinvested into the new developments needed for the financial institutions to stay relevant and

competitive.

Manufacturing

The manufacturing industry is poised for massive transformation, according to KPMG's Global

Manufacturing Outlook3. This transformation is led by innovation, disruptive innovators and technology

and will involve product development, manufacturing processes, automation, supply chains and

business models. Specifically, KPMG include the following key drivers for transformation:

Manufacturers are increasingly innovation-led and focused on improving R&D efficiency and

value

Sales growth and cost reductions continue to top the agenda as manufacturers prepare for

increased competition

Reducing costs and preparing for new product launches are high priorities for manufacturing

supply chain organisations

Manufacturers are entering into partnerships and adopting new technologies in order to

improve speed-to-market and lower innovation costs

Again, as we have seen above, it is clear that the dual trends of continued focus on cost and efficiency

while looking at how to grow the top line are at play. The adoption of new technologies will play a

strong role in fulfilling both of these objectives.

Retail

The retail sector has perhaps borne the brunt of many of the technology changes that are forcing

industry transformation. Clearly, consumers are becoming much more demanding in what they expect

from their retailer – in terms of different ways of buying, different ways of browsing, different ways of

paying – and the speed that they expect from delivery.

Customers want to be able to customise their interaction with their retailer and have their preferences

remembered. This means that retailers need to invest strongly in delivering an omni-channel strategy

to ensure the optimal customer experience. This will also involve ensuring that any online presence

can be accessed by any device and still deliver a consistent experience.

At the same time, many are struggling with high operating costs, including what to do with the physical

retail locations, which may no longer be needed or at least may need to be smaller. They are also

looking at how to increase the collaboration with suppliers, since this is one of the ways to decrease

delivery times, ease returns, and lower physical stocks. For all of these (apart from selling off the

physical locations), digital technologies play key roles.

2.2 A definition of Digital Transformation

As described above, organisations across different industries are trying to balance cost and growth

agendas simultaneously. This is a typical state as we move out of an economic downturn. What is

different this time are the significant changes that are happening in IT and in organisations' adoption of

IT to deal with the balancing act. While many organisations have been in a bit of a "lock down" mode

in the past seven years, the possibilities for innovation using ICT have accelerated – and have in

some cases taken industries by surprise. Perhaps the most quoted instance at the moment is Uber

3 "Global Manufacturing Outlook – Preparing for Battle: Manufacturers Get Ready for Battle", KPMG, 2015


and how it has disrupted the taxi trade in many countries. But we have seen others: HMV being

disrupted by Netflix, Airbnb upsetting online hotel booking, Spotify the music business, and of course

the impact of Amazon on traditional book shops.

However, as with any technology developments, there is a tendency to hit the "hype" button early on in

the cycle and in this case state that almost any new development is digital transformation. This, in

IDC's opinion, is not the case. For the adoption of new technology to be labelled digital transformation,

IDC would argue that the following need to apply:

It is a continuous process by which enterprises adapt to or drive disruptive changes in their

customers and markets (external ecosystem) by leveraging digital competencies to innovate

new business models, products, and services that seamlessly blend digital and physical

and business and customer experiences while improving operational efficiencies and

organisational performance.

There are some key elements to notice here. One is "continuous process". IDC would argue that if an

organisation treats the adoption of new technology as a one off project, because of the speed of

change in technology and in competitive landscape in any industry, that organisation would fall behind

quickly again unless it had at the same time created a culture for on-going change and transformation.

Another key element is that it has to "innovate new business models, products and services". It is not

enough for example to put a mobile interface on an existing application to give access to customers or

employees. This will not change anything long-term. This is not transformation – even if it does

leverage digital technologies. There has to be a fundamental change to either processes, products or

services.

Think of it this way: since the start of the IT industry some 50+ years ago, essentially we have applied

IT to do what we were using people to do more efficiently. What digital transformation is about is doing

things differently. For this reason as well, there needs to be the link between the "fancy" front-end,

outward facing use of digital technologies and the operational business process aspect. Innovate for

example at the customer experience level only – and there will be no fundamental change to the way

that the organisation operates. The internal systems will find it difficult to keep up for example with

billing, delivery or other aspects of the customer fulfilment process.

So digital transformation is a massive undertaking. Consequently, European organisations are still at

the early start of the journey. IDC has developed an approach to measuring the maturity of adoption of

technologies, which has also been applied to the broader concept of digital transformation as shown in

Figure 1 below.


Figure 1: European Digital Transformation Maturity Distribution across the Stages

Source: IDC's European Digital Transformation MaturityScape Benchmark Survey, June 2015 (n=413)

There are five stages of maturity: ad hoc, opportunistic, repeatable, managed, and optimized. For

each stage, the IDC Digital Transformation MaturityScape Benchmark addresses how capabilities for

a particular dimension need to change to improve the business' ability to leverage digital technologies

for competitive advantage. The key characteristics of the five maturity stages are:

Ad hoc: Management goals for digital transformation are poorly defined and occasionally

chaotic. Success often depends on individual effort and benefits are not widely shared within

the business. Business and IT digital initiatives are disconnected and poorly aligned with

enterprise strategy and not focused on customer experiences.

Opportunistic: Basic capabilities are established. The necessary disciplines for digital

transformation are in place to repeat earlier successes on similar initiatives. The business

somewhat lags behind best performing peers. Business has identified a need to develop

digitally enhanced customer business strategies, but execution is on an isolated project basis,

and progress is neither predictable nor repeatable.

Repeatable: Business-IT goals are aligned at enterprise level to near-term strategy and

include digital customer product and experience initiatives but are not yet focused on the

disruptive potential of digital initiatives. Capabilities are documented, standardized, and

integrated at the enterprise level. Digital transformation at the business level is a strategic

business goal. The business maintains parity with its competitors and peers.

Managed: Capabilities for digital transformation are embedded in the enterprise and tightly

linked to an agile management vision. The business leads its peers and competitors.

Integrated, synergistic business-IT management disciplines deliver digitally enabled

product/service experiences on a continuous basis.

Optimized: Enterprise is aggressively disruptive in the use of new digital technologies and

business models to affect markets. Ecosystem awareness and feedback is a constant input to

business innovation. Continuous improvement is a core business management philosophy.

Leadership embraces risk taking and experimentation to develop innovative, ground-breaking

capabilities.


As can be seen from benchmark, only 5% of European organisations can currently be termed digital

disruptors while at the other end of the spectrum, one in five can be characterised as digital laggards.

Many European organisations are currently only laying the groundwork in terms of establishing the

enabling ICT environments that will allow them to transform digitally. The following section establishes

a broad-based consensus of what these enabling technologies are.

2.3 Review of the Main Sources

As explained above, most industries are fast adopting ICT innovations to improve productivity,

increase market share, and decrease operational costs. A rapid decline in ICTs prices and the

improvement in these technologies performance are enabling the development of new products and

services as well as the way enterprises produce and deliver goods and services.

In order to understand what the industry is going to look like and consequently which skills will be

more demanded, we need to understand which technology trends are going to catch on in the

upcoming years. To identify and select the most important technology trends, how they are shaping

industries and ways of working, we carried out a comparative analysis of the most relevant public

sources.

To do so, we carried out a desk research with which we consulted a number of sources. In this

paragraph we are going to select and propose the trends of a selected number of sources; these

sources are the ones specifically focusing on ICTs technologies and on their impacts on the economy.

With the desk research, we examined the following sources: OECD (Organisation for Economic Co-

operation and Development); STOA (Science and Technology Options Assessment, European

Parliament); the European Commission, DG CNCT; the World Bank; and some private sources like

Accenture, McKinsey, and IBM.

The public and international organisations confirmed the framework we adopted for the adoption of

ICTs and the consequent transformation of the industry. All the sources in fact present digitally driven

economies where digital technologies will be available to anybody and to any business at the same

time, with knowing-based systems facilitating savings and market reach (OECD, 2014; European

Internet Foundation, 2014).

On the overall, the different sources examined converge because they all see that in the next decade

ICT innovation will transform business processes as well as competition and business organisation in

most of the industries. Some of them insist more on one or on another technology but the output

seems to be a different organisation of production and distribution. Specifically, what seems to be

really relevant in all the sources analysed is the combination of all the innovation trends. There are in

fact strong interdependencies in the ICT innovative technologies (cloud supports mobility, IoT and

social media support the production and use of data) and what is really relevant for the digital

transformation is the combination of the main relevant technology trends.

Nevertheless, to understand the impact technology trends are going to have on demand of skills, we

need to focus on the main single technologies. The private sources better focus on specific technology

trends and therefore we are going to present a quick overview of the trends they believe are going to

emerge and consolidate in the next five years. The main private sources we have taken in exam are:

1- Accenture, Technology Vision 2015

2- McKinsey Global Institute “Disruptive Technologies”, 2013

3- IBM, Global Technology Outlook, 2015


McKinsey did not update its last technology report, which was already presented in our last report4; we

present here a quick overview since this technology report is still valid and confirmed by the McKinsey

Global Institute with recent articles and interviews.

2.3.1 Accenture

Accenture's technology vision centres on the digital business, which means that competitive

enterprises leverage Social, Mobile, Analytics, and Cloud (SMAC) technologies. These technologies

are used to improve internal processes, but also a driving force for how to grow and gain

competitiveness and market share.

Digital businesses are changing the way they work. However, in order to become a true digital

business this does not simply entail incorporating technologies into the organisation, but also to

integrate the businesses into a broader digital ecosystem, which includes customers, partners,

employees, suppliers.

The Accenture Technology Vision maps five key trends:

The Internet of Me: everyday objects are online as well as experiences. News, playlists, and

customisation of personal goods. Enterprises are actively creating connected worlds in which

their customers’ preferences, habits, and context help making daily experiences. Digital

devices enable personalised experience and every experience is becoming a digital one. As

an example, cars can learn drivers’ habits and improve their performance. The connected

world (cars, home, wearables) says Accenture, creates a world of access to customers.

Personalisation of products and services is no longer a peculiarity of products and services for

B2B but it is the peculiarity of products and services designed for customers and households.

Outcome Economy: in the outcome economy, companies do not sell things; they deliver

results. Hardware is playing a leading role in the outcome economy; hardware is becoming

increasingly intelligent, otherwise known as IoT. Enterprises are embedding hardware and

sensors in their digital toolboxes. By putting sensors at the edge of networks companies gain

end-to-end insight on their entire value and supply chain. Accenture highlights how delivering

results is a strategy for sustaining competitive advantage today but it will be a survival strategy

beyond that.

Platform (R)evolution: rapid advances in cloud and mobility are eliminating technology and

cost barriers associated with platforms. Digital technologies such as mobile, social, analytics,

cloud and IoT are underpinning platforms. Industry technology platforms will increasingly

create new kinds of products, value, and differentiation for buyers and sellers across the entire

supply chain. As Accenture states: “Today, it’s not enough to simply develop and deploy

digital tools. Companies must apply their industry knowledge to build platforms that allow them

to rapidly innovate, develop, and deploy the products and solutions needed to drive their

digital business strategies.” Digital industry platforms are driving the next major wave of

technology and business change. Based on an Accenture survey, industry boundaries will

blur, as platforms will reshape industries into interconnected ecosystem.

Intelligent Enterprise: Until now, advanced software-supported employees make better and

faster decisions, and organise their work in a more effective and efficient way. In the future,

the emergence of Big Data and software intelligence is supporting machines to make better

informed decisions. Enterprises increasingly use the data they identify, capture, categorize,

analyse and they share data throughout the supply chain. More decisions are being made by

software. Moreover, machine learning can learn from software data, and discover

4 See: Hüsing, Tobias, Dashja, E., Gareis, K., Korte, W.B., Stabenow, T., Markus, P.: e-Leadership Skills for

Small and Medium Sized Enterprises - Final Report, October 2015


connections. Software intelligence is a game changer for businesses and getting smart

software may considerably change industry competitiveness.

Workforce Reimagined: the acceleration of the digital revolution will require that humans and

machines cooperate more than in the past. Advances in mobile devices, interfaces, smart

machines, and analytics will require empowerment of workers through technology. To drive

future businesses humans will not be sufficient; a combination of humans and machines will

be necessary.

Figure 2: Evolution of Main Trends in Accenture's Vision

Source: Accenture, 2015

In 2015, the Accenture vision focuses on a workforce (reimagined) becoming a strategic and relevant

carrier of the technology evolution. A couple of years ago, becoming a digital business could still

depend on being able to integrate technologies into the organisation. From now on, it will be about

using digital technologies to weave together customers, suppliers, employees, other industries

upstream and downstream in order to build a digital fabric and supply chain always interconnected.

2.3.2 McKinsey Global Institute

In 2013, the McKinsey Global Institute (MGI)5 reviewed a long list of over 100 technologies before

selecting the 12 most disruptive ones. The 12 technologies selected by MGI are presented in the table

below. The first four concern ICT directly and represent the most important potential impact on the

demand for e-skills.

Table 1: Twelve Potentially Economically Disruptive Technologies

5 McKinsey Global Institute: “Disruptive technologies: Advances that will transform Life, Business, and the

Global Economy”, May 2013


Technology Description

Mobile Internet Increasingly inexpensive and capable mobile computing devices and Internet connectivity

Automation of knowledge work

Intelligent software systems that can perform knowledge work tasks involving unstructured commands and subtle judgments

Internet of Things The Internet of Things Networks of low-cost sensors and actuators for data collection, monitoring, decision making, and process optimization

Cloud Computing Cloud technology Use of computer hardware and software resources delivered over a network or the Internet, often as a service

Advanced Robotics Increasingly capable robots with enhanced senses, dexterity, and intelligence used to automate tasks or augment humans

3D printing Additive manufacturing techniques to create objects by printing layers of material based on digital models

Autonomous and near-autonomous vehicles

Vehicles that can navigate and operate with reduced or no human intervention

Next-generation genomics Fast, low-cost gene sequencing, advanced big data analytics, and synthetic biology (“writing” DNA) Energy storage Devices or systems that store energy for later use

Energy storage Devices or systems that store energy for later use, including batteries

Advanced oil and gas exploration and recovery

Exploration and recovery techniques that make extraction of unconventional oil and gas economical

Renewable energy Generation of electricity from renewable sources with reduced harmful climate impact

Advanced materials Materials designed to have superior characteristics (e.g., strength, weight, conductivity) or functionality

Source: McKinsey Global Institute May 2013

According to Mc Kinsey (Finding your digital sweet spot, 2013) digital transformation drives value in

businesses through: enhanced connectivity, automation of manual tasks, improved decision making,

and product or service innovation, as shown in the below figure. McKinsey underlines that where

digital tools are applied selectively by enterprises, this can create missed opportunities to gain

advantages from digital investments.


Figure 3: McKinsey's view of digital transformation

Source: McKinsey, Finding your digital sweet spot, 2013

An ongoing research from McKinsey (November 2015) also forecasts that 45 percent of the activities

individuals are paid for can be automated, and that even the highest-paid occupations in the economy,

such as financial managers, physicians, and senior executives, including CEOs, have a significant

amount of activity that can be automated. The figure below illustrates how automation can be used

and capabilities this can require. The organizational and leadership implications of such an automation

are very relevant. The preliminary results show that the benefits (ranging from increased output to

higher quality and improved reliability) typically are between three and ten times the cost. The

magnitude of those benefits suggests that the ability to staff, manage, and lead increasingly

automated organizations will become an important competitive advantage.


Figure 4: Impact of technological automation based on 2,000 work activities

Source: McKinsey Quarterly, Four fundamentals of Workplace Automation, November 2015

2.3.3 IBM, Global Technology Outlook, 2015

The Global Technology Outlook (GTO) is IBM's vision of the future for IT, including its implications on

industries. This research highlights emerging software, hardware, and services technology trends that

are expected to significantly impact the IT sector in the next three to ten years. Specifically, the GTO

identifies technologies that may be disruptive to existing businesses, may create new opportunities,

and can provide new business value.

The key topics for the 2015 GTO include the following technologies and issues:


Cloud Data Foundation: how to respond to the increase in volume and types of data stored

in the cloud

Industry Data Curation: building a data ecosystem that combines organisation’s data with

open data to derive more insights

Transforming Healthcare Through Personalised Systems of Insight: how the rapid growth

of exogenous data is transforming healthcare to improve the personalised medicine

Payments Insights and Digital Cash: the benefits of accelerating the digitisation of cash

payments, which comprise 85% of retail payments today

Ad-hoc Infrastructure and Data: the volumes of data generated by wearables, video and the

Internet of Things are becoming more challenging to move, so processing has to move to the

edge, where it is generated

Neuromorphic Computing: a new processor architecture based on the human brain that can

process the data generated at the edge using significantly less power.

The 2015 GTO is mainly based on the concept that since the beginning of the 2000s, IT technology is

based on and evolving on the fact that data are growing exponentially and the use and exploitation of

data is demanding new approaches in terms of technology and strategy.

In 2012, the IBM GTO focused on the emergence of a new technology: Big Data characterised by the

four Vs (Volume, Velocity, Variety, and Veracity) and their penetration in the socio-economic system.

In 2013, IBM highlighted the confluence of social, mobile, cloud, Big Data and analytics technologies.

Since 2014, IBM's vision has underlined how demand for more and more data is transforming all

industries.

This shows that there is a new technology paradigm: innovation centred on data use seems led, from

now on, by a demand-pull trajectory. IBM believes that from 2014 data are starting to transform

industries and will have disruptive effects on all industries because technology is changing the use

and relevance of data. This will affect and transform decision-making processes, the way

organisations produce and deliver products and services and the way they compete.

The technology trends presented above all agree about the transformational impacts of digital

technology on businesses and their supply chain. Some organisations may have a vision very much

focused on businesses and on their organisation (Accenture), others (McKinsey and IBM) also

consider technologies which impact on everyday life. This is the case for example of IBM considering

the transformation of healthcare. McKinsey as well considers technologies like genomics, energy

storage, renewable energy and advanced materials. For both McKinsey and IBM the digital

technologies are part of a pool of innovative technologies, which are transforming the businesses and

citizen and consumer life. Moreover, the vision of these last organisations is based on the idea that the

digital technologies are multipurpose technologies affected by other technologies and that they

interfere with other innovations (energy, materials…).

In any case, when considering businesses and supply chains, all the sources considered believe that

we are going to face a transformation that will considerably re-shape enterprises and industries.

ICT innovation is complemented by KET (Key Enabling Technologies) innovation which is also

transforming the European industry, as documented by PWC's analysis. These technologies are in

fact instrumental in modernising the European industrial base: KETs are strategic because they are

used and installed in virtually all technical equipment (dishwashers, microwave, ovens, flat screens,

cars, trains, ships…); specifically, KETs are also fundamental in mobile devices, pcs, servers and

many electronic devices. The main KET trends and their complementary role to digital innovation

trends is analysed in chapter 11 of this report.


2.3.4 Automation and Robotics

We should here spend some words on automation and robotics. Automation and robotics is in some

way the synthesis of the new production and business processes and one of the trends which could

have major impacts on employment both at qualitative and quantitative level. This is the reason why

robotics and automation are currently at the centre of analysts’ debate.

"The Rise of the Robots: Technology and the Threat of a Jobless Future" (Martin Ford, 2015) analyses

the effects of automation and robotics on industries. One of the major effects is the destruction of jobs

beside the need for very qualified jobs. Today it is no longer an issue confined to the factories only; it

is an issue affecting whatever kind of job and industry from radiologists to lawyers to designers to

analysts and so on. Tasks that some years ago seem to require a distinctively human capacity are

increasingly assigned to algorithms.

The first consequences of these trends are already evident: college-educated people sometimes do

not find a job for years after graduation, companies hesitate rehiring people they laid off, substituting

them through a more intensive use of IT.

What is certain, is that the advent of automation and robotics will significantly change the demand for

labour, in terms of quantity and quality, as well as well as work distribution. For sure, the overall

impact of automation and robotics in the medium to long term will be very relevant. All innovations

have always involved new business models and new distribution of labour and resources in general,

and the same will happen this time. There is no reason to think otherwise.

However, excessive alarmism should be avoided. What matters are the overall net effects on the

labour market, which do not depend solely on technology change but also on socio-economic and

policy factors. Also, automation and robotics will be implemented together with other innovations,

which may in turn create new work opportunities. When business models and the distribution of labour

and other resources change, the ex-ante estimates of impacts requires a complex analysis.

2.4 The Effect of New Technologies on Business Models

Digital innovation is giving rise to a number of new business models (OECD, 2014). It is well known

that ICTs for example have made it possible to conduct businesses over long distances. Digital

innovation is creating different new ways to do business and to create value. We do not want to make

here an exhaustive discussion about business models but just to provide and idea of how far

technology can change the way we are doing business and creating value.

Cloud computing is the result of both new technology and new business models: value has

moved to new proprietary applications that are not stand-alone software products but internet-

based applications.

We are currently seeing the emergence of various sharing applications using different

business models and focusing service or products. New online services enabling a sharing

and service economy have also appeared, allowing people to rent out their homes, vehicles

and skills to third parties.

The digital economy is generating business models which can be described in terms of

vertical integration between layers. Businesses pay operators to put their application on line,

and their interactions with users generate revenues either directly from the user or indirectly

through the generation of value elsewhere in the business model.

Multi-sided business models are emerging: these are markets where multiple distinct groups

of persons interact through an intermediary or a platform. The decisions of each group affect

the outcome of the other groups of persons through a positive or negative externality. In a


multi-sided business model, the prices charged to the members of each group reflect the

effects of these externalities. The payment card system is an example of a multi-sided

business model. The payment card system is more valuable to merchants if more consumers

use the card, and more valuable to consumers if more merchants accept the card. On the

same way, an operating system is more valuable to end users if more developers write

software for it, and more valuable to software developers if more potential software

purchasers use the operating system.

Big Data plays a special role as the enabler of most of the innovative services and

applications being currently developed. Particularly the combination Big Data, IoT and Cloud

Computing is highly effective for digital transformation in the business environment. The

diffusion of IoT solutions will generate huge amounts of data for real-time processing and

predictive analytics, while cloud computing is the delivery channel enabling the transmission of

data and the use of remote data-based services to all enterprises, with pay-as-you-go models.

The diffusion of mobile and social technologies in turn generates huge amounts of consumer

and business data.

Data value: Data pricing is a difficult exercise since the value of data may not follow market-

based rules and converge, more or less naturally, towards the point where demand and offer

meet. In fact, data monetization (i.e. the process by which data producers, data aggregators

and data consumers exchange, sell or trade data and establish a possible monetary value to

this data) depends on a multitude of factors, often subjective ones, such as the perceived

worth and utility of the data, their source, their accuracy, but also the incentives (which may

vary considerably by type of data stakeholder) in exchanging the data. As an example,

according to the OECD some economic experiments and surveys the United States indicate

that individuals are willing to reveal their social security numbers for USD 240 on average,

while the same data sets can be obtained for less than USD 10 from private data brokers and

data marketplaces.6 Evidence gathered so far by IDC in Europe’s business-to-business

environment, however, tends to highlight the prominence of the bundling model when

exchanging and trading data – data-based services are bundled with other services and priced

accordingly. As an example, SWIFT, the Belgian headquartered organization enabling

financial institutions to make financial transactions in a secure, standardized and reliable

environment, has founded SWIFT Ref7, a payment reference data utility, which sources data

directly from banks and offers other companies data-based services aiming at minimizing

payment delays, reduce financial risks, and improve regulatory compliance. These services

are provided in packaged offers often including additional non-data-based services, hence the

difficulty to isolate the “value” of data and define the mechanism adopted to price them.

In The Sharing Economy: Why People Participate in Collaborative Consumption8, the authors define

the sharing economy as "peer-to-peer-based sharing of access to goods and services (coordinated

through community-based online services)". We are seeing many examples of this model emerging –

and they are all enabled by digital technologies. Perhaps the first major example of this was eBay as

an online marketplace accessible for anyone, but the current oft-cited example is Airbnb.

These business models have potential disruptive effects on existing social and economic models. For

example when start-up Uber launched Uber-pop, enabling individuals to provide private transport

services with their own car, it generated a storm of lawsuits around the world because of accusations

of unfair competition with traditional taxi companies (who must comply with rigid safety, fiscal and

6 Data-Driven Innovation for Growth and Well-Being: Interim Synthesis Report”, OECD 2014

7 https://swiftref.swift.com/about-swiftref

8 The Sharing Economy: Why People Participate in Collaborative Consumption, Juho Hamari, Mimmi Sjöklint, Antti Ukkonen, Journal of the Association for Information Science and Technology, July 2015


social costs regulation). In May 2015, Uber ceased UberPop and replaced it by UberX which is more

similar to a conventional chauffeur service.

Underpinning these new business models is that principle that the use of technology makes it possible

for individuals, businesses and governments alike to optimise the use of resources by sharing,

redistributing or reusing spare capacity in its widest form, such as money (social lending),

accommodation (Airbnb), any used goods (freecycle), and car sharing (RelayRides) to name a few.

2.5 Main Disruptive Shifts in the Coming Years

Analysts agree that advances in technology are going to transform dramatically every-day life,

businesses, and the global economy. This trend already started in the beginning of the 2000s, and

most analysts believe that the digital transformation is going to be quite evident in the upcoming years.

The drivers highlighted above by the different studies and research institutes are very relevant for this

development. However, what is even more relevant is the combination of these drivers in a global

economy; they hold the power to disrupt the industry landscape and the way modern industries work,

produce, and deliver.

The technology trends we have mentioned may accelerate the transformation of the industry

landscape and structure. The main structural characteristics of digitally transformed industries will be:

Integration and very structured organisations. Digital transformation is going to drive an

unprecedented reorganisation of production processes, of value creation and of industry

structures. Digital platforms and social connections may help achieving scales previously

attainable only by large organisations, so that the size of the business may not be as relevant

as it was in the past since even the smallest company can achieve global reach. The

emergence of industry platforms will create new products and services, and modify and

integrate the supply chain: more integration but also more flexibility will be a characteristic of

the future production processes. Industry platforms will allow personalisation of products both

in B2B and B2C relationships, which were previously inconceivable without high costs. A new

generation of organisational concepts and work skills are going to be necessary; new work

skills will come from game design, neuroscience, and happiness psychology.9

A globally connected world. The past couple of decades has witnessed both increasing

globalisation of products and services and increasing globalisation of the production system.

Nowadays, availability of computing power, memory, connectivity, and high-speed networks

are increasing the ability to connect factories and businesses, much more than was possible

just a few years ago. This connection capacity is changing the way manufacturers interact with

customers and with their suppliers, and is modifying the traditional relationships and

exchanges along the supply chain. Previously, economic theories and analysis were based on

the idea that large companies could take advantage of scale factors around cost and supply-

chain efficiencies. With the digital factory, we need to re-think production processes,

competitive advantages, and stakeholders’ relationships.

Automation driven by artificial intelligence transforming work. Digital innovation is

progressively increasing the activities that can be automated. The magnitude of the

automation benefits seem to be very relevant and they can provide unexpected competitive

advantages. Sometimes we can hear that automation is a threat for the employment.

Nevertheless, it is not known whether the net effect on employment is positive thanks to the

competitive advantage provided by automation. Automation will transform the vast majority of

occupations which will require a redefinition and a transformation of business processes. The

9 Institute for the Future, 2011


benefits will not only affect cost savings aspects but they may extend beyond that and require

a profound re-organisation of business processes. This will create new social and economic

challenges and require a change in the governance of the labour market.


3 Overview of the Key ICT Trends and Skills

3.1 Overview

In IDC's vision, the ICT industry is in the midst of a "once every 20–25 years" shift to a new technology

platform for growth and innovation (the Third IT Platform), expected to dominate the market by 2020

(Figure 5). This platform is characterised by the disruptive combination of the following technologies:

The diffusion of cloud computing, a disruptive delivery model of IT software and services,

based on flexible and on-demand business models;

The incredibly rapid penetration of mobile devices and technologies, including mobile apps

and M2M, machine to machine connectivity through billions of sensors (the Internet of things);

The emergence of Big Data analytics, driven by the huge increase of data generated by

mobile devices and the Internet;

The diffusion of social technologies, migrating from the personal to the business

environment will be affecting profoundly business and social interactions within enterprises

and in supply chains.

In addition it is necessary to consider another, horizontal transformational trend, that is:

IT security: affected by the new technology environment, shaped by emerging cyber threats

and the evolution of regulation, this trend requires specific attention and influences the mix of

skills required to deal with these new challenges.

These core technologies have already built momentum, but they are now becoming the "building

base" for an additional wave of technologies – called innovation accelerators by IDC – which will

radically change and expand the possibilities and opportunities that ICT can bring in terms of

innovation and value creation. The additional innovation accelerators that IDC assesses will have a

major impact in Europe out to 2020 are:

The Internet of Things (IoT) which enables objects sharing information with other

objects/members in the network, recognizing events and changes so to react autonomously in

an appropriate manner. The IoT therefore builds on communication between things

(machines, buildings, cars, animals etc.) that leads to action and value creation.

Virtual/augmented reality: Technology that allows immersive visual experience that removes

or complements external visual input and follows the user's head movement;

Wearables: At the broadest level, wearable computing devices include any wearable device

with a microprocessor. "Wearable" implies that the device operates in a hands-free fashion

and the user can readily put it on and take it off. "Computing" means that it is capable of

digitally processing data.

3D printing of all kinds: Materializing all sorts of physical things from digital blueprints — from

food to clothing to eventually even living tissue and organs.

Cognitive systems and robotics: Systems that observe, learn, analyse, offer suggestions,

and even create new ideas — dramatically reshaping every services industry. Includes

artificial intelligence (AI), machine learning, cognitive computing, and robotic process

automation.

This section discusses in detail these main technology trends, their rate of adoption and the new or

changed skills that will be demanded for the successful adoption of the technology.


Figure 5 The 3d Platform and Innovation Accelerators

Source: IDC 2015

3.2 Approach to the Assessment of Impact on Skills

In order to assess the impact of ICT trends on the demand of e-leadership skills we have expanded

upon approaches already taken in previous work10

. This has resulted in the following approach.

The first part of the assessment is focused on changes of demand of ICT skills. This analysis provides

the basis for the "digital savvy" component of e-leadership and the conceptual framework to

understand how technology trends shape business innovation.

The ICT-related skills are segmented as follows:

Technical Skills:

o Core technology – Infrastructure including: information systems outsourcing,

network and desktop outsourcing, network consulting and integration services, hosted

infrastructure services, hardware deploy and support, and system integration

contracts where the main purpose is implementation of hardware or network solutions;

o Core technology – Applications including custom application development,

application management, hosted application management, software deploy and

support, and system integration contracts for implementation of application solutions;

R&D skills required to deal with the main research challenges driven by the ICT trends and

their intersection in the next 5 years, enabling the development of new products and services.

This is focused on applied research, not long-term and basic research.

10

ICT Trends 2020 - Main Trends for Information and Communication Technologies (ICT) and their Implications

for e-Leadership skills, IDC, August 2014; Skill requirements for KETs, Vision and Sectoral Pilot on Skills for Key

Enabling Technologies, PWC, June 2015


Quality, Risk & Management Skills: Competences related to quality, risk & safety aspects

(e.g. quality management, computer-aided quality assurance, emergency management and

response, industrial hygiene, risk assessment etc.). This item has been extrapolated because

of its increasing relevance in the development and implementation of new products and

services based on the innovative trends examined.

The second part of the assessment is focused on e-Leadership skills defined as follows.

E-Leadership Skills: the skills required of an individual to initiate and achieve digital

innovation including:

o Strategic Leadership skills: Lead inter‐disciplinary staff and influence stakeholders

across boundaries (functional, geographic);

o Business Savvy: Innovate business and operating models, delivering value to

organisations

o Digital Savvy: Envision and drive change for business performance, exploiting digital

technology trends as innovation opportunities.

To carry out the assessment, we have developed a matrix (see Table 2 below) classifying the main

impacts for each major trend and for each skills domain.

The assessment was carried out in two steps:

For each technology trend, qualitative description of the type of skills expected to be needed

in the next years up to 2020, which will drive skills demand; this is focused mainly on the new

requirements driven by innovation in the considered trend.

Summary assessment of the main changes in ICT and e-leadership skills demand across the

main ICT trends, underlining the balance of incremental demand (more of already required

skills), new demand (of new skills) and decreasing demand (of traditional skills).

The main criteria guiding the compilation of the matrix tables were the following:

For each ICT trend, the identification of the new skills requirements is based on IDC's

research on forecast demand, developed on the basis of 300,000 interviews per year to IT

suppliers and users organizations; on IDC's maturity models (maturityscapes is their IDC

brand name), elaborated by technology and vertical market; on IDC's expert opinion about the

perspectives of adoption of the new technology in a context of business evolution towards

digital transformation.

The assessment of demand of R&D skills relates to applied research challenges and

development of innovative products or services to be brought to market, not basic or long-term

research;

The decreasing demand for old/traditional skills is not specified by ICT trend, because it not so

much tied to specific technologies but to each organisation's approach to migration from

legacy systems and traditional technologies, so it is extremely difficult to generalize by

technology. It is however examined in the cross-trend summary assessment.

Since e-leadership skills are essentially new, we do not foresee a decrease of demand for any

of them in the forecast period. Also, e-leadership skills by definition are horizontal and the

variations of demand by specific technology trend are not as relevant as with technology skills,

as will be shown in the following paragraphs.


Table 2: Assessment Matrix of Trends Impacts on Skills Demand

Technical Skills R&D

Quality,

Risk and

Safety

e-Leadership Skills


Strategic

Leadership

Business

Savvy

Digital

Savvy

Trend Type of skills Type of skills

Type of

skills

Type of skills

Type of skills

Type of skills

Type of skills

Source: IDC, 2015


4 Mobility and Mobile Applications

4.1 Main trends

The mobile industry is becoming one of the core enablers for business innovation. However, IDC sees

mobility moving slowly in the hands of IT departments in Europe. From a technology perspective,

mobility entails mobile devices (tablets, smart phones, etc.), mobile software (including mobile device

management, mobile application platforms and mobile applications), the related IT professional

services and mobile telecom services.

Consumerization has affected the way we work, and continues to do so, but the organisational

changes that are necessary for enterprise mobility to unleash its full potential are by no means

universally in place. Many IT departments are failing to introduce mobility as an enabling tool for

business transformation, and for many reasons, including:

• Security and compliance are at stake, and Europe presents a complex regulatory field.

• IT budgets are under increasing scrutiny; and mobility, despite its business appeal, is not

getting the necessary investment boost.

But it is not all gloom. IDC's Western Europe Enterprise Mobility Survey provides evidence that a

growing number of companies (44%) are planning to increase mobility budgets in the next two years,

suggesting that companies will quantify the business benefits derived from mobility even if it is more in

the medium term instead of now. Additionally, European IT departments report a growing mobile

workforce. IDC finds that the percentage of mobile workers has risen to 37% in 2015, from 33% in

2014, and is expected to increase to 43% in 2016.

In line with this continued growth in mobility we find that overall, European IT departments are

harnessing the potential of mobility and some are creating an enterprise-wide strategy, governance,

and architecture. Further, in a growing number of organisations, dedicated, cross-disciplinary mobility

teams are being put in place. In 2015, enterprise mobility has been and continues to be all about

applications. Once the majority of the workforce is equipped to use mobile applications, forward

looking CIOs are able to address how to evolve their organisations' mobile application development,

life-cycle management, and governance processes to cope with new demands — and the new

potential — that arise from the enterprise-wide mobilisation of IT systems.

There has been rapid growth in both the types of applications being mobilised and the number of

employees using mobile devices. Enterprise applications, such as enterprise resource planning (ERP),

customer relationship management (CRM), human capital management (HCM), and expense

management are now widely available in mobile form, as are more specialised types of applications.

In parallel, an increasing number of European enterprises are eager to build mobile applications that

improve customer engagement and employee productivity while reducing the cost of doing business.

For a growing number of organisations, the business risks of not addressing mobile applications

outweigh security concerns and development and deployment costs. There is a clear shift in the types

of mobile applications being built. Business to business (B2B) and business to employee (B2E) mobile

applications are now almost as diffuse as business to consumer (B2C) applications.

This said there continues to be a fair amount of experimentation and in many cases an overall lack of

centralised control over mobile application development, testing and management. Mobile applications

are being developed almost on an ad-hoc basis as and when required or even desired, both by line-of-

business (LOB) departments and IT, with little thought as to the overall business impact or value. In a

mobile first business world the definition of application quality has morphed beyond just a bug free and

secure application; delivery of superior customer experience and value becomes critical not just to the


application's success but to the brand integrity of the organisation itself. Designers, developers, LoBs,

and IT must be in a constant feedback loop of communication to deliver applications that drive return

on investment. Both front-facing elements like usability, performance, and content, and back-end

issues such as functional quality and security need to be factored in.

This insatiable demand for mobile devices and applications continues to grow, pressing IT

departments to increase support of multiple mobile platforms, but also to ensure that the applications

work across a plethora of devices and form factors as well. As an example of the magnitude of

spending on mobility, Figure 5 shows the forecasted spending on mobile applications in Western

Europe out to 2019.

Figure 6: Western Europe Spending on Mobile Applications, 2015 and 2019 ($ Million)

Source: IDC, 2015

4.2 Current and Future Adoption

As stated above, there is wide variation in the speed and sophistication with which European

enterprises are getting to grips with mobility and in how successfully enterprises are managing to

reconcile business needs with IT priorities. IDC's semi-annual Western Europe Enterprise Mobility

Survey, fielded in April 2015 across 923 CIOs, IT managers, and business decision makers across

seven countries (the U.K., Germany, France, Italy, Spain, the Netherlands, and Sweden), highlights

the following key trends in mobile maturity.

IT departments are working on a common integrated mobile architecture. In a bid to centralise

mobility, some IT organisations are focused on developing a common mobile platform,

connecting this with back-end systems and developing a central mobile compatible website.

Choose your own device (CYOD) becomes more popular than bring your own device (BYOD)

in Europe. The adoption of BYOD programs has reached a plateau across many countries in

Europe. Complexities around data privacy regulations, billing, and employees' concerns about

the "Big Brother" syndrome are contributing factors. By contrast, corporate ownership of

devices is on the rise again, with various types of CYOD policies becoming increasingly

popular.

651

1.343

0

200

400

600

800

1.000

1.200

1.400

1.600

2015 2019


Support for mobile collaboration and apps development is in high demand. CIOs are reporting

mobile collaboration and mobile apps development as top technologies supporting their

mobile workforce today, which is a remarkable advance in embracing mobility as an

enablement IT platform.

European firms are still in the very early phases of mobile application development and

management. Only one in five IT departments develop mobile apps in-house, and fewer

companies have a centralised enterprise repository for app distribution, security, and

management. In terms of mobile application development, about half of IT departments are in

the early stages with one mobile app at most. Only 1 in 10 advanced companies are

introducing a standardised cross-enterprise platform for native, web, and hybrid mobile app

development.

Tablets in the hands of at least one in three employees. On average over 50% of employees

are using smartphones, a figure that is expected to rise to 60% by 2016. Important as they

are, smartphones are not the only mobile device: 28% of employees are also using tablets, a

figure expected to increase to 37% in a year's time. Tablets are no longer "executive

jewellery"; in an increasing number of cases, they are the form factor of choice. At present, the

two largest OS platforms are Android (46%) and Apple iOS (35%), but Microsoft with Windows

10 in third place is likely to create major disruption soon.

To be able to assess overall enterprise mobility maturity IDC has created a model to gauge enterprise

mobility competence and sophistication through five stages of maturity: ad hoc, opportunistic,

repeatable, managed, and optimized. Figure 6 shows the different phases in the enterprise mobility

maturity journey.

Figure 7: Mobile IT across Maturity Stages

Optimized

Managed

Repeatable Opportunistic

Ad Hoc

Sustain leveraged competitive advantage with continuous improvement and innovation in mobility

Drive competitive differentiation with enterprisewide governance and management in mobility

Improve cost/benefit performance of continued implementations with integrated capabilities in mobility

Reap early stage benefits and increase constituent buy-in with initial mobility implementations

Prove value of mobility with proof-of-concept or pilot projects


Source: IDC, Western Europe Enterprise Mobile Adoption Maturity, 2015, Doc Number #LM01X

The relative distribution of European companies across the five stages of maturity (based on the results from IDC's semi-annual Western Europe Enterprise Mobility Survey) is represented in Figure 7.

Figure 8 : the Maturity of European Organisations in Mobility

Source: IDC, Western Europe Enterprise Mobile Adoption Maturity, 2015, Doc Number #LM01X

The following explains each of the maturity stages:

Ad hoc. In this phase, organisations are in mobile experimentation mode, with mobile

initiatives developed in a pilot approach. One in five European companies is in the ad hoc

phase of enterprise mobility maturity: 19% of IT departments rated mobility as low or no

priority in IT strategies, have no dedicated resources, and do not have an enterprise mobility

strategy. Mobile deployments are siloed and driven by the line of business (LOB).

Consequently, there is a lack of integration, and platform inconsistency prevails across the

organisation.

Opportunistic. In this phase, the need for mobility is established, but enterprise-wide capabilities are still "under design". Almost half of European organisations fit into the opportunistic phase of enterprise mobility maturity. These companies understand the business value of mobility and prioritise investments, but find it difficult to create leadership and a suitable architecture for a mobile-first business environment. The lack of platform standardisation, heavy systems integration needs, and organisational challenges hold back these companies. In this phase, IT departments feel overstretched and under-resourced. BYOD/CYOD policies are immature or non-existent. Frustrated business users take a do-it-yourself approach with local support from shadow IT, or they outsource development to a third party.

Repeatable. In this phase, mobility is recognised as strategic for the business, and the organisation leverages standardised platforms and configurations to provide basic mobility

18,8%

46,7%

29,5%

4,5%

0,5%0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Stage 1

Ad Hoc

Stage 2

Opportunistic

Stage 3

Repeatable

Stage 4

Managed

Stage 5

Optimized


services to all employees. Close to a third of European firms are at the repeatable phase. In this phase, IT has implemented a common standardised platform to industrialise and become more efficient in the provision of mobility services across the organisation. With the mobile architecture integrated with the enterprise infrastructure and systems, security is tightened and enterprise app stores are in place. IT still has a supportive role and provides mobility as a basic service to employees who can enrol in BYOD/CYOD schemes, but not for business innovation or competitive edge yet.

Managed. In this phase, mobility delivers business innovation with all business stakeholders involved; IT departments provide a consistent user experience (UX) across platforms and devices. Less than 5% of European IT departments fit into the managed phase of the maturity model. These organisations take mobility seriously as an enabler of business productivity and innovation. With stakeholder buy-in and financial support from executive management, the enterprise-wide, mobile strategy provides the business with valuable apps and contextual information. IT is user-centric, and employees enjoy a consistent UX across devices and platforms. App life-cycle management and development follow an integrated and continuous testing and quality control process. App usage, performance, and business impact are monitored.

Optimised: In this phase, organisations deliver agile, adaptive, and flexible enterprise mobility

solutions; the business has built and sustained competitive advantage through mobility. The

percentage of companies in the optimised stage is very small in Western Europe. In this

phase, IT departments are leveraging mobility to deliver competitive edge and business

differentiation to their organisations. In close alignment with market needs, the mobile

architecture is agile, adaptive, and able to deliver innovative mobile services from an elastic

cloud infrastructure.

In 2016, IDC expects European IT departments to move to the repeatable phase, while some

advanced companies will be gradually progressing toward the managed phase. In this phase, mobile

initiatives are a company priority, and IT leverages mobility to deliver business innovation as well as

competitive advantage for both employees and customers.

4.3 Skills Impact

Despite the cultural transition towards a more mature approach to mobility, IT departments have been

slow in the development and deployment of mobile applications. While a certain amount of mobile

application development (AD) and deployment is and will occur within internal enterprise IT teams,

IDC finds that European organisations are increasingly seeking expertise in mobile application UI/UX

design, development (shift to new agile development models, such as DevOps for mobile), testing and

integration services (back-end integration). This is simply because there is limited internal expertise

available or it is too expensive and challenging to hire in the right talent to keep up with rapid pace of

mobile technology change.

This trend has been observed for some time. IT departments are overstretched and under-resourced

to support the complex requirements of mobile IT. In reality, we find that demand for mobile

applications is outstripping available development capacity, making the quick creation of applications

even more challenging. IDC identifies that the following skills are required for successful future

adoption and maturity in enterprise mobility:

Cross-Platform Capabilities: As the mobile market grows, so does the fragmentation of

mobile users across mobile operating systems and devices. Developers need to have a cross-

platform plan when they begin coding for a new mobile application. Learning how to develop

correctly applications across platforms such as iOS, Android and Windows is an important skill


that can help IT managers and their admins get ahead and stay ahead in this environment. In

addition to multiple mobile operating systems, users are starting to demand that their mobile

phone experience translate onto other mediums like wearable technologies and any other

connected device. While both Google and Apple are trying to bridge the gap between

smartphones and other platforms, cross-platform capabilities of this kind are still in their

infancy stages. As focus expands beyond web and mobile applications to wearables and any

connected device (IoT) management of the talent network against client expectations will be

critical.

Modern Programming and Technical Skills. Mobile application developers must have a firm

grasp and experience of modern programming languages. Familiarity with front end

development and a good understanding of programming languages like PHP, Java, HTML5

and C#, as well as the likes of Adobe Flash Lite, Python, Objective C, CSS and JSP (to name

a few). Developers will be required to develop native, web, and hybrid mobile applications.

Native apps are developed specifically for an operating system such as Apple's iOS that

allows the app to take advantage of all the native functionality of the OS, providing a rich,

tailored experience. Hybrid apps are developed using HTML5/JavaScript and then are ported

for use on an operating system utilising tools such as Apache Cordova, a grouping of open

source APIs that allow developers to access native device functionality without having to use

the native SDKs and convert the HTML5/JavaScript to native executables. Skills in toolsets

such as Cordova will be increasingly critical.

User Experience and Interface Design (UI/UX). The definition of application quality has

fundamentally changed and user experience is now firmly in the driving seat with functional,

bug-free and secure code only half of the equation for a successful application. The need for

mobile applications to have unique and well-designed UI/UX requires access to skilled UI/UX

designers. However, expertise in this space is in short supply and as a result rather costly.

Mobile Project Management Skills. When it comes to mobile applications most people focus

on the developer skill-sets, however understanding the intricacies of mobility as it affects

methodology, testing, quality assurance, and architecture are equally important to the success

of any mobile project. Furthermore, designing and implementing enterprise business

applications for mobile is a different proposition to designing consumer applications. Teams

need to be brought together who can span the needs of front-end app design and

implementation and the back-end services upon which they will rely. UI/UX designers often do

not understand the needs of transactional systems and others will be required to implement

and tune the database, check and implement security requirements, consider the implications

of putting potentially sensitive personal and company data on devices outside the firewalls and

indeed the physical enterprise. Requirements analysts who understand the business process

needs and goals of the organisation must also be part of the team. The implications of

assembling and managing multi-disciplinary teams to meet the needs of mobile enterprise

requires a high level of skill and knowledge.

Device management is more complex due to the multiplicity of platforms, OS (iOS, Windows,

Android, etc.) and the faster pace of change. Support specialists will need to update their skills

more regularly, and be able to work across different platforms. Alternatively, the IT function

within enterprises will need to recruit more people to cover all technical requirements 24x7.

DevOps for Mobile. The breadth of demand for mobile application development talent as

stated previously is impressive. In line with this demand, we foresee an increasing focus on

finding talent skilled in DevOps practices. DevOps as a methodology, or set of practices,

unifies a team consisting of business leadership, development/testing, and operations to be

responsible for the creation and delivery of business capabilities. Enterprises deploying

DevOps report numerous benefits, including faster deployment of applications, increased

collaboration, greater use of applications by employees and customers, and improved


application quality and performance. In the mobile space, every one of these benefits are

essential, and forward thinking enterprises understand why DevOps is key to winning the

mobile battle. However, the fight to acquire these skills is just beginning and talent is for the

present still scarce.

These considerations show that applications development is the current focus for mobile innovation

today. From the point of view of R&D, the focus in the next years will be mainly on:

The design of new products and services based on mobile solutions, combining digital

innovation with business innovation; this is likely to require multidisciplinary competences in

the convergence of wireless technologies, IoT systems and devices, cloud computing and Big

Data.

The development of 5G wireless technologies that will provide ubiquitous super-fast

connectivity and seamless service delivery in all circumstances, completing the convergence

between telecom and IT, mobile and fixed access. As indicated by the 5G PPP (public-private

partnership) vision11

, most of the research in 5G technologies is focused around wireless, for

example one of the key technology challenges will be to facilitate "very dense deployments of

wireless communication links to connect over 7 trillion wireless devices serving over 7 billion

people". This will drive the demand for highly sophisticated R&D skills in wireless technologies

and software.

Table 3: Mobility impacts on demand of new skills


Quality, Risk and

Safety


Mobility

Mobile tech support skills

Mobile devices management

Cross-platform capabilities

New programming skills

DevOps for mobile

UI/UX design

Design of new products & services based on mobility

Development of 5G technologies

New challenges mainly linked to IT security aspects (see IT security)

E-Leadership Skills

Mobility


Capability to re-design business and marketing strategies to exploit mobility opportunities

Lead R&D to design new mobile products and services for business goals

Lead/coordinate mobility projects management

Capability to understand new mobile products & services potential for specific industry/ function

Source: IDC, 2015

11 https://5g-ppp.eu/about-us/


5 Cloud Computing

5.1 Main trends

Cloud is a model for delivering and consuming IT resources as a service in real time across the

network, replacing traditional models, where each client buys and own its own IT. In cloud, resources

are shared typically in pay-per-use models and with self-service. Cloud providers offer cloud services

to clients from their resource pools, and clients buy access to a standardised service, which makes it

both faster and cheaper for organisations to adopt new solution, and removes the burden of capex

investments.

This original cloud model is today called public cloud, because resources are shared openly between

everybody who wants them. However, because of security and compliance concerns a new cloud

version has appeared: private cloud, where the resource sharing is restricted to a pre-defined group,

typically only a specific organisation. This reduces flexibility and agility, as resource pools are typically

smaller and more difficult to enhance, and further require capital investments. Figure 9 provides an

overview of the segments and characteristics of the different cloud models.

Figure 9: IDC's Definition of Cloud Computing Deployment Models

Source: IDC: 2015


Public and private cloud models are seen to be appropriate for different purposes – and typically

security concerns are bigger in Europe than elsewhere in the world leading to a higher preference for

private cloud solutions. Today, typically mail and collaboration solutions are migrated to public cloud

whereas ERP and other solutions handling critical data are migrated to or implemented on private

clouds – hosted or on-premises.

Three key trends dominate cloud in Europe today: hybrid cloud adoption, uptake of a wide range of

new applications, and use of cloud as a basis for digital transformation.

5.1.1 Hybrid Cloud

Hybrid cloud solutions integrate public and private clouds in order to use a single tool to provision,

orchestrate and manage services on the different clouds, and potentially to support movements of

applications between different clouds, for instance for developing an application in public cloud but

deploying it in a private cloud, or to expand capacity in periods of peak load. The growing interest in

hybrid cloud models are leading vendors to launch hybrid cloud platforms and to design their own

supporting architectures.

Hybrid cloud portals will make it easier to deploy applications to different clouds from one tool, making

it substantially easier to use multiple clouds. Cloud platform services vendors, such as Accenture,

CSC and Atos compete on which clouds they allow their subscribers to use. Others like HP and IBM

are increasingly moving towards open stack technology that enable integration across several

vendors. However, the open stack solutions are still immature and lack a lot of functionality. Further,

they are not yet well suited for on-premises cloud, i.e. they make integration easier between public

clouds, but makes it harder to integrate private clouds.

However, the market is still in the early days of having software-defined datacenters – in 2015, 70% of

Western European organisations still did not have a unified service catalogue from which users could

get access to applications using self-service.

5.1.2 Explosive Uptake of Applications

Cloud models are leading to an explosion in the uptake of applications in Europe's organisations. This

includes smaller organisations getting access to SaaS-based applications at a more affordable cost as

well as new applications developed directly on the cloud. Cloud applications increasingly publish APIs

and make them available in the market for other users to tap into and this brings a contour of the

market, where new services are created by combination of modules from many sources. The need to

deploy new applications quickly also drives rapid growth in platform services. Hand-in-hand with this

phenomenon is a change in development models, focusing on DevOps as discussed above – a model

where the development from the start takes into account requirements for efficient operation in the

cloud.

5.1.3 Cloud for Digital Transformation

European organisations are very keen to use digital technologies (cloud, mobile, big data, social

media) to transform their operations. At the moment, they mainly invest in digital solutions to improve

the customer experience or to enhance their products and services with digital capabilities, but their

expectations are that they will see a big efficiency gain – and impact on customer experience – by

using digital technologies to integrate and automate internal processes. Digital transformation requires

an underlying cloud infrastructure, and organisations are not only investing in cloud to do what they


already do in a more cost-effective manner, but also to do new things to develop their businesses and

enhance their market potential and create growth.

5.2 Current and Future Adoption: Cloud Computing

Today practically all Western European organisation use cloud in one form or another, whereas

adoption in Central and Eastern Europe is lagging behind somewhat, especially on the private cloud

side (Figure 10).

The figure shows that SaaS and in-house private cloud are so far the most popular models. After a

slow start, European organisations are now moving standard business applications, such as ERP to

private cloud. Uncertainty about security and data residence has so far kept these applications on on-

premises clouds, but especially hosted private cloud models are growing rapidly for critical

applications. The surveyed organisations on average use two different cloud models – and typically

many applications within each model. This is partly a result of experimentation with different models,

but also partly a result of a conscious choice of which model is suited for which type of applications.

Figure 10: Cloud Adoption and Plans in Western Europe, 2015.

Source: IDC, 2015

In total, organisations in Europe will spend around €35 billion on cloud in 2015. Around 45% will be

spent on public cloud services, about 25% on hosted private cloud, and the rest on technology and

services for on-premises private cloud. Increase in cyber security capabilities and growing confidence

in public cloud will lead to higher growth in hosted private and public cloud spending than in on-

premises spending. Total spending on cloud will grow to around €70 billion in 2019 (an average

annual growth rate of 23%) with the composition changed to around half on public cloud services,

about 20% on hosted private cloud and about 30% on technology and services for on-premises private

cloud. Figure 11 illustrates these estimates.


Figure 11: Cloud Spending in the EU, 2015 and 2019

Source: IDC, 2015

Security and compliance requirements are still the main barriers to cloud adoption. The PRISM

scandal in 2013 brought security to people's attention – if it wasn't already. The Safe Harbour ruling by

the European Court of Justice in October 2015 under which data held in the US as "safe harbour" is

no longer compliant with EU data protection laws has again raised the attention around security and

compliance, and makes it more complicated for European organisations to understand, which cloud

providers live up to the EU legislation. This could have a favourable impact on the choice of Europe-

based vendors however, the new uncertainty will most likely put a brake on growth of use of cloud for

critical applications.

5.2.1 Cloud Maturity

While there are key technical barriers to cloud adoption, the low maturity in European organisations

are in itself a barrier to increased cloud usage. Most organisations struggle to take a systematic and

enterprise-wide approach to cloud adoption. Results from a survey of more than 900 European

organisations undertaken by IDC in December 2014 shows that 20% of the Western European

organisations are at the lowest maturity level of just doing pilots, while another 37% have moved to the

next level of investing in cloud, driven by needs in individual groups (see Figure 12). This leaves 43%

that has a systematic approach but where only 5% have reached the most mature stage of having a

cloud first approach and using cloud proactively to drive innovation.

45%

50% 25%

20%

30%

30%

0

10

20

30

40

50

60

70

80

2015 2019

€35 billion

€70 billion

€ Billion


Figure 12: Cloud Maturity in Western Europe, 2015

Source: IDC, 2015

5.3 Skills Impact

Succeeding in the cloud world requires a broad range of skills that are lacking in most European

organisations:

Business skills among IT savvy people. This includes understanding the organisation's

business processes and which are the critical parameters and priorities for the organisation. But it

also includes collaborative skills. A key challenge is that in many organisations the IT department

and the Lines of Business often speak different languages and have little understanding of what

the impact of changes to IT delivery (including introduction of cloud) may be and how to either

take advantage of – or alleviate – these effects.

Technology understanding among business people. According to various surveys (and

perhaps understandably), employees in the Line of Business appear to be more sceptical about

the benefits that IT can bring, than do employees in IT departments. The fact that the average IT

user is becoming savvier as a user of e.g. new devices does not guarantee that they really

understand what is possible with technology or indeed have the know-how to take advantage of

technology to change the organisation's processes, products or services. Even the digital natives

often lack the understanding to use the technology for real change.

Specific cloud related skills. These skills include dynamic scaling, provisioning, cloud

management and integration. An IDC survey in 2014 showed that two thirds of organisations in

Western Europe lacked these skills, and even if dramatically improved, there is still a long way to

go.

Most critical technical skills in shortage are network and architecture skills. The lack of these

skills is a major factor delaying enterprise-wide strategies and consistent implementations, and it

creates a potential risk of wasting money or complicating integration further because of the many

solutions available and often in use in organisations. Getting the architecture right is critical before

the broad adoption of applications and requires these combined technology capabilities. Poor

5%

10%

20%

28%

37%

0% 5% 10% 15% 20% 25% 30% 35% 40%

Cloud first strategy to proactively drive business innovation

Widespread proactive use of cloud by business and IT leaders

Pilots driven by individual decision makers

Consistent use of best practices across multiple groups

Driven by business needs of individual groups and departments


network architecture will lead to bottlenecks and service delays, resulting in inconsistent service

performance, which is one of the traits of a service that will alienate users most.

R&D skills Recent trends in cloud computing move towards the development of new paradigms

(heterogeneous, federated, distributed clouds) as opposed to the current centralised model, with

tight interactions between the computing and networking infrastructures. An area to be

investigated is the integration and cooperation between Fog Computing (a new concept developed

by Cisco) and the Cloud. Fog Computing is to some extent, an extension of the Cloud to network

and its edge in particular. The long term vision of Fog Computing envisages the dynamic, on

request allocation of processing, analysis or storage capabilities provided by the network and the

Cloud data centers to address the specific, at that moment needs of devices. Mobile Cloud

Computing is a good example of the potential benefits that Fog Computing can provide, in

particular when using approaches like Cloudlet computing. There will be a need for R&D skills to

address, from the research and experimentation perspectives, the necessary evolution in cloud

architectures, cloud networking, deployment practices and run-time management as well as the

associated security and privacy needs.

A key challenge with cloud is that it breaks down traditional silos between technology areas, and the

key personnel involved in design need competences that cross all areas of servers, storage, network,

management etc. Preferably, they should also have some business understanding. There is a

dramatic shortage of people with this breadth of skills. This is not just a short-term phenomenon –

when the focus moves to digital, the breadth of skills for each person will be as critical as ever.

Enterprises and vendors alike will need to collaborate with universities to ensure a more relevant skill-

set in new candidates but will also need to retrain their most senior people to have them take on these

roles. In order to cope with the skills gap, senior people currently have to take on roles and tasks that

should really be performed by junior or medium experienced people to help drive cloud. Reskilling is

therefore a major issue.


Table 4: Cloud Computing Impact on demand of new skills


Quality, Risk

and Safety


Cloud

Computing

Selection, configuration, combination, orchestration of cloud services, either public, private or hybrid

Specific cloud infrastructure technology skills

Network and architecture skills

Cloud management and integration

Skills to assess cloud readiness of applications

Skills to help change and migrate applications to cloud

Cloud management and integration

Research on heterogeneous, federated, distributed clouds and their architectures, and new models such as Fog computing

Manage new challenges mainly linked to IT security

E-Leadership Skills

Cloud

Computing


Strategic management of relationship with cloud providers/contracts/ SLA

Strategic management of data ownership/ data protection/privacy issues in cloud environment

Identify new products/services exploiting cloud potential combined with other technologies (IoT, Big Data) Lead/coordinate cloud projects management

Make the business case for cloud services adoption

Analysis and understanding of business demand and how cloud models can streamline/change business processes

Source: IDC, 2015


6 Big Data

6.1 Main Trends

Big Data is now a well-recognized phenomenon in Europe, and, while maturity of usage in operational

systems is still quite low, it is starting to take hold. The first generation of new technologies that took

data management beyond relational data management and access technologies into a range of non-

schematic or NoSQL software have now been tried and tested by many organisations.

Big Data and analytics allow organisations to improve the quality of decision making at the

operational, tactical, and strategic levels in order ultimately to improve organisational performance.

IDC research shows a correlation between greater use of analytics and better organisational

performance. However, the increase in complexity as business analytics evolves into Big Data means

that gaining value from information is a significant and growing challenge. For example, IDC research

shows that about 40% of large organisations report having at least one Hadoop deployment (either on-

premises or as a cloud service).

The current state of Big Data and analytics technology adoption and deployment is focused on data

architectures that blend relational and non-relational, streaming and batch data management

technology, and enables an ever-growing number of different users to access relevant data with a new

generation of visual discovery and advanced analytics tools, and applications that embed operational

intelligence. However these new technologies and techniques require new skills and approaches, and

these skills are not always widely available, and nor are the governance techniques widely known and

bedded in.

IDC defines Big Data as follows: "Big Data technologies describe a new generation of technologies

and architectures, designed to economically extract value from very large volumes of a wide variety of

data, by enabling high velocity capture, discovery, and/or analysis."

In essence, a broad understanding of Big Data is that it covers data sets that grow so large or so fast

that they are difficult to handle using traditional technology. The trouble with this as a definition is the

difficulty in defining "large", "fast", or "traditional". For example, accelerated databases are a broadly

accepted technology that has been around for over a decade, but they differ from a traditional

relational database, in that they constitute a non-traditional solution such as a Big Data technology.

Also, Big Data is not only about specific attributes of customers' data sets. It is also about using new

technologies and techniques to manage rapid growth, increased variability, and accelerating velocity

in those data sets to drive business growth. Every organisation can face a Big Data challenge if its

current IT infrastructure is not fit to handle the increasing requirements for availability and performance

of their growing volumes of data. Therefore, a further and pragmatic definition for Big Data may be

"what you have at the point in time when your existing architecture can no longer deal with the volume,

variety, and/or velocity of your organisational data."

The market hype around Big Data is substantial and continues to grow. In one sense, Big Data is an

evolution of what business analytics has been doing under various names for over two decades.

However, from a technology perspective, Big Data comprises a set of genuinely new technologies

(e.g., Hadoop, highly scalable databases, advanced data visualization tools, and high-performance

search engines) and a convergence of more mature technologies (e.g., event-driven processing,

business intelligence or BI, and data mining). One thing is certain from two decades of experience with

business analytics — to embrace fully Big Data, organisations need to be dedicated and determined to

embrace a more information-led culture, and have the skills and approaches to match. IDC research


shows clearly that the factors differentiating Big Data leaders and followers are primarily of culture,

approach and governance, not just a matter of technologies deployed per se.


IDC's most recent study of software usage in Europe, covering 1,451 European organisations across a

wide range of company sizes, industries and countries, found that Big Data initiatives had the third

highest planned spending increase amongst those organisations for 2015 (second highest was the

related area of increasing storage). Thus while big data maturity is still relatively low amongst

European organisations, it is set to rise quite considerably in the coming months and years.

The survey also showed that:

There remains a broad focus on gathering data, more so than on analysing it, which is based

on the corporate belief that amassing data is in itself a valuable proposition. This is a sign of

immaturity: in order to get value from all the newly gathered and stored data, there has to be

an element of applied analysis.

Penetration of the cloud has dramatically increased and this is affecting Big Data initiatives.

Penetration of Hadoop continues to rise, showing a considerable increase and approaching

the 20% threshold.

In another recent survey, IDC found that, in the past 12–24 months, three-quarters of organisations

have expanded data types and sources they analyse, and the number of users with access to Big

Data and analytics solutions. Importantly, the same number have also started using new metrics and

KPIs to manage their organisations.

Many vendors have jumped on the Big Data bandwagon, presenting offerings branded as Big Data or

"Big Data ready," but the understanding and interest of the IT end-user community are lagging

somewhat behind. With Big Data, the compelling use cases really need to come from the business

users that want to overcome the current limitations of their IT setup in order to create more agile

business processes, to segment and target their customers more accurately, or to design completely

new business models based on the new opportunities created by technology advances. Selling Big

Data technologies successfully will be about opening up new business opportunities and, to a lesser

extent, selling technology.

A key element of Big Data is the nature of the technologies involved. Big Data products include many

new and often open-source technologies. Most important is Hadoop, an open source, processing

framework that allows large analytical queries to be broken down to many small queries that can be

run in parallel and then reassembles the results into one dataset. Other associated open source

project developments include Pig, Hive, Spark and Yarn. Skills in these are in short supply and

experience of building, implementing and managing Hadoop environments is even rarer. The vast

majority of Hadoop projects are pilots and proof of value, and there are very few live production

environments in Europe. However, the Hadoop ecosystem is expected to grow quickly.

IDC started to measure the penetration of Hadoop into the European market in 2013, when 6% of

survey respondents overall were either piloting with Hadoop or running Hadoop in production. In the

last 12 months, adoption has dramatically increased, driven by two factors: vendor push – from

Californian start-ups to the biggest, most established systems vendors – and end-user pull, thanks to

the increasing awareness of Big Data technologies and their potential. The adoption pattern of

Hadoop is shown in Figure 13.


Figure 13: Europe's Hadoop Adoption Trajectory, 2013–2015

Source: IDC European Software Survey 2013, n = 700; IDC European Software Survey 2014, n = 1,309

6.3 Scenarios of evolution of the European Data Market

Big Data is a new generation of technologies, enabling the development of a whole range of new

products and services based on data-driven innovation, which in turn creates economic impacts and

benefits for the data user companies and the whole economy. To fully understand the potential impact

on skills of this technology trend, it is important to analyse in depth the dynamics of data-driven

innovation and its potential impacts on the European economy. To do so we present here a summary

of the first round of results of the European Data Market (EDM) Monitoring Tool, a comprehensive

system of indicators developed by IDC on behalf of DG CONNECT to monitor progress towards the

objectives of the EU Data Value Chain policy12

.

In this study we define the data market as follows:

The data market is the market where digital data is exchanged as "products" or as "services" derived

from raw data. The exploitation of the exchanged data enables a better understanding of the

environment, and helps improve existing services, increase efficiency, and eventually launch new

products/services also in the more traditional sectors of the economy (such as manufacturing,

transport, and retail)13

.

The European data market amounted to more than EUR 47 Billion in 2013, raising to EUR 50.4 Billion

in 2014, at a growth rate of 6.3%. This represents a share of total ICT spending in the EU28 of 8.7% in

2014, which is significant for an emerging market. Because of its still emerging nature, the diffusion of

12

The full report is public and can be downloaded at https://idc-emea.app.box.com/files/0/f/5092704946/ European_Data_Market_-_Public_Deliverables

13 See Taxonomy Annex of D2 — Methodology Report, August 2, 2014, European Data Market Study SMART

2013/0063

4%

22%

36%

4%

23%

37%

6%

33%

49%

0%

10%

20%

30%

40%

50%

60%

2013 2014 Planned for 2015

Hadoop Pilot Hadoop in Production Any Hadoop Activity

https://idc-emea.app.box.com/files/0/f/5092704946/


data-driven innovation by industry is likely to go through considerable change in the next few years.

However, the snapshot presented by these indicators at industry level shows a clear gap between a

set of industries picking up fast data innovation — mostly private (manufacturing, finance, retail,

information and communication, utilities) and the public sector and general public services

(government, healthcare, education, but also construction and transport), which appear to be lagging

behind. There are examples of pioneers and successful use of data-driven innovation in these

sectors, but widespread adoption will take time. Data and privacy protection issues are also barriers

for the public sector and in general for vertical markets dealing with highly sensitive data (such as

healthcare).

The value of the data economy includes the estimates of all the economic impacts produced by the

adoption of data-driven innovation and data technologies in the EU: this comprises direct impacts of

the data industry and its suppliers, indirect impacts on user industries, and induced impacts created by

the additional growth and spending generated by data-driven innovation across the whole of the

European economy.

As outlined in the figure below, the overall value of the data economy in the EU is estimated at about

EUR 255 billion in 2014, representing a contribution to the EU GDP of approximately 1.8%. Indirect

impacts on the user industries represent the largest share of total impacts (55%). This is a remarkably

high value for an emerging market, hinting at an even greater potential.

Figure 14 Value of the European Data Economy, 2014

Source: IDC, European Data Market Monitoring Tool, 2015

To investigate this matter we have developed three scenarios covering the evolution of the European

data market and data economy to 2020, analysing the interplay of the main technical, political and

socio-economic factors affecting the development of this market.

For each scenario, we have examined the potential role of policies, with a specific focus on the action

plans of the Data-driven economy strategy and the Digital Single Market strategy.

The three scenarios provide the storylines, the contextual framework and the main assumptions which

have been used to model and forecast the European Data Market Monitoring Tool’s indicators. In turn,

the quantitative models’ results have been used to refine and validate the scenarios.

18% DIRECT

IMPACTS

Revenues of data

products and

services

56% INDIRECT

IMPACTS

Benefits and growth of

data user companies

26% INDUCED IMPACTS

Increased wages, consumption

and spending across the

economy

Est. €B 255

1.8% of EU GDP


Baseline Scenario

The Baseline scenario is defined by a continuation of the 2015 positive moderate growth trend of the

European economy, creating favourable conditions for investments in digital innovation in general and

data technologies in particular. The increasing diffusion of IoT and Cloud Computing will encourage

business demand for Big Data technologies, while the nearly universal penetration of mobile and

social technologies by 2020 will herald the emergence of a "hyperconnected" society, where

consumers will rely on multiple real-time services for their daily life, often supported by data

applications. It is also expected that high-speed broadband infrastructures will be available across

Europe and will not become a bottleneck for the data market development.

In this scenario, policy will play an important role to support supply, but have a mixed success in

promoting demand, an inherently more difficult objective. Policy initiatives will succeed in supporting

the growth of the data industry through R&D investments, the support of digital entrepreneurship, and

the successful deployment of the contractual Public Private Partnership on Big Data Value (BDVA

PPP). The EU will protect trust in the data economy by successfully deploying the General Data

Protection Regulation, achieving greater harmonization across the EU and reducing the administrative

burden on businesses. On the other hand, the removal of regulatory barriers preventing the free flow

of data cross-borders is unlikely to have effects before 2019-2020. The support of pilot projects and

innovation spaces for experimenting with data innovation will help advanced and already interested

potential users.

This scenario foresees a healthy growth of the European data industry, a continuing improvement of

the offering of data products and services, and a corresponding gradual development of demand,

especially by the most advanced, competitive and innovative enterprises, large and small. However,

advanced enterprises are a minority of the potential users’ population, and in this scenario we foresee

only a slow growth of take-up by mainstream, traditional enterprises. For that reason, in this scenario

the supply-demand interaction is still strongly dominated by the supply push.

High Growth Scenario

In the High Growth scenario, Europe's economic growth in the next years will be similar to the

Baseline scenario, but it will be characterised by a stronger driving role of digital innovation, with

higher overall ICT investments as a share of GDP. Solutions combining innovative digital technologies

(such as IoT, Cloud and Big Data) will be more widely implemented and more European enterprises

will engage in Digital Transformation before 2020. The data market will enter a faster growth trajectory

and the adoption of data technologies will spread beyond the minority of pioneers to a wider

population of mainstream users. The supply-demand dynamics will change from technology-push to

demand pull, with a fully developed ecosystem generating positive feed-back loops between data

companies and users. This is a classic virtuous cycle mechanism, which may happen if data

technologies take-up starts climbing fast enough to generate momentum. Because of network effects

typical of ICTs, rapid diffusion multiplies the benefits for users in their interactions and makes it easier

to consolidate standards and interoperability, reducing further the barriers to adoption.

To enable this scenario, we must assume a set of very favourable framework conditions which are

able to trigger a faster take-up. First, the adoption of all digital technologies is mutually reinforcing, so

we assume a faster pace of diffusion for IoT, Cloud, Mobile as well as data technologies. Second, we

must assume a leap ahead of potential benefits’ awareness and willingness to adopt data

technologies by mainstream users and specifically by SMEs. Third, but not less relevant, we must

assume a removal of existing regulatory barriers within the forecast period. In this scenario, policy

initiatives will succeed in supporting supply as detailed above, but will also have better success in

promoting demand. Policies enabling the free flow of cross-borders data and the re-use of data sets

will create positive effects on demand starting from 2017-2018. All the other positive factors described


in the Baseline scenario must also be present. As a consequence, the value of the data market and of

the data economy by 2020 will be substantially higher than in the Baseline scenario.

Challenge Scenario

In the Challenge scenario, the combination of a less positive macroeconomic context than in the

Baseline scenario, less favourable framework conditions, and slower diffusion of digital innovation will

combine to push the data market into a low growth development path. This is a fragmented scenario,

where the Digital Single Market will fail to materialize before 2020. The supply-demand dynamics will

be dominated by the technology push, since the demand pull will be weak. The level of adoption of

data technologies by 2020 will be limited to a smaller population of potential users than in the

Baseline, as market barriers to entry will remain high. This scenario therefore explores the potential

risks and consequences of failing to remove the barriers to the development of the data economy in

Europe.

This scenario still foresees an increase of the diffusion of digital technologies such as IoT and Cloud,

but at a slower pace than in the Baseline. The dynamics of mobile and social technologies should not

be much different in this scenario, given their strong momentum and their closeness to nearly

universal diffusion. Therefore the "hyperconnected" society will become closer in this scenario too, but

will be less well developed than in the Baseline or High Growth scenarios. It is possible that the

diffusion of high-speed broadband infrastructures across Europe will be incomplete, with the risk of a

digital infrastructures divide between and within the Member States. This will be another element of

weakness for the development of the data market.

In this scenario, both supply-side policies and demand-side policies will tend to have weaker impacts

and to be deployed more slowly in time. Policy initiatives will still succeed in supporting the growth of

the data industry through R&D investments, the support of digital entrepreneurship, and the successful

deployment of the BDVA PPP, but to a lesser extent than in the Baseline scenario, given the lower

propensity to invest by the private sector. Policies addressing enabling conditions, such as the

removal of regulatory barriers to the free flow of cross-border data, will be delayed in time and be less

effective than in the Baseline scenario. As result, the value of the data market and of the data

economy by 2020 will be substantially lower than in the Baseline scenario.

Figure 15: Three Scenarios for the European Data Market in 2020

Source: IDC, European Data Market Monitoring Tool, 2015

Challenge

Scenario:

Lower

GDP Growth

Less Digital

Innovation

Baseline

Scenario:

Continuing on

the Positive

Growth Path

High-Growth

Scenario: a

balanced

Supply-

Demand

Ecosystem

High-Growth

Scenario

EU Data Market

~ 111 €B

Data Economy

~ 886 €B

4.7% of EU GDP

Baseline Scenario

EU Data Market

~ 83 €B

EU Data Economy

~ 566 €B

3% of EU GDP

Challenge

Scenario

EU Data Market

~ 68 €B

Data Economy

~ 360 €B

2.3% of EU GDP


6.4 Skills Impact

European organisations undertaking Big Data and analytics initiatives will need to source, nurture and

grow a wide range of skills, ranging from technical infrastructure related skills to ensure that the IT

architecture can handle the tracking, storage and accessibility of the high volumes of data discussed

above to the ability to analyse the data and bring it to use in the organisation. They can be described

as follows.

Technical infrastructure skills: Includes thorough understanding of to design, process and

manage a storage hardware and software architecture that can handle handling large volumes

and different styles of digital data, such as unstructured and real time sensor data. This will

include technologies and languages, such as Hadoop, R, Perl and Python. It also includes

developing expertise in handling large volumes and different styles of digital data, such as

unstructured and real time sensor data.

Technical application skills. These types of skills involves deep understanding of how to

design, implement and apply Big Data analytics applications to the organisation from a

technical perspective (not applying the outcome of the analytics to the business problem). This

also involves techniques around process mining and data mining. Current typical specific

technology skills in demand include JackBe, Accretive, Tibco Spotfire, Pentaho, ParStream,

Concurrent, Birst, SAS, ClearStory Data and Terracotta.

Business data skills – and e-leadership skills. This really is about understanding the

business issues and how to get the actionable data analysis from the organisation's vast pool

of information. This is where the role of the data scientist is at the centre, combining analytical

and statistical skills with some level of business understanding. The job of the data scientist is

to bring the data together from diverse datasets and then explore it to find patterns, trends and

insights. By necessity, the data scientist has in-depth knowledge of statistical tools and

techniques, but also needs either the business acumen to apply what they have learned to the

organisation, or the communication skills to explain the implications of their findings to

business executives. Ideally, too, they will have a flair for the exploratory and experimental

side of the role; required to tease out interesting and previously unknown insights in vast pools

of data. The best data scientists tend to be both intensely curious and competent

communicators.

Skills to create a "data savvy" organisation. However organisational ‘data literacy’ isn’t just

about a small group of experts – it’s about everyone in the company being more aware of why

data is valuable, how it can help people make decisions better, move faster, avoid risks, and

the importance of managing it (and its quality) effectively. The need for skills for workers in

any data-savvy business are changing because of more data-automated decision-making

processes. Staff need to be more IT literate generally (in the tools they use), but they also

need to be more data literate. Hence, data skills shouldn’t solely be the preserve of the data

scientist, because in an organisation successfully utilising Big Data and analytics there are

likely to be in a multiple touch-points with the customer/partner and therefore multiple

opportunities to gather, process, learn, and act upon what data tells us. This in turn will require

more and more business people effectively to interpret and understand the importance of

data, and the data insights produced from it. From that starting point, the organisation will be

able to bring the information and knowledge from Big Data to bear on the R&D process to

develop new products and services for customers.

Quality, risk and governance skills. Throughout the Big Data process (from inception to

analysis to action), a solid understanding of the provenance of data and the possible


(business process) causes of errors and data quality issues are of utmost importance as are

privacy and security. Data-driven businesses have a responsibility to balance innovation with

safeguards for personal privacy if they expect to earn as well as retain people’s trust in the

uses put to their data. In this way, organisations need to become open about the trade-offs

and opt-outs, the entitlements and obligations around the use of data which often will have

derived from the individual themselves.

R&D skills. The development and deployment of Big Data technologies is far from mature

and considerable investments in research are planned for the next years. The convergence

between cloud computing, IoT and Big Data also requires research to solve the complexity

challenges raised by these emerging systems and solutions. The Business Data Value

Association (BDVA14

) in its Strategic Research Agenda (due for updating soon) identified 5

main research priorities, they are: Principles and techniques for data management; Optimized

and scalable architectures for analytics of both data-at-rest and data-in- motion with low

latency delivering real-time analytics; Deep analytics to improve data understanding, deep

learning, and meaningfulness of data; Privacy and anonymization mechanisms; Advanced

visualization approaches for improved user experience. This shows that Big Data research in

the next years will drive increasing demands for sophisticated data analytics and data

management skills. A specific focus of demand will be the capability to develop privacy-

preserving Big Data data technologies.

Table 5: Big Data impact on demand of new skills


Quality, Risk

and Safety


Big Data

Skills in analytic technologies, architectures and languages –for storing, processing and manipulating this type of data, such as, Hadoop, R, Perl and Python

Skills to acquire, prepare and explore data, and then discover and identify meaningful patterns

Governance skills needed to ensure data is reliable, secure and ready to use

Sophisticated data analytics, data management, data visualization skills; development of architectures for real-time analytics

Skills in the area of privacy-preserving BD technologies

Manage new challenges mainly linked to data protection, data privacy, IT security

14 http://www.bdva.eu/sites/default/files/europeanbigdatavaluepartnership_sria__v1_0_final.pdf


E-Leadership Skills

Big Data


Strategic change management to create data savvy organization

Capability to re-design business and marketing strategies to exploit Big Data opportunities

Strategic management of data protection/ privacy issues

Lead R&D to design new data-driven products and services for business goals

Oversee Big Data projects management

Organize recruitment or training of data scientists

Combination of business analytics skills with industry-specific skills and understanding of Big Data potential

Source: IDC, 2015


7 Social Business

7.1 Main Trends

Social business, which IDC has identified as one of four key drivers of IT innovation, is an umbrella

term that refers to all social-driven workflow, which can be both internal and external to an

organisation. Social business can be embedded across the organisation and all business processes to

improve performance. In a way, social business virtualises all interactions and, in doing so, changes

how consumers, partners, and even employees engage with each other and businesses. People

generally take a single perspective on social business, based on their role or personal experience with

specific social tools. For example, a customer support manager might think of social business in the

context of the organisation's customers (collecting customer feedback over social networks, or

managing customer inquiries via social channels), while others might think of collaboration tools or

sourcing product/service ideas from partners and customers. IDC believes that social business

benefits have common attributes across industries and organisations. The business functions that are

most alike in terms of the need (or business urgency) to leverage social business include sales and

marketing, IT service delivery (external and internal), customer services and HR management (incl.

training and assessment).

In essence, organisations are applying social technologies for three key areas: interacting with the

customer, interacting internally and interacting with partners as shown in Figure 16.

Figure 16: Social Business Experiences

Source: IDC MaturityScape: Social Business, 2015

Customer Experience. Social business and communities have a vital role to play as a

communication channel for customer experience. Word of mouth has always been one of the

most important sources of information for people to learn about recommendations, to share

experiences, or to exchange details about a product, brand, or service — social business is


the large-scale digital equivalent of word of mouth. The rise of mobile devices, visual web, and

omni-channel strategies changed how people engage with organisations and their peers.

Despite the fact that social business and communities tools are still young in comparison to

other communication methods, an IDC study in 2014 showed that among line of business

managers social networks rank third after websites/portals and email, and in front of customer

sales representatives, phone services, and in-store experiences. This indicates a view of

customer experience that focuses on digital rather than physical aspects. This is a very

important trend — and it is critical for businesses to recognize and understand this. Examples

of technologies that support the customer experience are recommendation engines that help

customers find what they need online; systems that configure the user experience based on

customer preferences; systems that allow the customer to see their previous orders; and

omni-channel tools that enable the organisation to interact with customers across various

media.

Workforce and Employee Experience. An increasingly connected, yet distributed, business

environment affects how we work and how we will work in the future. Although the workforce

and employee experience is subject to a variety of trends and technologies, the introduction of

social business within the workplace is enabling connected workers to interact with content,

systems, and stakeholders in new ways. Enterprise social networks (ESNs) facilitate these

interactions inside and outside the organisation to create a community of users. An ESN can

become the social backbone of an organisation by forming a relationship layer that facilitates

information sharing and collaboration in the context of work processes. More importantly, it

can help accelerate decision making by providing the right people, data and information at the

right time – in context. This networked business model is commonplace in modern

organisations, with users relying on the ability to connect with other users in order to make

business decisions. However, the impact and ROI of social business initiatives for the

workforce depends on various factors, such as employee autonomy, workflow, hierarchy,

leadership, organisational culture, and so forth. There have been many successful and

unsuccessful examples of ESN rollouts. The experience seems to be that 'generic' social

initiatives are failing. Instead, organisations need to focus on specific use cases (e.g. deal

rooms, idea sourcing, mobile connectivity, or even sharing corporate news) to build value for

the business.

Partner Experience. Businesses are connected by customers, employees, partners, and

suppliers. The ability to deliver a seamless and streamlined handoff between business and

technology silos is complex and not easy to do, but it is essential. By connecting components

of the business and supplier network that may collaborate through disconnected but shared

processes, organisations can start to build an experience that transcends existing business

relationships. Partners and suppliers have the largest presence of managed online

communities today. This is primarily due to the business–to-business nature of transactions

but also the element of feedback sought after in supplier relationships. As the community

evolves in a company, it is becomes possible to integrate it into other systems. The

community is an important data source for marketing, sales, customer service, and

product/service development functions so integration into those systems is common.

Ultimately, integrating the customer community into internal communications is important for

getting the voice of the customer distributed into the company across all employees.


Due to its broad impact across various categories of technologies, the number of social business

activities are end-less. Results presented in Figure 17 from IDC's Western European Software Survey


in early 2015 illustrates what businesses in Europe reported to be doing in terms of the most common

social business initiatives.

Figure 17: Current and Planned European Social Business Initiatives

n=1451

Note: Multiple responses were allowed

Source: IDC European Software Survey, 2015

IDC's survey results over the past few years clearly shows social business has been maturing among

European organisations. Social business activities and processes tend to group around several broad

areas including customer experience (enhanced by social sales enablement, social customer support,

social marketing automation, and so forth), employee experience (including social talent

management), and partner and supplier experience. These "experiences" are supported by

technologies that interact and interoperate across all three components — enterprise social networks,

innovation management, and socialytics.

7.3 Skills Impact

Organisations implementing social business solutions often run into challenges due to a disconnect

between the IT and Lines of Business executives' skills and expectations. IDC's surveys show that

some of the most frequently recurring challenges to successful social business initiatives are:

The technology is complicated to install, manage, and support

It is difficulty to qualify the ROI of social software

There is low participation in external social workflow initiatives

Organisations lack an enterprise social software policy

Organisations lack internal skills to support social software

27%

29%

29%

29%

28%

32%

34%

36%

36%

21%

20%

22%

23%

25%

22%

23%

23%

23%

0% 10% 20% 30% 40% 50% 60% 70%

Crowdsourcing

Enterprise social network

Social selling

Partner communities

Customer communities

Social analytics

Recruiting

Customer service

Marketing

Using now Planning to roll out in 12 months


Although it is important that social business initiatives and investment start with specific use cases,

executives often forget to realize that it involves the broader organisation to make it successful. The

opportunities to connect the employee, customer and partner experience are endless, but it needs

strong leadership and careful planning and execution. Table 5 presents the impact and skills required

to deliver social solutions successfully across the organisation.

Table 6: Business Impact and Skills Required

Social Business

Champion

Business Impact Skills required

CEO Product / service transformation,

redefined business model

Understanding social business portfolio

integration; assessing business value of emerging

IT solutions

CFO

Forecasting performance based on

customer-driven social business and

data

Big Data analytics and integration with social

channels to predict financial performance

CMO Shifting customer engagement and

reputation; agile collaboration

Social media sentiment data analysts; back-end

integration into CRM and customer support

systems

CHRO Motivation, learning, knowledge,

collaboration, privacy

Collaboration infrastructure and application

delivery; community management;

Source: IDC 2015

There is a new class of service providers emerging that engage with both businesses and customers

as part of this social business environment. For example, data brokers may be a necessary cog at the

touch points to ensure that businesses get "clean" and pertinent data. Their role may be to validate

information, scrub data for errors and extraneous information, and present businesses with a refined

data set that can be incorporated into the appropriate internal (e.g., sales, HR, marketing, finance)

application.

Similarly, new business roles may emerge within the functional areas that include innovation

management, ESN, and social analytics expertise. This involves being able to collect big data across

the social spectrum and, within seconds, conduct complex analytics functions that show what the

organisation's customers are saying and buying, what competitors are saying and doing, and what is

happening in the markets in real time. Along the way, basic business models and processes are likely

to change in fundamental ways.

From the point of view of R&D, there is a need for further research in the Future Internet space in

order to further merge social computing and pervasive computing through open and scalable service

architectures and platforms, as well as reliance on cloud computing. Next generations of social

business technologies are expected to increasingly incorporate Big Data applications such as

predictive analytics and more sophisticated services such as influencers' marketing automation, which

will require competences in a wide portfolio of technologies and the capability to design and develop

their convergence.


Table 7: Social Business Impact on demand of new skills


Quality, Risk and

Safety


Social

Business

Collaboration between infrastructure and application delivery

Collaboration between infrastructure and application delivery

Integration between cloud-based systems and internal applications

Merging of social computing and pervasive computing

Convergence of cloud, social business and Big Data technologies

Management of data privacy and security risks

Risk/return assessment for social applications and services

E-Leadership Skills

Social

Business


Strategic change management leading adoption of social business technologies in the organization and with partners in the value chain

Capability to tailor social business technologies to different stakeholders (e.g. workforce experience and HR; customer experience on sales) Lead/coordinate social business projects management

Capability to re-design business and marketing strategies to exploit social business opportunities

Source: IDC, 2015


8 The Internet of Things

8.1 Main Trends

The Internet of Things (IoT) is a significant market within Europe, both in terms of its strategic impact

on all businesses but also in terms of the attention gathered from all board levels executives within the

last couple of years.

IDC defines the Internet of Things as an aggregation of endpoints — or "things" — that are uniquely

identifiable and that communicate over a network without human interaction using some form of

automated connectivity, be it local or global. Effectively, an IoT solution brings together people,

processes, data, and things to make networked connections more relevant by turning information into

actions. Crucial elements are data capture, transport and analysis but the essence of IoT is what

organisations or users do with the data itself, leading to better, timelier, and more accurate decision

making.

A survey of more than 800 European organisations conducted at the start of 2015 by IDC confirms

that ICT buyers have begun to grasp the importance of the IoT (see Figure 18). As shown below, 8%

view IoT as extremely important for their business, and a further 22% very important. On the other

hand, 32% of ICT buyers see IoT as unimportant or only slightly important, which means at least a

third of the market is still unconvinced.

Figure 18: Business Importance of IoT

Source: IDC, 2015

There are many components to an IoT solution including modules and devices (sensors), connectivity,

platforms, applications, analytics, security and of course professional services – from consulting and

implementation / integration to management and support – as illustrated in Figure 19.

Extremely important

8%

Very important 22%

Moderately important

38%

Slightly important

20%

Not at all important

12%


Figure 19: Components of an Internet of Things Solution

Source: IDC, 2015

Today, users perceive connectivity, sensors and security to be the most valued components of an IoT

solution. This is not surprising in the sense that the market is currently at the IoT “build-out” phase,

where much of the attention is on creating the underlying infrastructure for an IoT solution. However,

as the market mature and organisations start to move towards monetisation of IoT, the focus will move

towards the practical application and usage of the technology the analytics of the data that will be

produced or captured by the "things".


Considering the overarching business and industrial trends in Europe, IoT should be poised for strong

adoption in the coming years. The increasing focus of European businesses to find new revenue

streams, develop new products and services that help capture new markets and customers but still

with a strong view on improving the organisation's productivity level all plays into the benefits that IoT

can bring.

However, while these are all drivers of adoption, there are also concerns that hold back adoption

levels. Firstly, there is still a need for standards to ensure the highest levels of efficiencies in solution

development to drive down costs – but also to ease security concerns. Despite the progress in the

development of several standards, bodies that provide and facilitate open and agnostic connectivity

and data protocols have not seen tangible outcomes. Multiple standards organisations are actively

forming and marketing themselves to lead the penultimate IoT standard. While it is not clear if it will be

one or several IoT protocols that will rule the IoT market worldwide, it is clear that for the value-added

layers of the IoT solution stack to result in the business and consumer benefits envisioned, the

network of networked "things" will have to talk to and understand each other.

In balance, the adoption of IoT is expected to grow significantly in the coming years. IDC estimates

that the number of IoT connections within the EU28 will increase from approximately 1.8 billion in 2013

(the base year) to almost 6 billion in 2020. The main driver behind this is the increased connectivity

within consumer goods (such as TVs, fridges etc.) combined with the widespread deployment of

sensors (in manufacturing plant, bus shelters, attached to livestock, heartbeat monitors, remote

medical devices). Because of more and more things being connected, the installed base is expected

to increase at a Compound Average Growth Rate (CAGR) of 18.7% over the period.


As the installed base increases, so revenues follow suit. Based on a study carried out by IDC for the

EC IoT revenues in the EU28 will increase from more than €307 billion in 2013 to more than €1,181

billion in 2020. Revenues will come from the complete lifecycle of an IoT solution as they would do

from any ICT deployment (i.e. Plan, Build, Operate, and Maintain) although the mix will change across

time. Hence, we expect to see a greater weighting towards professional services and design as part of

planning and or building IoT solutions in the early years of the forecast period. Later service revenues

in the Operate and Maintain categories are expected to dominate.

IDC estimates in terms of both IoT installed base and revenue growth are summarized in the figure

below.

Figure 20: IoT EU Market Forecast, installed base of sensors and revenues, 2013-2020

Source: "Definition of a Research and Innovation Policy Leveraging Cloud Computing and IoT Combination"

by IDC and TXT, final report, SMART 2013/0037 for DG CONNECT, 2014

Because of the nascent state of IoT in Europe and its rapid evolution, IDC has added a dynamic

element to the baseline estimates presented above. Two alternative scenarios taking in to account a

possible different evolution of macro-economic, technological, political and market factors

underpinning the current growth of the IoT market in Europe have also been devised.

An optimistic scenario (Alternative 1) would be created if the EU economy picks up more

strongly than expected, embedded computing and Internet users grow at a faster rate than

anticipated, and regional influencers have a more positive effect from 2016 onwards (once EU

policies came into effect). The drivers for this upside could be varied. For example, an upside

outlook on the regional influencers could be the result of the creation of a single and consistent

European market for IoT sooner rather than later, or the completion of the standardization work

and the more rapid adoption of these standards.

In contrast, we could envisage a pessimistic scenario (Alternative 2) in which the EU economy

continues to stagnate and regional influencers do not exert a meaningful effect due to a less

successful implementation of EU policies. Even by leaving all other factors unchanged (i.e.

embedded computing will persist to exercise a positive influence because of the growing number

Revenues: €1.2 Billion

Installed Base: 5.9

Million


of connected “things”; Internet usage will continue to grow because of the proliferation of

connecting devices), the lack of economic recovery, coupled with tepid Government support, could

lead to a much negative picture for the development of the European IoT market with IoT

revenues down of approximately 18% by 2020 with respect to the baseline scenario and of almost

24% by 2020 if compared with the optimistic scenario (see Figure 21 below).

Figure 21: Alternative IoT European market scenarios, revenues, 2014-2020



The benefits of IoT are often discussed in terms of efficiency, the next stage in automation, or greater

integration. However, all true IoT is about opening up not only new business but also new revenue

streams. This is happening across multiple sectors where an increasing number of IoT-based use

cases is rapidly turning into tangible business opportunities spreading over the entire industry

spectrum (from industries traditionally characterized by high levels of IT penetration – such as financial

services or manufacturing – to industries less familiar with IT – such as agriculture and local

government). What is more, IoT-based use cases can hardly be assigned to a specific industry sector:

they tend to stretch across several sectors and/or create “new sectors” that are hard to capture

through the traditional concept of “vertical market” – smart cities, for example, encompass an element

of local government, transport, consumer, financial services and probably other traditional vertical

markets. As a result, the concept of traditional vertical market may no longer be the best place where

IoT-related business opportunities are to be identified. Instead, the notion of “smart environment”

appears to be much better suited to apprehend the complexity of use cases involving IoT within their

potentially new positioning within a dynamic and changing industry spectrum.

IDC has carried out a cross-industry analysis of all main IoT-related case studies in Europe and

identified eight most significant smart environments according to two fundamental variables:

the estimated size of each Smart Environment in terms of IoT spending in 2020;

the estimated growth of each Smart Environment in terms of IoT spending over the period 2014-

2020.

365000

465000

565000

665000

765000

865000

965000

1065000

1165000

1265000

2014 2015 2016 2017 2018 2019 2020

Base case Positive scenario Negative scenario

€ millions

Baseline: €1.2 Billion

Negative Scenario:

€0.9 Billion

Positive scenario:

€1.3 Billion


A visualization of this analysis is presented in the following figure 22, where Smart Environments’

relative size of IT spending in 2020 is plotted on the x-axis and expected growth rates for the period

2014-2015 are plotted on the y-axis.

Figure 22: Smart Environments by IoT Spending Size and Growth



In essence, each of the eight identified smart environments is already producing (or will produce by

2020) a considerable number of use cases successfully exploiting IoT technologies. More specifically:

In Smart Manufacturing, operations and asset management already represent fertile ground for

IoT solutions and applications; by 2020, they will be joined by other opportunity-rich use cases

such as connected vehicles, driverless cars and e-call.

Smart Homes will offer business opportunities in relation to home security, energy applications

(thermostats & HVAC) and household appliances.

Personal wellness applications and the varied world of wearable devices for both generic and

health-specific purposes constitute the number-one opportunity area in Smart Health. They will be

accompanied by remote health monitoring and staff identifications by 2020.

Smart Customer Experience is and will be driven mainly by retail-oriented opportunities such as

omni-channel operations, digital signage, in-store digital offers and Near Field Communication

(NFC) payment solutions.

IoT has the potential to be a growth engine, also for SMBs in EMEA. The technology is not just about

the enterprise — it is about developing smart homes, connected cars, smart meters/grids, smart

environments, telehealth, smart cities, smart services from local authorities, telecare, and so forth. In

this picture, SMBs can either innovate their own products and services but can also find niche roles in

conjunction with major corporates in the complex IoT ecosystem.

Smart Manufacturing

Smart Finance

Smart Government/ Environment

Smart Customer Experience

Smart Health

Smart Homes

Smart Energy Smart

Transport

0%

5%

10%

15%

20%

25%

30%

35%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 110%

CA

GR

2

01

4-2

02

0

Relative Size of IoT Spending (2020)


8.3 Skills Impact

As with any new technology, the supply of relevant skills lags behind the fast-growing demand around

the IoT technology components – not to mention the expertise and capability to envision the solutions

that IoT enables. Effective implementation of IoT solutions can be quite complex, and will require

specialist skill sets, which need to be vertical as well as IT orientated. Skill shortages are a challenge

for many companies, especially those that need to make a major leap from their traditional IT

environment to embrace IoT. Companies wishing to implement IoT will need to think carefully about

the availability of the skills, particularly associated with integration with existing systems. This problem

will vary from country to country and will bring the need to outsource where appropriate.

Specifically, IoT’s complexity requires different skills including:

• A mix of IT, business, connectivity and networking skills are required. Very few possess all of

these in abundance.

• Analytics / Big Data skills are increasingly relevant as buyers move away from the

technological view of IoT, towards a more “data centric” view.

• Industry specific skills – the skills to be able to lead a project and sustain a vision from its

inception to its implementation will be required within the IoT market.

Finally, and perhaps the most challenging part is that a mix of all of the above technical and

management / leadership skills will be required. This cannot be addressed by retraining alone. New

entrants into the ICT and business world will have to be shaped / moulded / trained to the realities of

what IoT requires.

R&D skills. Concerning R&D, IoT solutions are far from maturity. As documented by the most recent

research agenda developed by the AIOTI15

(Alliance for IoT Innovation), promoted by a research and

industry partnership in the area, the next years will see considerable research in order to integrate the

future generations of applications, devices, embedded systems and network technologies and other

evolving ICT advances, based on open platforms and standardised identifiers, protocols and

architectures. The IoT technology is evolving and demonstrating the features in various applications

require the integration of the highest, most generalized layer of intelligence and user interface that ties

together connected devices and web services using interoperable platforms that deliver the

functionality required by the end-users. In the virtual world, the development of network virtualization,

software-defined hardware/networks, device management platforms, edge computing and data

processing/analytics will be needed as enabling technologies to IoT systems. The research and

innovation in nanoelectronics, semiconductor, sensors/actuators technology, and cyber-physical

systems are essential for the successful deployment of IoT applications. Overall, this means that

solving IoT R&D challenges will require cross-domain ICT competences and multidisciplinary skills.

15 https://ec.europa.eu/digital-agenda/en/news/aioti-recommendations-future-collaborative-work-

context-internet-things-focus-area-horizon-2020


Table 8: IoT Impact on Skills Demand


Quality, Risk

and Safety


IoT

Skills on Big Data technologies (Hadoop, Cassandra, NoSQL databases)

Systems management skills for highly integrated, automated and scalable infrastructures

Skills for developing applications on connected devices and on embedded systems

Multidisciplinary ICT skills to integrate future devices, systems and networks into IoT solutions

Skills for designing and developing new products and services with intelligent devices as key components

Management of data privacy and security risks

Risk/return assessment for IoT solutions

E-Leadership Skills

IoT


Strategic change management leading adoption of IoT systems in the organization and with partners in the value chain

Capability to re-design business and marketing strategies to exploit IoT business opportunities

Strategic management of data protection/ privacy issues in IoT environment

ICT vendor management skills for handling vast and diverse vendor ecosystems Oversee IoT projects management

Combination of business analytics skills with industry-specific skills and understanding of IoT

Source: IDC, 2015


9 IT Security

9.1 Main Trends

Occasionally in the IT industry, a seismic macro trend comes along that shifts fundamentally the

market dynamics. For security, there are not one but three such trends that, together, are changing

the way security is approached, procured and delivered.

The first trend is what IDC calls the 3rd

Platform, the combination of social, mobile, analytics and cloud

technologies that are driving fundamental changes in the ways that organisations interact with their

customers, partners and employees. These digital transformation technologies offer huge benefits in

productivity and flexibility, but they also bring substantial challenges to security professionals. The

concept of a perimeter that protects the organisations has disappeared, as cloud and BYOD enable

anyone to connect to systems across the Internet from any device. Device proliferation, compounded

these days by the Internet of Things, means that the attack surface exposed to potential hackers has

multiplied beyond control. New approaches that embrace, rather than prohibit, 3rd

Platform

technologies are required.

The second trend is more sinister. The dynamic threat landscape that faces organisations is growing

at a rate unfathomable even 12 months ago. Symantec recently noted that it had detected 317 million

new pieces of malware created in 2014 – almost one million each day. How can organisations keep

this many attack forms at bay forever? In truth, they can't. ENISA reports that over 50% of malware

stays undetected by antivirus products. The average time to detect a major security breach is around

seven months, meaning that thieves have more than enough time to map any organisation and

exfiltrate sensitive or valuable data. Consequently, the presumption must be that organisations are

breached, and finding and mitigating the breach become the priority. For an industry that prides itself

on prevention and protection, security professionals find it hard to change traditional approaches and

mindsets.

The third trend facing security is increasing regulation, particularly in the field of data protection. In

Europe, the data protection legislation is twenty years out of date, codified before widespread adoption

of the Web and almost a decade before Facebook was founded. It is now being updated, placing new

demands on organisations to classify and protect their data, lest they be subject to punitive fines.

While the details of the General Data Protection Regulation are still being worked out, it will have a

profound effect on almost all organisations in the EU, and those organisations trading with the EU.


Data security has been on the minds of IT, business, risk, and audit professionals for as long as data

has been stored on magnetic drums, tapes, disks, and other storage devices. In recent years,

however, because of the massive expansion of data repositories, the types of data being stored, and

the advent of the Internet, it has become much more profitable to steal data and much easier to get it

than ever before. To make matters worse, recent highly publicized data breaches at various major

corporations have cost these firms tens of millions of euros in corrective action, reputational damage,

and in some cases, major internal organisational realignments. In short, no company wants to be next.

This is also reflected in survey data. According to IDC's 2015 European Software Survey of over 1,450

IT decision-makers and influencers, the need to invest in improving IT security is seen to be either an

extremely or a very important strategic IT issue for 62% of survey respondents as shown in Figure 23.


This makes it a stronger priority than critical topics such as improving general IT costs, business

innovation, IT processes, and business analytics.

Figure 23: The importance of IT security improvements

Note: 1,450 respondents, % of answers

Source: IDC European Software Survey, 2015

A further driver for the prioritization of improvements to IT security is the fragmentation of IT spend

away from IT departments and towards companies’ lines of business (LoBs). Awareness of and ease

of access to (for example) SaaS applications, boosted in some cases by the availability of corporate

‘app stores’, means that there is no longer a monopoly of control over corporate application

selection/usage. This in turn has ramifications for IT security, where CIOs’ and CISOs’ lack of control

and visibility over application use is increasingly apparent.

This concern is intensified by the rise of shadow IT, whereby individuals enabled by access to cheap

or even free SaaS applications (e.g. Box.com, Dropbox, etc.) are making use of applications that are

outside the corporate IT umbrella. What is more, the employees that make use of such shadow IT

solutions are concerned by their functionality and ease of use rather than the strength of their security

measures, let alone compliance with corporate security policies.

As a result of the deepening concern about data breaches, data security awareness has moved from

the back room to the boardroom. This move has brought with it increased visibility, higher

organisational accountability, and dramatic increases in funding. This funding, in turn, has spawned a

plethora of new hardware devices, software-based technologies, new and innovative best practices,

and a full array of newly created job titles, organisational structures, and many open job requisitions

that are proving to be very hard to fill.

9.3 Skills Impact

It is a common theme in the press and at security conferences today that there is a huge security

personnel shortage plaguing the profession. A survey of 155 Chief Information Security Officers

conducted by IDC in the US in 2015 attempted to determine the veracity of the claim.

The survey found that it is fairly easy to fill less senior roles: 99% of respondents felt that any roles for

employees with 0–5 years of experience could be filled in the first 6 months with close to 85% filled in

the first 3 months. According to this survey, the perceived job shortage in security is not happening at

2%

10%

26%

39%

23%

0% 5% 10% 15% 20% 25% 30% 35% 40% 45%

Not at all important

Slightly important

Moderately important

Very important

Extremely important


the entry levels, where expectations are basic. Rather, the shortage comes at the higher-experience

levels (after about 10 years), even though there are fewer positions to fill. Notably, this is where

expectations are much higher than for the early-career individuals.

The more experienced people are typically also those that have not just depth but also breadth in their

skills and knowledge. As we have seen in the previous sections, most of the other key technology

trends require also security skills to understand and manage that the organisation becomes

increasingly open to the outside world. For example, for every new cloud adoption, there needs to be

an assessment of the impact on the organisations security stance, implementation of needed security

solutions, on-going monitoring for potential breaches and remedial action to be taken in case this

happens.

From the point of view of Technical skills, there is increasing demand of

Concerning R&D, there is an ongoing effort to streamline and

Table 9: IT Security Impact on Skills Demand to 2020


Quality, Risk

and Safety


IT Security

Professional and product and industry certifications

Design and management of end-to-end protection of emerging smart networks and cyber infrastructures

Skills to design and implement sophisticated identity and access management solutions

Skills to safeguard applications against intrusion – already in design and development phases

Development of privacy by design technologies

IT security standardization skills

Develop and implement the company’s security strategy coherently with the business strategy, insuring that information assets are protected over time

E-Leadership Skills

IT Security


Strategic leadership of IT security as a business responsibility rather than a technical focus (CISO - Chief Information Security Officer role)

Capability to adapt IT security practices to company departments and external processes Oversee IT security practices implementation and evolution

Combination of business analytics skills with industry-specific skills and understanding of IT challenges

Source: IDC, 2015


10 Innovation Accelerators

10.1 Main Trends

This chapter deals with the 4 innovation accelerators identified by IDC as able to shape the business

environments in the year to come (see also par.3.1). These technologies are in an earlier maturity and

deployment stage than the 4 technology pillars of IDC's 3d platforms (mobile, cloud, social business

technologies and big data) or the IoT. In summary they are:

Virtual/augmented reality: Technology that allows immersive visual experience that removes

or complements external visual input and follows the user's head movement.

Wearables: Wearable devices with a microprocessor, that is capable of digitally processing

data.

3D printing: technology used for additive manufacturing, that is able to materialize all sorts of

physical things from digital blueprints — from food to clothing to eventually even living tissue

and organs.

Cognitive systems: Systems that observe, learn, analyse, offer suggestions, and even create

new ideas — dramatically reshaping every services industry. This includes artificial

intelligence (AI), machine learning, cognitive computing, and robotic process automation.

Robotics is the branch of technology that deals with the design, construction, operation, and

application of robots, as well as computer systems for their control, sensory feedback, and

information processing. A robot is a mechanical or virtual artificial agent, usually an electro-

mechanical machine that is guided by a computer program or electronic circuitry.

Harnessing this expanding innovation platform, a rapidly expanding community of developers will

create a tenfold increase in the number of new killer solutions over the next four to five years. Many

will be big data intensive, and many will harness the extended reach of the Internet of Things. Two-

thirds of these new apps will have an industry-specific or role-specific focus.

In fact, industry-focused developer communities on the 3rd

Platform will become epicentres of

innovation in just about every industry on the planet and will seriously disrupt traditional leaders in

these industries as competitors use the 3rd Platform to create new offerings, new business models,

and new cost structures to drive revenue growth and expand value.

This movement of IT, way beyond traditional boundaries of datacentres and IT departments, will be

the most dramatic aspect of the 3rd

Platform's innovation stage. The end goal is nothing less than the

reinvention — and continuous transformation — of every industry on the planet. In fact, at IDC, we

believe the 3rd

Platform is not just a technology innovation platform; it is fast becoming a business

innovation platform. Figure 24 provides a more detailed look at the four innovation accelerators with a

specific focus on the business innovation opportunities which are appearing on the market or will take

off in the next few years.


Figure 24: Major Innovation Accelerators in Europe

Source: IDC, 2015


As new technologies, these innovation accelerators are still in the early phases of adoption. In line

with the typical market development for ICT, this means that the possibilities and opportunities that

technology may bring are often based on vendor push rather than customer pull. Consequently, in the

ICT markets we often observe that the investments and announcements that vendors are making are

setting the scenes for what may come. Subsequent steps to ensure wider adoption entails the

development and showcasing of use cases – and the European market is still in the early stages of

this step. This section illustrates some of these investments and announcements and provides IDC's

view of what the affect may be on the near and long-term adoption in Europe (and globally) and how

these innovation accelerators intersect.

IDC calls these trends innovation accelerators because of their combined potential to drive innovation.

As shown in the figure 25, these trends have strong technology intersections creating new business

opportunities. The IoT is the main technology platform underlying these technologies, providing them

with the universal connectivity and data communication capabilities needed for their operation. Then

there is a cluster connecting Robotics with 3D printing and Cognitive computing: 3D printing combined

with robotics enables automated manufacturing; Cognitive computing through the development of

software for tasks automation provides the "brains" for the new robots: both require new types of

sensors to function through IoT. This cluster is particularly relevant for industrial manufacturing, but

also for evolving business processes in main services sectors such as healthcare and government.

A second cluster underlines the intersection between Wearable devices (which can function because

of the IoT, naturally) and Virtual/ augmented reality systems (providing the context and software for

Virtual/ Augmented

Reality

Eye sets and related software ecosystems

Allow immersive visual experience that removes or complements external visual input and follows the user's head movement

Different types of input devices supported

Strong link with social network activities

Wearables

Devices

Can be worn by consumers all day

Have computing capabilities

Have a user interface

Linked with cloud infrastructure

Can be part of an IoTview

3D Printing

Devices and services

Enables the creation of objects and shapes

Process material that is laid down successively upon itself

Various print technologies (e.g., printhead and inkjet nozzle)

Source is a digital model or file

Cognitive Systems

and Robotics

Automated modeling of relationships between recorded/sensed data and outcomes/responses

Used to automate decision making, discovery, and planning in software and hardware (robotics)

includes artificial intelligence (AI), machine learning, cognitive computing, and robotics

Will improve apparent machine intelligence and autonomy as well as affect jobs and the economy


wearables such as portable augmented reality glasses, e.g. Google glasses). Both Virtual/Augmented

reality and Wearables have addressed so far mainly the consumer market, but the next years are

likely to see greater diffusion in the business worlds as new applications are being developed.

Figure 25: Intersection of Major Innovation Accelerators in Europe

Source: IDC, 2015

The deep intersection between these technologies means that they face common development

challenges, particularly concerning the need for a seamless interconnected environment with sufficient

capacity and bandwidth to allow for real-time interaction and the exchange of data flows.

10.2.1 Virtual/Augmented Reality

This market includes eye sets and related software ecosystems allowing immersive visual

experiences. There are several different types of input devices falling in this category but most have a

strong link with social network activities.

Recent announcements and investments by the likes of Google, Facebook, and Microsoft confirm that

virtual reality (VR) and augmented reality (AR) will impact the European consumer market in the

second half of 2016 and reach a significant level of penetration in European enterprises from 2018

onward:

In 2015, Google unveiled enhancements to its VR effort with Cardboard. Cardboard is an

affordable approach to VR, consisting of cardboard frames which, combined with a regular

21

Robotics

Internet of Things

Wearables

3D printing

Cognitive computing

Virtual/ augmented

reality

Software for

automation of

task workers

Sensors

Portable

augmented

reality

glasses

Automated

manufacturing


smartphone, allow users to plug in their regular iOS or Android smartphone and use it as a VR

headset. Google revealed that it has shipped 1 million Cardboards already.

Oculus VR, a Facebook subsidiary specializing in VR hardware and software, announced that

its first commercially available headset product, the Oculus Rift, will be available in the first

quarter of 2016. Earlier this year, Oculus VR launched Oculus Story Studio, its own movie

production studio, to develop original VR content for its devices — another sign, IDC believes,

of the looming content wars around VR.

A number of other large vendors are also pushing in this or the adjacent AR space, including

AMD, Apple, HTC, Intel, Microsoft, Qualcomm, Samsung, and Sony.

Standardisation of the hardware and software components is still a way off, but initial signs are

promising, with several large players betting on it. However, IDC doesn't expect VR or AR technology

to be ready for initial adoption in large European enterprises until 2017, and mainstream commercial

use in 2018. The tablet and smartphone experience proved that logistics and support chains need to

be well oiled before a product can be rolled out in a large enterprise environment.

In addition, while most of the platforms are in beta or developer version hardware-wise, major

suppliers realize that without enticing content, VR device distribution risks a quick death. Crucially, it is

only after the consumer market has reached critical mass in devices installed that developers will start

making investments in "horizontal" software for commercial use.

Finally, pressure on margins in many sectors such as manufacturing and transport has pushed

enterprises to look into new technologies and their potential savings on processes in the mid to long

term. This should accelerate adoption of innovative VR/AR solutions in specific verticals — if and

when they become easy enough to deploy.

Against this backdrop, we are starting to see use case examples emerging, which will also assist in

increasing adoption:

Consumer entertainment. Video gaming is clearly the first target market. VR entertainment

use cases, however, also include movies shot in "VR mode," but also potentially concerts and

other live events streamed in a VR mode. It might also spur a wave of virtual tourism to

museums and landmark sites. Over a longer period — looking at 2020 — VR might become a

place for meeting other people (Facebook's end goal with Oculus VR's acquisition).

Education. The Cardboard Expeditions efforts that Google highlighted provided a glimpse of

how VR could be used in education. In that example, classrooms are provided with VR sets

and teachers can "guide" students through a VR version of museums or natural landscapes,

directing the tour with the help of a tablet.

Customer experience/retail. Some of the most advanced digital customer experience

suppliers in Europe are already testing and in some cases have implemented virtual

showrooms for retailers in the luxury segment.

Professional training. Some companies already offer 3D visualization tools for monitoring

and training. Siemens offers a system called COMOS Walkinside, whereby 3D CAD models of

industrial plants (e.g., an oil platform) can be turned into virtual landscapes for training

purposes. Some of those uses involve VR glasses combined with a joypad and a third-person

avatar acting in the 3D landscape (similar to third-person videogames). As the next wave of

VR takes off, such experiences might become even more immersive, with first-person, motion-

command type environments.

Engineering and design. Microsoft has shown in its HoloLens announcement video how

designers, architects, or engineers can potentially create and visualize their work with

holograms. Rather than creating prototypes or waiting for models, in a couple of minutes

multiple employees could share and discuss their ideas. For more information on the

announcements, please see here.


Healthcare. From surgeon training to patients' education and recovery paths, VR offers

multiple solutions. For medical staff it is a great opportunity to train, diagnose, and treat

various situations without any risk to patients. For patients, a number of pilots have already

started, some around situation simulation to help subjects overcome fears and phobias, for

example. IDC is aware of a number of advanced university clinics in the U.S. exploring this

space.

10.2.2 Wearables

IDC believes that over the next few years, the wearable device market will be shaped by evolutions

and innovations in form factors, functionalities of devices, apps for smart wearables, and new product

launches. The effects of these evolutions will be felt both in the consumer and in the enterprise space,

but the enterprise is positioned to drive unique benefits in productivity as wearable devices enable

new and innovative ways to revolutionize business processes.

As indicated by the AIOTI16

report, wearables are integrating key technologies (e.g. nano-electronics,

organic electronics, sensing, actuating, localization, communication, energy harvesting, reconfigurable

cognitive antennas, low power computing, visualisation and embedded software) into intelligent

systems to bring new functionalities into clothes, fabrics, patches, aids, watches and other body-

mounted devices As such, they may be to some extent “hidden” to the end-user and the end user may

be more or less aware of the wearable device. This provides enormous opportunities for new

applications and services but also raises a number of concerns (privacy, security, dependability and

so on) that must be understood and mitigated in order to encourage adoption and usage.

Wearables are still finding their way into the enterprise. Smartwatches continue to evolve, and we are

just getting to the point where the user experience is intuitive and seamless, and applications have

only recently gained momentum. IDC also expects smart eyewear to find its footing in the 2017–2018

time frame, opening the door for greater adoption and usage within the enterprise. Figure 26 shows

IDC's forecast for wearable devices in Western Europe.

Figure 26: Future View of the Wearable Market (Western Europe Wearables Forecast, 2014–2019, Units)

Source: IDC Worldwide Quarterly Wearable Devices Tracker, June 2015

16

https://ec.europa.eu/digital-agenda/en/news/aioti-recommendations-future-collaborative-work-context-internet-things-focus-area-horizon-2020

0

10

20

30

40

50

60

2014 2015 2016 2017 2018 2019

Basic Wearable Smart Wearable

Units

(M

)


Also for wearables are we starting to see use cases emerging in a commercial or enterprise-level

context:

General: Authentication/personal identification (wearables can replace keys and swipe cards

to enter restricted areas or start vehicles)

Customer service:

o Hotel/airline check-ins can be done via facial recognition or beacons, giving seamless

updates on who the guests/passengers are and what they need without the use of

PCs.

o For service technicians (e.g., onsite maintenance and repair) in refineries, aircrafts,

manufacturing plants, and others so that they no longer need to carry manuals, they

can see "inside" the plant/machinery and so colleagues in other locations can watch

what you are doing and provide assistance

Sales:

o Help customers configure the vehicles they are looking to buy

o Link to customer/product database for seamless ordering

Operations:

o Warehouse packing support and guidance

o Stock taking and replenishment in stores and warehouses

Healthcare:

o Doctors can access patient records as they move around the hospital.

o Patients can be easily monitored for condition changes.

o Smart fabrics and accessories (e.g., smart gloves) allow surgeons and technicians to

perform complicated tasks with the aid of technology.

10.2.3 3D Printing

3D printing is taking the manufacturing sector by storm. Despite being at the initial phases of maturity,

the benefits of this technology have seldom fallen short of expectations. However, the current

deployment of 3D printing is mainly focused on research and development (R&D) and prototyping,

with some companies having their first forays into small-batch production.

The applications of 3D printing are still somewhat limited, but in the fields where it has been tested,

there is almost univocal agreement on its efficacy, with many results exceeding expectations. The

metrics used to evaluate 3D printing are usually precision and quality of the output as well as time to

market. Whenever companies were able to measure it, 3D printing proved to give a very rapid ROI.

However, there are also less quantifiable (albeit important) collateral benefits related to customer

satisfaction. The benefits of 3D printing are as follows:

Faster time to market. In many cases, 3D printing has revolutionized the prototyping process

for good. Prototypes can now be produced faster than before, and they waste less materials

and human workforce. In particular, many companies appreciate the ability to design quickly

and produce prototypes at astonishing speed. In some cases, companies that once

outsourced the prototyping process to third-party companies were even able to do it internally.

All of these easily translates into cost savings.

Better product quality. In the vast majority of cases, including high-precision sectors such as

car racing and aerospace, 3D printing was able to satisfy high expectations in terms of quality

and precision. It was also able to create very complex shapes that were otherwise impossible

or very complicated to produce.

Simplified process. It appears that once the initial steep learning curve has been overcome,

the actual printing process is much simpler than expected. Complexity usually lies in the

modelling or computer-aided design (CAD) part of the process. 3D printing often replaced

entirely old, cumbersome techniques and simplified the prototyping process.


Quick ROI (and getting quicker). Given that many use cases of 3D printing were disruptive

enough to simply make the comparison of processes before and after the technology's

introduction impossible, many companies find it hard to measure the ROI. However, all of

them agree on some sort of bottom-line benefit, whether on cost and time savings or

increased business opportunities. But for those that did attempt to measure the financial

advantages of 3D printing, the results were staggering. For instance, a bottling equipment

manufacturer was able to reduce the cost of prototyping by 70%. In another case, a ceramics

firm was able to achieve an ROI of 12 months, although it reckons that this time has been

elongated due to the impact of the learning process. Lastly, a dental surgery centre was able

to achieve an ROI of three month, and it sees an opportunity to decrease to a month. For a

technology that has just started to realize its potential, these numbers speak for themselves.

More business possibilities. Arguably, the biggest and most disruptive advantage brought

about by a new technology is opening up new possibilities and widening a target market. For

many industries, especially those relying on customization, 3D printing has widened their

business possibilities with the ability to produce shapes once deemed impossible or too

expensive to produce (e.g., dental surgery and ceramics production). However, this holds true

even for even for sectors that deal with commoditized, mass-produced goods (e.g., bottling

equipment manufacturing and bike/ski binding manufacturing). The ability to better customize

the final product opens up new business opportunities.

Higher customer satisfaction. A less quantifiable but probably the most important advantage

of 3D printing is better customer satisfaction. Clearly, the ability to better match customer

needs give them a more precise idea at the modelling stage of what will be produced reduces

business risks. Finally, quicker time to market allows for more variety of goods to reach the

stores (e.g., in footwear manufacturing).

Figure 27 shows IDC's forecast for the 3D printing market in Western Europe to 2018.

Figure 27: Future View of 3D Printers Market (Western Europe, 3D Printer Shipment Forecast, units, 2013–2018)

Source: IDC, 2014

10.2.4 Cognitive Systems

There is a combination of heavyweights IT vendors and specialists in cognitive systems all pushing

the development of the market. These include IBM, Palantir, Saffron, Customer Matrix, Nuance, Digital

Reasoning, and HP to name a few. IBM is predicting that it will see revenues of $10 billion from


Watson by 2024, illustrating the massive potential of the market. The market also sees participation

from cloud business-to-consumer (B2C) players (e.g., Facebook, Google, and Microsoft) who plan to

offer parts of their internal tools to the market.

Some organizations are already adopting IBM Watson and spending commercially. For instance,

CaixaBank in Spain is running pilots with IBM Watson to translate its language analysis ability to

Spanish (translation is nontrivial for cognitive systems). However, generally use cases vary greatly in

cognitive computing:

Advisory capabilities to augment specific services (e.g., wealth management and healthcare)

Extensive analysis of unstructured data (e.g. genomics to provide quicker cancer diagnoses)

Office assistance

Mergers and acquisitions (M&A) analysis suggestions

10.2.5 Robotics

According to the SPARC17

public-private partnership for robotics between the EC and the European

research and industrial community, the robotics industries will double their revenues from today to

2020, achieving worldwide revenues between €50bn and €62bn. Moreover, the traditional distinction

between industrial and service robotics markets is going to blur. For example, the industrial market will

demand smarter and more cooperative robots, exploiting technologies developed in the services

sector, while industrial robot technologies will find wider markets through diversification (for example

mobile platforms transforming manipulators). Overall, the increasing diffusion of robots is expected to

improve the competitiveness of the manufacturing and service industries, and also the quality of life of

citizens (for example providing automated assistance and support to the elderly).

IDC has classified five broad categories of robots, intended as mechanical artificial agents, as of

specific relevance for market development18

:

Unmanned aerial vehicles (UAVs) also known as unmanned aerial systems, or more

commonly drones: these are aircrafts controlled either autonomously by onboard computers or

by the remote control of a pilot.

Autonomous vehicles (AVs): these include autonomous and semi-autonomous cars, trucks,

trains and any other self-moving vehicle equipped with wheels to move on land. These

vehicles are capable of fulfilling the main transportation capabilities of a traditional vehicle by

sensing its environment and navigating without human input. Autonomous vehicles sense their

surroundings with such techniques as radar, lidar, GPS, and computer vision. Advanced

control systems interpret sensory information to identify appropriate navigation paths, as well

as obstacles and relevant signage.

Unmanned underwater vehicles (UUVs): these are underwater machines controlled either

autonomously by onboard computers or by the remote control of a pilot. They include

ethorobotics robot fishes and robot swarms, as well as robot submarines.

Exoskeletons also known as powered armors, exoframes, or exosuits: these are mobile

machines consisting of an outer framework worn by a person, and powered by a system of

motors that assist the wearer by boosting their strength and endurance.

Humanoid robots: these are autonomous or semi-autonomous machines with their shape, or

part of it, built to resemble the human body and replicate its functions, such as moving across

rugged terrain, grasping objects and mimicking facial expressions. In this report, this category

includes semi-autonomous robots with a full body being tested for disaster response in

17 Strategic Research Agenda, http://www.eu-robotics.net/cms/upload/PPP/SRA2020_SPARC.pdf

18 IDC Techscape: Robotics in Government, 2015, by Massimiliano Claps


extreme environments, explosive ordnance robots with arms and hands mounted on wheels or

tracks used by military and police bomb disposal units, and robots that can climb high

structures, such as bridges, wind turbines and buildings for inspection and maintenance.

Potential benefits of robots include:

Increased effectiveness: robots tend to perform better than humans at calculating with speed

and precision, lift heavy loads, moving and carrying out repetitive tasks in certain contexts,

where humans cannot focus entirely on the task. Robot capabilities can increase the precision

of those activities, hence enhance the quality and consistency of the output.

Increased efficiency: machines can carry out the tasks they are good at without taking

breaks and their productivity can be enhanced through technological progress; both represent

an advantage in terms of efficiency, relative to humans, as they need breaks and productivity

can be increased only to a certain extent through training and repetition. Furthermore, by

focusing robots on certain tasks, humans can concentrate on other activities that require

creative thinking, reasoning, learning from experience and creating new ideas and things,

which artificial agents are less good at.

Improved safety: tasks that require carrying heavy loads, or using tools, such as chainsaws,

or operating in extreme environments, such as nuclear plants, fire, outer space, deep waters,

and disaster zones, are either very dangerous, if not impossible for humans; robots can make

them possible, or safe for human operators that can control them remotely.

10.2.6 The Intersection between Advanced Cognitive Systems and Robots

As anticipated, a key feature of the new robots will be the use of advanced cognitive systems. The

future manufacturing and assembly lines will be influenced by today’s research topics in the domain of

robotics and automation. Future robotic systems need to reach a level of cognition that will allow them

to understand and effectively operate specifically in industrial environments. Those systems will

interact with humans in close proximity, and adapt their actions to an ever growing range of situations.

Realizing cognitive robotics and systems (CRS) will therefor require advances along multiple research

challenges, form sensing through learning to acting.

According to SPARC, the European industry has a 32% share of the industrial robotics market and a

63% share of the non-military robotics services market. This is a global market and the EU industry

and research community is fully engaged in the race to develop next generation's robots.

Looking more specifically at the main actors of the evolving robotics market, there are some European

specialist players (e.g., Moley Robotics) and IDC is also observing new constellations of

manufacturing companies in coopetition with Silicon Valley companies experimenting in the market

(e.g., Uber vs. German carmakers in Nokia HERE maps acquisition). This push from the vendor side

for driving robotics innovation will also lead to lower price points. IDC predicts that by 2018, the

average selling price of an industrial robot will be one fifth of what it is today, but it will have five times

the capability. Consequently, robotics which already has limited adoption in some verticals

(manufacturing, defense, etc.), will reach the other sectors within the next 5–10 years (retail, banking,

hospitality, and education), leading to:

Automation of intellectual labor tasks

Automation of physical labor tasks

Figure 28 illustrates IDC's view of the predicted development of robotics and cognitive computing

market.


Figure 28: Robotics and Cognitive Computing Future View of the Market

Source: IDC, 2015

The development of robots with advanced cognitive capabilities is raising critical challenges in multiple

fields, including:

Socio-political challenges, such as investigating human-robot co-working patterns in terms

of decision-making (when should the human being take over from the robot), psychological

impacts (think of military pilots bombing with drones), ethical choices (when and who should

make them), and simply trust (according to recent surveys, most people still would not trust an

automated driving vehicle).

Economic challenges: Design and fabrication tools and competencies need to be further

developed to manufacture full robots, add-on modules, and fixtures, at scale and with

affordable costs.

Employment challenges: the diffusion of robots and the automation of knowledge tasks will

deeply affect jobs and roles in the labour market, with unclear social and economic

consequences (see also par.2.3.4).

Legal challenges: safety regulations and all kinds of legislative frameworks will need to be

revised and updated. For example, to allow autonomous vehicles on the road insurance

models will have to change and maintenance of vehicles will require a while different set of

rules and certifications.

There are also multiple research and technology challenges, including:

Artificial intelligence software challenges, ranging from better machine learning to novel

cognitive architectures to make robots more autonomous at perception, reasoning, control,

and coordination; knowledge representation and reasoning;

Mechatronics, mechanical engineering needed to complement software to overcome robot

physical limitations and improve robots' dexterity and capability of autonomous movement (for

example, to stand up again after a fall. At the June 2015 DARPA robot challenge, Carnegie

Mellon University's CHIMP robot was one of the first to be able to do it).


Network infrastructure challenges: robots will communicate through the IoT, more often

than not through mobile networks and cloud computing. This will create increasing network

capacity and bandwidth challenges.

New land and air traffic management systems will be needed to insure that automated cars

or flying drones do not crash or create damages. NASA for example would like technology that

will automatically “geo-fence” drones to keep them away from sensitive areas like the White

House, ground drones in bad weather, help them to avoid buildings and each other while

flying and decide which drones have priority in congested airspaces. According to Duke

University, the only practical way to do so is to build a new system combining radar, orbiting

satellites and cell phone signals in a new UTM, cloud based network.

10.3 Skills Impact

The innovation accelerators explored above are in the early phase of adoption, with substantial R&D

activities expected in the short-medium term to generate new generations of products and services

and solve implementation challenges. Given this context, they will affect the demand for skills in two

main ways, as reflected in the Table 10 below:

Concerning core technical skills organizations will demand a good knowledge of the

innovative products and services coming to the market and the capability to select and

implement those most appropriate to each organization's positioning in the market and

competitive strategy. This will imply state-of-the art technology competences, in some cases

rather advanced and far from traditional IT (for example in the case of Cognitive systems and

robotics).

Concerning R&D skills, ICT vendors and pioneer uses will demand R&D skills allowing the

design and development of new products and services in each of the new technology

domains. Demand is likely to be less strong by mainstream users who are likely to adopt these

technologies when commercial offerings will be more mature. However all these technologies

influence business processes and require systemic innovation and change management, and

even the more traditional users are likely to find themselves requiring some technical design

and development competence in their teams.

Concerning Quality, Risk and Safety, all these innovations are going to require a deep

revision of former processes, in order to define and comply with new quality standards and to

identify and deal with new risks and safety challenges. This will require specific competences

of quality and risk management.


Table 10: Innovation Accelerators Impact on Skills Demand


Quality, Risk

and Safety


Virtual/

Augmented

reality

Knowledge of and capability to select appropriate VR/AR systems/ devices and exploit/integrate them in the company's infrastructure or add them to the company's offering

Capability to develop/adapt VR/AR applications to company needs, for example for digital customer experience or professional training

Design and development of new generations of VR/AR devices and immersive environments

Revision of former quality, risk and safety processes and ability to adapt them to new quality standards and new risks (personal health; data and privacy protection; IPR infringements; exc.)

Wearables

Knowledge of and

capability to select

wearables and

exploit/ integrate

them in company’s

infrastructure

Capability to

adapt/develop

company's wearables

application

environments

Design and

development of new

generations of

Wearable devices

integrating key

technologies and

embedding new

functionalities into

textiles and other

body-mounted

devices

3d Printing

Knowledge of and


appropriate 3D

printing systems and

exploit/integrate them

in the company's

infrastructure

Capability to combine

3D printing with

evolution of CAD/CAM

software: development

of additive

manufacturing

applications

Design and

development of new

3D printers; of new

materials to be used

for 3D printing; of

new additive

manufacturing

systems

Cognitive

Systems/

Robotics

Knowledge of and


robotics and

automated systems to

exploit and integrate

them in company’s

infrastructure

Knowledge of and


cognitive systems and

robotics applications

and exploit them in

company's application

environment

Robotics systems

development;

human-robot

interaction;

mechatronics,

perception,

navigation and

cognition(e.g. Novel

cognitive

architectures),

cognitive vision;

knowledge

representation and

reasoning; machine

learning


Source: IDC 2015

Innovation accelerators will drive demand of e-Leadership skills with a strong accent on strategic

vision and change management capabilities. As the perspectives of business exploitation are just

emerging, all organizations will need e-leaders capable to see the way and guide them towards the

most appropriate evolution path. In the case of e-leadership skills we do not foresee specific

differences in demand driven by the different technologies, therefore the type of skills demanded are

the same for all the examined trends.

Table 11: Innovation Accelerators Impact on e-Leadership Skills Demand

E-Leadership Skills


Virtual/Augmented

reality Strategic vision of new technologies business potential and capability to involve business line managers and partners in the development of new business ideas and opportunities

Knowledge of new technologies potential and capability to lead the development of new products/services/ processes suited to organization's strategy

High degree of business domain knowledge, business analytics skills and industry-specific skills in order to implement necessary changes for innovation adoption

Capability to plan and schedule integration of new products and processes into business and supply chains

Wearables

3d Printing

Cognitive

Systems/

Robotics

Source: IDC 2015


11 Main KETs Trends

11.1 Main Trends

Key Enabling Technologies (KET) are a group of six technologies: micro and nanoelectronics,

nanotechnology, industrial biotechnology, advanced materials, photonics, and advanced

manufacturing technologies19

. These technologies are strategic because they have applications in

multiple industries and support societal challenges and advanced changes.

KETs are a priority for European industrial policy because of their potential to support industry growth:

they are in fact among the priority action lines of European industrial policy20

. The European

Commission has identified KETs as a key priority within its Europe 2020 strategy because KETs are

seen as essential to flagship initiatives such as Innovation Union and Digital Agenda for Europe.

One of the necessary conditions for the development and deployment of KETs themselves is the

availability of people with appropriate skills, which means that such skills are themselves an enabling

condition for the development of KETs. The growth potential of KETs heavily relies on both the quality

of skills possessed by the current and future employees, as well as the number of people qualified,

available and willing to work in KETs. Those skills cover a range of advanced technical capabilities

including ICT skills on one hand and on the other hand entrepreneurial skills, project management and

problem solving skills, soft skills like multidisciplinary and creativity.

This chapter is based and presents the PWC approach and analysis conducted in the study "Vision

and Sectoral Pilot on Skills for Key Enabling Technologies-State of Play Analysis for Skill

Requirements, 201521

".

The analysis of skills requirements for KETs heavily relies on the exploration of individual

competences, i.e. focusing on the relevant knowledge and skills that one needs to have to be able to

carry out the tasks of a certain job in the KETs. Nevertheless, a highly complex multidisciplinary nature

of KETs requires intensive teamwork and active collaboration of multiple people simultaneously.

Working in KETs requires a team to function as a unit or collective, with collective performance, and

therefore the team needs to be competent also at the collective level. These collective competences

cannot always be decomposed into an aggregate of individual competences.

Consequently, in case of KETs, looking at individual competences only would be a one-sided

approach, and in this analysis, both individual and collective competences needed for KETs will be

considered.

19

Communication of the European Commission “Preparing for our future: Developing a common strategy for key

enabling technologies in the EU”, COM(2009) 512 final, Brussels, 30.09.2009.

20 Communication from the Commission to the European Parliament, , the Council , the European Economic and

Social Committee and the Committee of the Regions, A Stronger European Industry for Growth and Economic

Recovery Industrial Policy Communication Update / COM/2012/0582 final / and technologies in the EU”,

COM(2009) 512 final, Brussels, 30.09.2009.

20 Communication from the Commission to the European Parliament, , the Council , the European Economic and

Social Committee and the Committee of the Regions, For a European Industrial Renaissance, COM/2014/014

final

21 Draft report, July 2015

http://ec.europa.eu/research/innovation-union/index_en.cfm

http://ec.europa.eu/digital-agenda/


11.2 Demand of KETs Skills

Up till now, only fragmented attempts have been made to assess supply and demand of KETs skills at

the level of individual KETs. To our knowledge, the first attempt of a complete analysis of supply and

demand for KETs was conducted by PWC in 2013. This paragraph summarize briefly the main results

of this PWC model on the demand-supply balance of KET skills.

The demand for KETs skills refer to the number of jobs that exist in KETs. The supply assesses the

number of people qualified, available, and willing to work in KETs.

The estimates of demand and supply were calculated for low, medium and high-level skills in order to

show the development over time in these specific groups. For matching demand and supply, Pwc

focused on medium-level and high-level skills that are specifically relevant to KETs.

The analysis of supply and demand showed that:

Demand for KETs skills in 2013 equaled an estimated total of 2,234,000 technical KETs

professionals and associates. This includes jobs at all skills levels within the KETs fields.

Highly-skilled KETs employment accounts for 55% of total employment, followed by 37%

medium-skilled employment and 8% low-skilled employment.

When considering the future demand for KETs skills, PWC's estimates show that between

2013 and 2025 an additional 953,000 KETs professionals and associates with technical skills

are needed to satisfy demand.

On average, between 2013 and 2025, there will be an additional demand of 79,000 KETs

workers per year. Put differently, between 2013 and 2025, an increase in demand for KETs

skills of 43% is expected.

The key share of the extra demand is made up by replacement demand (e.g. due to

retirement or moving to other sectors) with a total of 772,000 KETs professionals and

associates. Expansion demand (i.e. new jobs) is estimated to be a relatively small share of

total additional demand for KETs skills till 2025, with a total of 181,000 KETs jobs.

Most of jobs related to additional demand (62%) will require highly skilled people, though there

is also a relatively strong increase in demand expected for medium skilled people in KETs

(30% of additional demand).

The data show potential for a skills gap, both for high and medium skills:

o A possible gap in the range of approximately 21,000 to 83,000 highly-skilled KETs

employees per year and 10,000 to 44,000 medium-skilled KETs workers per year,

depending on how the field develops.

o This is under the assumption that KETs will continue to grow in significance relative to

the STEM occupational fields. The ranges also take into account that proportionally

more STEM graduates could be attracted to KETs when the field relatively grows in

size.

However, there is also a potential surplus if the share of KETs in STEM employment remains

constant over time.


o Under this assumption, our calculations show an average surplus of highly-skilled

KETs graduates per year in the range of 12,000 to 37,000 and an average surplus of

medium-skilled KETs graduates per year in the range of 15,000 to 28,000 up till 2025.

Numbers aside, trend analysis shows that medium-level KETs skills potentially face both an

increase in demand and a decrease in the number of graduates, which could further

aggravate the current situation;

o Companies facing difficulties in attracting medium-level KETs skills right now are likely

to find it increasingly more difficult to attract qualified professionals with these skills in

the future.

PwC estimations show that ample supply of STEM graduates is anticipated in the future to satisfy the

demand for KETs skills. However, currently, most of these graduates do not flow to KETs, which can

partially be explained by a relatively unattractive image of KETs as a field to work in.

11.3 Main KET's Competences

As explained above, in KETs, individuals and (even more) teams need to be competent and that

collective competences are more than a sum of individual competences. The following table presents

the KETs competences.

Figure 29 the KETs Skills Box

Source: PwC, Vision and Sectoral Pilot on Skills for Key Enabling Technologies, 2015

KETs rely on a balance of both technical and non-technical competences. Emotional intelligence,

innovation and communication are all skills included in the area of the so called soft skills.


Technical competences can be considered the heaviest category in terms of required knowledge and

skills due to a highly knowledge-intensive nature of KETs.

When it comes to quality, risk & safety, KETs present an environment where workers need to operate

with a high level of accuracy as the equipment is highly expensive, and errors are costly. This

accuracy requires a specific mind-set, the ability to concentrate over a long period of time, attention to

detail, and the ability to work in an environment with stringent and specific quality and safety

procedures. This type of competence is particularly relevant to middle-skilled professionals involved in

manufacturing.

The complex commercialisation trajectories within KETs, including high-risk product demonstration

and proof-of-concept projects, also heavily rely on advanced management skills. The latter include

market analysis and strategy development in a chaotic and unpredictable environment, the need to

acquire and manage large investments due to highly capital-intensive nature of KETs, the need to

coordinate multidisciplinary international teams, the need to manage complex processes with high

risks and strict deadlines etc.

Given the importance of teams in KETs (which are typically formed from people with diverse

professional and cultural backgrounds), communication-related competences represent another key

competence category for KETs. Communication here refers to all kinds of interpersonal exchange of

information, including verbal and written communication, but also virtual collaboration or

communication in virtual teams. The latter refers to the ability to work productively, drive engagement

and demonstrate presence as a member of a virtual team.

Innovation competences refer to the ability of KETs workers to use and integrate various disciplines

into joint solutions to complex problems, the ability to find new patterns and connections between

multiple fields, where these patterns and connections have never been found before. Innovation

competences are central for KETs, the very nature of which is defined by their multidisciplinarity and

(potential) connection to an endless number of application areas.

Finally, emotional intelligence is related to the ability to operate with own and other people's emotions,

and to use emotional information to guide thinking and behavior, including the use of intuition or so

called ‘gut feeling’ about market-related and other developments. Emotional Intelligence emphasises

the central role of human aspects in innovation.

11.4 Skills Impact

Key Enabling Technologies play an important role in enabling innovation, broadly complementing and

enhancing the deployment of the ICT trends identified in the previous chapters. While they grow from

different scientific domains, KETs have in common a positioning at the basis of supply value chains

(they develop basic components and technologies for use by other industries) and a fast pace of

evolution, driven by high R&D intensity.

Concerning technical and R&D skills, the following table 11 shows the areas of emerging skills

demand for each KET, defined in a similar way as done for ICT trends. This table was elaborated on

the basis of the results of the PwC's KET study. These areas of competence are highly specialized

and quite different.

However, in addition to these competences the development of KETs will also require computing

skills, as computational science is by now a must for all research domains, as well as access to

sophisticated information infrastructures with high scientific and research Big Data analytics

capabilities. Also, KETs are likely to drive increasing demand of HPDA (High-performance data

analysis) a term coined by IDC to describe the formative market for big data workloads that exploit


HPC resources, and therefore to require HPC skills. Therefore the development of KETs is also

driving the demand for highly sophisticated ICT skills.

Table 12: Emerging Areas of Demand of skills in KETs field

Trend Technical and R&D Skills

ICT Skills

Micro and nanoelectronics

Performance of ultra-small electronic devices or structures

Computational science skills

HPDA (high performance data analytics) skills

e-infrastructures access and support skills

Assembly of objects with microscale

Nanoscale devices

Microfabrication

Micro assembling and packaging technologies

Nanotechnologies

Manipulation of materials on atomic or molecular scale

Development of nanoscale systems

Industrial biotechnologies

Molecular biology, biochemistry, biophysics, genomics

Biomedical engineering, biosystems engineering

Advanced materials

Properties of conventional solid materials

Materials composition and structure (macroscopic and microscopic)

Photonics

Generation, emission, transmission, modulation, signal processing, switching, amplification, detection of light

Biophotonics, microphotonics, nanooptics, optical computing

Advanced manufacturing technologies

Joining different sub-systems or components

Ability to fabricate complex micro-systems integrated and packaged in 3D with various heterogeneous parts

Establish intelligent/smart assembly for manufacturing

Ability to custom manufacture

Ability to manufacture high or low volumes

Source: IDC elaboration on PWC data


KETs are technologies, not industry sectors. The main actors in the KET field are research centres of

leading enterprises, universities, start-ups and spin-offs, and high-tech companies who tend to have a

knowledge-based strategy rather than a purely commercial strategy (for example selling IPRs or rights

of exploitation of their patents). KETs managers are likely to have a mixed profile with research and

technology competences as well as managerial competences, long-term strategic vision and strong

leadership capabilities. Many of them will have strong ICT skills as well, but KET innovation rather

than digital innovation will be their priority. However, we can still see in these domains specific

demands for e-leadership capabilities, as illustrated in the following table 13:

In terms of strategic leadership, there will be demand for a deep understanding of the role of

innovative digital technologies in supporting KETs and the capability to communicate it to

other top managers and partners, to share a common vision;

In terms of digital savvy, the important skill will be the capability to leverage digital innovation

to support each specific KET development, based on updated knowledge of emerging ICT

trends;

In terms of business savvy, there are at least two main drivers of demand:

o The first is the capability to actually plan and implement the integration of digital

innovation into each KET development process;

o The second is the capability to manage data protection and cybersecurity challenges,

given the strategic importance of IPRs and data in these organizations.

Table 13 Demand of e-Leadership skills by KETs organizations

E-Leadership Skills

KETs


Deep understanding of the role of innovative digital technologies to support each KET development and capability to share it with top management and partners

Capability to leverage digital innovation to support and promote specific KET innovation, based on state--of-the art knowledge of ICT trends and understanding of technical requirements

Capability to plan and schedule integration of digital innovation into KET development processes

Management of cybersecurity and data protection issues

Source: IDC elaboration on PWC data


12 General Conclusions

12.1 Overview of Main Innovation Trends

Europe today is already a "technological society". European citizens have seen technology progress,

driven by ICT, pervade every facet of work and personal life as well as the public domain. But the

speed of technology evolution is not slowing down and according to many observers, the cumulative

impact of the current trends in the next decade is likely to be even more far-reaching and disruptive

than whatever has been experienced until now.

The turning point of the next years, according to IDC, is going to be the combination of the four key

technologies which have driven innovation in the last few years (Mobile technologies, Cloud

Computing, Social technologies and Big Data) with so-called innovation accelerators which will

multiply their transformative effects. They include the triad Cognitive systems-Robotics-3D printing

deeply transforming manufacturing but also the services sectors, and the diffusion of Wearable

devices allowing to access immersive environments of Virtual or Augmented reality for gaming,

learning, but also for business tasks. Innovation accelerators are in the early phase of adoption but

they are out of the lab and are expected to grow fast in the market in the next years. Nothing of this

would be possible without the take-off of the Internet of Things, the ubiquitous connectivity and

communication platform which is the main enabler of the Innovation accelerators and a multiplier in its

own right of digital innovation, together with Big Data and Cloud computing. According to IDC, Mobile,

Cloud, Social business and Big Data already account for more than a quarter of enterprise IT

spending; one or more of innovation accelerator technologies have already been adopted by

approximately 12% of European enterprises with more than 10 employees, but growth rates are

expected to be very fast, as documented in the previous chapters.

ICT innovation is complemented by KET (Key Enabling Technologies) innovation which is

transforming the European industry, as documented by PwC's analysis. Micro and nano electronics

provide the components for hardware and software advances; nanotechnologies and advanced

materials revolutionize the very substance of new products, and provide components for IoT;

advanced manufacturing technologies complement 3D printing and enable additive manufacturing;

photonics advances will transform networks and may revolutionize computing; industrial

biotechnologies are pushing to the market scientific breakthroughs of the last years in fields as

different as molecular biology, biochemistry, biophysics, genomics.

The cumulative transformational impacts of these ICT trends are described by IDC as the

phenomenon of "Digital transformation", a continuous process of disruptive innovation experienced by

enterprises by leveraging digital competencies to innovate new business models, products, and

services that seamlessly blend digital and physical and business and customer experiences. Every

business will become a digital business, not in the sense that digital will become their core business,

but that in every organization digital processes will be deeply embedded with traditional processes.

According to IDC's European Digital Transformation maturity benchmark, only 5% of European

organisations can currently be termed digital disruptors while at the other end of the spectrum, one in

five can be characterised as digital laggards. Many European organisations are currently only laying

the groundwork in terms of establishing the enabling ICT environments that will allow them to

transform digitally, but this is expected to change rapidly in the next years.

Digital transformation is also supporting the flourishing of a variety of new business models, perhaps

the most talked about are those created by the "sharing economy", providing access to peer-to-peer

goods and services through community-based online services. Underpinning these new business


models is that principle that the use of technology makes it possible for individuals, businesses and

governments alike to optimise the use of resources by sharing, redistributing or reusing spare capacity

in its widest form, such as money (social lending), accommodation (Airbnb), any used goods

(freecycle), and car sharing (RelayRides) to name a few.

This process of evolutionary as well as radical digital transformation is also foreseen by leading

consultants, such as Accenture, IBM and Mc Kinsey. A key component of their recent research is the

investigation of the automation impacts on work because of the forthcoming diffusion of cognitive

systems, intelligent software tools for decision making and new generation of robots capable of

performing new kinds of tasks.

Accenture's 2015 technology vision centers on digital business processes re-organization and

underlines the consequences of the diffusion of intelligent software, cognitive systems, robotics and

the IoT. For example Accenture underlines the trend towards the "Intelligent Enteprise" (driven by

intelligent software decisions), the emergence of digital platforms reshaping industries into

interconnected systems (platforms revolution) and the deep change of human-machine cooperation

(workforce reimagined).

McKinsey agrees that digital transformation requires comprehensive innovation and underlines that

applying digital tools selectively may lead to missed opportunities. More important, McKinsey's recent

research on the impact of automation on work forecasts that 45 percent of the activities individuals are

paid for can be automated, and that even the highest-paid occupations in the economy, such as

financial managers, physicians, and senior executives, including CEOs, have a significant amount of

activity that can be automated. The preliminary results show that the benefits (ranging from increased

output to higher quality and improved reliability) typically are between three and ten times the cost.

IBM's vision centres on data-driven innovation. IBM believes that from 2014 data are starting to

transform industries and will have disruptive effects on all industries because technology is changing

the use and relevance of data. This will affect and transform decision-making processes, the way

organisations produce and deliver products and services and the way they compete.

In summary, emerging innovation trends are transforming the socio-economic system, driving the

digital transformation of enterprise business processes, and changing the very nature of work.

Robotics and artificial intelligence tools will lead to the increasing automation of knowledge tasks, with

unclear consequences on the number of jobs, while the demand of new skills may come from areas

such as game design, neuroscience, and happiness psychology22

which however will pose new

challenges to the education and training system.

12.2 The Impacts on Skills Demand

The drivers of new demand of ICT and e-leadership skills have been considered separately for each

technology trend: even if the largest impacts come from their combination, each technology has some

specificity and therefore it was important to consider each of them in depth.

The following tables present a summary of the impact on demand of each category of skills for

comparison, based on a three steps semantic scale (high, medium and low increase of demand). This

is a qualitative assessment, since it was not possible to quantify the potential increase or decrease of

demand separately for each trend compared to an average benchmark. However, this summary

assessment allows drawing some interesting conclusions, commented below.

22

Institute for the Future, 2011


12.2.1 Impact of ICT Trends on Core Technical Skills

These are ICT skills needed to develop and implement the trend-related innovation in the

organization: infrastructure skills concern the deployment, implementation and management of

hardware or network solutions, while applications skills, as the term says, concern the implementation

and management of software and applications.

Based on IDC's analysis, Big Data and IoT trends will generate the highest demand for both

infrastructure and applications-related skills, because of the need to deploy and implement complex

systems solutions; also the other innovation accelerators (Virtual/Augmented reality, 3D printing and

Cognitive systems/Robotics) will drive a high increase of demand (Table 14). This is going to include a

good proportion of new skills, such as data science skills, since these trends have a strong component

of disruptive innovation.

For Cloud computing and IT security infrastructure-related innovation is more relevant than

applications-related innovation, therefore we expect high demand of infrastructure skills and a medium

level of demand of application skills. For these trends we expect mainly incremental demand of

existing skills correlated with incremental innovation.

Mobile technologies are the opposite of Cloud, with higher demand of applications-related skills

(especially DevOps skills) and medium level demand of infrastructure skills (mainly driven by the need

to manage multiple infrastructures). In the case of social business, IDC foresees a low level of

demand of infrastructure-related skills (all outsourced to social networks) and a medium level of

demand of applications-related skills. For this trend we expect mainly incremental demand of existing

skills.

Finally, wearables are devices sold as products, plugged into Virtual/Augmented reality solutions

which are considered separately. Therefore we expect a medium-level increase of the demand for

new skills in this area, mainly because they are still fairly new products only at the start of their

penetration in the market. The main demand will be for integration of wearables in the company's

infrastructure and application environment, so the demand is likely to be incremental demand of

existing skills.

Demand decrease

The main impact of these trends will be to accelerate the reduction of demand for traditional IT skills,

including specifically:

Operational skills to manage and maintain corporate IT systems

Maintenance and support of legacy systems (PCs, desktops...)

Maintenance and support of legacy applications

Traditional IT management skills focused on proprietary systems and custom developments

12.2.2 Impact of ICT Trends on R&D Skills

R&D skills are required to deal with the main research challenges driven by the ICT trends and to

design and develop new products and services based on these emerging technologies. This is

focused on applied research, not long-term and basic research.

The projected impact on demand is clearly divided by trend.

In the case of Mobility and Cloud Computing we expect a low increase of demand of R&D skills. There

is already considerable research ongoing and while there are important challenges, they may not

require new skills in these specific domains but linked with other converging domains (5G

technologies for example). This is likely to be incremental demand of existing skills.


For social business and IT security we expect a medium-level increase of demand, driven in the first

case by the convergence of social with Big Data and cloud, for IT security by the development of

privacy-enhancing technologies. This is likely to be incremental demand of existing skills.

For the other trends instead we expect a high increase of demand because of the early stage of

development of these technologies and the need for solving countless deployment and

implementation problems.

12.2.3 Impact on Quality, Risk and Safety Skills

These new trends will pose new challenges in terms of new quality standards to be developed;

understanding of new typologies of risks and dealing with them with a comprehensive approach;

completely new safety challenges (think of automated cars, for example). Therefore they will require

new or updated skills in this area. The trends most likely driving a strong increase of demand of skills

in this area are Big Data, Social business (because of data privacy, naturally, but also of the new ways

to interact with customers), IoT, IT Security, Cognitive systems/Robotics. The other trends will

generate a medium-level increase of demand (Table 14).

The demand of these skills is likely to be a mix of traditional and multidisciplinary new competences,

no longer limited for example to back-office accounting, process control and contract management,

but also to the capacity to envision potential new risks and to negotiate-deal with line managers and

partners to set-up countermeasures and define guidelines of behavior.

Decrease of demand

There is likely to be a decrease of demand for traditional quality and risk management skills based

only on back office accounting competences.

Table 14 Summary of ICT Trends Impacts on Demand of Skills to 2020

TREND Technical Skills R&D

Quality, Risk and Safety


Mobility M H L M

Cloud Computing H M L M

Big Data H H H H

Social Business L M M H

IoT H H H H

IT Security H M M H

Virtual/ Augmented reality H H H M

Wearables M M H M

3d Printing H H H M

Cognitive Systems/ Robotics H H H H



12.2.4 Impact of ICT Trends on e-leadership skills

E-Leadership Skills are those required of an individual to initiate and achieve digital innovation,

including strategic leadership, digital savvy and business savvy. E-Leadership skills are relatively new

so we don't expect a reduction of demand.

First of all we notice that all trends generate a high or medium level increase of demand. There are

however relevant variations between trends (Table 15).

The three technologies which could be arguably considered as the most established in the market –

Mobility, Cloud and Social Business – are expected to drive a medium level of demand of e-

Leadership, for all its skills typologies. There are two main reasons; the first is that existing e-

Leadership skills are probably in these domains, so demand does not need to increase as much; the

second is that they are less disruptive than the other trends and are more easily understood and

managed by line managers.

Big Data and IoT on the other hand will drive high demand of e-leadership in all its components: both

data-driven innovation and IoT systemic innovation require sophisticated leadership skills as well as

digital and business savvy and are starting to take-off in the market.

IT security is a case apart; we project medium-high demand of e-leadership skills, with high demand

particularly of digital savviness, due to the need to develop and adapt IT security practices to the new

digitally transformed business environment.

Finally, for the main innovation accelerators (Virtual/Augmented reality, Wearables, 3D printing and

Cognitive systems/ Robotics) we foresee high demand for all the components of e-leadership, since

these technologies will require strategic vision and a high degree of industry specific competences to

be implemented in the digitally transformed environment.

Table 15 Summary of ICT Trends Impacts on Demand of e-Leadership Skills to 2020

E-Leadership Skills

Strategic

Leadership Digital Savvy Business Savvy

Mobility M M M

Cloud Computing M M M

Big Data H H H

Social Business M M M

IoT H H H

IT Security M H H

Virtual/Augmented reality H H H

Wearables H H H


3d Printing H H H

Cognitive Systems/ Robotics H H H


12.2.5 Impact of KETs on ICT Skills

KETs are technologies, not industry sectors. While they grow from different scientific domains, KETs

have in common a positioning at the basis of supply value chains (they develop basic components and

technologies for use by other industries) and a fast pace of evolution, driven by high R&D intensity.

The main actors in the KET field are research centres of leading enterprises, universities, start-ups

and spin-offs, and high-tech companies with know-how based strategies. Their main demand for skills

will be in each of their technology field (Table 12). However, the development of KETs requires also a

high degree of ICT skills, in terms of computational science skills, high scientific and research Big

Data analytics capabilities. Also, KET organizations require access to sophisticated information

infrastructures with high computing capabilities, not simply run-of-the-mill enterprise IT networks.

However, we expect that most KET organization already have most of the ICT skills they require, and

will generate a low-medium increase of demand of these skills. We expect a low increase of demand

from micro-nano electronics and from advanced materials organizations, and a medium level of

demand increase from the other KETs which are currently growing faster.

12.2.6 Impact of KETs on e-Leadership skills

KETs will generate medium-high demand of e-leadership skills, as illustrated in the following Table 16.

Given the profile of these organizations, we expect them to require strategic e-leadership capabilities

in terms of a deep understanding of the role of innovative digital technologies in supporting KETs and

to share this vision with other managers and partners. We also expect them to require skills of

leveraging digital innovation to support each specific KET development (digital savvy); we foresee

lower demand of business savvy e-leadership skills, simply because the business and for-profit

activities of these organizations are less relevant.

Overall, we foresee most KET domains to drive high demand for strategic e-leadership skills, because

of their rapid evolution and disruptive innovation perspectives. In the case of micro-nano electronics

and advanced materials we foresee a medium demand increase, because of their perspectives of

more incremental rather than disruptive innovation in the next years. In the case of digital savvy we

foresee a medium increase of demand for all domains, as KET staff is likely to already have some

level of these skills.


Table 16 Summary of KET Trends Impacts on Demand of ICT and e-Leadership Skills to 2020

KETs

ICT Skills E-Leadership Skills

Strategic

Leadership Digital Savvy

Business

Savvy

Micro and nano electronics L M M L

Nanotechnologies M H M L

Industrial biotechnologies M H M L

Advanced materials L M M L

Photonics M H M L

Advanced manufacturing technologies M H M L


12.3 The Experts' Opinion

12.3.1 Profile of the sample

There is a broad consensus among the leading stakeholders surveyed by empirica that all major ICT

trends covered in this report will have a strong impact on the demand of ICT and e-leadership skills in

the next years to 2020.

The survey23

collected over 700 answers from a group composed of policy makers, university and

research, e-skills experts. The majority of them belonged to the ICT domain (59%), small groups came

from liberal professions (6%), Advanced Manufacturing Technologies and other KETs (overall 7%)

and the rest is a mixed group (see figure below). It is specifically interesting that answers vary very

little by stakeholder group: ICT respondents tend to give higher impacts scores than the other

surveyed experts, but no other significant variations are visible in the group. This points to a broad

convergence of opinions in the stakeholder environment.

23

Empirica: European and national e-leadership skills policies, initiatives and partnerships, challenges and technology trends and their impact on digital leadership skills – empirical evidence and expert views (working document), January 2016 (forthcoming)


Figure 30 Survey sample by domain (% of respondents)


12.3.2 Impacts of ICT Trends on Industry and Daily Life

The large majority of experts believe that the impacts of ICT trends on industry will be high or very

high, and this holds for all trends (Figure 31). If we consider only the top score answers (very high

impacts) a clearer ranking emerges (Table 17), with IT security, Mobile and Big Data appearing as the

most relevant trends, closely followed by Cloud Computing and IoT. Only for artificial intelligence the

share of "very high impact" opinions falls to a minority of 23% (25 for ICT domain respondents). This

could be due to the use of the term "artificial intelligence" (AI) which is probably too general: if we had

asked about Cognitive systems, robotics and Virtual/ Augmented Reality, currently the main frontiers

of commercial applications of AI, we would probably have received answers in line with the other

trends.

IT security, Mobile and Big Data are consolidated trends with strong presence in the market. So is

Cloud Computing, but its perspectives of future impacts are probably considered as less disruptive.

Mobile technologies, while already universally diffused in the market, are still evolving fast and

generating continuously changing impacts. IoT shows the higher relative share of sceptics after AI,

even if it is quite small in absolute terms (with 22% assigning it a medium impact level).

ICT experts' answers (Table 17) follow the same ranking as the total sample, but with higher average

scores; this seems natural since they are closer to the ICT environment and more likely to believe in

their disruptive innovation impacts, as well as being the majority of the sample. The other stakeholder

ICT (information and

telecommunication technology)

59%

KET4%

AMT3%

Liberal professions

6%

Other 28%


groups do not differ substantially for most trends, only for Big Data and IoT there is a greater

differentiation: for example the liberal professions experts believe in the influence of Big Data but are

less convinced by IoT. The mixed group also is more skeptical of IoT and AI. No trend scores at 3

(neutral impact) or below, for any of the respondent groups.

Figure 31 Impact of Key ICT trends on Demand of Skills to 2020, % of Respondents by score


Table 17 ICT trends Impact on Industry (Share of "Very High" answers)

TREND ICT Domain (% of Very

High) All Respondents (% of Very

High)

IT security 63.7 61.1

Mobile 62.9 56.0

Big data 58.2 50.7

Cloud Computing 56.3 48.5

Internet of Things 49.3 43.4

Artificial intelligence 25.0 23.3


Impact on inductry

3,6%

4,9%

6,8%

14,3%

11,2%

13,6%

14,7%

22,0%

7,3%

26,8%

27,8%

32,0%

27,7%

24,4%

26,7%

26,5%

56,0%

48,5%

50,7%

43,4%

61,1%

23,3%

Mobility and mobile apps

Cloud computing

Big data

Internet of things (IoT)

IT security

Artificial Intelligence

Very low (1) (2) (3) (4) Very high (5)


Figure 32 ICT Trends Impacts on industry and Skills Demand, Average Scores, All Respondents


Compared to the impact on industry, experts evaluate the influence of ICT trends on daily life as

slightly lower, but still generating a medium to high impact in the next years (Figure 32). It is

worthwhile noticing that a large majority of experts (over 75%) agree on the high level of impact of

mobile and IT security technologies, while only half of them believe the same about Big Data, IoT and


Cloud; the other half believe that they will have a medium to low impact. In the case of Artificial

Intelligence, the majority of experts (60%) believe that it will have a medium to low impact, but there is

still 40% who evaluate its relevance for daily life as high or very high.

Overall, there is a clear consensus that digital innovation is going to shape daily life in the next years

as much as or more than in the past few years.

12.3.3 Impacts on the demand of ICT and e-Leadership skills

The majority of experts evaluate the impacts of ICT trends on the demand of skills as very high or

high, with shares ranging from 57% to over 80% for technical skills and from 63 to 75% for e-

leadership skills (Figure 32 and Table 18). The ranking of trends by level of impact here changes from

those seen above: IT security remains the most relevant, but is closely followed by Big Data, IoT and

Artificial Intelligence, while Mobile and Cloud are last. The impacts on the demand of technical skills

are expected to be slightly higher than those on the demand of e-leadership skills, but differences are

really minor. Looking more closely only at "very high impacts" answers (Table 19) IT security, Mobile

and Big Data collect the highest shares of "very high impact" answers; Artificial Intelligence, IoT and

Cloud the lowest share (but still about one third of respondents consider their future consequences

high or very high). When looking at the results by respondent group, it is clear that the ICT

respondents raise the average with their complete belief in the increase of demand for e-leadership

skills, while the other groups give lower scores, but still consider this impact to be relevant.

Table 18 Impact of ICT Trends on Demand of Skills and Risks of Skills Gap (share of "Very High + High" answers)

% of "Very High + High" answers

Impact on Technical Skills demand (%)

Impact on e-Leadership skills

demand (%)

Risk of Skills Gap (%)

TREND All Respondents All Respondents All Respondents

IT security 83.6 75.6 75.4

Big data 81.2 71.9 74.7

IoT 72.6 67.2 69.3

Artificial Intelligence 73.4 56.0 62.9

Mobile 62.3 64.0 60.8

Cloud 57.1 63.5 62.6

Source: IDC 2015


Table 19 Impact of ICT Trends on the Demand of technical and e-leadership skills, share of "Very High" answers

% of "Very High" answers Impact on Technical Skills demand

(%) Impact on e-Leadership skills

demand (%)

TREND ICT Domain All

Respondents ICT Domain

All Respondents

IT security 58.9 55.9 50.6 48.2

Big data 50.6 45.7 47.3 42.3

IoT 45.6 40.3 46.4 39.6

Artificial intelligence 38.6 37.5 28.8 28.0

Mobile 34.6 31.5 32.5 28.5

Cloud 33.6 30.0 32.7 28.4


Finally, the opinion on the risks of a skills gap is universally shared: the share of respondents believing

this risk is high or very high is between 60-70% of the sample for all trends, with a similar ranking of

trends as for the impact on demand (Figure 32 and Table 18). Looking more closely, we notice that

almost twice as many experts think that the risk is very high for IT Security and Big Data than for

Mobile and Cloud (Table 20). However, also for Mobile and Cloud the average level of risk of lack of

skills is considered to be relevant. Clearly the experts believe that the increase of demand of

specialized skills driven by all ICT trends is not likely to be satisfied by the labour market, the more so

the more disruptive and innovative a technology is. These survey answers highlight the main pain

points in sourcing skills now experienced in the market and expected to become worse. These results

are coherent with the analysis presented in this report about the potential impacts of the main ICT

trends and the disruptive nature of the combination IoT Big Data and Cloud, which will pose the

greater challenges in skills recruitment.

Table 20 ICT Trends Impact on Risk of Skills Gap in 2020 (share of "Very High" answers)

% of "Very High" answers Risk of Skills Gap (%) Risk of Skills Gap (%)

TREND ICT Domain All Respondents

IT security 50.2 48.4

Big data 46.9 43.4

IoT 42.2 37.4

Artificial intelligence 39.9 36.7

Mobile 29.2 29.4

Cloud 29.4 28.3



Figure 33 Impact of Key ICT trends on the Risks of Skills Gap in Europe, % of Respondents by score


12.3.4 E-Leadership Demand: Main Challenges

Both IDC's analysis and the experts' survey have concluded that there is a strong upcoming demand

of e-Leadership skills in all its components, generated by the innovation trends examined in this

report. To satisfy this demand there is a need to:

Improve the understanding and knowledge of digital technologies by managers and

professionals coming from non-ICT competence areas

Improve the understanding and knowledge of industry and functional business by ICT

managers and professionals

According to the experts' survey (Figure 34), some of the actions to be taken could be:

To integrate digital savviness in formal educational programmes relevant by industry (60% of

respondents strongly agree)

To promote MBA-style training courses on digital savviness for managers (53% of

respondents agree)

However, opinions are more mixed about the role of the private sector in paying for reskilling and

training. While 59% of respondents agree that the public sector should not be the only one funding

changes in education which are needed by a specific industry, 48% agree that the private sector

should initiate efforts to improve digital savvyness in the current professionals and managers, and only

44% agree that this should be funded by the private sector. This should include reskilling, training

and/or additional education efforts on e-leadership.

Risk of skills gap in Europe

8,8%

4,3%

6,5%

8,0%

24,5%

24,8%

17,4%

21,6%

16,4%

24,7%

31,4%

34,3%

31,3%

31,9%

27,0%

26,2%

29,4%

28,3%

43,4%

37,4%

48,4%

36,7%

Mobility and mobile apps

Cloud computing

Big data

Internet of things (IoT)

IT security

Artificial Intelligence

Very low (1) (2) (3) (4) Very high (5)


Figure 34 Experts Opinions on e-Leadership Skills

Please indicate to what extent you agree with the following statements:

14,2%

13,0%

10,5%

8,1%

10,2%

10,4%

10,2%

8,1%

29,8%

28,0%

40,2%

30,0%

6,3%

25,2%

31,0%

29,7%

26,9%

29,7%

30,4%

34,0%

30,9%

37,2%

30,8%

23,1%

51,3%

54,1%

66,5%

58,6%

22,0%

21,4%

14,7%

21,3%

60,5%

36,6%

People that have a leadership position in my industry require more knowledge on the

possibilities that new digital technologies have to offer

People that have a leadership position in my industry need to be better at integrating digital

technology in their business approach

For companies to stay competitive in the future, leadership need to become more digital-savvy

Digital savviness is crucial for leadership positions now and in the years to come

People that have a leadership position in my industry could use an MBA-style training course on

the latest digital technologies

People that have a leadership position in my industry require extensive reskilling through formal

educational programmes to their knowledge on digital technologies

Reskilling, training or additional education efforts to improve digital savviness of current

professionals and their leaders should be funded by the private sector

Reskilling, training or additional education efforts to improve digital savviness of current

professionals and their leaders should be initiated by the private sector

To prepare the future generation of professionals, digital savviness should be integrated in the formal educational programmes relevant to my industry

Changes in university curricula, educational requirements or courses relevant to my industry should not be funded by the public sector alone

Strongly disagree (1) (2) (3) (4) Strongly agree (5)



12.4 Conclusions

The innovation push of the main ICT trends and KETs will generate in the years to 2020 strong

transformational impacts on the EU economy and society, driving a strong increase of demand of ICT,

R&D but especially e-leadership skills. The demand of e-leadership skills varies by type of technology

trend and type of skills, but Big Data, the Internet of Things and the combination Cognitive

systems/Robotics are likely to generate the most disruptive impacts and drive the highest demand of

e-leadership skills. Both IDC research and the experts' opinions converge on these conclusions.

Approximately 70% of the experts surveyed agree that the increase of demand of skills will create a

very high risk of skills gaps in Europe.

However, experience says that complaints about the difficulty of sourcing skills do not necessarily

translate into a concrete increase of employment, if skills become available. There are all kinds of

mismatches between demand and supply which must be dealt with (from unrealistic expectations, to

wrong timing, to mismatched geographical location: supply in Europe is not always available where

demand is).

In the experts' survey the technology trend generating the highest impacts on the demand of skills is

IT security. The increased demand for IT security skills, for example, is a constant in IDC surveys.

However, this has never prevented business or consumer users from adopting new technologies: also

investments in IT security, being defensive rather than oriented to grow the business, are done

cautiously and never at the level one would expect from the intensity of concern shown in surveys.

Therefore, the demand of IT skills is more likely to translate into demand for training and specialized

certification for existing IT employees and managers than into the creation of new, additional jobs.

Nevertheless, the innovative nature and technology profiles of some of these trends, particularly Big

Data and IoT, will definitely create demand for genuinely new skills and, thanks to the potential of

increasing business revenues, also the creation of new jobs.


Annex – Main References

AIOTI, Association for Innovation in the Internet of Things: 12 Reports containing the "Recommendations for future collaborative work in the context of the Internet of Things Focus Area in Horizon 2020" covering the main focus areas of the Internet of Things (IoT) Work Programme 2016-2017 - https://ec.europa.eu/digital-agenda/en/news/aioti-recommendations-future-collaborative-work-context-internet-things-focus-area-horizon-2020

Accenture, "Accenture Technology Vision, Digital Business Era, Stretch your Boundaries", 2015

Danish Technological Institute, Fraunhofer, Cloud Computing, Cyber Security and Green IT- The

Impacts on e-skills requirements, Final Report, 2012

Economist Intelligence Unit, Global firms in 2020 - The next decade of change for organisations and

workers, 2010

Empirica, e-Leadership Digital Skills for SMEs, 2015

Empirica: European and national e-leadership skills policies, initiatives and partnerships, challenges

and technology trends and their impact on digital leadership skills – empirical evidence and expert

views (working document), January 2016 (forthcoming)

European Internet Foundation, The Digital World in 2030, What Place for Europe, 2014

European Parliament, Ten technologies which could change our lives, Potential Impacts and Policy

Implications, STOA Unit, January 2015

IBM Global Technology Outlook 2015, Data Transforming Industries

Institute for the Future, the University of Phoenix Research Institute, Future Work Skills, 2020- 2011

McKinsey Global Institute, Disruptive technologies: Advances that will transform life, business, and the

global economy, 2013

McKinsey Global Institute, The Internet of Things: Mapping the value beyond the hype, June 2015

McKinsey Quarterly, Michael Chui, James Manyika, and Mehdi Miremadi Four fundamentals of

Workplace Automation, November 2015, http://www.mckinsey.com/insights/ business_technology/

four_fundamentals_of_workplace_automation

McKinsey&Company, Tunde Olanrewaju and Paul Willmott Finding your digital sweet spot, November

2013 http://www.mckinsey.com/insights/business_technology/finding_your_digital_sweet_spot

McKinsey&Company, Cornelius Baur and Dominik Wee, Manufacturing’s next act, June 2015

McKinsey&Company, Brian Hartmann, William P. King, and Subu Narayanan, Digital Manufacturing,

the Revolution will be virtualized, August 2015

OECD, Innovation Strategy 2015 – An Agenda for Policy Action

OECD, BEPS Action 1: Address the Tax Challenges of the Digital Economy, 2014

OECD, Data-Driven Innovation: Big Data for Growth and Well-Being, October 06, 2015

PWC, Vision and Sectoral Pilot on Skills for Key Enabling Technologies, State of play analysis of Skills

Requirements, 2014

SPARC, Strategic Research Agenda for Robotics in Europe 2014-2020 by the SPARC PPP

http://www.eu-robotics.net/cms/upload/PPP/SRA2020_SPARC.pdf

The Conference Board, Unlocking the ICT growth potential in Europe: Enabling people and

businesses, study for the EC, 2012

http://www.mckinsey.com/insights/


Blank Page

promotion of e-leadership skills in europe [scale] business,...

Documents