Supporting specialised skills development : big data, Internet of things and cybersecurity for SMEs : final report.
Date: 2020-03-09
Institutions: Executive Agency for Small and Medium-sized Enterprises
Subjects: Internet of Things, big data, digital literacy, impact of information technology, information security, information technology, professional qualifications, small and medium-sized enterprises

Skills for SMEs 

Supporting specialised skills  

development: Big Data,  

Internet of Things and  

Cybersecurity for SMEs 

Final report 

Written  by C apgemini Invent, European DIGITAL SME Alliance, Technopolis Group  
December – 2019 

 
 
 
 
 
 
 
 
 
 
 
 
EUROPEAN  COMMISSION 

Ex e cutive Agency for Sm all and Medium-sized Enterprises (EASME) 
Unit A.1.3 COSME 

E-m ail: EASME-C O SME-ENQ UIRIES@ec.europa.eu 

Europe an Commission 
B-1049 Brussels 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Skills for SMEs 

Supporting specialised skills  

development: Big Data,  

Internet of Things and  

Cybersecurity for SMEs 

Final report 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Europe Direct is a service to help you find answers  
to your questions about the European Union. 

Freephone number (*): 

00 800 6 7 8 9 10 11 

(*)The information give n is fre e , as are  m ost calls (though some operators, phone    

box es or hotels may charge you). 

LEGAL NOTICE 

The  information and views set out in this publication are those of the author(s) and do not necessarily reflect 
the  official opinion of EASME or of the  C ommission. Ne ither EASME, nor the  C ommission can guarantee the 
accuracy of the data included in this study. Neither EASME, nor the Commission or any person acting on  their 
be half may be held re sponsible for the use which m ay be made of the information  contained therein. 

More  information on the European Union is available on the Internet (http://www.e uropa.eu). 

Lux embourg: Publications O ffice  of the European Union, 2020 

ISBN 978-92-9202-778-0 

doi10.2826/772332 

This service contract is carried out by Capgemini Invent, the Technopolis Group and the 
European Digital SME Alliance.  

© Europe an Union, 2020 

 
  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ABSTRACT 

This study report concludes an initiative by the European Commission and EASME to 
supporting specialised skills development related to Big Data, Internet of Things (IoT) 
and Cybersecurity for small and medium-sized enterprises (SMEs) in Europe. The 
report includes an analysis of the potential benefits and barriers for technology 
adoption by SMEs and presents a vision, roadmap and toolbox to increase the capacity 
of industry, social partners, education and training organisations and policy  makers at 
all levels to promote and support the acquisition of these skills by SMEs in Europe. It 
is built on broad stakeholder and expert consultation via workshops, surveys, 
interviews and a high-level conference. It includes references to good practices and 
lessons learned derived from them to identify elements relevant to scaling up.  

 
  
 
Table of contents 

EXECUTIVE SUMMARY ............................................................................. 5 

1. 

INTRODUCTION ..............................................................................15 

1.1.  Rationale ...............................................................................15 
1.2.  Objectives ..............................................................................17 
1.3.  Scope ...................................................................................18 
1.4.  Approach ...............................................................................19 
1.5.  Structure of this document .........................................................21 

2.  THE RELEVANCE OF BIG DATA, INTERNET OF THINGS AND CYBERSECURITY 

FOR SMES .....................................................................................22 

2.1.  The emergence of big data, Internet of Things and cybersecurity..........22 
2.1.1.  Big data ......................................................................22 
2.1.2.  Internet of Things ..........................................................25 
2.1.3.  Cybersecurity ...............................................................25 
2.2.  Opportunities for SMEs to benefit from these technologies ..................29 
2.2.1.  Big data ......................................................................29 
2.2.2.  Internet of Things (IoT)...................................................32 
2.2.3.  Cybersecurity ...............................................................35 
2.3.  The impact of technological trends on the take-up by SMEs.................37 
2.3.1.  Impact of technological trends on technology adoption ............37 
2.4.  Adoption of big data, Internet of Things and cybersecurity by SMEs ......40 
2.4.1.  Segmentation of SMEs ....................................................40 
2.4.2.  Big data ......................................................................41 
2.4.3.  Internet of Things ..........................................................44 
2.4.4.  Cybersecurity ...............................................................46 
2.5.  Barriers and drivers for the take-up of the technologies .....................50 
2.5.1.  Barriers for adopting emerging technologies .........................50 
2.5.2.  Barriers for skills development within SMEs ..........................56 
2.5.3.  Synthesis ....................................................................58 

3.  SKILLS REQUIREMENTS RELATED TO BIG DATA, INTERNET OF THINGS AND 

CYBERSECURITY .............................................................................61 

3.1.  Generic skills ..........................................................................61 
3.2.  Specific skills ..........................................................................67 
3.2.1.  Big data ......................................................................68 
3.2.2.  Internet of Things ..........................................................70 
3.2.3.  Cybersecurity ...............................................................71 
3.3.  Skills gaps, shortages and mismatches ..........................................73 
3.3.1.  General.......................................................................73 
3.3.2.  Specialised skills gaps.....................................................76 
3.3.3.  Conclusions..................................................................80 

4.  SKILLS STRATEGIES ........................................................................81 

4.1.  Strategy needs ........................................................................81 
4.1.1.  A skills strategy implies a conscious decision ........................81 

 
  
 
 
4.1.2.  Different  strategy  needs  for  different  users  of  the 

technologies in the SMEs .................................................84 
4.2.  Choosing the right strategy.........................................................84 
4.2.1.  Size of investment .........................................................84 
4.2.2.  Approaches to fill skills gap ..............................................85 
4.2.3.  Providers to fill skills gap .................................................86 
4.3.  External skills strategies ............................................................87 
4.4.  Internal skills strategies .............................................................88 
4.5.  Conclusion .............................................................................90 

5.  KEY STRATEGIES AND POLICIES .........................................................90 

5.1.  Overview of relevant initiatives ....................................................91 
5.2.  Initiatives led and/or funded by the EU ..........................................92 
5.2.1.  Blueprint for sectoral cooperation on skills ...........................94 
5.3.  Initiatives funded by Member States governments ............................94 
5.3.1.  Regional initiatives.........................................................96 
5.4.  Initiatives funded by the private sector in Member States ...................97 
5.4.1.  Insurance companies and accountancies can play a key role 

in making SMEs more cyberproof .......................................97 
5.4.2.  Various private sector led training activities ..........................98 
5.5.  Initiatives funded by public-private collaborations in Member States......99 
5.6.  Examples of initiatives in US ..................................................... 100 
5.6.1.  Overview of US support................................................. 100 
5.6.2.  Comparing the US and the EU......................................... 102 
5.7.  Learnings from the good practices .............................................. 102 
5.7.1.  Upskilling the current workforce ...................................... 102 
5.7.2.  Reskilling the current workforce ...................................... 103 
5.7.3.  Educating the future workforce ....................................... 103 
5.7.4.  Conclusions................................................................ 104 

6.  A FIVE-YEAR STRATEGY ON SKILLS DEVELOPMENT FOR SMES .................. 108 

6.1.  Design principles.................................................................... 108 
6.2.  Vision statement .................................................................... 109 
6.3.  Supporting measures to be considered to boost skills development ..... 110 
6.3.1.  Stream A - Strengthening the ecosystem ........................... 111 
6.3.2.  Stream B - Strategic outlook development ......................... 118 
6.3.3.  Stream C - Structured skills development .......................... 125 
6.3.4.  Stream D - Tailoring training to SMEs’ needs ...................... 131 
6.3.5.  Governance: Creating overarching governance for skills ........ 137 

7.  TOOLBOX .................................................................................... 139 

7.1.  Purpose of the toolbox............................................................. 139 
7.2.  Design of the toolbox .............................................................. 139 

8.  PROVIDE  A COMPARISON WITH THE US AND  PROPOSE INDICATORS AND 

MONITORING MECHANISMS FOR INTERNATIONAL COMPARISONS ............. 142 

8.1.  Overview this task .................................................................. 142 
8.2.  Conceptual considerations accounted for in the proposed monitoring 

mechanism........................................................................... 142 
8.3.  The Monitoring mechanism ....................................................... 143 
8.3.1.  Sources .................................................................... 144 
8.4.  Monitoring mechanism indicators explained................................... 146 
8.4.1.  Supply ...................................................................... 146 

 
  
8.4.2.  Demand .................................................................... 150 

8.5.  Building  on  existing  frameworks  –  towards  a  single  monitoring 

framework............................................................................ 154 

 
  
 
 
 
EXECUTIVE SUMMARY 

Rationale for an SME-centred skills development strategy  

The digital revolution is  not only about large tech companies but also essentially about 
start-ups and SMEs that provide or use digital solutions. SMEs are vital to the European 
economy, making up 99% of Europe's businesses1 and accounting for two-thirds of total 
employment. The variety is huge, from innovative and fast-growing companies that provide 
or  use  digital  solutions, to those that face significant challenges such as  acquiring the 
necessary skills to benefit from digital technologies.  

Whereas improving basic digital skills is already a challenge, the emergence of technologies 
such as big data, IoT and cybersecurity is creating significant new specialised skills gaps, 
shortages and mismatches, especially for SMEs, who cannot afford to compete with la rge 
enterprises to  attract and  retain  the  scarce digital  talents. There  are  serious  skills 
shortages at every level in the hierarchy of  SMEs: from  e-Leadership skills to ICT-
professionals to users’ digital skills.  This is  an  issue, as European SMEs run  the  risk  of 
missing out on the huge market potential. German association Bitkom estimates economic 
damage for  German  companies to be around 10-billion-euro of revenues as a result of 
shortage of IT specialists2. Strategies such as up- or  re-skilling  via  offering training to 
employees in SMEs is far from common practice. Less than 10% of SMEs provide training 
to  ICT  specialists and less  than one  in  five  SMEs  offers training  to  other employees. 
Currently, more than 90% of European SMEs consider themselves lagging behind in digital 
innovation.3  

The Commission  has identified IoT, big data and cybersecurity as areas where European 
SMEs  would  benefit from  an  increase in  the  skills  level.  Both  IoT  and  big  data hold 
enormous potential to maximise customer intelligence, optimise internal processes, renew 
business models and develop innovative services and solutions. In times where SMEs are 
increasingly  targeted  by  cyber-attacks,  cybersecurity is  essential  to  ensure  business 
continuity and protect the value chain that SMEs are part of. 

A strategy that enables technology adoption and skills development 

Ambitious skills policies and well-targeted supporting measures are thus needed 
to facilitate the access of SMEs to Europe’s digital talent pool. After thorough stakeholder 
consultation, this initiative brought forward a strategy for supporting SMEs with skills 
development to adopt new technologies such as cybersecurity, big data and internet of 
things (IoT).  

Designing solutions to solve this skills gap at all levels requires an understanding of both 
why and how an organisation adopts technology as business opportunity, and the required 
human capital to deliver on that investment. A study for the European Commission 4 showed 
that digital transformation is enabled by strong IT competences and professionalism at the 
individual  and team level, and digital organisational capabilities at enterprise level. It is 
about investing in building a capability at the organisational level, and consequently finding 

1   Europe an C ommission (2018), Entre preneurship and small and m edium -sized e nterprises (SMEs). Available 

at:  https://ec.europa.eu/growth/smes_nl  

2   https://nos.nl/nieuwsuur/artikel/2315072 -duitsland-past-im m igratie we t-aan-om -honde rdduize nde n-

vacature s-te-kunnen-vullen.html 

3   Europe an C ommission (2018), C apitalising on the  benefits of the  Fourth Industrial R e volution. Available at: 

https://publications.europa.eu/en/publication-detail/-/publication/cf1793da-184c-11e8-ac73-
01aa75ed71a1/language-en/format-PDF/source -66408543  

4   Digital organisational fram eworks and IT Professionalism, by C apgemini Invent with e m pirica and IDC, for 
EC /EASME.  Published he re : https://op.europa.eu/en/publication-detail/-/publication/58563e8f-3e30-11e9-
8d04-01aa75ed71a1/language-en. 

5 

 
 
 
 
                                              
the right people to build competences necessary for that capability. Employees fulfil roles 
associated with those competences, using methods and tools to add specific value. The 
developed  digital  capability  reference  framework  could  help  SMEs  to  better 
understand—when deciding to invest in certain capabilities—what they need in terms of 
competences development and  provides  an  overview of  the relevant frameworks  (and 
related certification) for selection. 

SMEs using technologies tend to perceive cybersecurity as ‘some operational IT function’ 
rather than as a core part of their digital strategy. Other SMEs find it difficult to grasp the 
potential that big  data and  IoT offer to their  business.  For  these SMEs, awareness of 
business opportunities and the translation of this awareness into a  clear business case 
could be a start to their digital transformation journey. This journey could subsequently 
lead them to accurately plan and implement digitalisation measures as well as facilitating 
a  proper  understanding of what concrete skills  are  needed to deliver on  that promise. 
Digital  SMEs might  be more  advanced and already have a clear understanding of which 
skills  they require  and  how these skills  contribute to  the functioning of  their  business 
model.  They still  compete with large  enterprises on  a  tight job  market,  which hinders 
growth. SMEs need a strategy on developing those digital skills in their organisation.  

Joint leadership to strengthen Europe’s digital sovereignty 

To keep  Europe  competitive on a  global  stage, and to  create a  stro ng and  vital  SME 
landscape, there is a clear need for leadership to guide European SMEs in their progressive 
acquisition  of  strategic  digital  skills.  This  endeavour  will  strengthen  Europe’s  digital 
sovereignty and stimulate triple-helix collaboration to achieve better tailoring of education 
and training.  

Such leadership should enable an increased adoption of cybersecurity, big data, and IoT 
by European SMEs via supporting measures that strengthen ecosystems and structurally 
enhance the supply  of  necessary skills  and  facilitate organisational  development. We 
envision  a  “European Skills  for  SMEs Partnership” consisting of  private and  public 
stakeholders to provide the necessary strategic leadership. The aim  of  the  European 
Skills  for SMEs Partnership is to focus on measures, which can be put into action at 
EU  level, while taking into account the wider digital  strategy of the EU.  This way, the 
partnership could go beyond the focus on IoT, Big  Data and Cybersecurity skills that was 
present in this initiative. 

An evidence-based roadmap to deliver the ambition 

The vision is operationalised in a roadmap5 with supporting measures targeting both the 
European as well as national, regional and local levels. This plan builds on good practices 
identified across Europe  (see an  overview of  these in  chapter 5)  and  rests on  three 
evidence-based principles: 

  Industry-led: effective workforce development requires a good understanding of 
the needs of those it addresses: the small- and medium-sized enterprises. Via 
collaboration and participation, intelligence can be gathered on the actual needs of 
the companies to feed into and accelerate policy and education initiatives. A closer 
connection to enterprises and their owners will contribute to increased awareness 
since information and skills on new technologies can also travel along the supply 
chains and via B2B relationships.  

5   The  proje ct de veloped four stre ams to support the  vision of e nhancing SME sk ills in IoT, Big Data and 
C ybe rsecurity: (I) Stre ngthening e cosystems, (II) Strate gic outlook de velopment, (III) Structure d skills 
de ve lopment, (IV) Tailoring  training to  SMEs’  ne e ds. The  m e asures are  de rive d at  diffe rent le ve ls of 
gove rnance and actors: SMEs/business owne rs, e cosystems (including e ducation providers, chambers e tc.) 
vs. re gional & local governments as we ll as national and EU le ve l.   Sk ills4SMEs Partnerships e xtracts those 
m e asures and actions developed as part of the proje ct, which can be applied on the European level. 

6 

 
 
 
 
                                              
  Tailored and innovative education and training: offerings need to be tailored to 

make them useful for SMEs. This requires innovation of current approaches: 
modular, blended courses, targeted at SMEs in their specific sector and geography, 
delivered with flexible timing, with practical content to enable direct action of the 
SME. Since technology adoption is a strategic choice, training should be tuned 
towards the ICT professional in an SME as well as the leadership/management. Co -
creation is another element of this principle. 

  Government (co-)funded and data-driven: upskilling and reskilling  of the 
workforce requires a strong commitment of the public sector to invest in new 
initiatives and to ensure the continuity of existing successful initiatives. Good 
practices have shown that SMEs need to contribute on the operational level (e.g. 
when taking courses, via cost-sharing models), but the overall strategy will require 
substantial public investment. A proper monitoring of how the money spent yields 
results, combined with research to monitor trends in industry needs, should allow to 
efficiently and effectively invest and feed into education and training offerings.  

Figure 1 Visualisation of the roadmap’s main streams of action 

The need to look beyond IoT, Big Data and Cybersecurity 

SMEs encounter skills gaps at every layer of their organisation and are increasingly under 
pressure as they compete with large  companies on a  tense job  market  short of  digital 
talent.  

In  line with the overall rationale to enhance ‘digital sovereignty’6, i.e. to reach a certain 
level of autonomy in ICT related technologies which would allow the EU to independently 
pursue its own interests, there is a need to enhance the uptake of skills that allow SMEs 
to autonomously handle technology. Consequently, this would require the development of 
specialist skills in  the identified areas (cybersecurity, IoT and big data) and beyond (e.g. 
AI, quantum computing, blockchain, critical chip technologies). To develop this capacity in 
a sustainable manner, it is necessary to strengthen monitoring and foresight (see Pillar II 

6   Von de r Le yen does not speak about ‘digital sovereignty’, but used the  te rm “ mastery and ownership of 

key technologies in Europe” in a speech at the European Parliament (27 November 2019),  

Available at: https://ec.europa.eu/commission/presscorner/detail/en/SPEEC H_19_6408  

7 

 
 
 
 
                                              
of the Partnership), and to build EU skills  leadership in areas that are considered vital to 
the economy. 

Figure 2 Skills  gaps related to roles in a SME7 

It seems reasonable to build on areas where Europe already has a competitive advantage 
and  which  would,  at  the  same  time,  advance  the  goal  of  greater  “digital 
autonomy/sovereignty”, e.g. in Open Source software development or distributed ledger 
technologies/blockchain.  Education and training schemes developed to that end need to 
be of high quality (meet conditions for a quality label, see Pillar I) and make sure that they 
do  not only  help  SMEs gain  skills  in  using  certain ICT  tools, but enhance their  digital 
autonomy by increasing ICT specialist skills. 8 The aim is to not just train a wide range of 
SME employees, but to digitise the economy via a highly skilled workforce in SMEs.  

A European Skills for SMEs strategy to focus on growth 

At the same time, policymakers need to be aware that measures need to be tailored to the 
different types of SMEs, which can be roughly categorised according to maturity and size. 
Maturity  (as  displayed  in  figure  below):  frontrunners  and  developers ,  appliers  and 
followers, non-innovators (in terms of maturity). Regarding size it is important to distinct 
between micro SMEs (up to 10 employees), small enterprises (up to 50 employees), and 
medium-sized  companies  (50-250  employees)9. While  it  will  be  pivotal  for  nearly  all 
businesses to digitise in the short to medium term (at least to a certain degree), an EU-
driven  strategy needs to focus on  those aforementioned SMEs, where it  will  be  most 
beneficial, effective, and have the greatest impact on driving competitiveness and growth. 
It  should  also  contribute to  the  development of  EU  technological/digital sovereignty. 
Therefore, the European Skills  for  SMEs Partnership should  focus on those SMEs in  all 
sectors,  not  only  the  ICT  sector,  that  have  a  propensity   to  grow,  to  digitise  and 
internationalise their business to make use of the EU internal market. The main targets are 
thus “followers & appliers” and “frontrunner & developer” SMEs. 

7  The  EU lack s around 1 m illion IC T spe cialists and this figure could grow to 2 m illion by 2030. Source: DG 

C O NNEC T, VICTORY (Vacancies for ICT- Online R epository: Data C ollection) 

8   In ge neral, digital skills e ncompass a range of basic to highly advanced skills that e nable th e  use of digital 
te chnologies (digital knowle dge) on the one hand, and basic cognitive, emotional or social skills necessary for 
the  use  of digital te chnologies on the other hand. In its background re port on skills for a digital world, the  
O rganisation for Economic Cooperation and Development (OECD) distinguishes four types of ICT-re lated skills 
ne ce ssary 
See: 
http://www.e uroparl.europ a.eu/RegData/etudes/IDAN/2017/595889/EPRS_IDA(2017)595889_EN.pdf  

work place. 

the  

at 

9   Se e : https://ec.europa.eu/growth/smes/business -friendly-environment/sme-definition_en 

8 

 
 
 
 
 
 
                                              
Figure  3  Segmentation of SMEs  based on  maturity in  the uptake of  big  data, IoT and 
cybersecurity 

The European Skills for SMEs (Skills4SMEs) Partnership 

This proposal sets out the different recommended actions of the Skills4SMEs Partnership 
by grouping them into four pillars. The actions build on the principles set out above, i.e. 
the Partnership needs to be industry-led, data-driven and provide a  knowledge-sharing 
platform on how to develop tailored, innovative education and training to SMEs.  

Figure 4 Skills4SMEs Partnership 

Skills4SMEs 
Partnership 
Consisting of key partners in the ecosystem:  Industry (SMEs and large companies), intermediaries (clusters, sectoral 
associations, chambers of commerce,  accountants, insurances, etc), education providers, public administrations (cities, regions, 
etc.) 

Training  and education 
platform

Gather intelligence and 
develop foresight

Strengthen ecosystem 
leadership

Support EU digital sovereignty

• Grow a business support and 
advice funtion to strenghten 
single point of access: e.g. 
tools that clarify the business 
case to illustrate ROI of skills 
investment, practical 
frameworks and tools that 
support SMEs to build a smart 
(HR) strategy; self-
assessments; funding 
information

• Develop quality labels for 

training schemes

• Procure strategic courses & 
develop sectoral schemes

• Enable scaling and 

Internationalisation of 
training programmes

• Develop concepts to support 
mobility of scarce expertise

• Monitor skills development & 
forecast skills needs/supply

• Reserch & promote data-

driven approaches in SME 
support programmes

• Research the motives of SMES 

to participate in training

• Activate ecosystem 

leadership to promote 
strategies and best practices 

• Develop & coordinate SME 
training & business support 
accounts

• Mapping of ecosystems: 

research capacities and state 
of play

• Provide funding to ecosystem 

and SME community to 
provide local support to SMEs 
and finance expert exchanges
• Develop common criteria of 
best practices to develop 
blueprints of successful 
private/public collaboration 
that can be scaled up in other 
countries/regions

• Source talent and bring 

together 
SMEs/industry/education for 
support of SME strategic 
projects (e.g. European Cloud)

• Support matchmaking 

between SMEs to pool talent 
for creation of innovative 
services

• Further open-source-based 

technologies and skills
• Continue to invest in 

infrastructure that enables 
technology adoption

• Invest in facilities to support 

training programmes

We  propose  to  develop  a  European Skills4SMEs  Partnership  that  is  dedicated to 
building  a stronger alliance between the public and the private sector to offer leadership 
and  a  vision  for  skills  development  for  SMEs  in  Europe.  The  Partnership  should  be 
accompanied with dedicated investments that enable a long-term, strategic approach 
and reduce uncertainties by allowing for long-term commitments. 

The platform should drive and coordinate the following pivotal measures aimed at achieving 
the projected vision in the period up to 2030: 

1.  Training & education platform. This platform will be the single access point to 
information about SME skills development at EU level. It targets the intermediaries 

9 

 
 
 
 
 
 
 
 
that are engaged to support SMEs directly. The platform will provide and promote 
quality labels on selected training schemes and give SMEs and individuals throughout 
Europe access to those courses. The platform also needs to develop a  proactive 
business support function where intermediaries can find tools, practical frameworks, 
assessments, funding schemes etc. that they can bring to their local SME 
communities—and which will also be promoted across Europe by a dissemination 
campaign. It will support the scaling and internationalisation of selected courses by 
providing translations and promoting them on a European level.  

  Enable scaling up of successful training programmes, from basic translation to 
providing methods or blueprints for developing successful training programmes 

  Grow a business support and advice function on the platform: e.g. offer tools that 
clarify the business case to illustrate ROI of skills investment, publish (links to) 
practical frameworks and tools that support SMEs to build a smart (HR) strategy; 
offer self-assessments for SMEs in specific technology domains; provide 
information on funding for trainings. It should be accessible for and 
promoted/pushed towards intermediaries 

  Develop quality labels of European training schemes based on quality criteria and 
standards (e.g. e-CF) and mapping according to strategic skills priorities from 
Pillar II “Intelligence” to increase transparency and trust as well as overall quality  

  Develop concepts and practical examples to support the mobility of scarce 
expertise (within education & training systems and between industry and 
education & training systems) 

  Procure strategic courses and/or develop sectoral schemes that can benefit SMEs 

across Europe; ideally courses or schemes tailored to the needs of a specific 
sector (building on the Blueprint projects) or technology 

2.  Intelligence & monitoring. This task of the partnership aims to gather insights that 
establish a coherent, clear picture of the needs of SMEs and the supply of training 
and skills on the market. It should apply the methodology to forecast future 
developments around supply and demand of skills for SMEs. It should also take stock 
and research data-driven approaches at the national level to increase insights into 
demand/supply at aggregated level. 

  Monitor SMEs’ skills development and develop foresight on skills needs and supply  

  Promote data-driven approaches in SME support programmes 

  Research the motives of SMEs to participate in training  

3.  Ecosystem10 leadership. Measures consisting of strengthening and facilitating the 
ecosystem and aimed at involving all relevant stakeholders in the partnership. This 
would include developing a joint approach with triple helix actors (policy, education, 
and industry associations) but also with accountants and insurance providers. It 
would require building strong partnerships at the European and national level. 
Develop SME training & business support accounts in collaboration with national 
administrations and the ecosystem, considering the national contexts.  

10   The   e cosystem  (consisting  of  cluste rs,  associations  or  cham bers  and  the   supply  chain  and  business 
e nvironment of SMEs) needs to be aware  of skills needs – they are the intermediaries that can raise awareness 
am ong SMEs or develop collective action to bridge a skills gap, e .g. by offering VET training in collaboration 
with SMEs or by e stablishing stronger partnerships with universities or re search communities, or by designing 
training programmes according to SMEs’ needs. At the same time, they need to work towards developing the 
capacity for strategic outlook in SMEs. SMEs need to be aware  of their skill s needs and develop strategies to 
fulfil them. These insights and actual training schemes need to be developed at the local le vel – the EU level 
will only be  responsible for sharing best practices and developing “blueprints” based on successful cases. 

10 

 
 
                                              
  Activate ecosystem leadership to promote strategies and best practices to raise 
awareness of SMEs for technology adoption, e.g. via their B2B  environment and 
supply chains 

  Research the potential of SME training & business support schemes that would 

allow SMEs to invest in training 

  Mapping of ecosystems: research capacities and state of play, and connect to 

parallel initiatives at EU level to create synergies 

  Provide funding to ecosystem and SME community to provide local support to 

SMEs and finance expert exchanges 

  Develop common criteria of best practices to develop blueprints of successful 

private/public collaboration that can be scaled up in other countries/regions  

4.  Support EU Digital Sovereignty. Build on ICT industry frontrunners to strengthen 
SME skills and develop leadership in strategic areas by bringing together larger 
companies, SMEs, and research and education. Based on the strategic priorities at 
Pillar II (“Intelligence”), stimulate the collaboration of innovative SMEs with industry 
and academia to engage in consortia for innovation projects. Build on the strong open 
source community to further skills in developing an ecosystem of non-proprietary 
software and related skills. 

  Source talent and bring together SMEs/industry/education to support strategic 

projects (e.g. European Cloud, blockchain, AI, open source software) 

  Support matchmaking between SMEs to pool talent for the creation of innovative 

services11 

  Promote open source-based technologies and skills 

  Continue to invest in infrastructure that enables technology adoption 

 

Invest in facilities to support training programmes 

Required investments at national and EU level 

The actions at EU level refer to initiating and intensifying collaboration, knowledge sharing, 
and providing tools at EU level that support the creation of a common European language 
and  will  require  funding  to  initiate  this  development.  The  countries,  and  various 
stakeholders in those countries, can benefit from the actions deployed here. However, they 
will have to deploy their own national and/or regional skills strategies, and especially start 
to plan  for investing in  skills  development schemes that are pivotal to support SMEs in 
their digital transformation. This requires a long-term and dedicated investment.  

An essential element in advancing skills development in SMEs is the scaling of existing 
good practices in learning programmes. A recent study12 for the European Commission 
analysed  the  funding  models  of  education  and  training  programmes  targeting  the  
workforce at national and EU level to understand how successful initiatives can be scaled 
up  to  increase impact.  Practices that  have  proven  their  value  and  address a  strong 
stakeholder demand  need  –  deserve! –  scaling to  increase impact. The  study comes 
forward with recommendations in five areas: vision & long-term strategy, scalable multi-
stage funding intervention, massive investments & new ways of funding, means to guide 
future policy development, and high-tech skills hubs to connect key actors.   

11   Se e  ICT Competence C enter initiative in Berlin 

12   High-tech skills for Europe – Scaling-up best practices and re -focusing funding programmes and incentives, 

for the  EC /EASME, available via http://skills4industry.eu . 

11 

 
 
 
                                              
Investments  needed  in  skills  strategies  are  indeed  massive   but  essential  to 
advance. To give an order  of magnitude of what is needed: according to Eurostat, only 
32%  of European SMEs had a formally  defined ICT security policy in place. This means 
approximately 17 million  SMEs did not and will have to acquire these skills by investing in 
training courses to develop that knowledge in-house or hire it externally. In similar fashion, 
statistics reveal that only 12% of SMEs were using some type of big data sourc e, compared 
to 33% of large enterprises. Closing that gap would require to reach at least five million 
SMEs. From good practices, it becomes apparent that co-funding or cost-sharing models 
are most effective. Good practices across Europe reveal current lev els of investments – at 
different government levels:  

  Skillnet Ireland runs a budget of €35.9 million  for 2020, with the total investment 

in upskilling by Skillnet Ireland likely to exceed €60 million  when employers’ 
contributions are added.13 Skillnet Ireland works in partnership with 50 industry 
bodies and enterprise clusters, providing training and innovation support to over 
16.000 businesses, and they upskill 56.000 workers throughout the country every 
year. 

  The German Federal Ministry for Economic Affairs and Energy14 (BMWi) 

launched a funding programme  called ‘Go-Digital’ of €7.2 million  (in 2 phases) which 
enables nearly 700 projects. The subsidy voucher system that activates skills 
development in SMEs via external consultants has been successful and revealed an 
appetite for further expansion of this scheme. 

  The JADS SME Data-lab15 is an excellent local example from Den Bosch (NL), which 
helps SMEs to create value with data. Over 100 SMEs entered the lab to come out 
with a proof-of-concept or tailor-made solution that helped them reduce costs or 
increase revenues. There is a standard fee of €2500 and half of the money goes to 
the data science students that JADS staffs on these projects. 

However, more  dedicated funding schemes for  skills  development in  SMEs are  needed 
across Europe to increase technology adoption and close current skills shortages in SMEs. 
Part of this could come from EU funding, but most of this amount will be an investment by 
national, regional and  local entities aiming  to boost competitiveness of SMEs and  drive 
their economies forward. 

Further investments would be needed at EU level to secure the development of the 
proposed  Skills4SMEs  platform  and  partnership, including  the  proposed  measures  to 
develop quality labels, concepts for  sc aling good practice of learning  programmes  and 
funding models, to monitor SMEs’ skills development and develop foresight on skills needs 
and supply, to activate ecosystem leadership, and to support matchmaking between SMEs 
to pool talent for creation of innovative services.  

The ‘blueprint for sectoral cooperation on skills’16 is one of the key initiatives of the skills 
agenda for Europe, investing €28 million  of funding in 201817 and launching new sectors 
yearly. Recently, a new chapter was launched that addresses the cybersecurity, software 
and blockchain sector, among others. 

Another initiative to start in 2020 is the European Digital Academy. The overall objective 
of  the  European  Digital  Academy is  to  contribute to  the  development, reskilling  and 
upskilling  of European citizens and SMEs on some of the key emerging technologies (AI, 

13   https://www.sk illnetireland.ie/we lcomes-increase-in-funding-budget-2020/  

14   https://www.bm wi.de /Redaktion/DE/Pressemitteilungen/2019/20190429-mit-einem-klick -zur-passe nde n-

digitalisierungs-beratung-startschuss-go-digital.html 

15   https://jadsmkbdatalab.nl/about-us/  

16   https://ec.europa.eu/social/main.jsp?catId=1415&langId=en 

17   https://eacea.ec.europa.eu/erasmus-plus/actions/key-action-2-cooperation-for-innovation-and-e x change -

good-practices/sector-skills-alliance s_en 

12 

 
 
                                              
Blockchain, robotics, cybersecurity, IoT). It will  be done by  developing a  new platform 
closely connected to the European Portal for Digital Skills and Jobs. The platform will ma p 
the online learning opportunities from different providers in an easy-to-access manner. In 
addition, modern and highly engaging online training modules will be developed based on 
the needs identified by the project.  

Further investments would be needed at the national level (including regions and 
cities) to invest in skills development for all relevant digital areas (not only cybersecurity), 
to push for change in education and training systems to become more  adaptive to new 
demands, and to mobilise  expert ise with relevant intermediaries in regions and cities to 
increase  engagement  of  SMEs  in  digital  transformation  and  corresponding  skilling 
activities. 

13 

 
 
 
PART I: THE STATE OF PLAY 

14 

 
 
 
 
 
 
 
 
 
 
 
1.  INTRODUCTION 

This final report has been prepared for the European Commission as part of the service 
contract EASME/COSME/2017/007 on Supporting Specialised Skills Development: Big 
Data, Internet of Things and Cybersecurity for small and medium-sized enterprises 
(SMEs).  

1.1.  Rationale 

Businesses all over the world are going through a new wave of disruptive technological 
change. This digital revolution is powered by digital technologies characterised by very 
fast innovation, high-growth rates and substantial market potential. This digital 
revolution is not only about large tech companies but essentially about start-ups and 
SMEs that provide or use digital solutions. SMEs are vital to the European economy, 
making  up 99% of Europe's businesses18. The variety is huge, from innovat ive and fast-
growing companies that provide or use digital solutions, to those that face significant 
challenges such as acquiring the necessary skills to benefit from digital technologies.  

To fully leverage the potential of the digital revolution to the advantage of European 
businesses and citizens and to address the challenges that come with it, the European 
Commission adopted the Digital Single Market Strategy19 and a Communication on 
"Digitising European Industry: Reaping the full benefits of a Digital  Single Market"20. The 
latter Communication introduces a set of coherent policy measures and aims to establish 
a framework for coordination between national and EU-level initiatives and relevant 
policy actions including investments in digital innovations and infrastructure, accelerating 
the development of ICT standards, exploring regulatory conditions and adaptation of the 
workforce, including up-skilling the (future) workforce.  

This is important, as unlocking the potential that comes with the digital revolution is not 
always straightforward. The potential benefits of realising the DSM for the EU economy 
are estimated at almost 415 billion EUR per year, creating hundreds of thousands of new 
jobs21. At the same time, several factors hinder European enterprises to unlock this 
potential. An important factor here is skills, as the need for new multidisciplinary and 
digital skills is exploding22. 90% of all jobs23 are expected to require some kind of digital 
competence in the near future, and at the same time 37%24 of the EU labour force has 
an insufficient level of digital skills. This is an issue, as Europe underperforms on its 

18 Europe an C ommission (2018), Entrepreneurship and Small and medium-sized e nterprises (SMEs). Available 

at:  https://ec.europa.eu/growth/smes_nl  

19 Europe an C ommission (n.d.), Digital Single Market: Bringing down barrie rs to unlock online opportunities. 

Available at: https://ec.europa.eu/commission/priorities/digital-single-market_en  

20 Europe an C ommission (2016), C ommunication: Digitising European Industry - R eaping the full benefits of a 

Digital Single Mark et. Published April. Available at: https://ec.europa.eu/digital-single-
m ark et/en/news/communication-digitising-european-industry-reaping-full-benefits-digital-single-market  

21Europe an Commission (n.d.), Digital Single Market: Bringing down barriers to unlock online opportunities. 

Available at:  https://ec.europa.eu/commission/priorities/digital-single-market_en  

22 Europe an C ommission (2016), C ommunication: Digitising European Industry - R eaping the full benefits of a 

Digital Single Mark et. Published April. Available at: https://ec.europa.eu/digital-single-
m ark et/en/news/communication-digitising-european-industry-reaping-full-benefits-digital-single-market 

23 Europe an C ommission (2017). Ne w re port shows digital skills are re quired in all types of jobs. Published May. 

Available at: https://ec.europa.eu/digital-single-market/en/news/new-re port-shows-digital-skills-are-
re quire d-all-types-jobs  

24 Europe an C ommission (2017), Human capital: digital inclusion and skills. Available at: 

http://ec.europa.eu/newsroom/document.cfm?doc_id=44390   

15 

 
 
                                              
digital potential relative to the United States. The European digital frontier, represented 
by the ICT sector and its digitisation of assets, uses, and labour, is only 60% as digitised 
as the US frontier25. 

The European Commission, EU Member States and stakeholders have been active in 
addressing the digital skills gap for several years. For instance, already in 2007, a 
Communication was adopted on "e-Skills for the 21st Century: Fostering 
Competitiveness, Growth and Jobs26. The latest major EU action to address the skills gap 
is focussing the Skills Agenda for Europe, adopted by the European Commission in 2016. 
The agenda recognises the need for EU citizens to receive opportunities to develop 
transversal skills. Skills acquisition and development are recognised as essential to 
increase the performance of national and international labour markets. The agenda in 
particular demonstrates a need for a unified approach in combating the widening skills 
gap. While it is true that national labour markets as well as education and training 
systems are tackling country-specific issues, at the same time the EU Member States 
face similar problems. Precisely these similarities should act as a unifying factor when 
producing and promoting common means to answer the growing demand for a highly 
skilled workforce. Several measures support the implementation of the Agenda, including 
a Blueprint for Sectoral Cooperation on Skills27 and the Digital Skills and Jobs Coalition28.  

Whereas improving basic digital skills is already a challenge, the emergence of 
technologies such as big data, IoT and cybersecurity is creating significant new 
specialised skills gaps, shortages and mismatches, especially for SMEs, who cannot afford 
to compete with large enterprises to attract and retain the scarce digital talents. This is 
an issue, as European SMEs run the risk to miss the huge market potential. Currently, 
already more than 90% of European SMEs consider themselves lagging behind in digital 
innovation29.  

25 Bughin, J., Hazan, E., Labaye, E., Manyika, J., Dahlström, P., R amaswamy, S., & C ochin de Billy, C. (2016), 

Digital Europe: R ealising the continent’s potential. Published June. Available at: 
https://www.m ck insey.com/business-functions/digital-mckinsey/our-insights/digital-europe-re alizing-the-
contine nts-potential  

26 Joinup (2007), EU: e -skills for the 21st ce ntury: fostering competitiveness, growth and jobs. Published 

Nove m ber. Available at: https://joinup.ec.europa.eu/document/eu-e-skills-21st-century-fostering-
com petitiveness-growth-and-jobs  

27 Europe an C ommission (2017), Blueprint for sectoral cooperation on skills: R esponding to skills mismatches at 

se ctoral le vel. Available at: http://ec.europa.eu/social/BlobServlet?docId=16962&langId=en 

28 Europe an C ommission (2014), The Digital Skills and Jobs Coalition. Published October. Available at: 

https://ec.europa.eu/digital-single-market/en/digital-skills-jobs-coalition  

29 Europe an C ommission (2018), C apitalising on the benefits of the 4 th Industrial R evolution. Available at: 

https://publications.europa.eu/en/publication-detail/-/publication/cf1793da-184c-11e8-ac73-
01aa75ed71a1/language-en/format-PDF/source -66408543  

16 

 
 
                                              
Figure 5 Skills  gaps across  roles  in an enterprise 

Ambitious skills policies and well-targeted supporting measures are thus needed to 
facilitate the access of SMEs to Europe’s digital talent pool. The present initiative 
researches, identifies, designs, tests and validates such specific measures for support ing 
specialised skills development related to big data, Internet of Things (IoT) and 
cybersecurity – hereafter referred to as BIC technologies - for SMEs in Europe.  

This report is part of a service contract EASME/COSME 2017/007, which is based on the 
Regulation (EU) No 1287/2013 of the European Parliament and of the Council of 11 
December 2013 establishing a Programme for the Competitiveness of the Enterprises and 
small and medium-sized enterprises (hereafter "COSME") (2014-2020) and repealing 
Decision No. 1639/2006/EC. More particularly, it is based on the Commission 
Implementing Decision concerning the adoption of the Work Programme for 2016 and the 
financing for the implementation of Programme  for the Competitiveness of Enterprises 
and Small and Medium-sized Enterprises (C (2016) 63 final of 18/1/2016) and its Annex. 
It is foreseen under item "GRO/SME/16/C/12 - New skills for the digital transformation of 
enterprises, manufacturing and key enabling technologies" of the COSME 2016 Work 
Programme.  

1.2.  Objectives 

The main objective of this new initiative was to research, design, test and validate 
specific measures supporting specialised skills development related to big data, Internet 
of Things (IoT) and cybersecurity for SMEs in Europe. The results of the init iative 
contribute to strengthening SMEs' workforce adaptability and capacity for the short to 
medium  term. 

The ultimate goal is to increase the capacity of industry, social partners, education and 
training organisations and policy makers at all levels to promote and support the 
acquisition of these skills by SMEs in Europe. 

The work is based on a demand-led, pragmatic and results-oriented approach with a view 
to proposing concrete measures. Concrete results of this initiative include, inter alia:  

  A shared vision for skills development for SMEs on BIC technologies for the 

coming years until 2023;  

  A roadmap consisting of supporting measures to achieve that vision, and a 

toolbox facilitating the implementation; 

  A monitoring mechanism to monitor skills gaps and to track progress of the 

implementation in the coming years until 2023.  

17 

 
 
 
 
 
The figure below summarises these three elements and shows how the vision, the 
implementation of the vision and a monitoring mechanism for tracking the realisation of 
the vision fit together.  

Figure 6 Holistic  perspective on the activities  under  this initiative 

The activities are performed with a view to supporting the goals set out in the New Skills 
Agenda for Europe, and the activities build on previous and on-going activities supported 
by the European Commission, such as the New Skills Agenda for Europe 30, the Blueprint 
initiatives on Sectoral Cooperation for Skills and other related initiatives. It is input for 
the new SME strategy the European Commission is working on 

1.3.  Scope 

This initiative focused on supporting specialised skills development related to BIC 
technologies for small and medium-sized enterprises (SMEs) in Europe. Hence, this 
initiative focuses on a group of enterprises that the European Commission defines as 
following: an enterprise is classified as being an SME if it does not have more than 249 
employees and if its annual turnover does not exceed 50 million  EUR or its balance sheet 
total is less than 43 million  EUR31.  

From a geographical perspective, this initiative focused mainly on the EU Member States. 
However, good practices from other regions are also taken into account and used for 
creating the roadmap and toolbox.  

For this service contract, three major technological areas have been selected: big data, 
Internet of Things (IoT), and cybersecurity (BIC technologies). They have been identified 

30 Europe an C ommission (n.d.), Ne w Sk ills Agenda for Europe. Available at: 

http://ec.europa.eu/social/main.jsp?catId=1223   

31 Europe an C ommission (2003), C ommission re commendation concerning the definition of micro, small and 

m e dium-sized enterprises. Published May. Available at: http://eur-lex.europa.eu/legal-
conte nt/EN/TXT/?uri=CELEX:32003H0361&locale=en  

18 

 
 
 
 
 
                                              
as priority areas in the context of the Digital Single Market strategy32 and are very 
closely interrelated. Multiple definitions are being used in the available literature for the 
three technologies. Sticking as close as possible to definitions used in related European 
initiatives, this initiative defines the technologies as following: 

  Big data: “Big data refers to large amounts of data produced very quickly by a 

high number of diverse sources. Data can either be created by people or 
generated by machines, such as sensors gathering climate information, satellite 
imagery, digital pictures and videos, purchase transaction records, GPS signals, 
etc.”33 

  The Internet of Things: "The Internet of Things enables objects sharing 

information with other objects/members in the network, recognising 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”34 

  Cybersecurity: “Cybersecurity shall refer to security of cyberspace, where 

cyberspace itself refers to the set of links and relationships between objects that 
are accessible through a generalised telecommunications network, and to the set 
of objects themselves where they present interfaces allowing their remote control, 
remote access to data, or their participation in control actions within that 
cyberspace”35 

1.4.  Approach 

A thorough approach was adopted to implement this service contract. This initiative was 
structured in three phases: 

Figure 1-3  

32 Europe an C ommission (2015), Shaping the Digital Single Market. Published March. Available at: 

https://ec.europa.eu/digital-single-market/en/policies/shaping-digital-single-market  

33 Europe an C ommission (2018), Big Data. Available at: https://ec.europa.eu/digital-single-mark et/en/big-data  

34 Europe an Commission (2014), Definition of a Research and Innovation Policy Leveraging Cloud Computing 

and IoT Combination. Available at: http://ec.europa.eu/newsroom/dae/document.cfm?doc_id=9472  

35 ENISA (2016), Definition of Cybersecurity - Gaps and overlaps in standardisation. Available at:  

https://www.e nisa.europa.eu/publications/definition -of-cybersecurity  

19 

 
 
 
 
 
                                              
It built upon seven methods to collect data and insights to analyse the current state of 
play and to shape the way forward with regards to supporting specialised skills 
development for SMEs:  

(1)  Desk research – extensive literature and web source review aimed at detecting 

the most important policy papers, studies, strategies, reports, databases and 
training initiatives to analyse the current state of play with regards to skills 
development for SMEs.  

(2)  Steering Committee and informal group – a Steering Committee was installed 

at the start of the initiative. The steering committee consists of five independent 
experts renowned in the field, representing different stakeholder groups. They 
were asked to review the draft interim and final reports and provide written 
comments. The informal group represents the most relevant Key Stakeholders 
and consisted of 100 experts at the start and grew towards 250 over the course of 
the project.  

(3) 

Interviews – over 80 interviews were conducted with stakeholders stemming 
from different backgrounds to better understand the state of play and to collect 
input for the way forward: academia, national and regional policy makers, SME 
manager/owners, educational institutions, network/cluster representatives, 
chambers of commerce, associations and independent experts. The interviews 
were conducted in 2018 and 201936. 

(4)  Surveys – a comprehensive online questionnaire was developed to obtain 

quantitative insights in SMEs skills needs, barriers and strategies, as well as 
gaining input on supporting measures for fostering skills development. The survey 
targeted both SMEs and SME experts, and was run twice. In 2019, a consultation 
survey was conducted with the aim to review the vision and roadmap with 
supporting measures. 

(5)  Workshops – six expert workshops37 were conducted in 2018 and 2019. During 
these workshops, initial findings were validated, input was collected for a shared 
vision on supporting specialised skills development for SMEs and proposals of 
deliverables were discussed and improved. Members of the informal group and the 
Steering Committee participated in the workshops, representing different roles, 
expertise and countries within the European SME ecosystem. 

(6)  High-level conference38 - the conference marked the final stage of this initiative 

to analyse and support SMEs’ skills development, especially in the fields of Big 
Data, Internet of Things and Cybersecurity. It brought together around 150 
participants who engaged in discussions with the experts that composed various 
panels covering the most essential themes of this initiative. 

(7)  Alignment with other relevant initiatives – To avoid reinventing the wheel and to 
learn from other but related initiatives, synergies were sought in order to leverage 
value. Most notably alignment with (but not limited to) initiatives such as the 
Blueprint initiatives for Sectoral Cooperation on Skills39, the Digital Skills and Jobs 

36 Ple ase see annex A for an overview of interviewe es 

37 All work shop reports, agenda and participants’ overview, and presentations are published here: 

https://www.digitalsme.eu/skills_publications/ 

38 Se e  for a coverage: https://www.digitalsme.eu/we -need-europe-for-a-comprehensive-upskilling-strategy-

the -skills-for-smes-conference/  

39 Europe an C ommission (2017), Blueprint for sectoral cooperation on skills: R esponding to skills mismatches at 

se ctoral le vel. Available at: http://ec.europa.eu/social/BlobServlet?docId=16962&langId=en   

20 

 
 
                                              
Coalitions and the European Commission Pilot Project on digital skills: New 
Professions, New Educational Methods, New Jobs 40. 

1.5.  Structure of this document 

This report groups the results into three main clusters. Part I describes the current state 
of play, and in addition to the present introduction it includes the following chapters:  

  Chapter 2 describes the relevance of BIC technologies for SMEs, including among 
others adoption of these technologies by SMEs and barriers and drivers for taking 
up these technologies; 

  Chapter 3 presents skills requirements for adopting BIC technologies;    

  Chapter 4 zooms in on the skills strategies SMEs possess to acquire or develop the 

skills necessary to work with the three technologies; 

  Chapter 5 highlights key public and private initiatives in the area of SME skills 

development in the area of BIC technologies. 

After having described the current state of play in Part I, Part II can be characterised as 
forward-looking: 

  Chapter 6 presents the five-year strategy on skills development for SMEs, 

describing the vision, and roadmap with supporting measures; 

  Chapter 7 describes the toolbox. 

Finally, Part III focuses on monitoring the state of play with regards to skills 
development: 

  Chapter 8 presents a monitoring framework for monitoring supply and demand of 

skills necessary for SMEs to work with BIC technologies.   

40 Europe an C ommission (2018), Upskilling Europe's small businesses for the digital age. Available at: 
https://ec.europa.eu/digital-single-market/en/news/upskilling-europes-small-businesses-digital-age  

21 

 
 
 
 
                                              
2.  THE RELEVANCE OF BIG DATA, INTERNET OF THINGS AND CYBERSECURITY FOR 

SMES 

By completing the Digital Single Market, the EU could boost its economy by almost 415 
billion EUR  per year and create hundreds of thousands of new jobs 41. New digital 
technologies play an important role in realising this potential. Within the context of this 
service contract, three technological areas have been selected: big data, IoT and 
cybersecurity. These areas are interrelated, as IoT devices for instance need to be secure 
as they are often connected over the Internet, and at the same time generate a wealth of 
data. The emergence of these technologies brings significant opportunities, but at the 
same time creates significant specialised skills gaps, especially for SMEs.  

This chapter firstly provides some background about the emergence of the three 
technologies and related market developments (2.1), and then zooms in on the relevance 
of these technologies for SMEs (2.2). Section 2.3 presents how current technological 
trends impact the take-up of BIC technologies by SMEs, and section 2.4 describes the 
current state of play: to what extent are SMEs nowadays using these technologies? 
Section 2.5 concludes with an overview of barriers and drivers for the adoption of the 
emerging technologies by SMEs.  

2.1.  The  emergence  of  big  data,  Internet  of  Things  and 

cybersecurity  

2.1.1.  Big data 

More and more volumes of data are produced, stored and published every day, every 
hour, every minute, and every second. In every domain, across every geography. With 
the emergence of IoT, the amount of data across the world is expected to increase 
further exponentially, with new market players, large operators and smaller niche actors. 
We have all seen the colourful infographics picturing the number of petabytes of data 
created over the Internet each second (figure 2-1). 

Figure 7 A  global explosion of data42 

41 Europe an C ommission (n.d.), Digital single market: Bringing down barriers to unlock online opportunities. 

Available at: https://ec.europa.eu/commission/priorities/digital-single-market_en  

42 Europe an C ommission (2017), Enter the data economy: EU policies for a thriving data e cosystem. Published 
January. Available at: https://ec.europa.eu/epsc/sites/epsc/files/strategic_note_issue_21.pdf , based on the 
Inte rnational Data C orporation Digital University Study 

22 

 
 
 
 
                                              
Data holds an enormous potential in various fields, such as health, food security, climate 
and resource efficiency to energy, intelligent transport systems and smart cities – and is 
considered “an essential resource for economic growth, job creation and societal 
progress”43 by the European Commission.  

Numerous studies have assessed the size of the potential prize. The data economy was 
valued at 272 billion EUR in 2015, with an expected growth of 5.6% per year to reach 
739 billion  EUR by 202044. At the same time, the European Data Portal published a study 
assessing the overall direct value of open data (i.e., data that can be freely used, 
modified, and shared by anyone, for any purpose) for the EU 28+ to be of 75.7 billion 
EUR by 202045. Some numbers may overlap slightly, but whatever it is that is measured, 
the numbers are substantial and will continue to grow.  

The 2017 European Data Market study46 showed that the data economy is already a 
reality today. Approximately 6.1 million  EU citizens could be considered ‘data workers’ in 
2016, and this number grows with around 2 to 3% per year, faster than average, 
potentially rising up to 10.4 million  by 2020. Furthermore, these are not merely ICT jobs 
as might be expected: the ICT industry accounts for only around 11% of data workers, 
as opposed to professional services (20%), wholesale and retail (18%), and 
manufacturing (12%). The distribution of these jobs shows that the economy is 
increasingly becoming data-driven, including in sectors that are more traditional.  

Figure 8 Key figures  illustrating  the European  Data Market47 

In 2016, the European data industry comprised almost 255,000 companies with a share 
of 14.1% of the 1.8 million  enterprises populating the ICT and professional services 

43 Europe an C ommission (2017), Building a European data economy. Published January. Available at: 

https://ec.europa.eu/digital-single-market/en/policies/building -european-data-economy  

44 IDC  (2017), European Data Market Study Final R eport SMART 2013/0063 . R eport prepared for the European 

C om mission. Available at: https://www.k e y4biz.it/wp -content/uploads/2018/04/SMART20130063_Final-
R e port_030417_2.pdf  

45 C apgemini C onsulting (2015), Creating value through open data. R eport prepared for the European 

C om mission. Available at: 
https://www.e urop eandataportal.eu/sites/default/files/edp_creating_value_through_open_data_0.pdf   

46 IDC  (2017), European Data Market Study Final R eport SMART 2013/0063. R eport prepared for the European 

C om mission. Available at: https://www.k e y4biz.it/wp -content/uploads/2018/04/SMART20130063_Final-
R e port_030417_2.pdf  

47 IDC  (2017), European Data Market Study Final R eport SMART 2013/0063. R eport prepared for the European 

C om mission. Available at: https://www.k e y4biz.it/wp-content/uploads/2018/04/SMART20130063_Final-
R e port_030417_2.pdf  

23 

 
 
 
 
                                              
sectors. Growth in these numbers is constant in the period 2013-2016, and occurs across 
the EU, albeit more strongly in countries with a more highly concentrated ICT industry. 
Nonetheless, there is a margin  for improvement: only 661,000 enterprises in 2016, 
corresponding to 6.4% of the 10.3 million  potential user companies (excluding the 
government sector) can be characterised as data-driven users. This is relatively modest 
and shows that significant gains are still possible. Under high growth scenarios, an 
increase to around 359,000 companies by 2020 should be viable. 

Many companies have understood the potential benefits of implementing data-driven 
decision making and are investing rapidly in big data technologies and services. The 
global market for big data-related hardware, software and professional services is 
growing rapidly and is expect ed to reach 43.7 billion euros by 201948. However, not all 
companies have equal opportunities to reap the benefits of the emerging data market. 
Access to data and the ability to exploit the value are key. With limited access to data 
and data analytics, European companies will not be able to compete in global markets 
and SMEs and emerging companies are the ones set to lose the most 49. What is worrying 
in this regard is that especially in Europe, too few companies are embracing digitisation: 
in 2015, only one in five European companies displayed a high or very high digital 
intensity50, while only 6% of ICT and professional services companies were making 
strategic and intense use of data51.  

Equipping European SMEs with the means and tools to mine, process, store a nd analyse 
big data and generate value from it “is a means of securing future wealth and 
prosperity”52. In this regard, it is encouraging that the importance of the data economy is 
recognised on a European level, with the EU developing its vision for the da ta economy 
already more than a decade ago. In 2003, the EU for instance adopted legislation to 
foster the re-use of Public Data in Member States via the Public Sector Information (PSI) 
Directive 2003/98/EC53. Today, building a European data economy is a crucial part of the 
Digital Single Market strategy. The data economy initiative aims at fostering the best 
possible use of the potential of digital data to benefit the economy and society. It 
addresses the barriers that impede the free flow of data to achieve  a European Digital 
Single Market 54.  

48 Europe an C ommission (2017), Enter the data economy: EU policies for a thriving data e cosystem. Published 

January. Available at: https://ec.europa.eu/epsc/sites/epsc/files/strategic_note_issue_21.pdf   

49 Ibid.   

50 Europe an C ommission (2016). C ommission staff work ing document: Europe’s digital progress re port 2016. 
Published May. Available at: https://ec.europa.eu/transparency/regdoc/rep/10102/2016/EN/10102-2016-
187-EN-F1-1.PDF  

51 IDC  (2017), European Data Market Study Final R eport SMART 2013/0063. R eport prepared for the European 

C om mission. Available at: https://www.k e y4biz.it/wp -content/uploads/2018/04/SMART20130063_Final-
R e port_030417_2.pdf 

52 Europe an C ommission (2017), Enter the data economy: EU policies for a thriving data e cosystem. Published 

January. Available at: https://ec.europa.eu/epsc/sites/epsc/files/strategic_note_issue_21.pdf  

53 Europe an C ouncil/ European Parliament (2003), Dire ctive 2003/98/EC of the European Parliament and of the 

C ouncil of 17 November 2003 on the re -use of public sector information. Available at: http://eur-
le x .europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2003:345:0090:0096:en:PDF  

54 Europe an C ommission (2017), Building a European data economy. Published January. Available at: 

https://ec.europa.eu/digital-single-market/en/policies/building -european-data-economy  

24 

 
 
                                              
2.1.2.  Internet of Things 

The promise and potential of IoT is substantial. The worldwide IoT market is expected to 
grow to more than 7 trillion dollars by 202055. At the same time, the development of the 
IoT market has only rec ently started, as in 2015, of all physical objects that can be 
connected to the Internet, less than 1% actually were connected. This means that just 
under 15 billion of the approximately 1.5 trillion items on earth were connected to the 
Internet at that time. This number is expected to increase up to level of more than 50 
billion devices connected to the Internet by 202056. Specifically, for the EU28, IDC 
expects the number of IoT connections to grow to a level of almost 6 billion in 2020, and 
revenues growing up to a level of 1,181 billion EUR in 202057. Within the EU, the number 
of IoT connections is expected to increase from 1.8 million  in 2013 to almost 6 billion in 
2020, which means the IoT market will be worth more than one trillion dollars by then 58.  

The growth in connectivity is expected to bring economic benefits, with IoT reshaping 
and transforming existing industrial structures. Borders between products and services, 
as well as borders between industries will become less obvious than today. This may 
materialise in innovative IoT services or applications, improved products, more efficient 
processes and a reduced consumption of resources and a better understanding of 
customers’ needs. Examples include energy-saving smart streetlights, intelligent 
transport systems reducing congestion and IoT -based solutions supporting health 
monitoring and independent living at home – with demonstrated efficiency gains of care 
efforts of more than 20%59. 

2.1.3.  Cybersecurity 

The emergence of new technologies brings new opportunities for enhanced business 
performance and operations, but also introduces several information security and privacy 
risks. We all remember  the massive WannaCry ransomware attack from 2017, targeting 
more than 200,000 systems from companies, government agencies and individuals in 
more than 150 countries. Major organisations such as the National Health Services (NHS) 
in the United Kingdom and Renault -Nissan had to halt production in some areas as a 
result 60. Experts warn that WannaCry was just the beginning61, and the numbers confirm 
this view. Since the beginning of 2016, more than 4,000 ransomware attacks occurred 
worldwide daily. This is an increase of 300% since 2015. Speaking about cyber incidents 

55 Spe ncer, L. (2014), Internet of Things m arket to hit $7.1 trillion by 2020 : IDC. Published June. Available at: 

http://www.zdne t.com/article/internet-of-things-market-to-hit-7-1-trillion-by-2020-idc/  

56 Macaulay, J., Buckalew, L., & C hung, G. (2015), Internet of Things in logistics. Available at: 

http://www.dhl.com/content/dam/Local_Images/g0/New_aboutus/innovation/DHLTrendReport_Internet_of_t
hings.pdf  

57 IDC  & TXT (2015), Definition of a re search and innovation policy leveraging cloud computing and IoT 

com bination. Report prepared for the European Commission. Available at: https://ec.europa.eu/digital-single-
m ark et/en/news/definition-research-and-innovation-policy-leveraging-cloud-computing-and-iot-combination  

58 Europe an C ommission (2016), Advancing the Internet of Things in Europe. Published April. Available at: 

http://eur-lex.europa.eu/legal-content/de/TXT/?uri=C ELEX%3A52016SC0110   

59 Europe an C ommission (2016), C ommission staff work ing document: Advancing the Internet of Things. 

Published April. Available at: https://eur-lex.europa.eu/legal-
conte nt/EN/TXT/PDF/?uri=CELEX:52016SC0110&from=de  

60 Langde, R . (2017), W annaCry ransomware: A detailed analysis of the attack. Published Se ptember. Available 

at: https://techspective.net/2017/09/26/wannacry-ransomware -detailed-analysis-attack/  

61 C onstantin, L. (2017), W annaCry attacks are only the beginning, experts warn. Published May. Available at: 

https://www.pcworld.com /article/3196927/security/wannacry-attacks-are-only-the-beginning.html  

25 

 
 
                                              
in general, around 80% of companies in Europe have experienc ed at least one 
cybersecurity incident in 201662.  

More and more often, news items about various forms of cybercrime are dominating the 
news, illustrating that cybersecurity is now more important than ever. Various forms of 
cyber threats can be distinguished. The most important ones are the following63: 

 

Internal attacks, such as malicious employees that leak sensitive data; 

  Phishing and spear phishing; 

  DDoS attacks; 

  Malware, such as ransomware, spyware, adware, bots and Trojans; 

  SQL injection (vulnerabilities that allows hackers to steal or tamper with the 

database behind a web application); 

  Bring Your Own Device (BYOD) technology that sets corporate networks at risk 

from unsecured devices that contain malicious applications . 

The costs of cybercrime for those impacted are high and growing. Estimates show that 
the annual global costs of cybercrime will grow to around 4.8 trillion EUR by 2021 64. 
However, the reputational damage for affected companies is often even bigger than the 
direct monetary damage65.  

Not only big companies, but also SMEs fall victim to cyber threats more and more often66. 
Although many owners of SMEs underestimate their risk of becoming the target of a 
cyber-attack, they are likely targets for cyber criminals 67 or state-sponsored attacks68. 
Today, SMEs are increasingly dependent on their information systems and networks to 
provide services and products and meet their business objectives. The vast majority of 
SMEs (excluding micro-enterprises) rely on some form of information system and many 
of them already have an online presence. Electronic communication networks, 
interconnected information systems and digital services are an essential part of an 
increasing number of SMEs69.  

62Europe an Commission (2017), State of the Union 2017 - Cybersecurity: Commission scales up EU's re sponse 

to cybe r-attacks. Published September. Available at: http://europa.eu/rapid/press -release_IP-17-
3193_e n.htm  

63 Information Age (2017), Seven nightmare cyber security thre ats to SMEs and how to secure against them. 
Published May. Available at: http://www.information-age.com/7-nightmare-cyber-security-threats-smes-
se cure -123466495/  

64 C ybe r Ventures (2017), 2017 Cybercrim e report. Available at: https://cybersecurityventures.com/2015 -

wp/wp-conte nt/uploads/2017/10/2017-Cybercrime-Report.pdf  

65 Ham ilton Places Strategies (2016), Cybercrime costs m ore than you think. Published February. Available at: 

https://www.ham iltonplacestrategies.com/insights/cybercrime-costs-more -you-think/  

66 The  Guardian (2016), Huge rise in hack  attacks as crim inals target small businesses. Available at: 

https://www.the guardian.com/small-business-network/2016/feb/08/huge-rise-hack-attack s-cyber-criminals-
targe t-small-businesses  

67 IQ  in IT (2017), Why cybersecurity for SMEs is e ven more important in 2017. Available at: 

https://www.iqin.it/blog/why-cyber-security-smes-even-more-important-2017  

68 The  Guardian (2018), UK businesses face growing threat from cyber-attacks – re port. Published April. 

Available at: https://www.the guardian.com/technology/2018/apr/10/uk-businesses-face-growing-threat-
from -cyber-attacks-report  

69 Mazzarol, T. (2015), SMEs e ngagement with e -commerce , e -business and e -marketing, Small Enterprise 
R e search, 22:1, 79-90. https://doi.org/10.1080/13215906.2015.1018400  & Enisa (2016), Information 

26 

 
 
                                              
What also makes SMEs vulnerable is that they generally have relatively ma ny different 
digital assets per individual user, their security is limited compared to bigger companies 
and they generally are less careful to prevent cyber-attacks70. Now that most large 
businesses have dedicated cybersecurity teams, cyber criminals increasingly target 
smaller enterprises. Perhaps SMEs are even a more likely target than large corporates, 
as due to a perceived lack of security, cyber criminals are increasingly looking towards 
SMEs as a gateway into the supply chain71. SMEs are not always aware of the fact that 
they contain valuable information for cyber criminals. On top of that, because of their 
limited resources, the damage for SMEs can be harder to overcome than for large 
businesses. Cybersecurity is therefore of crucial importance for the business continuity of 
an SME. Lack of cybersecurity sets SMEs at risk of reputational damage, financial 
damage and lower customer satisfaction. In the Netherlands, 40% of SMEs suffered from 
any form of digital fraud in 201772. From the companies suffering from any form of digital 
fraud, 57% indicated that it caused financial damage 73. Especially for SMEs, this financial 
damage can have a profound impact: 60% of SMEs that were victims of cyberattacks did 
not recover and had to shut down within six months 74. 

Cyber threats are not only a threat for business continuity but can also be a driver for 
growth for companies active in the cybersecurity market. It can even bring competitive 
advantage according to Capgemini research75. The increase in cybersecurity incidents 
stimulates the demand for high-quality, affordable and interoperable cybersecurity 
products and solutions. Cybersecurity is one of the fastest growing sectors of the ICT 
market. Worldwide spending on cybersecurity products and services reached more than 
120 billion  USD in 2017. In the last decade, the market was growing 8-10% annually, 
while predictions for 2017–2020 envisage further steady growth76. This number is 
estimated to exceed 0.8 trillion EUR cumulatively over the next years until 2022 77. In 
Europe specifically, the cybersecurity market is estimated to grow from 21.8 billion EUR 
in 2015 to 30.6 billion EUR in 202078. 

se curity and privacy standards for SMEs. Published June. Available at: 
https://www.e nisa.europa.eu/publications/standardisation-for-smes  

70 Ibid. 

71 Fre sh Business Thinking (2016), C ybersecurity is a growing priority – don’t be the we ak link. Published May. 
Available at: http://www.fre shbusinessthinking.com/cybersecurity-is-a-growing-priority-dont-be-the-we ak-
link /  

72 Kam er van Koophandel (2018), Boost je  business met big data. Available at: 

https://kvk.instantmagazine.com/e-zines-kvk/big-data#!/big-data-en-veiligheid  

73 Ibid.  

74 SMESEC  (n.d.), A lightwe ight cybersecurity framework  for thorough protection. Available at: 

https://smesec.eu/index.html  

75 https://www.capgemini.com/2018/05/cybersecurity-the-new-competitive-advantage-for-retailers/ 

76 C ybe rsec (2017), European cybersecurity market. Published June. Available at: 

https://cybersecforum.eu/en/the-2nd-issue-of-the-european-cybersecurity-market-already-available-
download/  

77 C ybe r Ventures (2017), 2017 Cybercrim e report. Available at: https://cybersecurityventures.com/2015 -

wp/wp-conte nt/uploads/2017/10/2017-Cybercrime-Report.pdf  

78 MicroMarketMonitor (n.d.), Europe cybersecurity market. Available at: 

http://www.m icrom arketmonitor.com/market/europe-cyber-security-4129808188.html  

27 

 
 
                                              
The supply of ICT security products and services on the European market is being 
characterised as fragmented79. As a result, ICT companies might need to undergo 
different certification processes to sell its products and services in several Member 
States. The urgency of acting upon cybersecurity threats is being recognised at the EU 
level. To spur further a European single cybersecurity market, the European Commission 
has already initiated a framework for cybersecurity certification to overcome the issue of 
fragmentation80. Many European SMEs are active in the cybersecurity market, especially 
in niche markets (e.g. cryptography) and in well-established markets with new business 
models (e.g. antivirus software), but they are often unable to scale up their operations 81. 

Cybersecurity was also a central element in the 2018 State of the Union speech by 
President Juncker82. One of the proposals include the creation of a Network of 
Cybersecurity Competence Centres, coordinated by a new European Cybersecurity 
Industrial, Technology and Research Competence Centre. Leveraging the already existing 
660 cybersecurity centres across the EU, this new initiative seeks to 83: 

  Pool, share and ensure access to existing expertise; 

  Help deploy EU cybersecurity products and solutions; 

  Ensure long-term strategic cooperation between industries, research communities 

and governments; 

  Co-invest and share costly infrastructure. 

Figure 9 Creating  a European  Cybersecurity  Competence Network & Centre 84 

79 Europe an C ommission (2015), C ybersecurity industry. Published December. Available  at: 

https://ec.europa.eu/digital-single-market/en/cybersecurity-industry  

80 Europe an C ommisison, (2017), The EU cybersecurity ce rtification framework. Published September. Available 

at:   https://ec.europa.eu/digital-single-market/en/eu-cybersecurity-certification-framework  

81 Europe an C ommission (2016), C ommission signs agre ement with industry on cybersecurity and steps up 
e fforts to tack le cyber-threats. Published July. Available at: http://europa.eu/rapid/press-release_IP-16-
2321_e n.htm  

82 https://ec.europa.eu/digital-single-market/en/news/state-union-2018-cybersecurity-commission-proposes-

inve st-stronger-and-pioneering-cybersecurity  

83 Ibid. 

84 Ibid.  

28 

 
 
 
                                              
2.2.  Opportunities for SMEs to benefit from these technologies 

2.2.1.  Big data 

The amount of data produced is growing exponentially, as shown in section 2.1. 
These big numbers underline the macro-economic benefits of the data economy, 
but do not tell us how value is created at a mere micro-economic level  – and thus 
how individual  companies can benefit from the data economy. When we zoom in 
on the exploitation and commercialisation  of big data at a micro -level,  it appears 
that  data  has  potential  for  organisations of  all  shapes  and  sizes,  and  these 
organisations turn data into value  in various ways 8 5. Several different actors are 
involved in the process of data creation to data services and products, as shown 
in Figure 10.  

Figure 10 The data value chain – including  archetypes 

The emerging data economy offers opportunities for new types of companies. Data 
creation is done by the Suppliers. The data is subsequently collected and aggregated by 
the so-called Aggregators. Developers use the data for the development of new 
applications, while Enrichers use data to gain new and better insights from the analysis of 
the data. Enablers facilitate the supply or use of open data for the other archetypes, for 
instance by providing platforms from which the data can be extracted.  

The emerging data economy offers new opportunities for specialists and niche players – 
naturally a domain of SMEs. Specialisation and differentiation of products and services 
are among the most significant success factors for SMEs. The development of more niche 
market demand could enable SMEs to strengthen their competitive advantages and to 
reduce their structural disadvantage stemming from resource constraints and limited 
ability to develop economies of scale.  

Companies not only re-use data generated by themselves. Datasets can be purchased on 
the market, but perhaps more importantly, increasingly companies can also make use of 
open data. The European Data Portal shows that governments are maturing on their 
open data journey, meaning that more and more EU governments publish high-quality 
open data86. The European Data Market Monitoring Tool illustrates that big data offers 
market value in different industries – with substantial differences between industries. 
(Figure 2-5).  

85 C apgemini Invent (2017), R e-using open data: A study on companies transforming open data into e conomic 

& socie tal value. Available at: https://www.e uropeandataportal.eu/sites/default/files/re-using_open_data.pdf  

86 C apgemini Invent (2017), O pen data maturity in Europe in 2017. Published November. Available at:  
https://www.e uropeandataportal.eu/sites/default/files/edp_landscaping_insight_re port_n3_2017.pdf   

29 

 
 
 
 
 
 
                                              
DI FFE R E N CE S A C R OSS  I N DUST R IE S

s
r
e
s
u

a
t
a
d
f
o

r
e
b
m
u
N

200.000
180.000
160.000
140.000
120.000
100.000
80.000
60.000
40.000
20.000
0

14.000

12.000

10.000

8.000

6.000

4.000

2.000

0

R
U
E
n
m
n

l

I

Data Market Value 2016

Number of Data Users 2016

Figure 11 Market value and data workers across  industries87 

While the above paragraphs show that the expected benefits depend on the type of 
company and the sector in which the company is active, it does not tell us what the 
benefits of working with big data are for the ‘average’ company. A recent study showed 
that the use of big data can result in several competitive advantages 88: 

 

 

Improving business intelligence; 

Improving research and accelerating innovation; 

  Reducing costs and improving customer satisfaction by more personalised 

services89; 

 

Improving and renewing products and/or services and creating new ones 
according to customers’ needs; 

  Better adjusting their marketing to their target  group, thus making marketing 

more effective; 

  Better understanding and optimised business processes, such as optimised 

product stocks based on models that predict buying behaviour. 

In addition, the EU publication on the data economy states that “companies can use big 
data analytics to help them develop new products and services, to re-engineer their 
business processes and better manage their supply chains, to strengthen fraud detection, 
to improve security and risk management and to gain clearer insights into customer 
needs”90. An advantage that SMEs have in this regard, because of their size, is that they 
tend to be more flexible in using the insights generated from big data in order to increase 

87 IDC  (2017), European Data Market Study Final R eport SMART 2013/0063. R eport prepared for the European 

C om mission. Available at: http://datalandscape.eu/  

88 Ne w Ge n Apps (2017), 5 Be nefits: Competitive advantages of  Big Data in business. Published July. Available 
at: https://www.ne wge napps.com/blog/importance -benefits-competitive-advantage-big-data  

89 Europe an C ommission (2014), Big Data. Published July, updated March 2018. Available at: 

https://ec.europa.eu/digital-single-market/en/policies/big-data  

90 Europe an C ommission (2017), Enter the d ata economy: EU policies for a thriving data e cosystem. Published 

January. Available at: https://ec.europa.eu/epsc/publications/strategic-notes/enter-data-economy_e n  

30 

 
 
 
 
                                              
 
 
 
 
 
sales, reduce costs, improve customer satisfaction, increase productivity and accelerate 
innovation.  

Insight box – Producers of big data solutions 

An example is the Slovenian SME eVineyard91. This company provides solutions and an 
application based on big data to help growers with the management of their vineyard. 
By combining multiple sources of data, this application helps the grower making 
irrigation, harvesting or treatment decisions in the vineyard. Another company making 
successfully use of big data technologies is DataCentric. This Spanish SME builds data-
driven technology solutions. DataCentric expertise stems from its experience of 
creating and delivering databases for marketing and sales and managing its 
customers’ data92.  

SME owners indicate to expect benefits in several areas when working with big data, 
most notably an improved customer experience based on better insights and improved 
insights in client needs93. Other benefits include, inter alia, the ability to develop new 
products or services and better insights into internal processes, allowing SMEs to improve 
and further rationalise these processes (Figure 12).  

WHI C H O P P O R T UN IT IE S A S SO CI ATE D WI T H 
WO R K I N G WI T H ( B I G)  DATA  DO  YO U  C O N S I DER  
I M P O R TA NT  FO R  YO U R  C O M PA NY?

Improve internal processes
Develop new products and/or services
Determine strategy
Improve competitiveness
Improve insight in client appreciation
Increase revenu
Improve insight in client needs
Improve the customer experience

0%

10%

20%

30%

40%

50%

60%

70%

Figure 12 Opportunities  associated  with (big) data 

The quantified micro-level benefits of using big data and digital technologies in general 
are underscored in numerous studies. Firms that adopt data-driven decision-making have 
been found to have a 5-6% higher output and productivity94. SMEs already working with 
big data are growing faster than SMEs not using big data technologies, reporting an 
average growth of 5%95. Research among financial managers of larger organisations 

91 http://www.e vine yardapp.com/  

92 Big Data Value Association (2017), SMEs in the European data-economy. Published November. Available at: 

http://www.big-data-value.eu/wp-content/uploads/2018/01/SMEs -Brochure -2017.pdf  

93 Van der Ve en, M., Smetsers, D., Van den Born, A. & Bosma, B. (2017), Ondernemen m et (big) data door het 

m k b. Kamer van Koophandel and Jheronimus Academy of Data Science . Published January. Available at: 
https://www.k vk .nl/download/20170110%20Rapport%20Ondernemen%20met%20big%20data%20door%20
he t%20mkb_tcm109-431240.pdf 

94 Europe an C ommission (2017), Enter the data economy: EU policies for a thriving data e cosystem. Published 

January. Available at: https://ec.europa.eu/epsc/sites/epsc/files/strategic_note_issue_21.pdf  

95 Blue mine (n.d.), Big data in het mkb: wat levert het u op? Available at: http://www.blue mine.nl/wp -

conte nt/uploads/2017/06/Bluemine_infographic_Big_Data-V1.pdf 

31 

 
 
 
 
                                              
shows that in 60% of the cases, the deployment of big data results in increased 
revenues. Existing products and services become more profitable in 83% of the cases 96. 
Overall, the productivity of SMEs could increase by 30 to 75% by using modern 
automation in production, digital tools in product design, and an effective production and 
resource planning.  

This all points to the conclusion that big data is primarily  seen as an engine for growth, a 
view that is confirmed by our survey respondents. The fact that it provides opportunities 
for growth is seen as one of the biggest benefits by 30% of the respondents, followed by 
the perception that it can be used to distinguish companies from their competitors 
(indicated by 16%) and the belief that it is a driver of additional revenue streams (14%).  

WHAT  A R E  T HE  B E N E FI T S O F B I G DATA  FO R  
YO U R  C O M PAN Y?

Other (please specify)
I don't know
It is not relevant for our company
It is a driver of additional revenue streams
It provides opportunities for growth of the company
It distinguishes us from competitors
It is a prerequisite for the domain we work in
It is critical for business continuity

0%

5%

10%

15%

20%

25%

30%

35%

Figure 13 Benefits  of big data. Source:  survey 

2.2.2.  Internet of Things (IoT) 

The benefits described in the section above particularly apply for companies working with 
big data, but as there are many overlaps with IoT, benefits may also hold ground for 
companies working with IoT. IDC described the more specific benefits of IoT applications 

96 Ibid.   

32 

 
 
 
 
 
 
                                              
for large companies, SMEs and other businesses in their report ‘Leveraging Cloud 
Computing and IoT Combination’97:  

 

Increased return on R&D investments; 

  Additional innovative services; 

  Shorter time to market; 

  Supply-Chain management & logistics improvements;  

 

Increased business processes efficiency; 

  Productivity improvements;  

  Enhanced asset utilization.  

Other sources98 state that IoT can improve and optimise processes, goods and services, 
that IoT enables the design of new products and services, reduces the need for human 
interventions (and thus human errors) and enable new business models. According to 
research by THINKstrategies, the benefits of IoT for businesses fall into four categories 99: 

(1)  Diagnostics and reporting: IoT devices allow the company to better respond to 

product or service issues when they arise. More and more devices include an alert 
feature that notifies the supplier when a problem occurs. The supplier can 
remotely diagnose the issue and initiate a solution. This functionality can re duce 
the time needed to solve the issue and keep customer dissatisfaction to a 
minimum; 

(2) 

(3) 

(4) 

Predictive and preventive analysis: because of the possibility to embed greater 
intelligence into the product or service, the supplier can be notified of an issue 
before it becomes a real problem. This allows preventive action from the side of 
the supplier, so bigger problems will not occur; 

Information collection: IoT products and services allow for the collection of big 
data about the way the product or service is used. This makes it easier to serve 
the customer’s needs and also provides valuable insights into additional products 
and services that customers are interested in;  

Business transformation: the information and insights gathered by IoT can 
uncover new business opportunities. For example, data gathered in connected 
cars can be used by insurance companies to better determine appropriate 
insurance rate plans that are based on more accurate risk assessments.  

Our survey respondents largely confirm this picture, and similar to big data, this leads to 
the conclusion that IoT is primarily  seen as a driver of growth. 23% of the respondents 
indicate that it provides opportunities for growth of the companies, and 16% indicate 
that it is a driver of additional revenue streams.  

97 IDC  & TXT (2015), Definition of a Research and Innovation Policy Leveraging Cloud Computi ng and IoT 

C om bination. Report pre pared for the European Commission. Available at: https://ec.europa.eu/digital-single-
m ark et/en/news/definition-research-and-innovation-policy-leveraging-cloud-computing-and-iot-combination 

98 E.g. Business Ne ws Daily (2013), Internet of Things has big startup potential. Published November. Available 

at: https://www.businessnewsdaily.com/5450 -internet-of-things-business-opportunities.html  

99 Kaplan, J. M. (2015), Attaining four le vels of Internet of Things b enefits. Published February. Available at: 

http://sandhill.com/article/attaining-four-levels-of-internet-of-things-benefits/  

33 

 
 
 
                                              
WHAT  A R E  T HE  B E N E FI T S O F T HE  I N T E R N E T O F 
T HI N GS  FO R  YO U R  C O M PA NY? 

Other (please specify)
I don't know
It is not relevant for our company
It is a driver of additional revenue streams
It provides opportunities for growth of the company
It distinguishes us from competitors
It is a prerequisite for the domain we work in
It is critical for business continuity

0%

5%

10%

15%

20%

25%

Figure 14 Benefits  of IoT. Source:  survey 

It is important to note that one can distinguish benefits for users and benefits for 
suppliers. Much of the IoT market is based on business-to-business interactions, meaning 
that ICT vendors provide IoT technologies and solutions to business users, who leverage 
them to deliver services and applications to their customers. A group of so-called 
enabling companies play an important role in the IoT ecosystem, referring to big data 
companies, security providers, application developers, and other professional services 
companies100. The IoT ecosystem is populated by a number of different stakeholders, 
which can be categorised in three main categories 101:  

  Vendors providing components to the solution suppliers. This group covers a wide 
variety of companies in terms of size, vertical specialisation, and geographic 
reach. Examples are commercial service providers, systems integrators, 
hardware, software, and cloud service Providers. 

  Suppliers who create IoT solutions and services for other enterprise customers. 
Many of the vendors noted above also build solutions for customers using their 
own and other suppliers' components. These suppliers design, build, and operate 
IoT solutions on behalf of their enterprise customers based on the components 
supplied by vendors. 

  Customers/end-users who use the IoT solutions provided by ESPs. There are 

examples of users in most sectors who use IoT solutions.  

SME technology companies are a major source of innovat ion in IoT. Their smaller size, 
shorter decision cycles and flexibility allow them to act adapt quickly to this emerging 
market, which can keep them ahead of slower moving larger companies 102. Examples of 
SMEs successfully adopted IoT are presented below 

Insight box – IoT producers 

An example of a successful small company that applied IoT in product design is the 
Spanish company Drone Hopper103. Drone Hopper is a drone that can provide aerial 

100 IDC  & TXT (2015), Definition of a Research and Innovation Policy Leveraging Cloud Computing and IoT 

C om bination. Report pre pared for the European Commission. Available at: https://ec.europa.eu/digital-single-
m ark et/en/news/definition-research-and-innovation-policy-leveraging-cloud-computing-and-iot-combination 

101 Ibid.  

102 Staff, I. (2017), The business drivers and challenges of IoT for SMEs. Published January. Available at: 

https://iotuk.org.uk/the-business-drivers-and-challenges-of-iot-for-smes/  

103 https://www.drone -hopper.com/home  

34 

 
 
 
                                              
support for fighting wildfires. The drone has a maximum  capacity of 300 litres of water 
and includes control systems, thermographic cameras and a navigation system.  

SMEs can also facilitate the creation of IoT applications, such as the Swedish company 
H&D  Wireless AB104. This company enables wireless sensor and multimedia data access 
to the Internet for a low price. H&D Wireless solutions can be used in devices such as 
smart energy meters and smart medical devices.  

2.2.3.  Cybersecurity 

Digitalisation creates opportunities for businesses of all sizes, but these opportunities 
come with several information security and privacy risks. Addressing these risks plays a 
significant role in business success nowadays, as growing security threats may 
potentially disrupt business continuity and cause monetary and reputational damage to 
SMEs105. Effectively addressing cybersecurity risks results in concrete benefits. Research 
by ENISA106 shows that there are multiple specific drivers for European SMEs for the 
uptake of cybersecurity: 

  Mitigating  information security and privacy risks: adoption of information security and 

privacy standards is an effective way to mitigate these risks; 

 

Increasing consumer trust: users trust organisations more if they know their 
personal data will be safe with them; 

  Demonstrating commitment to regulatory compliance: these regulations can be on 

a national level or on a European level, such as the General Data Protection 
Regulation, for which noncompliance can result in fines of up to 4% of the annual 
turnover of businesses if they do not have their data security and privacy 
measures in order107; 

  Creating competitive advantage: when businesses have their cybersecurity in 

order, it could be easier for them to attract and retain customers. 

The increase in cyber incidents brings substantial business opportunities for those active 
in the cybersecurity market. Several domains within the cybersecurity ecosystem can be 
distinguished in which SMEs can be active: from cybersecurity governance, traceability 
and audit, identity access management, data security and cryptography, messaging 
security, application security, security of infrastructure and equipment, consulting and 
training to operational and outsourcing services108.  

104 http://www.hd-wire le ss.se/  

105 ENISA (2016), Information security and privacy standards for SMEs. Published June. Available at: 

https://www.e nisa.europa.eu/publications/standardisation-for-smes  

106 Ibid. 

107 GDPR  Portal (n.d.), GDPR key changes. Available at: https://www.e ugdpr.org/key-changes.html  

108 Digital SME Alliance (2017), Europe needs a cybersecurity strategy to foster its SME e cosystem. Published 
July. Available at: https://www.digitalsme.eu/europe-needs-cybersecurity-strategy-foster-sme-ecosystem/  

35 

 
 
 
 
                                              
Figure 2.9 

As cybersecurity is relevant for everyone using the Internet (organisations of all sizes, for 
companies, governments, consumers, etc.), the cybersecurity market is enormous. 
Examples of companies that benefit from this growing market by providing cybersecurity 
solutions are provided in below insight box.  

Insight box – Cybersecurity producers 

ZenMate109 is a German company that provides businesses with several services and 
products: international quality assurance, data and employee security solutions, a 
solution to encrypt private calls and for anonymous business research, IP address 
protection, and a solution for gaining unrestricted content for remote workers.  

Another example is FLO Live110, an UK-based company that provides IoT security 
solutions to create a secure, cloud-based ecosystem for IoT.  

The fact that business continuity is essential for every business is also underlined in our 
survey. When asked about the importance of the three technologies, cybersecurity is 
considered to be very important – scoring 5,72 out of 7. In fact, cybersecurity is 
considered to be substantially more important than big data and IoT.  

109 https://zenmate.com/home-page/  

110 http://flolive.net/  

36 

 
 
 
 
 
                                              
O N   A  S C A L E  F R O M  1 - 7 ,  H O W   I M P O R T A N T  A R E  T H E S E  
T E C H N O L O G I E S  F O R  Y O U R  O R G A N I S A T I O N ?

Big Data

IoT

Cybersecurity

5,02

4,72

1

2

3

4

5

1 = not important at all, 7 =  extremely important

5,76

6

7

Figure 2-10  Importance  of Big Data, IoT,  Cybersecurity. Source:  survey  

2.3.  The impact of technological trends on the take-up by SMEs 

2.3.1.  Impact of technological trends on 

technology adoption 

The technological landscape is evolving fast. As the digital frontier expands, there is 
constant pressure on SMEs to adapt and evolve. New technologies may change the status 
quo of the market and may bring opportunities for SMEs or act as a threat for positions 
gained in the market. Some trends may be more disruptive than others. New 
technologies may also impact the extent to which SMEs are able to adopt BIC 
technologies – and affect the demand for specialised skills. This section presents the 
most relevant technological trends for the three technologies and the way they will affect 
the take-up by SMEs. To identify and select the most important trends and their impacts, 
an extensive analysis of leading publications from major technology advisory firms was 
carried out. The selection of trends was based on the following criteria:  

  Publications are max. two years old; 

  Trends identified are documented by at least three separate sources; 

  Trends are related to or impact big data, IoT and/or cybersecurity; 

  They are disruptive technologies, meaning that they are rapidly advancing, they 
have a broad potential scope of impact, may affect significant economic value, 
and they can dramatically change the status quo of the market 111.  

Following these search criteria 25 trends have been discovered for 2018 and beyond, 
within the areas of cybersecurity, big data and IoT. These trends are expected to 
significantly impact SMEs. These 25 trends have been clustered into six main  domains, 
that all impact SMEs in a different way. Figure 15 presents an overview of the six 
domains and how they affect the take up of emerging technologies by SMEs. Annex B 
provides a more detailed overview.   

111 McKinsey (2013), Disruptive te chnologies: Advances that will transform life, business, and the global 

e conomy. Published May. Available at: https://www.m ck insey.com/business-functions/digital-mck insey/our-
insights/disruptive-technologies  

37 

 
 
 
 
                                              
Figure 15 The main technological  trends  affecting the take up of big data, IoT and cybersecurity  by SMEs  112 

At first, artificial intelligence will impact SMEs significantly, because today most AI 
technologies have appeared in the public domain and are underpinned by open-source 
components113. Therefore, it does not have to be a capital or HR-intensive activity. The 
increasing importance of AI facilitates the take-up of both big data, IoT, and 
cybersecurity. Whereas cybersecurity could be described as a precondition to deploy AI, 

112 For a de tailed description of the methodology and sources that underpin the identificati on of trends and he 

analysis of the impact on SME take up, please re fer to Annex B 

113 Financial Times (2017), SMEs can challenge big beasts by snapping up AI benefits first. Published O ctober. 

Available at: https://www.ft.com /content/8b053fe4 -a1ca-11e7-9e4f-7f5e6a7c98a2   

38 

 
 
 
 
                                              
AI might perhaps even more impact the big data and IoT domain, as AI relies on big data 
technologies – and possibly data generated by IoT technologies. For instance, digital 
twins114 are digital representations of (the behavior of) a physical object or process that 
help optimise business performance, using real-time data. They provide visibility and 
insight in the operations of their machines in the context of the (IoT) environment they 
are part of.  

Secondly, blockchain technology has the potential to impact SMEs significantly as well, 
because the cost savings as a result of using the decentralised ledger (i.e., an asset 
database that can be shared across a network of multiple sites, geographies or 
institutions115) of the blockchain technology will have a large impact as SMEs are less 
resource-intensive. It is especially useful in environments with a high level of security 
and trust (e.g., online identity verification). Blockchain will primarily  spur the take-up of 
cybersecurity, and to a lesser extent big data and IoT.  

Thirdly, business model reengineering refers to the newest business strategies linked 
inseparably to technology, which causes SMEs to rethink fundamentally how they 
envision, deliver and evolve technology solutions. The trends listed in this category 
impact all three technological areas – although some to a greater extent than others.  

Fourthly, SMEs should consider responsible data management to fully exploit their agility, 
because the use of data is perfectly suited to predict and analyse market and consumer 
behaviour. SMEs can thereby act on data-derived insights with speed and efficiency. 
Obviously, this domain mainly impacts the take-up of big data by SMEs, and to a lesser 
extent IoT. The trends ‘Identity and Access Management’ and ‘Privacy by Design’ also 
foster SME take-up of cybersecurity.  

Fifthly, digital reality is an umbrella  term for Augmented Reality (AR), Virtual Reality 
(VR), Mixed Reality (MR), 360° video, and immersive  technology. It offers various ways 
for SMEs to transform positively business areas such as internal workforce 
communication, collaboration, training and development. Digital reality primarily  affects 
the take-up of big data and IoT, as digital reality becomes increasingly essential for 
processing and presenting data. Digital reality technologies offer various prospects for 
enterprises to transform areas such as internal workforce communication and 
collaboration (e.g., new types of virtual meetings), training through simulation, and 
customer service. 

At last, the advent of the cloud will continue to proliferate in SMEs. Businesses are no 
longer using the cloud solely as a tool - the focus has shifted towards finding the right 
way to use it. The advent of the Cloud has created significant changes to organisations: it 
has evolved from personal cloud storage to entire organisations moving all their data to 
the cloud. Increasing usage of cloud solutions impacts all three technologies. Whereas 
SMEs in the past may have struggled with a lack of resources to create and/or buy 
software packages or other IT resources, they will now be able to subscribe to a cloud 
center and receive access to the IT infrastructure they need.  It reduces costs and 
improves efficiency as cloud-hosted servers enable mass-scale computing power and 
minimise  IT requirements, physical storage and software updates. Information becomes 
easily accessible and easy to use for collaboration. Lastly, the cloud adds se curity for its 
users by backing up data and decrease the opportunities for hackers. 

114 Koppel, A. (n.d.), Meet the digital twin –the k ey technology in your smart factory. Available at: 

https://medium.com/@i4ms_e u/meet-the-digital-twin-the-key-technology-in-your-smart-factory-
16d5cf0dd284  

115 Shankar, S. (2017), C entralized le dgers vs. distributed ledgers (layman understanding). Pu blished July. 
Available at: https://medium.com/@shyamshankar/centralized-ledgers-vs-distributed-ledgers-layman-
unde rstanding-52449264ae23  

39 

 
 
                                              
In general, the sectors that are most affected by the trends listed above are banking and 
financial services, manufacturing, health care, retail, media, and telecommunications116. 
From a geographical perspective, one can state that Member States that are performing 
well with regards to the integration of digital technologies by business are more likely to 
quickly adopt emerging digital trends. Member States performing well in  this regard are 
Denmark, Finland, Ireland and Sweden117. Romania, Poland, Bulgaria and Hungary are 
the least developed as for the integration of digital technologies by businesses. The 
emergence of these new technologies will undoubtedly affect the demand for skills, 
dependent on where an SME is positioned: is it an ICT user or an ICT supplier? From a 
supplier perspective, most of the technologies described point towards the development 
of integrated and automated infrastructures. This requires not only the skills to build and 
innovate hard- and software (e.g. data centres), but also requires standardisation and 
interoperability skills118. From a user perspective, the ability to understand, select and 
manage vendors, standards and interoperability become drivers of competitive 
advantage. Skills profiles required by ICT users will become more business -oriented and 
project-oriented, including the ability to outsource (e.g. ability to select vendors, be an 
informed buyer) and/or rely on standardised platforms and services119. Lastly, 
interviewees state that with the emergence of new technologies, human judgement will 
become more important than ever. For this, one needs to understand the intrinsic logic of 
technologies to come to a weighted decision.   

2.4.  Adoption of big  data, Internet of Things  and cybersecurity by 

SMEs 

The previous sections illustrated the increasing importance of BIC technologies, their 
relevance for SMEs and how current and future trends may impact the take -up of these 
technologies. This chapter zooms in on the current state of play: to what extent are SMEs 
already able to work with these emerging technologies? Big data, IoT or cybersecurity 
might be more relevant for some SMEs than others, depending on their characteristics. 
This section therefore firstly describes a segmentation model, providing a means to focus 
on those SMEs for who adoption of one of these technologies is most relevant.  

2.4.1.  Segmentation of SMEs 

The SME landscape is diverse, with varieties in terms of size, sector, geography, 
technological intensity, and markets served. SMEs can be (potential) users and suppliers 
of emerging technologies. This makes it necessary to reduce (part of) the complexity by 
clearly defining the target group of this initiative. In this respect, interviewees on the one 
hand stress the urgency of ensuring cybersecurity for “every company connected to the 
Internet”, and that “big data offers opportunities even for the bakery around the corner”. 
On the other hand, it is argued that an approach can only be effective if it is targeted, 
specific and industry-relevant. Building on a segmentation model from the Dutch 
Chamber of Commerce, five segments can be distinguished that indicate to what extent 
companies are engaged in (technological) innovation.  

116 For a de tailed description of the m ethodology and source s that underpin the identification of tre nds and the 

analysis of the impact on SME take up, please re fer to Annex B 

117 Europe an C ommission (2015), Integration of digital technology by enterprises. Published June. Available at: 

https://ec.europa.eu/digital-single-market/en/integration-digital-technology  

118 Hüsing, T., Dashja, E., Gareis, K., Korte, W. B., Stabenow, T., & Markus, P. (2015), e -Leadership skills for 

sm all and medium sized enterprises. Published O ctober. Available at: http://eskills-
le ad.eu/fileadmin/lead/re ports/lead_final_report.pdf  

119 Ibid.  

40 

 
 
                                              
Figure 16 Segmentation  of SMEs based on maturity  in the uptake of big data, IoT and cybersecurity 120 

The above four groups (frontrunners, developers, appliers and followers) are focusing on 
renewal and innovation of processes, products and services, whereas the non-innovators 
are not. Given the fact that this initiative focuses on innovative technologies, this 
initiative will primarily  focus on the above four groups. By building on and collaborating 
with companies that understand and are already working – or are potentially working - 
with these technologies, this initiative will be best able to define what is needed. The 
group of non-innovators will automatically benefit from the results, as they for instance 
might become better aware of the added value of one of the technologies as a result of 
one of the actions proposed but will require a different approach to get involved.  

Assuming that skills needs differ per type of SME, building on this model allows this 
initiative to identify skill needs for the different groups, and to target the vision and 
proposals for supporting measures accordingly.  

2.4.2.  Big data 

Focussing on the big data playing field, it can be noticed that in 2018, 12% of the 
European SMEs were actually using some type of big data source, compared to 33% of 
large enterprises121. There are still a lot of technological opportunities to be exploited by 
SMEs, with the adoption rates of big data lagging behind of other key digital 
technologies, most notably social media, eInvoicing and Electronic Information Sharing 
(Figure 17).  

120 https://www.k vk .nl/download/Hoe_innoveert_NL_rapportage_tcm109-451143.pdf  

121 Eurostat Community survey on the usage of information and communication te chnologies in e nterprises, 13 

De ce m ber 2018 

41 

 
 
 
 
 
                                              
Figure 17 Adoption  of some key digital  technologies  by company size  (Eurostat 2017/2018) 

Whereas data stemming from own internal processes (e.g., smart meter data, sensors) 
are the most used data source for large enterprises, SMEs are more likely to use geo -
data or data generated by social media. Substantial differences exist between countries 
regarding the use of big data by SMEs. SMEs from countries such as Malta, the 
Netherlands, and Ireland seem to be ahead of other countries, specifically Hungary, 
Austria and Cyprus (Figure 18) 122. 

Figure 18 Percentage  of enterprises  analysing big data sources  (Eurostat  2018)  

The above numbers refer to the situation in 2018. Other studies show similar findings. 
Based on a representative sample of more than 4,000 companies, evidence from the 
Netherlands shows that still only 13% of the Dutch SMEs is currently working with big 
data, and 15% is planning to do so123. Only a fraction – less than 1% - of Dutch SMEs is 
ready for the application of big data in their business processes. Size matters in this 
regard: Larger SMEs are more likely to be ready for big data 124.  

The picture sketched above relates to SMEs using big data technologies. Data users are 
organisations that generate, exploit, collect and analyse digital data intensely and use 
what they learn to improve their business 125. They represent the demand-side of the 
market and may use solutions provided by data suppliers: companies who have the 

122 Ibid.  

123 Van der Ve en, M., Smetsers, D., Van den Born, A. & Bosma, B. (2017), Ondernemen met (big) data door het 

m k b. Kamer van Koophandel and Jheronimus Academy of Data Science . Published January. Available at: 
https://www.k vk .nl/download/20170110%20Rapport%20Ondernemen%20met%20big%20data%20door%20
he t%20mkb_tcm109-431240.pdf  

124 C BS (n.d.), Are  SMEs re ady for big data? Available at: https://www.cbs.nl/en-gb/our-

se rvice s/innovation/project/are-smes-ready-for-big-data-  

125 http://datalandscape.eu/european-data-market-monitoring-tool-2018  

42 

 
 
 
 
 
 
                                              
production and delivery of data-related products, services and technologies as their main 
activity. The European Data Market Monitoring Tool estimates the total number of data 
users in the 28 EU Member States (EU28) at a level of 661,050 in 2016, of which most 
companies are SMEs: 98.9%126. Together, they represent 6.4% of the total number of 
companies in the EU28. The number of data users is growing over time, as show in 
Figure 19.  

N U M B E R  OF DATA  U S E RS  ( 2 0 1 3 -2 01 6 )

s
r
e
s
u

a
t
a
d
f
o

r
e
b
m
u
N

665.000
660.000
655.000
650.000
645.000
640.000
635.000
630.000
625.000
620.000
615.000

100%

99%

98%

97%

96%

e
r
a
h
s
E
M
S

2013

2014

2015

2016

Year

Number of data users

SME share

Figure 19 Number  of data users 

Looking at the distribution per country, two-third of the total population of data users can 
be found in the UK, Germany, Italy and Spain, with the UK being in the lead accounting 
for more than 150,000 data users127. Not surprisingly, these are also the larger EU 
economies, and the group of user companies reflects the overall structure of the 
economy. When looking at the share of data users on the total number of companie s, the 
Netherlands, the UK, Ireland and Luxembourg are leading the way, with user companies 
accounting for 9% to 12% of their total amount of companies. Data users can be found 
in every sector. Most data-user companies can be found in the professional services 
industry, manufacturing, wholesale and retail and transport – together representing 
almost two-third of Europe’s data users. At the same time, the ICT sector, healthcare 
and finance demonstrated strong growth rates in 2016, illustrating their dynamism  in 
terms of adoption of big data technologies128. 

The European Data Market Monitoring Tool has also provided estimates about the supply 
side of the market. It has to be noted that the boundaries between demand and supply 
are not so clear-cut, since for instance companies, which develop a good capability to 
exploit their own data, may become in turn resellers of their own data to third parties. 
The supply side is labelled as ‘data companies’. The SME share in data companies is more 
or less equal to the share of SMEs in the population of data users: 98.9% in 2016. The 
total number of data companies is however significantly lower than the number of data 

126 IDC  (2017), European Data Market Study Final R eport SMART 2013/0063. R eport prepared for the European 

C om mission. Available at: http://datalandscape.eu/  

127 Ibid.  

128 Ibid.  

43 

 
 
 
 
 
                                              
 
 
 
 
 
users: 254,850 in 2016. Similar  to the development noticed concerning data users, the 
number of data companies is growing (Figure 20).  

N U M B E R  O F DATA  C O M PAN IE S ( 2 0 1 3 -2 0 16 )

s
e

i

n
a
p
m
o
c

a
t
a
d
f
o

r
e
b
m
u
N

260.000

255.000

250.000

245.000

240.000

235.000

230.000

100%

99%

98%

97%

96%

e
r
a
h
s
E
M
S

2013

2014

2015

2016

Year

Number of data companies

SME share

Figure 20 Number  of data companies 

Data companies in Europe tend to be heavily concentrated in the UK and Germany. This 
distribution does not simply reflect the size of national economies, but is closer correlated 
with the presence of a strong ICT industry. When looking at the intensity of data 
companies’ presence – the share of data companies on t he total number of companies in 
the reference sectors – we notice that Ireland (22.6%) and the UK (20.8%) are topping 
the league129. Both are benefiting from their effort to pursue the data economy. The 
group of followers, consisting of the Netherlands, Italy, Austria, Germany, Sweden, 
Denmark  and Greece, used to have a lively ICT industry. From a sectoral perspective, 
data companies tend to be heavily concentrated in two sectors: the ICT sector and the 
professional services industry130.  

2.4.3.  Internet of Things 

As discussed in section 2.1.2, the market potential for IoT solutions is substantial. 
Specific numbers that detail the IoT uptake of SMES are hard to come by, and even more 
when also differentiating between IoT users and suppliers. At the same time, a 
comparison of several figures does shed light on the extent to which SMEs are able to 
work with IoT.  

IoT technology is becoming cheaper as the technology becomes more mainstream. The 
IoT market still continues to grow due to the considerable increase in the number of IoT 
devices. Europe has nearly a 40% share of the world’s IoT market. This share is expected 
to be stable in the coming years131. Substantial differences exist between countries and 

129 IDC  (2017), European Data Market Study Final R eport SMART 2013/0063. R eport prepared for the European 

C om mission. Available at: http://datalandscape.eu/  

130 Ibid.  

131 Europe an C ommission (2014), Definition of a R esearch and Innovation Policy Leveraging C lou d Computing 

and IoT Combination. Available at: http://ec.europa.eu/newsroom/dae/document.cfm?doc_id=9472  

44 

 
 
 
 
                                              
 
 
 
 
 
across sectors when it comes to the take-up of IoT. Although all EU Members States will 
participate to the IoT revolution, those countries that have traditionally invested more in 
ICT are expected to gain from the IoT revolution earlier than those that do not invest in 
ICT. Consequently, these countries (UK, Germany, and France) are forecasted to take 
over half the IoT revenues in the EU, with the top 6 (the above plus Spain, Italy, and 
Netherlands) over 75%132.  

I O T   M A R K E T   S I Z E   A N D   F O R E C A S T   BY   C O U N T R Y  ( I N  
M I L L I O N   E U R )

300.000

250.000

200.000

150.000

100.000

50.000

R
U
E

l

n
m
n

i

e
u
a
v

l

0

2014

2020

EU country

Figure 21 IoT  market size in 2014  and forecast of IoT market size in  2020 per EU country  

When looking at sectoral differences, those sectors that have traditionally invested more 
in ICT are expected to enjoy most of the benefits. IoT will impact all sectors, but the 
take-up in manufacturing, finance and utilities will grow faster than the EU average. 
Manufacturing, finance and the public sector are expected to be the biggest IoT markets 
in 2020 (Figure 22)133. 

I O T  BY  S E C T OR  I N  2 0 2 0

1%

2%

3%

2%

8%

11%

24%

13%

10%

6%

20%

Figure 22 IoT  by sector  in 2020 

Agriculture, construction, and mining

Business Services

Communications

Education & Health

Finance

Local & Central government

Manufacturing

Retail & Wholesale

Transport

132 Ibid.  

133 Ibid.  

45 

 
 
 
 
 
 
 
                                              
 
 
 
The potential of IoT is huge, but several studies point to the fact that many businesses 
are still in the early stages of IoT adoption, where its use is limited to a single business 
function, rather than being committed to a formal business–wide program134. As regard 
the role of SMEs in IoT adoption, the report ‘Definition of a Research and Innovation 
Policy Leveraging Cloud Computing and IoT Combination’135 states that SMEs play a 
relevant role in the development of the emerging IoT combined ecosystems and their 
diffusion. They mainly refer to the role SMEs can have in the supply ecosystem, and state 
that SMEs currently have insufficient capability to enter this market. One of the 
recommendations is to increase their capability, and to facilitate their access to the 
necessary technology platforms to develop applications and services. SMEs are primarily 
active in the group of ICT vendors – providing components to solution providers. 
Examples include systems integrators, hard- and software providers and cloud service 
providers. The role of SMEs within this IoT ecosystem can be more substantial, adopting 
IoT on a larger scale. Several factors are preventing SMEs from doing so: insufficient 
investments and organisational barriers to change, concerns about privacy and data 
protection, mismanagement of security risks, and a lack of standards and interoperability 
across fragmented European markets preventing economies of scale and scope136. 

Focussing on the user-side, the Vodafone IoT Baromet er137 shows that the proportion of 
companies using IoT (adopters) has more than doubled since 2013: Adoption has risen 
from 12% in 2013 to 29% in 2017. This conclusion is based on research among 1,278 
respondents (30% SMEs) globally. Furthermore, 84% of adopters agree that their 
adoption/use of IoT solutions has grown in the last 12 months. IoT is impacting almost 
every sector, and an increased use of IoT can be noticed across industries. Larger 
organisations show higher adoption rates but compared to 2013, smaller companies are 
much closer in 2017.  

2.4.4.  Cybersecurity 

In the cybersecurity industry, one can distinguish between companies active in 
developing and providing cybersecurity solutions (supply side) and companies that use 
cybersecurity solutions to ensure continuity of their business operations. Starting with 
the latter, the potential number of SMEs that might use cybersecurity solutions is 
enormous, given that ensuring cybersecurity is key for every SME connected to the 
Internet.  

In their 2016 study on Information security and privacy standards for SMEs 138, ENISA 
concludes that despite rising concerns on information security risks, the level of SMEs’ 
information security and privacy standard adoption in Europe is relatively low. Equally, 
their uptake is not largely perceived as a priority. This is in line with the 2018 Hiscox 
small business cyber-risk report 139, stating that seven in 10 businesses globally are 

134 Am ong others: Information Age (2017), US and Europe businesses lag behind in IoT adoption. Published 
Fe bruary. Available at: http://www.information-age.com/us-europe-businesses-lag-behind-iot-adoption-
123464372/ & C apgemini (2018), Unlocking the business value of IoT in operations. Available at: 
https://www.capge mini.com/wp -content/uploads/2018/03/dti-research_iot_we b.pdf 

135 Europe an C ommission (2014), Definition of a R esearch and Innovation Policy Leveraging C loud Computing 

and IoT Combination. Available at: http://ec.europa.eu/newsroom/dae/document.cfm?doc_id=9472  

136 Ibid.  

137 Vodafone (n.d.), IoT Barometer 2017/18. Available at: http://www.vodafone.com/business/news -and-

insights/white-paper/iotbarometer  

138 Enisa (2016). Information security and privacy standards for SMEs. Published June. Available at: 

https://www.e nisa.europa.eu/publications/standardisation-for-smes  

139 Hiscox (2018), Small business cyber risk re port. Available at: https://www.hiscox .com/documents/2018-

Hiscox -Small-Business-Cyber-Risk-Report.pdf  

46 

 
 
                                              
unprepared for a cyber-attack. Small businesses are disproportionately vulnerable 
because they are less likely to have strategies in place to avoid attacks, detect them 
early, and reduce the damage. In the US, 65% of small  businesses fail to act after a 
cyber-incident.  

Effectively ensuring cybersecurity is not limited to having technological solutions in place. 
SMEs need to implement formal information security processes, technical mechanisms 
and organisational measures, embedded in a solid cybersecurity policy. The existence of 
an ICT security policy would imply an enterprise's strategy to safeguard data and ICT 
systems as well as mandatory obligations for all employees. With such a policy, 
companies can address several risks, with the risk of destruction or corruption of data 
due to an attack or some other unexpected incident being the risk mostly address ed by 
enterprises’ ICT security policies. The Eurostat Community survey on ICT usage and e -
commerce in enterprises looked at adoption rates of ICT security policies and found that 
the share of large enterprises that had a formally defined ICT security policy was almost 
three times the share of small  ones140 (figure 2-19).   

E N T E R P R I S E S   H AV I N G   A   F O R M A L LY   D E F I N E D   I C T  
S E C U R I T Y   P O L I C Y   ( 2015)

e
s
i
r
p
r
e
t
n
e
f
o

e
p
y
T

All enterprises

Small enterprises (0-49)

Medium enterprises (50-249)

Large enterprises (>250)

0%

10%

20%

30%

40%

50%

60%

70%

80%

% of enterprises

Figure 2-19 

Company size clearly plays a role, with SMEs lagging substantially behind larger 
enterprises. Some countries are more advanced than others. On average, 32% of the 
enterprises in the EU28 had a formally defined ICT security policy in 2015, but shares of 
51% and 49% were registered in respectively Sweden and Portugal141. Frome a sectoral 
perspective, enterprises in the ICT sector are most likely to have such a policy in place 
(60% of enterprises), followed by enterprises active in professional, scientific and 
technical activities (49%). Lowest shares were found in the construction sector (20%) 
and real estate (25%).  

Zooming in on the degree to which SMEs actually adopt specific measures aimed at 
reducing their risk of becoming a victim of cyber criminals, evidence shows that there is a 
lot of room for improvement. For instance, according to the UK Government 2015 

140 Eurostat (2015), I CT security in enterprises. Available at: http://ec.europa.eu/eurostat/statistics -

e x plained/index.php/ICT_security_in_enterprises  

141 Ibid.  

47 

 
 
 
 
 
                                              
 
 
Information Security Breaches Survey142, only 49% of SMEs participating in the survey 
had conducted a security risk assessment in the previous year. Furthermore, research 
from the Dutch Chamber of Commerce shows that 88% of SMEs have installed virus 
scanners on company PCs143. Other measures taken by the majority of SMEs includes 
running frequent back-ups, checking the details of invoices and installing firewalls on 
company PCs (figure 2-20). At the same time, a substantial part of SMEs remains 
unprotected against digital fraud, as a result of lacking basic measures (e.g. virus 
scanner, firewall).    

W H I C H   O F   T H E   B E L O W   M E A S U R E S   D I D   YO U  
I M P L E M E N T   T O   P R E V E N T   C Y B E R   I N C I D E N T S ?

88%

86%

86%

79%

75%

64%

62%

Virus scanner on all company pc's

Frequent back-ups

Checking invoices (eg including small prints)

Firewall on all company pc's

Automatic updates software

Passwords on all company devices

Validating existence of companies before doing business

Checking online reputation of companies before doing…

Instructions for employees

Settings to block/disable cookies

No copy of passports on company pc's

Settings to block/disable ads

VPN connections

Encryption of files

Digital locker for passwords

Two-step verification

46%

45%

35%

29%

28%

23%

23%

19%

18%

Other

6%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Figure 23 Measures  implemented by SMEs to prevent cyber  incidents 

The industry in which an SME is active and the size of an SME influence their likelihood of 
protecting themselves against cybercriminals. Firstly, the industries, best protecting 
themselves against digital fraud in terms of measures taken, are: ICT and media, the 
industry, finance, and the professional services sector144. The agricultural sector and the 
construction industry are the least protected sectors. Secondly, micro-enterprises (up to 
10 employees) are less likely than larger SMEs (10-250 employees) to implement 
security measures, underlining again the factor company size.  

Taking the perspective of cybersecurity suppliers, the European market for suppliers of 
cybersecurity solutions can be characterised as fragmented, which is one of the main 

142 Proposal for a Regulation on the protection of individuals with re gard to the processing of personal data and 

on the  free m ovement of such data. Available at: http://eur-
le x .europa.eu/legalcontent/en/TXT/?uri=CELEX:52012PC0011  

143 Sm e tsers, D. & Van der Be ek, J. (2017), Pre ventie door het mkb tegen ditigale fraude. Kamer van 

Koophandel. Published September. Available at:  
https://www.k vk .nl/download/Onderzoeksrapportage_Fraude_sept170920-2_tcm109-449039.pdf  

144 Ibid.  

48 

 
 
 
 
                                              
barriers to the development of a strong European cybersecurity industry145. 
Unfortunately, reliable recent sources about the European cybersecurity industry in terms 
of number of enterprises, turnover or employees are scarce146. Following a study 
published in 2009147, the EU market has been dominated by a small  group of global 
vendors, competing with a high number of smaller  European suppliers. Back then, the 
top five vendors controlled 20.4% of total market (and they all came from outside the 
EU)148. A more recent ECSO position paper estimates the number of companies active in 
the EU cybersecurity market at a level of 60,000 companies, of which 98% are SMEs and 
start-ups149.  

Following another report prepared by ECSO150, the European industry can be divided into 
three parts: high grade, low grade and mid-grade cybersecurity. High grade refers to a 
niche market for companies originating from the defence sector. Given restrictions on 
public procurement, a protected and high-level European offer has been developed. The 
low-grade cybersecurity market is largely dependent on non-European companies. As the 
offer for the general public, Business-to-Consumer (B2C), is mainly based outside 
Europe, new European companies entering the market are often acquired by non-
European actors. Players such as Microsoft, IBM, CISCO, Symantec are dominating this 
market, often offering end-to-end solutions combining the implementation of network 
protection strategies with governance solutions and identity access management 
services. The mid-grade European cybersecurity market refers to the protection of critical 
infrastructures and public authorities is quite dispersed, and SMEs play an important role 
here. The large majority of the thousands of European companies active in this area are 
SMEs having a turnover under 5 million  EUR and less than 50 persons. They are highly 
specialised in one area and do not offer the whole range of cybersecurity solutions. These 
SMEs operate in specific niches in domestic markets, with low levels of 
internationalisation.  

An analysis of the French cybersecurity market and actors within it sheds some more 
light on the take-up of SMEs and the role SMEs play in the cybersecurity ecosystem151. 
The French market for cybersecurity solutions is highly polarised, relying on a very few 
big players on the one hand and a galaxy of small, to very small, companies on the other 
hand, with only a few medium-sized companies. SMEs are mainly operating in three sub-
sectors: 1) training, consulting and services; 2) encryption, signature and authentication 

145 Europe an Parliamentary R esearch Service (2017), Achieving a sovereign and trustworthy ICT industry in the 

EU. Published December. Available at: 
http://www.e uroparl.europa.eu/RegData/etudes/STUD/2017/614531/EPRS_STU(2017)614531_EN.pdf  

146 Ibid. 

147 IDC  & Government Insights (2009), The European network  and information security market: Scenario, 

tre nds and challenges. Report prepared for the European Commission. Available at: 
http://ec.europa.eu/information_society/newsroom/cf/dae/document.cfm?doc_id=2153  

148 Ibid.  

149 EC SO  (2017), Position paper: Initial position on the EU cybersecurity package. Report prepared for the 
Europe an Commission. Published October. Available at: http://www.e cs-org.eu/documents/uploads/ecso-
position-paper-on-cybersecurity-package.pdf  

150 EC SO  (2016), European cybersecurity industry proposal for a contractual public-private partnership. 

Published June. Available at: http://ecs-org.eu/documents/ecs-cppp-industry-proposal.pdf  

151 Dire ction Gé nérale des Enterprises (2015), Analyse du marché e t des acteurs de la filière industrielle 
française de sécurité. Published November. Available at: https://www.e ntre prises.gouv.fr/etudes-et-
statistiques/analyse-du-marche-et-des-acteurs-la-filiere-industrielle-francaise-securite  

49 

 
 
                                              
tools; and 3) analysis, detection and mapping tools 152. Whereas many SMEs are 
exclusively focusing on cybersecurity solutions, for the key players dominating the 
market – e.g. Atos, Orange, Airbus, Thales in France - cybersecurity is often only one of 
the several offerings they have in their portfolio.  

A report analysing the United Kingdom cybersecurity market comes to the same 
conclusions, by characterising the market as being complex and fragmented. More 
forward-looking, they state that the cybersecurity market will only become more diverse 
over the next ten years as a much greater array of devices become interconnected and 
the targets for cyber-attacks evolve153. 

2.5.  Barriers and drivers for the take-up of the technologies 

BIC technologies hold significant potential value for European SMEs but unlocking the 
value of these technologies can be cumbersome. While 70% of SMEs realise they need to 
do something now, only 17% knows what to do154. Several different barriers hinder SMEs 
to reap the full benefits of these technologies. Barriers hindering SMEs to benefit from 
new technologies are important to address, as they result in delayed innovation and 
incapacity to adopt new technologies. For instance, with limited abilities to work with 
data analytics, European companies will not be able to compete in global markets and 
SMEs and emerging companies are the ones set to lose the most 155. This section firstly 
describes the barriers for SMEs to adopt BIC technologies, and then zooms in on specific 
barriers for skills development.  

2.5.1.  Barriers for adopting emerging 

technologies 

The most-cited156 barrier for SMEs to adopt (one of) the three technologies is a lack of 
resources. The lack of resources includes shortages of human capital and insufficient 
financial capacity for the technologies and to compensate for the lack of human capital. 
These and other barriers are presented below.  

(1)  Human capital. In general, interviewees indicate Europe has a specialised skills 
shortage relevant to these technologies. People with the most essential skills for 
these technologies are in high demand and cost a premium  to hire. Attracting staff 
with specialised skills is done in competition with large companies that offer 
high(er) salaries. If an SME manages to hire a person with relevant specialised 
skills, retention remains a challenge. Access to skilled labour is t he number one 

152 C ybe rWorld (2017), The French cybersecurity industry: Its role in cre ating a European cybersecurity mark et. 
Published November. Available at: https://cyberworld.news/opinion -analysis/french-cyber-security-industry-
role -cre ating-european-cyber-security-mark et/  

153 Pie rre  Audoin Consultants (2013), C ompetitive analysis of the UK cybersecurity sector. Published July. 

Available at: 
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/259500/b
is-13-1231-competitive-analysis-of-the-uk-cyber-security-sector.pdf  

154 The  Association of Swe dish Engineering Industries and Research Institutes of Swe den (2016), Sve nska 

före tags syn på sin digitalisering. Available at: 
https://www.swe dishict.se/sites/default/files/pub/swe dishict.se/about/rapport -sverige-digitaliserar-2016.pdf  

155 Europe an C ommission (2017), Enter the data economy: EU policies for a thriving data e cosystem. Published 

January. Available at: https://ec.europa.eu/epsc/sites/epsc/files/strategic_note_issue_21.pdf   

156 During the interviews. Se e Annex X for more  details about the interviews.  

50 

 
 
                                              
obstacle to growth for Swedish SMEs 157. Skilled labour is becoming more and 
more a pain: whereas in 2011 just above 20% of Swedish SMEs indicated it as an 
obstacle to growth, this increased to a level of 28% in 2017. To illustrate, only 7% 
of Dutch SMEs indicate that they do have the in-house expertise to work with big 
data158. The skills required to work with data not only refer to the technical skills 
needed, but also interpersonal skills and the more generic expertise to recognise 
the relevance of big data. 

(2) 

(3) 

Financial resources. SMEs have fewer resources to buy new technologies and 
less access to stable revenue. Their return on investment also tends to have a 
larger lag as their customer base tends to be smaller than that of larger 
companies. As a result, they tend to struggle to commit to long-term financial 
investments, which are essential to internalise these technologies. Financial 
constraints also reduce risk-taking by SMEs, as newly acquired technologies are 
costly investments. These investments should be solutions to their current 
problems and leave little room for experimentation.  

Lack of understanding. To benefit fully from BIC technologies, knowing where 
and how to invest is essential. This requires people in strategic positions to 
understand the potential within their business model. This awareness is too often 
lacking. Whilst this holds true for the uptake of any new technology, it appears 
that the complexity of these new data-heavy technologies is a particular 
challenge. SMEs tend to be less aware of the potential and the activities required 
for making for instance optimal use of data. Risk averse behaviour is common, 
‘business as usual’ is favoured and results in a reluctance to experiment and 
invest. If there is an interest in investing in the right people and technologies by 
those in strategic positions in SMEs, they often lack knowledge of what they need 
and how to obtain this. 

(4)  Company size. The adoption of digital technologies varies strongly with company 

size. In Europe, larger companies are much more likely to adopt digital 
technologies such as big data than SMEs 159. As for the big data area, companies 
with an annual turnover less than 250,000 EUR generally do not see the added 
value of using big data. Companies with an annual turnover of over 1 million  EUR 
do not doubt about the relevance of big data for their business.  Growing 
companies also judge the relevance of (big) data more positively 160. 

(5)  Characteristics of the SME owner/manager. Interviewees indicate that tech-

savvy, younger, owner/managers are more inclined to adopt new technologies. 
Examples were provided of situations in which the ownership of a family -owned 

157 Swe dish Agency for Economic and Regional Growth (2018), Situation and C onditions of Enterprises 2017. 

Available at: https://tillvaxtverket.se/vara-tjanster/publikationer/publikationer-2018/2018-02-21-ratt-
k om petens-till-foretagen.html  

158 Van der Ve en, M., Smetsers, D., Van den Born, A. & Bosma, B. (2017), Ondernemen met (big) data door het 

m k b. Kamer van Koophandel and Jheronimus Academy of Data Science . Published January. Available at: 
https://www.k vk .nl/download/20170110%20Rapport%20Ondernemen%20met%20big%20 data%20door%20
he t%20mkb_tcm109-431240.pdf  

159 Europe an C ommission (2017), Integration of digital technology. Available at: 

http://ec.europa.eu/newsroom/document.cfm?doc_id=44392   

160 Van der Ve en, M., Smetsers, D., Van den Born, A. & Bosma, B. (2017), Ondernemen met (big) data door het 

m k b. Kamer van Koophandel and Jheronimus Academy of Data Science . Published January. Available at: 
https://www.k vk .nl/download/20170110%20Rapport%20Ondernemen%20met%20big%20data%20door%20
he t%20mkb_tcm109-431240.pdf  

51 

 
 
                                              
company is transferred from father to son. Personal experience with technology 
drives digital engagement of SMEs161.  

(6) 

Lacking SME ecosystem. The ecosystem of an SME contributes to its knowledge 
of and access to the technologies. Access, interconnection and exchange are 
important. SMEs in general tend to be adopters rather than inventors, unless 
research and innovation is their core business. While large companies may have 
innovation departments or in-house/co-funded incubators, SMEs tend not to be 
involved in the research and development of new technologies if it is not their core 
business. The following aspects of their ecosystem may influence an SME and its 
uptake of the technologies: 

(b) 

(a) 

SMEs that are primarily focused on research and innovation, and that work 
closely with academia and research organisations, have an advantage that 
makes them more likely to have the required skills to uptake the 
technologies; 
SMEs that are close to industrial clusters, or work for or with larger 
companies or other (public -private) partnerships are more likely to have 
access to up-to-date information and training. This makes them more likely 
to understand the benefits of the technologies (spill over effect);  
SMEs tend to be linked strongly in value chains, whereas larger companies 
are more likely to internalise functions. Such value chains create 
dependencies for SMEs, including risks of losing (part of) their position if 
they adapt to technologies that others do not wish to use. 
(7)  Privacy and security concerns. Privacy and security concerns may restrain 

(c) 

companies from adopting emerging technologies. 34% of the small  business in the 
US stated that privacy and security concerns are among their top three barriers to 
digital engagement 162.  

The above barriers  apply  to all  three technologies considered in  this initiative. Barriers 
specific for each of the respective technologies are discussed in the following sections.  

Figure 2-2124   

161 De loitte (2017), C onnecting small businesses in the US. C ommissioned by Google. Available at: 

https://www2.de loitte.com/content/dam/Deloitte/us/Documents/technology-media-telecommunications/us-
tm t-connected-small-businesses-Dec2017.pdf  

162 De loitte (2017), C onnecting Small Businesses in the US. Report pre pared for Google. Available at: 

https://www2.de loitte.com/us/en/pages/technology-media-and-telecommunications/articles/connected-small-
businesses.html  

52 

 
 
 
 
 
                                              
2.5.1.1.  Specific barriers for adopting big data 

Zooming in specifically on big data, a Dutch study focusing on the take -up of big data 
shows that in addition to the more generic barriers of respectively financial restraints, 
time restraints and a lack of expertise, data quality is also among the obstacles hindering 
SMEs to work with big data (figure 2-21). Releasing data and having a sufficient technical 
infrastructure in place are expected to be difficult.  

W H I CH   D I F F I CULT I E S   D O  YO U  ( E X P E CT  T O )  
FA CE   W H E N  W O R K I N G  W I T H  ( B I G )   D ATA?

Privacy concerns

Insufficient technical infrastructure

Difficulties with making data available

Limited quality of the data

Lack of expertise to analyse data

Lack of time to work with data

Lack of resources to invest in this area

0%

10%

20%

30%

40%

50%

60%

Highly likely

Likely

Slightly likely

Figure 25 Difficulties  faced by SMEs  when working with big data 163 

Furthermore, the 2016 paper ‘How Can SMEs Benefit from Big Data? Challenges and a Path 
Forward’164 lists  14  factors that condition the poor adoption of  business and  big  data 
analytics by SMEs, and they indicate the extent to which these barriers are related to what 
they classify as ‘specific people and skills’. Among the barriers moderately related to people 
and skills  are cultural barriers, shortage of affordable consulting and business analytics 
services, a non-transparent software market, a  lack of intuitive software, and financial 
barriers. The four barriers classified as ‘highly related to specific people and skills’ are the 
following165: 

(1)  Dominance of domain specialists. As operating in a niche or specialised field is 
a strength of SMEs, the major part of the employees are domain specialists, with 
more generic functions poorly covered. This is not beneficial for spotting new 
business opportunities and trends outside of the respective domain, such as big 
data analytics.  

(2)  Shortage of in-house data analytic expertise. SMEs lack own employees with 
data analytics capabilities. In an Austrian survey166, a lack of in-house data 

163 Van der Ve en, M., Smetsers, D., Van den Born, A. & Bosma, B. (2017), Ondernemen met (big) data door het 

m k b. Kamer van Koophandel and Jheronimus Academy of Data Science . Published January. Available at: 
https://www.k vk .nl/download/20170110%20Rapport%20Ondernemen%20met%20big%20data%20door%20
he t%20mkb_tcm109-431240.pdf  

164 C oleman, S., Göb, R., Manco, G., Pievatolo, A., Tort-Martorelle, X. & M. Se abra R eis (2016), How C an SMEs 

Be ne fit from Big Data? C hallenges and a Path Forward. Quality and Reliability Engineering International, 
Spe cial Issue Article. https://doi.org/10.1002/qre.2008  

165 Ibid. 

166 R ussegger, S., Fre udenthaler, B., Güntner, G., Kieseberg, P., Stern, H. & F. Strohmeier (2015), Big Data 

und Data-driven Business für KMU. Digital Ne twork ed Data. Published May. Available at: 
https://www.salzburgresearch.at/wp -content/uploads/2015/06/Bericht-Roadblocks_final.pdf  

53 

 
 
 
 
                                              
analytics expertise was identified as a major barrier in the take-up of big data 
projects. Several factors play a role here 167: 

(a) 

High set-up costs, c ombined with uncertainty about future return 
on investments; 
Lack of management expertise to set up and embed a data 
analytics unit; 
Shortage of qualified workers and excessive staffing costs.  
(3)  Bottlenecks in the labour market. There is a growing shortage of qualified data 

(b) 

(c) 

analysts on the labour market. IDC studied the European data landscape, and 
forecasts that the structural imbalance between demand and supply will result in a 
data skills gap in 2020168.  

(4) 

Lack of understanding. A recent e-Skills survey in the UK169 highlights an 
extremely low understanding of big data analytics by SME representatives, 
whereas among larger organisations, around 30% to 40% claim to have good or 
very good understanding of big data analytics. A recent Germany survey 170 
portrayed a similar  picture, with around 30% of respondents considering their big 
data knowledge to be good or very good.  

2.5.1.2.  Specific barriers for adopting IoT 

The potential of IoT often is not realised. There are a number of reasons for this, of which 
security concerns and constrained analytical capabilities are amongst the most pressing 
barriers171. For IoT, SMEs need strong technological competences 172. First, sensors 
increasingly generate huge volumes of data at a real-time basis. Companies would need 
a robust analytics platform to benefit from the growing volumes of structured and 
unstructured data – including the ability to ‘clean’ the unstructured data. Second, they 
need advanced analytics, and increasingly AI capabilities, ranging from descriptive to 
prescriptive analytics. Descriptive analytics are used to gain a granular view of the 
specific process that is being measured and monitored, and prescriptive analytics and AI 
to learn from past patterns and to anticipate on future developments. Third, the adoption 
of a ‘security-by-design’ approach is crucial to address cybersecurity threats. 

IDC & TXT 173 state that ensuring SMEs’ capability to enter the IoT market is a key 
challenge. Various obstacles need to be overcome: insufficient investments, 
organisational barriers to change, concerns about privacy and data protection, 

167 C oleman, S., Göb, R., Manco, G., Pievatolo, A., Tort-Martorelle, X. & M. Se abra R eis (2016), How C an SMEs 

Be ne fit from Big Data? C hallenges and a Path Forward. Quality and Reliability Engineering International, 
Spe cial Issue Article. https://doi.org/10.1002/qre.2008 

168 IDC  (2017), European Data Market Study Final R eport SMART 2013/0063. R eport prepared for the European 

C om mission. Available at: http://datalandscape.eu/  

169 E-Sk ills UK (2013), Big Data Analytics Adoption and Em ployment Trends, 2012 -2017. Available at: 

https://www.the te chpartnership.com/globalassets/pdfs/research -2013/bigdataanalytics_report_nov2013.pdf  

170 Vossen G, Lechtenbörger J, Fekete D. (2015), Big data in kleinen und mittleren Unternehmen - eine 
e m pirische Be standsaufnahme. W estfälische Wilhelms -Universität Münster, Germany. Available at: 
http://www.wi1.uni-m uenster.de/pi/iai/publikationen/BigData.pdf  

171 C apgemini (2018), Unlocking the business value of IoT in operations. Available at: 
https://www.capge mini.com/wp -content/uploads/2018/03/dti-research_iot_we b.pdf 

172 Ibid.  

173 Europe an C ommission (2015), Definition of a re search and innovation policy le veraging cloud computing and 
IoT combination. Published May. Available at: https://ec.europa.eu/digital-single-market/en/news/definition-
re se arch-and-innovation-policy-leveraging-cloud-computing-and-iot-combination  

54 

 
 
                                              
mismanagement of new security risk, and a lack of standards and interoperability across 
fragmented European markets – preventing economies of scale. Other barriers identified 
by Ericsson174 include the lack of a convincing business case, security concerns and risks 
associated with change. A lack of qualified personnel is also among the barriers, and 
refers not only to the technical perspective, but also to difficulties with evaluating the 
value capture of IoT. The Internet of Things Business Index175 highlighted a lack of IoT 
skills and knowledge as one of the top-three barriers holding businesses back from 
adopting IoT.  

Adding to the above, in 2018 Capgemini176 stated that the potential value associated with 
IoT is often going unrealised. IoT initiatives do not achieve their goals or reach a 
meaningful scale, with initiatives remaining stuck in a proof-of-concept stage. This is 
mainly the result of the inability to establish a clear business case, security concerns, 
constrained analytical capabilities and uncertainty about IoT standards and protocols.  

2.5.1.3.  Specific barriers for adopting cybersecurity 

There are various specific barriers for the adoption of cybersecurity by SMEs. This is 
problematic not only because SMEs are already vulnerable to cyber threats, but also 
because security concerns are barriers for the adoption of both big data and IoT. The use 
of these new technologies brings new opportunities, but also introduces information 
security and privacy risks. T here are many dimensions to effective cybersecurity and 
data protection—from strategy and operations, to governance and culture—but one of 
the biggest problems is simply the lack of talent 177. Those companies that attract and 
retain cybersecurity talent will be much more successful in managing digital risk and 
profiting from big data and IoT. In 2015, ENISA stated that despite rising concerns on 
information security risks, the level of SMEs’ information security and privacy standard 
adoption is relatively low178. The report clusters the barriers that contribute to the limited 
uptake of cybersecurity practices by SMEs in four categories 179:  

  Knowledge and engagement: awareness of standards, limited awareness of how 
standards add business value, prevailing perception that cyberattacks are mainly 
threatening large enterprises, design of standards mainly driven by larger 
enterprises; 

  Capabilities and resources: the implementation of information security and privacy 
standards can be demanding in terms of financial resources. For SMEs that have 
internalised the ICT function, often one employee is responsible for security along 
with his/her other ICT responsibilities, resulting in limited time and dedication for 

174 Ericsson, Deloitte & DI Digital (2015), Every. Thing. C onnected. A study of the adoption of ‘Internet of 

Things’ among Danish companies. Published July. Available at: 
https://digital.di.dk/SiteCollectionDocuments/Analyser/IoT_R eport_onlineversion.pdf  

175 The  Economist (2017), The Internet of Things business index 2017. Available at: 

https://www.e iupe rspectives.economist.com/sites/default/files/EIU-ARM-
IBM%20IoT%20Business%20Index%202017%20copy.pdf  

176 C apgemini (2018), Unlocking the business value of IoT in operations. Available at: 
https://www.capge mini.com/wp -content/uploads/2018/03/dti-research_iot_we b.pdf 

177 C agemini (2017), Cybersecurity talent: The big gap in cyber protection. Available at: 

https://www.capge mini.com/wp -content/uploads/2018/02/the-cybersecurity-talent-gap-v8_we b.pdf  

178 ENISA (2015), Information security and privacy standards for SMEs. Recommendations to improve the 
adoption of information security and privacy standards in small and medium enterprises. Available at: 
https://www.e nisa.europa.eu/publications/standardisation-for-smes/at_download/fullReport 

179 Ibid.  

55 

 
 
                                              
security practices. SMEs that have outsourced the ICT function may suffer from 
limited internal knowledge about cyber threats; 

  Shortage of standards in specific areas: there are limited European or 

international standards designed to assist small organisations towards ensuring 
appropriate protection of personal data; 

 

Implementation aspects: Standards are often hard to understand for SMEs not 
having the inhouse expertise for translating standards into specific tasks and 
activities. Especially when there is a lack of clear implementation guidelines.  

Digital transformation cannot take place without a solid cybersecurity approach. The 
more a company becomes dependent on ICT and the more a company embraces 
emerging technologies such as big data and IoT, the more crucial cybersecurity becomes. 
Moreover, measures aimed at addressing the barriers for cybersecurity will also positively 
affect the take-up of big data and IoT.  

2.5.2.  Barriers for skills development within 

SMEs 

The previous section made clear that the availability of the necessary skills is one of the 
top barriers for SMEs to adopt emerging technologies. To boost further specialised skills 
development, it is not only necessary to ensure that future professionals become 
educated in these areas, but also current employees will need to develop their skills 
portfolio. To keep their skills relevant, employees will need to keep learning during their 
career. There are concerns about lifelong learning and education and training of grown-
ups. For instance, in 2016, only 10.8% of adults aged between 25 and 64 years old 
participated in education and training180. Just under half (45%) of all persons employed 
by medium-sized enterprises and 46% of those employed by small  enterprises 
participated in vocational training programmes in 2010181. Larger enterprises are far 
more likely than SMEs to provide training to their persons employed (figure 2-22).  

E N T E R P R I S E S   T H AT   P R O V I D E   T R A I N I N G   T O   T H E I R  
P E R S O N S   E M P L O Y E D ,   BY   S I Z E   C L A S S ,   E U - 28,   2016  ( %  
E N T E R P R I S E S )

80

60

40

20

0

s
e
s
i
r
p
r
e
t
n
e
f
o
%

Provide training to ICT specialists

Provide training to other persons employed

Small and medium enterprises

Large enterprises

Figure 26 Enterprises  that provide  training182 

180 Eurostat (2017), Lifelong learning, 2011 and 2016. Available at: http://ec.europa.eu/eurostat/statistics-

e x plained/index.php?title=File:Lifelong_learning,_2011_and_2016_(%C2%B9)_(%25_of_the_population_age
d_25_to_64_participating_in_education_and_training)_YB17.png  

181 Eurostat (2017), Vocational education and training statistics. Available at: 

http://ec.europa.eu/eurostat/statistics -explained/index.php/Vocational_education_and_training_statistics  

182 Eurostat (2018), ICT specialists - statistics on hard-to-fill vacancies in e nterprises. Published May. Available 

at: http://ec.europa.eu/eurostat/statistics -explained/index.php/ICT_specialists_-_statistics_on_hard-to-
fill_vacancies_in_enterprises   

56 

 
 
 
 
 
                                              
 
 
When trying to meet their need for skills development, European SMEs face several 
barriers. These barriers can be c lustered into three categories: SME internal barriers and 
obstacles for training, finding suitable methods and techniques for training and coping 
with current and structural challenges of competence development 183. Concerning SME 
internal barriers, the barriers hindering SMEs most are the following:  

(1)  Organisational barriers. Company owners struggle with organising training for 
their employees especially within smaller firms, where each employee is needed 
every day, and where the absence of an employee directly impacts the daily 
operations; 

(2) 

Financial barriers. Sending employees to (external) trainings has a financial 
impact on a company. They might not only need to pay for the training itself, but 
the absence of employees can also have an impact on revenues. It is difficult for 
micro businesses and small firms to find the financial resources needed to offer 
training to their employees184.  

(3)  HR and skills development policy. Compared to larger enterprises, HR 

processes and skills development are not organised in a systematic way or with a 
long-term approach within SMEs. This might hamper a continuous focus on skills 
development.  

(4)  Perception of training needs. SME owners do not always perceive training as 

important. This might have to do with cultural particularities of a certain sector, a 
lack of opportunities or a lacking long-term approach, with SME owners not seeing 
the direct benefit of training. Training is often done informally on the job. For 
SMEs, it is difficult to determine the quality and alignment of training offerings to 
their needs.  

(5)  Resource pooling and SME cooperation. The involvement in networks, 
cooperation or cluster activities enable SMEs to engage more effectively in 
ongoing training and skills development. However, solid SME networks or clusters 
are not yet reality everywhere across Europe, and it requires managerial 
capabilities to become anchored in such networks.  

With regards to suitable methods and techniques for training, the barriers hindering SMEs 
most are the following: 

(1) 

(2) 

Training methods often do not fit the specific needs of SMEs. Training 
programmes and methods available on the market are too often unsuited to the 
size and needs of SMEs185, both in content and in form.  

Lack of training and competence development for managerial staff. The 
smaller a company, the more the performance of such a company is dependent on 
the owner or manager. The continuous development of skills and knowledge of 
managers is therefore of crucial importance. As compared to managers in larger 
companies, those in SMEs less often have an initial training period in management 

183 Europe an C ommission (2009), Guide for training in SMEs. Available at: 

http://ec.europa.eu/social/BlobServlet?docId=4202  

184 Europe an C ommission (2009), Guide for training in SMEs. Available at: 

http://ec.europa.eu/social/BlobServlet?docId=4202  

185 Ibid. 

57 

 
 
 
                                              
schools186. In the current rapidly evolving business environment, continuous 
upskilling might be needed to meet changing demands.  

(3)  Recognition of skills and competences is challenging. Informal learning 

processes are an important means to boost further firm performance in SMEs. At 
the same time, documenting informal learning might be challenging. 
Documentation of learning leads to increased confidence. For individual 
employees, the recognition and validation of learning experiences is also 
important since it enhances their opportunities on the labour market 187. 

With regards to addressing current and structural challenges of competence 
development, the most important barriers are the following:  

(4)  Demographic change. The European workforce is greying. Consistently low birth 
rates and higher life expectancy are transforming the shape of the EU’s age 
pyramid188. Age management has become a challenge for companies in general, 
and in particular for SMEs.  

(5) 

Against the background of demographic change, many SMEs struggle with 
retaining a qualified workforce and attracting new qualified talents189. The ‘digital 
native’ millennial  generation will make up 75% of the workforce by 2020, but is 
difficult to retain as employees. A benefit SMEs have is that whereas only 18% of 
millennials  believe large businesses are the ideal employer, 47% of millennials  are 
more willing to work at an SME than at a larger company 190.  

(6) 

Internationalisation. The emergence of global value chains forces SMEs to 
adapt themselves to global competition and allows them to benefit from new 
opportunities. Acting on a global playing field requires particular skills, for instance 
with regards to language, communication and cultural sensitivity.  

2.5.3.  Synthesis 

The above three clusters of barriers for skills development emphasize that skills 
development is not straightforward for SMEs. Participating in training courses not only 
depends on internal factors such as capacity and financial resources, but also on the ‘fit’ 
between SME training demands and courses available on the market, and external 
factors such as internationalisation and demographic change. Hence, measures 
addressing skills development within SMEs should be developed from a holistic viewing 
point, taking into account various categories of barriers. Based on the above, seven 
categories of barriers can be identified, all containing multiple specific barriers. These 
barriers are explained in more detail in Table 5. 

186 Ibid.  

187 Ibid.  

188 Eurostat (2018), Population structure and ageing. Published May. Available at: 

http://ec.europa.eu/eurostat/statistics -explained/index.php/Population_structure_and_ageing  

189 Europe an C ommission (2009), Guide for training in SMEs.  Available at: 

http://ec.europa.eu/social/BlobServlet?docId=4202  

190 McMath (2017), Millennials will m ake up 75% of the work force by 2020. Published November. Available at: 

https://blog.sodexoengage.com/big-businesses-vs-sme  

58 

 
 
 
                                              
Figure 27 Synthesis  of barriers  for skills  development in  SMEs 

Cluster 

Explanation barriers 

1. Content: Available trainings not tailored to specific needs of SMEs, e .g. too 
the ore tical, not focusing on BIC specifically, in other languages; 

A .  
Training 
offerings 

2. Form: Trainings are delivered in formats not always suitable for SMEs, e.g. too long, 
during work -hours, balance online/offline, e tc.; 

3. Costs: Available trainings are often too costly for SMEs, who have to prioritise their 
inve stments because of limited financial resources; 

B. 
A ccess to 
guidance,  
education & 
training 

C.  
Tech 
maturity 

D.  
Financial 
resources 

4. Standardisation & recognition competences: Available trainings are not part of 
wide ly acce pted framework. Informal le arnings processes are important for SMEs, but 
the se le arning experience s are  not documented / validated.  

1. Findability: If trainings, tools and information are  available, they are not always 
findable by SMEs and not made available at ‘natural’ place s SMEs go; 

2. A vailability: Spe cific trainings, tools and information in the area of BIC technologies 
are  not always available for SMEs; 

3. Fragmentation: Guidance & training is sometimes available, but highly fragmented 
across Europe: in some re gions, e xtensive support structures exist whe reas in other 
re gions hardly any information, tooling, training or other support is available.  

1. Internal – tech savvy: A lack of te ch savviness of SME m anager/owners leads to 
m anager/owne rs not understanding the value of BIC te chnologies, or not re cognising the 
se nse of urgency to adopt BIC. Lack of tech savviness also contributes to 
m anagers/owne rs not k nowing what types of products and services are appropriate to 
buy for the ir business. The lack of standards m akes this e ven more  complicated. It also 
m ak es SMEs dependent; 

2. Internal – operational focus: Too often, SMEs focus on the short te rm, on business 
as usual, and lack a long-term vision (e.g. on te chnology); 

3. External infrastructure: An e xternal infrastructure focusing on the take up of 
e m e rging te chnologies (e.g. open data, APIs, open source  solutions) m ight incentivize 
SMEs to de velop the skills needed to adopt BIC. 

4.Dependency on external contractor: Le ss capacity to test and try out (linked to 
ge neral financial risk above) and less k now-how on negotiation of contract terms for 
se rvice  level agreements, thus a higher risk of agreeing to unfavourable or unnecessary 
one s. 

1. Limited financial resources: It is difficult for SMEs to find the financial re sources 
ne e ded to offer training to their e mployees; 

2. A vailability of funding: Support in the form of funding has proven to be e ffective 
(e .g. Skillnet IE), but is not e qually available throughout the EU; 

3. A ccess to funding: If funding is available, SMEs m ight not be aware  or do not know 
how to ge t access to funding. Being connected or embedded in network s facilitates access 
to funding; 

4. Indirect Return on Investment (ROI): SMEs have limited financial resources. The 
re turn on training investments tends to have a re latively large lag. As a re sult, they tend 

59 

 
 
 
 
 
Cluster 

Explanation barriers 

to struggle to commit to long-term financial investments, which are e ssential to 
inte rnalise BIC technologies. 

1. Labour market: the availability of specialised BIC skills are scarce  on the market; 

2. Competitiveness on labour market: To attract talents, SMEs need to compete with 
big corporates who can afford higher salaries. At the same time, SMEs might benefit from 
‘m ille nnials’ who might appreciate the flexibility, agility and start-up culture  of SMEs; 

E.  
Human 
resources 

3. Retention: Eve n if one is able to attract BIC talents, re tention re mains a challenge in 
today’s competitive labour mark et; 

4. Leadership: The  smaller a company, the m ore the performance of such a company is 
de pendent on the  owne r or m anager. The continuous de velopment of the ir sk ills and 
k nowle dge is of crucial importance; 

5.  Greying  workforce: Age  m anagement has be come a challe nge for com panies in 
ge neral, and in particular for SMEs  

1. HR  department: HR  proce sses and skills de velopment are  often not organised in a 
syste matic way or with a long-term approach within SMEs; 

2. A wareness roles required: Pe rce ption and awareness of roles re quired to build the 
capabilities to adopt BIC; 

F. 
A wareness 
skills needs 

3.  A wareness  skills  needed:  Pe rce ption  and  aware ness  of  com pe tences  re quired 
(training needs) per role. Standardisation of roles;  

4.  Standardisation & recognition  competences: Available trainings are  not part of 
wide ly acce pte d framework. Informal le arnings processes are  im portant for SMEs, but 
the se le arning experience s are  not documented / validated; 

5. A wareness make-or-buy decision: Difficulties with decision to internalise skills or to 
hire  sk ills on the m arket – lack  of standardisation. This cre ates difficulties in professional 
com m issioning. 

1. A vailability networks: The  involvement in network s, cooperation or cluster activities 
e nable SMEs to e ngage m ore effectively in ongoing training and skills development; 

2. Structured approach: Availability of support structure s throughout the EU. Currently 
fragm ented and not coordinated at EU level;  

G.  
Ecosystem / 
network 

3.  A vailability  facilities:  Facilities for te sting and le arning (e .g. incubators) are  not 
always available; 

4. Organising shared services: Share d services (pooling of companies) within a network 
can be  beneficial, but can be perce ived as difficult to organise; 

5. A vailable knowledge: both tacit and e xplicit k nowle dge cannot always tapped in to 
(pe e rs, knowle dge institutes, big corporates);  

6.  Managerial  capabilities:  SME  m anager/owne rs ne e d to  have  the  capabilities to 
be come anchored in network s/clusters/ecosystems. 

60 

 
 
 
 
 
 
 
3.  SKILLS  REQUIREMENTS  RELATED  TO  BIG  DATA,  INTERNET  OF  THINGS  AND 

CYBERSECURITY 

The previous section underlined that lack of access to skills is one of the top barriers 
hindering SMEs to adopt BIC technologies. However, what are actually the competences 
needed to work with these technologies, and where is the mismatch between the skills 
needed by SMEs and the skills available most prominent? This chapter firstly describes 
generic and overarching skills needed to work with BIC technologies. It then zooms in on 
the specialised skills needed to work with each of the three technologies, by  presenting 
specific skills profiles (section 3.2 – 3.4). This chapter concludes with describing skills 
gaps in section 3.5: areas where demand and supply for specialised skills do not match 
and where action is needed.  

3.1.  Generic skills 

In general, skills requirements are evolving fast. The technological landscape changes 
rapidly, with skills requirements changing accordingly. Businesses are already having 
difficulties finding the right people. In 2015, 40% of businesses in the EU reported having 
difficulties in finding employees with the right skills191. This might even become worse in 
the near future, as 9 out of 10 jobs will require digital skills 192, and currently only 57% of 
Europeans has a basic level of digital skills 193.  

As for the actual uptake of big data, IoT and cybersecurity, interviewees stress the 
importance of technological expertise (‘hard’ skills), soft skills (or personal, transversal 
skills) and business expertise and the combination thereof. These skills areas  are 
summarised in figure 3-1.  

Figure 28 Skills  areas needed and examples of specific skills194 

191 C e defop (2015), Skill shortages and gaps in European Enterprises. Available at: 

http://www.ce de fop.europa.eu/files/3071_en.pdf 

192 Europe an C ommission (2017), The digital skills gap in Europe. Published O ctober. Available at: 

https://ec.europa.eu/digital-single-market/en/news/digital-skills-gap-europe  

193 Ibid.  

194 Base d on desk research and interviews  

61 

 
 
 
 
                                              
Hard skills refer to the mere technical skills needed to work with big data, IoT and/or 
cybersecurity. These skills are often highly specific in nature and particular to an 
occupation195. An example is the ability to acquire, structure and clean data for analysis. 
The analysis and subsequent ability to extract insights and value from data is also a hard 
skill, including working with tools such as SQL, Hadoop and Python. Typical jobs requiring 
a deep technical expertise include software engineers, programmers, data scientists, 
algorithm developers and security specialists.  

Soft skills are transferable skills that everyone has and that everyone uses, like the 
ability to work in a team, leadership, creativity, collaboration, the ability to establish 
partnerships, communication skills and problem-solving196. They are also called 
transversal skills, or (inter)personal skills. 

Business expertise refers to a set of skills essential to run a business, such as a basic 
knowledge of financial accounts, business development skills and risk management, the 
ability to form business and skills development strategies in a company, the ability to 
select appropriate and relevant technologies, and domain knowledge (e.g., 
understanding a specific market).  

The importance of both hard skills, soft skills and business expertise is in line with 
conclusions drawn from the literature. A French study 197 for instance distinguishes three 
core skills areas for working with cybersecurity: technical skills (e.g., protection of 
applications, access and identity management, security audit), functional skills 
(information protection, business continuity management, cybersecurity supervision) and 
transferable skills (adaptability and flexibility, confidentiality, intellectual curiosity). 
Furthermore, in the UK, small businesses consider technical skills, communication skills 
and self-management skills the most important skills for the future growth of their 
business. In ICT-related fields, research in the UK identified five different skill sets 
required in future employees: Security skills; business skills (balancing technical skills 
with wider business objectives); technology-specific skills; interpersonal skills; and 
analytical/research skills (e.g., to interpret operational data) 198. Small businesses 
consider technical skills as most important for the future growth of their company.  

195 Eqave t (n.d.), Soft skills. Available at: https://www.e qavet.eu/eu-quality-assurance /glossary/soft-skills  

196 UNESC O  (2016), Glossary article: soft skills. Published December. Available at: 

https://unevoc.unesco.org/print.php?q=Glossary+article:+soft+skills  

197 O PIIEC (2017), Les formations e t les compétences en France sur la cybersécurité. Available at: 

https://www.fafie c.fr/images/contenu/menuhaut/observatoire /etudes/2017/cybers%C3%A9curit%C3%A9/21
-05-2017_Etude_cybersecurite_infographie.pdf  

198 E-Sk ills UK (2012), Technology insights 2012. Available at: 

https://www.the te chpartnership.com/globalassets/pdfs/research -
2012/technologyinsights_2012_ni_15jan13.pdf  

62 

 
 
                                              
Figure 29 Skills  SMEs consider  most important  to their  future growth  (2017) 199 

This is not entirely consistent with the view of interviewees. In general, they confirm the 
need for technically skilled workers, but they tend to put even more emphasis on the 
importance of soft skills and business expertise. Business expertise in this co ntext refers 
among others to the ability to understand the basics of emerging technologies and its 
implications for an SME’s business model. Furthermore, experts argue that for SMEs, soft 
skills might be even more important than for larger enterprises. As SMEs might have 
difficulties with attracting digital talents due to limited financial resources, they might 
overcome this competitive disadvantage by connecting and collaborating with others 
(more on skills  strategies in section 4). This requires the skills to connect, communicate, 
establish partnerships and to work together.  

199 Pe ate, A. (2017), Learning the ropes: Skills and training in small businesses. Published De cember. Available 

at: https://www.fsb.org.uk/docs/default-source /fsb-org-uk/skills-and-training-report.pdf?sfvrsn=0 

63 

 
 
 
 
 
 
 
                                              
BIC technologies 

SMEs suffer from a lack of both ICT specialists and e-leaders 

In the future, 9 out of 10 jobs will require digital skills.  

However, evidence shows that today, only 57% of Europeans has sufficient 
basic digital skills.  

There were 8.2 million  ICT specialists in the EU in 2016, up from 7.3 million  3 
years earlier. However, the supply of ICT  specialists cannot keep pace with demand: it 
is estimated that there will be over 500,000 unfilled vacancies for ICT professionals by 
2020 

For e-leaders, it is estimated that there will be a gap of up to 250,000  
e-leaders by 2020 in Europe. Around 70% of e-leaders are found in 
SMEs. 

Specifically,  for BIC technologies,  the situation  is even worse 

Data specialists accounted for (far) 
less than 1% of total employment in 
most Member States, but demand for 
data specialists is increasing fast. 

Data 

In the UK, the demand for ‘big data’ 
specialists is forecasted to  increase by 
160% between 2013 and 2020,  and 
estimated to represent an additional 
346,000 big data jobs  

64 

 
 
 
 
Another lesson drawn from the interviews is that SME managers/owners tend to 
overestimate the complexity of big data technologies. They may associate big data with 
enormous datasets and complex algorithms in a programming  language most people do 
not understand. This can be the case, but data analytics is not necessarily about complex 
algorithms. For an SME, even a basic Excel sheet combining customer characteristics and 
sales data can be used to derive valuable insights from. Various sources suggest curiosity 
is the main skill  that people working with data should possess200 201. This again underlines 
the importance of soft skills. Domain knowledge is then necessary to derive insight from 
the data and understand the implications 202.   

Taken together, persons working with these technologies needs to possess a diverse 
range of interdisciplinary skills, which are difficult to find united in a single person. The 
importance of interdisciplinary skills is also reflected by the increasing demand for so -
called “T-shaped professionals”203. These professionals possess a deep knowledge about a 
specific area of expertise and have the ability to apply knowledge across multiple 
situations.  

The “T-shaped Professionals” are in high demand for their ability to innovate, advance 
research, build relationships and strengthen their organisation. They are sought after 
because of problem complexity and the pace of change. Complexity means the number of 
areas of knowledge that must be combined to solve problems is growing. Almost every 
unsolved problem today requires different disciplines - engineers, managers, behavioural 
and social scientists, communications, and policy makers – to work together204. The T-
shaped professional can be recognised for two main characteristics: 

  Depth of knowledge - The vertical stroke of “T” represents the knowledge of the 

person in the respective field (discipline, system). The c urrent education system is 
mainly producing I-shaped professionals with disciplinary knowledge about a 
particular industry. To understand the system, one must know how it functions 
from top to bottom. They must have intelligence regarding analytical thinking & 
problem solving. 

  Breadth of expertise - The horizontal stroke of “T” represents the ability to apply 
knowledge across multiple situations. It is made up of empathy and enthusiasm 
about other people’s disciplines. To create an innovative and creative process one 
has to be actively part of a wide range of activities with the industry that 
acknowledges particular expertise. It requires skills such as teamwork, 
communication, networking, critical thinking, and project management.  

200 C alugar, O. (2015). The curiosity advantage: the most important skills for data science. Published July. 

Available at: https://conferences.oreilly.com/strata/big-data-conference-uk-
2015/public/schedule/detail/39814  

201 Dave nport, T. H. & Patil, D. J. (2012). Data scientist: The sexiest job of the 21st ce ntury. Published October. 

Available at: https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century  

202 C arrara, W., Fischer, S., & Van Ste enbergen, E. (2015), Analytical report 2: E-skills and open data. 

Published December 2015. Available at: 
https://www.e uropeandataportal.eu/sites/default/files/edp_analytical_report_n2_-_e-skills.pdf 

203 C ride r, K. (2015), Bridging the gap to the future by investing in T-shaped professional development. 

Published November. Available at: https://trainingindustry.com/articles/it-and-technical-training/bridging-the-
gap-to-the-future -by-investing-in-t-shaped-professional-development/  

204 J.C . Sphore r, e Skills Manifesto 2016  

65 

 
 
                                              
There are several reasons why T -shaped professionals are valuable to businesses 206: 

Figure 30 The T-shaped professional205 

  T-shaped professionals are willing to keep on learning to keep their skills 

up to date; 

  They are empathetic, which allows them to tackle problems from different 

perspectives – which is useful for smooth collaboration in a team; 

  They have the analytical skills necessary to find solutions with a broad vision;  

  They are good at solving problems because of their combination of wide 

knowledge and specialised expertise; 

  T-shaped professionals are able to innovate, advance research, build relationships 

and strengthen their organisation. 

These T-shaped professionals might  be  even more  relevant for  SMEs  than  for  larger 
enterprises, as a single person might have to fulfil different roles within an SME because 
of SMEs’ limited human resources.  

This initiative focuses specifically on the skills requirements for three different roles within 
an SME, being managers, IT professionals and advanced users: 

  Managers: Small business owner/managers who are responsible for managing 

(parts of) their company. Management is commonly defined as the alignment and 
coordination of multiple activities in an organisation207; 

 

IT professionals: those who have the ability to develop, operate and maintain ICT 
systems and for whom ICTs constitute the main part of their job 208; 

205 C are ers Unbound (2016), Hiring T-shaped professionals to build collaborative teams. Published March. 
Available at: http://www.care e rsunbound.com/hiring -t-shaped-professionals-build-collaborative-teams/ 

206 C are ers Unbound (2016), Hiring T-shaped professionals to build collaborative teams. Published March. 
Available at: http://www.care e rsunbound.com/hiring -t-shaped-professionals-build-collaborative-teams/  

207 Vite z, O. (n.d.), The definition of small business management. Available at: 

http://smallbusiness.chron.com/definition-small-business-management-3994.html  

208 O EC D (2005), Ne w pe rspectives on ICT skills and e mployment. Published  April. Available at: 

http://www.oe cd.org/internet/ieconomy/34769393.pdf  

66 

 
 
 
 
                                              
  Advanced users: competent users of advanced, and often sector-specific, software 

tools. ICTs are used as a tool for these users but are not their main job209. 

With regards to BIC technologies, interviewees state that managers should at least possess 
a basic knowledge of the implications of emerging technologies and the solutions available. 
At the same time, as a manager does not have to be a qualified accountant to understand 
financial accounts, they do not need highly specialised skills to understand the implications 
of new technologies. 

As  for  both  IT  professionals and  advanced users, interviewees argue  that their  skills 
requirements are evolving. Whereas in the past, they were highly specialised in a specific 
software tool  and  used  to  work  for  years  with  the  same  software, they should  now 
increasingly be  able  to possess a helicopter view, as  technology evolves fast and new 
ready-to-use solutions become easily available. For many IT professionals, this implies a 
shift from  operational services to strategic services. This means  that they can monitor 
market developments, assess the usefulness of new solutions and provide advice relevant 
to the business model of their organisation. 

In  general,  working  with  BIC  technologies  requires  closer  collaboration between  the 
manager, the IT professional and the advanced user. Interviewees state that too often, 
managers  and  IT  professionals do  not  speak  the  same  langua ge.  On  the  one  hand, 
managers would need a digital strategy mindset, whereas IT professionals would need the 
technical skills but also a basic level of business understanding. Managers should be able 
to identify and organise the right processes and products, whereas IT professionals and 
advanced users should be able to provide on the one hand advice about solutions to be 
used within  these projects and processes, and on  the other hand  to implement  these 
solutions.  

3.2.  Specific skills 

This section focuses on the specific skills needed to work with BIC technologies. To 
provide the foundation for the actual assessment of skills gaps, skills profiles can be 
developed for each of the three focus domains. The key competence areas that 
employees in SMEs should obtain t o successfully work with one of the three technologies 
can be defined, further specified by using the European e-Competence Framework (e-
CF). This is a common framework for ICT Professionals in all industry sectors. It provides 
a reference of 40 competences as applied at the Information and Communication 
Technology (ICT) workplace, using a common language for competences, skills, 
knowledge and proficiency levels210. Each key competence area is further detailed with 
the relevant e-CF competences, specifying for each target user the required level of 
proficiency211.It is important to keep in mind  that the skills profiles are simplified  profiles, 
aiming  to portray a generic picture of the skills needed. They not claim to be exhaustive 
and may vary between sectors and different maturity levels.  

During the interviews, it was often mentioned that SME managers/owners not only lack 
awareness about the importance of BIC technologies. If they are aware of the benefits of 
a certain technology, they often do not know what is needed to work with it. The skills 
profiles developed for each of the technological areas provide SMEs with an overview of 
the competences they have to develop to work with big data, IoT and/or cybersecurity. 

209 O EC D (2005), Ne w pe rspectives on ICT skills and e mployment. Published April. Available at: 

http://www.oe cd.org/internet/ieconomy/34769393.pdf   

210 http://www.e com petences.eu/  

211 For the  m ethodology used for defining the skills profiles, please see Annex A. 

67 

 
 
 
                                              
This enables SMEs to assess the skills they c urrently have against the skills required, 
including proficiency levels.  

Three different roles are included in the skills profiles: the manager, the IT professional 
and the advanced user. The skills they need to possess depend on many factors, from 
which the type of company is an important one. In this study, we distinguish between 
producers of BIC technologies and supplier of BIC technologies. As for the manager, the 
type of company does not substantially impact the required competences and proficiency 
levels. Whether being a producer or user of for instance big data, the competence 
‘Business Plan Development’ is said to be equally important. The situation is different for 
the IT professional. Here, a clear distinction between users and producers is included in 
the skills profiles. On the producer side, IT professionals work on the development of 
solutions (e.g. software solutions) in the area of BIC technologies, for instance big data 
applications. This big data application can subsequently be purchased by  ‘users’, who use 
this application to generate new insights. Although the IT professional might be involved 
on the user side as well, their role is different from the IT professional on the side of the 
producer. Whereas on the producer side IT professionals need to develop such an 
application, on the user side it is for instance important that the IT professional can 
assess the different applications available on the market, which requires an 
understanding of the functioning of this application, knowing what its advantages and 
limitations are. Roughly speaking, one can state that the required competences for the IT 
professional are equal for both the user and the producer, but that proficiency levels 
differ. Therefore, in each skills profile, the IT professional is further broken down into the 
user side and the supplier side. Then, for the advanced user, this role refers primarily  to 
the user side. Here, it is important to note that ‘the’ user does not exist. For instance, in 
the big data area this may refer to either the data analyst, data steward or the data 
engineer. Therefore, although on a generic level we have included the required 
competences and proficiency levels in the skills profiles, for each skills profile this role is 
further specified and elaborated on below each table.  

Lastly, it is important to note that the skills profiles presented for each technology do not 
include soft (or ‘personal’) skills and business expertise, while our analysis showed that 
these skills categories are important with respect to BIC technologies. Reason for not 
including it into the skills profiles is that the e-CF not yet covers soft skills and business 
expertise – although it is planned to include these categories in the update of the e-CF to 
version 4.0.  

3.2.1.  Big data 

The e-competence skills required for deploying big data in an SME can be divided in eight 
fundamental core competence areas, as shown in Table 1. Firstly, qualified big data 
managers will need to develop a big data strategy, underlining the added value of big 
data for their company and how that added value can be generated. Secondly, the SME 
also demands business development skills, as to integrate the big data strategy 
(envisioned by managers), the technological possibilities (envisioned by IT professionals) 
and the core business of the SME (envisioned by advanced users). Then the several steps 
in the data value chain come into play. In the process of using big data, IT professionals 
and advanced users need to know how to collect relevant and reliable data. Then, IT 
professionals need to know how and where to safely and efficiently store data. 
Subsequently, the skills to analyse and visualise data are key for IT professionals and 
advanced users. After the collection, storage, analysis and visualisation of data, based on 
the data, managers should own the competence to make data-driven decisions. Since big 
data extends the volume and complexity of data, cybersecurity skills become 
fundamental as well to ensure data protection.  

Skill/related e-CF 
competence 

Managers 

IT professionals 

Producers 

Users 

Advanced users 

68 

 
 
 
Strate gy making: 

A.1. IS & Business Strategy 
Alignm ent 

Business development:  

A.3. Business Plan De velopment  

Data collecting: 

A.6. Application Design  

D.12. Digital Marketing  

Data storing/warehousing: 

A.6. Application Design  

Data analysis: 

D.10 Information & Knowle dge 
Management  

E.1. Fore cast Development   

Data visualisation: 

D.12. Digital Marketing  

De cision making: 

A.7. Te chnology Trend Monitoring  

D.12. Digital Marketing  

E.4. R e lationship Management 

C ybe rsecurity skills 

5 

5 

- 

- 

- 

- 

- 

- 

4 

2 

4 

- 

4 

5 

2 

5 

4 

3 

2 

- 

- 

- 

- 

4 

3 

2 

3 

5 

5 

2 

- 

- 

- 

- 

3 

1 

2 

- 

3 

3 

2 

- 

- 

- 

se e  profile C ybersecurity 

e -C ompetence proficiency le vel (1 -5) 

Table 1 Big  data e-CF skills  profile 

All of the above competence areas are to a certain extent important to work with big data, 
but some more important than others. According to our survey respondents, data analysis 
(indicated by  77%)  and  data-driven decision  making  (73%)  are  the  most  important 
competences, followed by cybersecurity, business development and strategy making. This 
again  underlines  the  conclusion that  a  mix  of  skills  is  required  to  work  with  these 
technologies, with different types of skills listed in this top-five of skills most important for 
big data.  

CO M P E T E N CE S  L I S T E D  A S  ' I M P O R TA N T '  O R  ' VE R Y  
I M P O R TA N T '  BY   S UR VE Y   R E S P O N D E N T S

100%

80%

60%

40%

20%

0%

Figure 31 Most  important competence areas  according  to survey respondents.  Source:  survey  

69 

 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
Whereas the above table primarily described the type of competences needed, we can 
also analyse big data from the angle of roles required. Following this perspective, the 
Capgemini Academy has developed a framework describing the various roles involved 
when working with big data. They distinguish between the Data Analyst, the Big Data 
Business Analyst, the Data Engineer, the Data Software Architect, the Data Steward and 
the Data Scientist 

Figure 32 Big  data roles 

3.2.2.  Internet of Things 

For IoT, seven fundamental competence areas can be distinguished that employees in 
SMEs should obtain to successfully use and implement IoT solutions in their organisation. 
Managers must know how to make a strategy that accommodates and extends the 
business of the SME. Managers, IT professionals and advanced users should be capable 
of defining how this strategy can promote business development. Thereafter, IT 
professionals on the supplier side need software and application engineering skills to 
build IoT solutions, and IT professionals on the user side need a basic proficiency level of 
these skills in order to work with the IoT solutions. In some cases, they might also need 
to have the hardware engineering competencies to actually build the robotics, 
electronics, sensors, actuators, etc. In order to connect successfully all parts of the IoT 
network, the IT professionals require knowledge of interoperable network engineering. As 
IoT solutions generate more data, more data security issues and more complex data 
structures, SMEs with IoT usage need to rely on cybersecurity skills, as well as big data 
skills. Precise cybersecurity and big data skills depend on the nature and impact of the 
IoT solution adopted by the SME.  

Skill/related e-CF competence 

Managers 

IT professionals 

Producers 

Users 

A dvanced users 

Strate gy making: 

A.1. IS & Business Strategy Alignment 

Business development:  

A.3. Business Plan De velopment  

Software  and application engineering: 

A.6. Application Design  

5 

5 

- 

- 

4 

3 

- 

4 

2 

- 

3 

- 

70 

 
 
 
 
 
 
  
  
  
  
  
  
  
  
  
B.1. Application Development  

B.6. Syste ms Engineering  

Hardware  e ngineering: 

B.1. Application Development  

B.6. Syste ms Engineering  

Inte roperable network e ngineering: 

B.4. Solution Deployment  

C ybe rsecurity skills 

Big data skills 

- 

- 

- 

- 

- 

3 

4 

3 

4 

3 

2 

2 

2 

2 

4 

- 

- 

- 

- 

- 

se e  profile C ybersecurity 

se e  profile Big data 

e -C ompetence proficiency le vel (1 -5) 

From the competence areas listed above, survey respondents indicate – perhaps a bit 
surprisingly – that business development and strategy making are the competences 
mostly needed to work with IoT. An explanation could be that, as an interviewee stated, 
‘IoT applications are everywhere nowadays. The trick is to pick the right  ones – the safe 
ones – and to use them to the advantage of your business model – or to innovate your 
business model’. The third most important competence area is software and application 
engineering, which can be categorised as a typical ‘hard’ skill 

CO M P E T E N CE S  L I S T E D  A S  ' I M P O R TA N T '  O R  ' VE R Y  
I M P O R TA N T '  BY   S UR VE Y   R E S P O N D E N T S

100%
80%
60%
40%
20%
0%

Figure 33 Most  important competence areas  according  to survey respondents.  Source:  survey  

3.2.3.  Cybersecurity 

As for the cybersecurity skills profile, seven fundamental competence areas can be 
identified as being relevant for adopting cybersecurity (Table 4). Firstly, cybersecurity 
requires strategy-making competences to define a suitable overall cybersecurity 
framework for the company. Managers and IT professionals should be capable of 
assessing risks and obtaining the legal compliance knowledge to prevent privacy issues 
and legal claims. Knowledge on how to develop risk and compliance policies that connect 
the strategy and risk assessment to procedures that fit the way employees work is 
necessary for managers and advanced users. IT professionals and advanced users should 
have knowledge of data protection and network protection. Lastly, IT professionals and 
advanced users also need to be skilled in monitoring and mitigating threats to prevent 
and solve cybersecurity issues. 

Also for cybersecurity, for IT professionals there is a difference in the skills required by 
providers of cybersecurity software as compared to users of cybersecurity solutions.  

71 

 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
 
Sk ill/corresponding e-CF competence  

Managers 

IT professionals 

Producers  Use rs 

Advanced users 

Strate gy making: 

A.1. IS & Business Strategy Alignment 

D.1. Information Security Strategy De velopment 

Le gal compliance:  

B.3. Te sting  

E.8. Information Security Management  

R isk  assessing: 

E.3. R isk Management  

E.8. Information Security Management  

De ve loping risk and compliance policy:  

E.3. R isk Management  

E.8. Information Security Management  

Data protection:  

B.6. Syste ms Engineering  

D.12. Digital Marketing  

Ne twork  prote ction:  

D.1. Information Security Strategy De velopment  

Thre at monitoring and mitigation:  

A.6. Application Design  

D.1. Information Security Strategy De velopment  

E.3. R isk Management  

5 

5 

2 

4 

4 

4 

4 

4 

- 

- 

- 

- 

- 

- 

- 

- 

3 

3 

3 

3 

- 

- 

4 

2 

5 

3 

5 

3 

- 

- 

3 

3 

3 

3 

- 

- 

3 

3 

5 

2 

5 

3 

- 

- 

1 

2 

- 

- 

2 

2 

3 

2 

4 

1 

4 

2 

e -C ompetence proficiency le vel (1 -5) 

More than for big data and for IoT, survey respondents indicate that all of  the above 
competence areas are quite important for working with cybersecurity. For every 
competence area, at least 60% of the respondents find that this competence is 
‘important’ or ‘very important’ to adopt cybersecurity. Most important areas are data 
protection and the awareness or education of employees, for instance with regards to 
recognising suspicious emails.  

CO M P E T E N CE S  L I S T E D  A S  ' I M P O R TA N T '  O R  ' VE R Y  
I M P O R TA N T '  BY   S UR VE Y   R E S P O N D E N T S

100%
80%
60%
40%
20%
0%

Strategy
making

Legal
compliance

Risk
assessing

Data
protection

Network
protection

Developing
risk and
compliance
policy

Cloud
security

Threat
monitoring
and
mitigation

Figure 34 Most  important competence areas  according  to survey respondents.  Source:  survey  

Whereas the above table primarily described the type of competences needed, we can 
also analyse cybersecurity skills from the angle of roles required. Following this 
perspective, the Capgemini Academy has developed a framework describing the various 
roles involved when working with cybersecurity. They distinguish between the following 
generic roles: Chief Information Security Officer, Information Security Officer, Business 
Information Security Architect, Information Security Manager, Information Security 
Architect, Technical Information Security Specialist 

72 

 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
 
 
 
3.3.  Skills gaps, shortages and mismatches 

Figure 35 Generic  roles  cybersecurity 

The previous sections highlighted the generic and specific skills SMEs would need to 
adopt BIC technologies. This section zooms in on the areas where mismatches between 
the supply of skilled labour and SME demand for skills are the biggest. These areas are 
being referred to as skills gaps. This section first describes generic digital skills gaps and 
then zooms in on specialised skills gaps.  

3.3.1.  General 

The digital talent gap is widening. In the light of today’s trend towards digital 
transformation, information and communication technology has become an integral part 
of business functioning. This has resulted in an increasing demand for both employees 
with basic digital skills and ICT specialists 212. In the future, 9 out of 10 jobs will require 
digital skills213. Evidence shows that today, only 57% of Europeans has sufficient basic 
digital skills. Looking only at those people currently in employment, there are 145 million 
workers (67%) who have at least basic level skills 214. There were 8.2 million  ICT 
specialists in the EU in 2016, up from 7.3 million  3 years earlier215. The share of highly-
skilled ICT professionals varies considerably between countries: from 6.6% of total 
employment in Finland to 1.4% in Greece 216.  

The number of persons employed as ICT specialists in the EU28 grew by 39.5% during 
the period from 2006 to 2016, which was more than 10 times as high as the 

212 IC T specialists are defined as persons who have the ability to develop, operate and maintain ICT systems 

and for whom ICTs constitute the main part of their job. Source: OECD, 2004 

213 Europe an C ommission (2017), The digital skills gap in Europe. Published O ctober. Available at: 

https://ec.europa.eu/digital-single-market/en/news/digital-skills-gap-europe  

214 C apgemini C onsulting, Empirica, & IDC (2018), Digital organisational frameworks and IT professionalism. 

Published January. Available at: https://www.capgemini.com/nl-nl/wp-
conte nt/uploads/sites/7/2015/12/digital-organisational-framework s-and-it-professionalism.pdf  

215 Europe an C ommission (2015), The Digital Economy and Society Index (DESI). Published February. Available 

at: https://ec.europa.eu/digital-single-market/en/desi  

216 Eurostat (2017), ICT specialists in e mployment. Published December. Available at: 

http://ec.europa.eu/eurostat/statistics -explained/index.php/ICT_specialists_in_employment  

73 

 
 
 
                                              
corresponding increase (3.6%) of total employment 217. However, the supply of ICT 
specialists cannot keep pace with demand: it is estimated that there will be over 500,000 
unfilled vacancies for ICT professionals by 2020218. 

I C T   S P E C I A L I S T   J O B S   A N D   D E M A N D   I N   T HE   E U 28  ( 2016 
– 2020,   M O D E R AT E   G R O W T H   F O R E C A S T   S C E N A R I O )

l

a

i
t
n
e
t
o
p

d
n
a
m
e
d

d
n
a
s
b
o
J

10.500.000

10.000.000

9.500.000

9.000.000

8.500.000

8.000.000

526,000 
jobs potential

2016

2017

2018

2019

2020

Demand Potential Total

Jobs Total

Figure 36 ICT specialist  jobs and demand in the EU28  (2016-2020)219 

The same study differentiated by role, distinguishing ICT practitioners and ICT 
management. In the ‘moderate growth forecast scenario’, the ICT specialist workforce in 
Europe will grow from 8.5 million  in 2016 to 9.0 million  in 2020, of which 7.6 million  will 
be ICT practitioners and 1.5 million  ICT management and analysis level employees. 
Figure 3-10 shows that the skills gap widens, both for ICT management and ICT 
practitioners220.   

217 Ibid. 

218 Europe an C ommission (2017), The digital skills gap in Europe. Published O ctober. Available at: 

https://ec.europa.eu/digital-single-market/en/news/digital-skills-gap-europe  

219 This re port was drafted in O ctober and November 2018 – ahead of new publications re garding these 

statistics (expected in December 2018 or January 2019).  

220 C apgemini C onsulting, Empirica, & IDC (2018), Digital organisational frameworks and IT professionalism. 

Published January. Available at: https://www.capgemini.com/nl-nl/wp-
conte nt/uploads/sites/7/2015/12/digital-organisational-framework s-and-it-professionalism.pdf  

74 

 
 
 
 
                                              
 
 
 
I C T   S P E C I A L I S T   E XC E S S   D E M A N D ,   2016 - 2020

e
g
a
t
r
o
h
s

s
l
l
i
k
S

500.000
450.000
400.000
350.000
300.000
250.000
200.000
150.000
100.000
50.000
0

2016

2017

2018

2019

2020

ICT Management

ICT Practitioners

Taking into account the moderate growth scenario, we can conclude that although the 
supply of ICT specialists is growing, the supply is still being outperformed by an 
increasing demand – both for managers and ICT practitioners.  

Other sources also underline skills gaps with regards to both technically skilled personnel 
as well as managers that need the competences which enable an individual to initiate and 
guide ICT-related innovation at all levels of an enterprise – described as e-Leadership 
skills221. For instance, for three groups of industry employees (engineers, researchers, 
production workers) the European Commission states that skill shortages are most 
significant in technical training, ICT literacy, science, technology, engineering and 
mathematics (STEM), problem solving skills, self-directed learning, communication, 
teamwork and time management 222. A lack of technical specialist skills was also found to 
be the main explanation for digital skills shortages in the ‘tech’ sector, with surveyed 
employers reporting 85% of hard-to-fill positions within their workforce in this area 223. 
The Dutch Employee Insurance Agency UVW frequently maps hard-to-fill vacancies224 in 
the ICT area, reporting a shortage of technically skilled specialists in several roles – 
primarily  persons with a higher professional education.  

Hard-to-fill  vacancies  2018 

Higher professional education 

Academic education 

ICT programmers 

ICT Architects 

Embedded software engineers 

Data-warehouse developers 

PLC-programmers 

System designers 

221 Hüsing, T., Dashja, E., Gareis, K., Korte, W. B., Stabenow, T., & Markus, P. (2015), e-Leadership skills for 

sm all and medium sized enterprises. Published O ctober. Available at: http://eskills-
le ad.eu/fileadmin/lead/re ports/lead_final_report.pdf  

222 Europe an C ommission (2018), C apitalising on the benefits of the 4 th Industrial R evolution. Published 
Fe bruary. Available at: https://ec.europa.eu/info/sites/info/files/4thre volution_p4p-re port_2017.pdf  

223 TP 2015b. Employer Insights: skills survey 2015. The Tech Partnership. Published May 1. Available at: 

https://www.the te chpartnership.com/link/7498c7abf3664f28a644246d1da9348b.aspx?id=1335&epslanguage
=e n. [Acce ssed June 17 2015]. 

224 UW V (2018), ICT-beroepen: factsheet arbeidsmarkt. Published April. Available at: 
https://www.uwv.nl/ove ruwv/Images/ICT_beroepen_factsheet_arbeidsmarkt.pdf   

75 

 
 
 
 
 
 
                                              
 
Database- and application administrators 

BI specialists 

Information/business analysts 

Specialists technical infrastructure 

CRM/ERP advisors 

Security specialists 

Advisors information security 

Table 2 Hard-to-fill ICT vacancies  in the Netherlands,  2018 

Also, for e-leadership skills, necessary for driving successful innovation and capitalising 
on advances in information and communication technologies, demand will not match 
supply in the future225. It is estimated that there will be a gap of up to 250,000 e-leaders 
by 2020 in Europe226. Around 70% of e-leaders are found in SMEs227. 

3.3.2.  Specialised skills gaps 

Skills shortages are hindering SMEs across the three technologies, and these shortages 
are expected to increase even further in the near future according to interviewees. 
Interviewees and workshop participants stressed the importance of hard skills and 
business expertise but tend to put even more emphasis on the importance of soft skills. 
With reference to hard skills, interviewees mention data scientists, software engineers, 
algorithm developers, programmers, data engineers, data structurers, data architects, 
data administrators, (AI) developers, product owners and security specialists as roles 
where the mismatch between supply and demand is most prominent. These highly 
specialised skills are scarce in supply on the labour market, and SMEs need to compete 
with bigger corporates to acquire people with these skills. The extent to which these skills 
are needed obviously depends on the maturity level of an SME working with one of the 
three technologies. Interviewees state that these highly specialised hard skills are 
especially relevant for frontrunners and developers.  

Looking at what our survey respondents indicate, the results are somewhat surprising. 
When asked about their access to skills as to one of the technologies, they indicate for all 
technologies a quite positive score. Each technology reports a score higher than five, 
meaning that they have sufficient access to skills.208 

225 Em pirica (2015), e -Leadership skills for small and m edium sized enterprises. Available at: http://eskills-

le ad.eu/fileadmin/lead/re ports/lead_final_report.pdf 

226 http://eskills-lead.eu  

227 Hüsing, T., Korte, W. B., & Dashja, E. (2015), e -Skills in Europe: Trends and forecasts for the European ICT 

profe ssional and digital leadership labour markets. Published November. Available at: http://eskills-
le ad.eu/fileadmin/lead/work ing_paper_-_supply_demand_forecast_2015_a.pdf  

76 

 
 
 
 
 
 
 
 
 
 
                                              
O N  A  S CA L E  F R O M   1 - 7 ,  T O  W H AT  E X T E N T  
D O E S  YO UR   O R G A N I S AT I O N  H AVE  
E N O UG H   A CCE S S  T O  S K I L L S ?

Big Data

IoT

Cybersecurity

5,12

5,5

5,29

1

2

3

4

5

6

7

1= completely lacking, 7 = completely sufficient

Figure 37 Access  to skills. Source:  survey 

Whereas both the literature, interviewees and experts during the workshop all underline 
a skills gap, our survey seems to point to a different conclusion. An explanation could be 
the nature of the respondents. Above, we already stated that the ‘hard’ skills gap 
particularly hold ground for frontrunners and appliers. These groups are not that much 
represented in our survey. The group labelled as ‘already professionally working with one 
of the technologies’ represents less than 45% of the total, with other groups being in 
lower maturity stages (e.g. ‘beginning to apply BIC’, or ‘aware of the value, but not yet 
applying it’). As the skills gap primarily  holds ground for those companies in higher 
maturity stages, this could explain while our survey did not reveal the skills gap as such.  

The skills gap seems to hold ground for the management level as well as for the 
professionals working with the technologies, interviewees state. Firstly, managers often 
lack understanding of the basics of new technologies and its business implications. As 
described earlier, technological solutions might (partially) replace skill needs for 
particular SME segments. However, this still requires a basic proficiency level of 
understanding the technologies, and one has to be able to assess several technology 
vendors against predefined criteria. Managers too often lack these competences, 
interviewees indicate. Secondly, SME managers may lack soft skills, such as the skills to 
connect, to communicate and to work in interdisciplinary teams. This is especially true for 
founding managers with a technology background (tech-entrepreneurs). As for both the 
IT professional and the advanced user, interviewees argue that increasingly they 
generally lack the ability to possess a helicopter view. This means that, given the fact 
that technology evolves fast, they are not locked in to software or solutions, but that 
their skills  and knowledge exceeds a single solution. As of today, more is demanded from 
IT professionals and advanced users than just executing their task. This implies a shift 
from operational services to mere strategic services. They for instance need to have the 
proficiency of multiple programming  languages, and the ability to switch between those. 
They generally lack the consultancy and advice skills that are increasingly needed to 
provide the management with input about solutions available on the market. 
Interviewees often speak of a distance between the manager and the professionals 
working with the technologies. Taken together, persons working with these technologies 
needs to possess a diverse range of interdisciplinary skills, which are difficult to find 
united in a single person.  

Skills shortages are thus found both for managers as well as for professionals working 
with BIC technologies, and shortages are faced across the three technologies. The 
numbers below illustrate the magnitude of the problem for each of the technologies.  

77 

 
 
 
 
Looking at the big data area, it is stated that the lack of supply of a data-savvy workforce 
in Europe is a problem228. Data specialists accounted for (far) less than 1% of total 
employment in most Member States229. To illustrate, in the UK, the demand for ‘big data’ 
specialists is forecasted to increase by 160% between 2013 and 2020, and estimated to 
represent an additional 346,000 big data jobs230. Furthermore, Sweden will be short of 
70,000 ICT-specialists by 2022231. This shortage is found in several competence areas, 
most notably in programming  and system architecture. Groups that are smaller today but 
where the need is growing rapidly are qualified data analysts and information security 
specialists. Looking specifically at SMEs, survey respondents indicate that data analysis, 
business development and data storing and warehousing are the competence areas 
where shortages are most prominent in the big data area. 

With regard to cybersecurity, the forecast is that Europe will face a projected skills gap of 
350,000 cybersecurity professionals by 2022, according to a recent Frost & Sullivan 
report 232. The demand for professionals is growing, but supply is not keeping pace. In 
Europe, 66% of the professionals believe there are too few cybersecurity professionals 
within their department. North America shows a similar  shortage (68%), and a majority 
believes that it is a result of a lack of qualified personnel. Capgemini233 assessed a set of 
core digital skills necessary for organisations with aspirations of digital leadership and 
concludes that corporate demand for cybersecurity skills is rising faster than supply, and 
the demand for cybersecurity is not likely to diminish  in the next few years. 68% of 
organisations surveyed reported a high demand for cybersecurity skills compared to 61% 
demanding big data skills and 64% analytics skills. Demand for these skills was then set 
against the availability of proficient skills already present in the organisation. This 
identified a 25-percentage point gap for cybersecurity skills, compared to a 20 
percentage point gap for big data and a 13 percentage point gap for analytics (figure 3-
12).  

228 Europe an C ommission (2017), Enter the data economy. Published January. Available at: 

https://ec.europa.eu/epsc/sites/epsc/files/strategic_note_issue_21.pdf   

229 O EC D (2015), Science, Technology and Innovation Policy Note on ‘Datadriven Innovation for Growth and 

W e ll-being’, OECD Publishing, Paris, October 2015.  

230 SAS & The  Tech Partnership (2014), Big Data Analytics. Assessment of Sk ills for Labour and Sk ills 2013-

2020. Available at: https://www.the te chpartnership.com/globalassets/pdfs/research-
2014/bigdata_re port_nov14.pdf  

231 IT & Te lekomföre tagen (2017), IT -kompetensbristen - e n rapport om den svenska digitala sektorns behov av 

spe tskompetens. Published November. Available at: https://www.itot.se /2017/11/it-kompetensbristen-en-
rapport-om-den-svenska-digitala-sektorns-behov-av-spetskompetens/  

232 Ashford, W. (2017), Europe faces shortage of 350,000 cyber security professionals by 2022. Published June. 
Available at: http://www.com puterwe e kly.com/news/450420193/Europe-faces-shortage-of-350000-cyber-
se curity-professionals-by-2022  

233 Lie vre , F. (2018), Business le aders re port urgent need for cybersecurity skills as digital talent gap widens. 

Published February. Available at: https://www.capge mini.com/news/business-leaders-report-urgent-need-for-
cybe rse curity-skills-as-digital-talent-gap-widens/  

78 

 
 
 
                                              
Figure 38 The digital  talent gap is  widest in the cybersecurity  domain234 

Looking specifically at SMEs, survey respondents indicate that cloud security is the 
competence area where the skills gap is most prominent in the cybersecurity domain, 
followed by data protection and threat monitoring and mitigation. Fourth comes network 
protection.  

For IoT, no specific figures for Europe were found. However, based on the evidence with 
regards to shortages of ICT professionals, STEM-educated professionals, cybersecurity 
professionals and big data professionals, it would be safe to assume that the skills gap 
identified for big data and cybersecurity also (at least partially) holds ground for IoT. 
According to our survey respondents, this is partially true, as business development and 
strategy making are the competence areas where the skills gap is most prominent for IoT 
– which is more or less in line with the big data domain. After these, a series of more 
hard skills stands out as areas where skills shortages are experienced, such as machine 
learning and various types of engineering.  

%  O F   R E S P O N D E N T S  I N D I CAT I N G  A  
S H O R TA G E  O R   H I G H   S H O R TA G E  O F   S K I L L S  
( I O T  D O M A I N )

Machine learning
Cybersecurity skills
Big data skills
IP netw orking
Interoperable network engineering
Hardware engineering
Software and application engineering
Business development
Strategy making

0%

5%

10% 15% 20% 25% 30% 35%

234 Buvat, J., Turner, M., Slatter, M., & Puttur, R . K. (2018), Cybersecurity talent: the big gap in cyber 

prote ction. Available at: https://www.capgemini.com/wp -content/uploads/2018/02/the-cybersecurity-talent-
gap-v8_we b.pdf  

79 

 
 
 
 
 
 
                                              
Figure 39 Skills  gaps IoT. Source:  survey 

Several sources underline that a talent shortage is hampering IoT development 235. The 
industry is currently experiencing a major shortage of qualified IoT professionals, and it 
could persist for the next five to seven years. The talent challenge in the IoT is not down 
to a lack of a specific skill, but a lack of professionals with the required combination of 
IoT skills. Among others, IoT professionals need big data skills, software engineering 
skills and IT security skills236.  

3.3.3.  Conclusions 

As stated earlier, ‘the SME’ does not exist. SMEs take various forms and have different 
natures. The different groups of SMEs as identified in the segmentation model have 
different skill needs, and as such, skills gaps differ per group. In general, the demand for 
highly specialised skills tends to concentrate at the supply side of the market, among the 
ICT suppliers. Hard skills – related to e.g. software engineers, data scientists, 
programmers, security specialists – are said to be especially relevant for frontrunners 
and developers, according to interviewees. These specialised skills are scarce in supply 
on the labour market, and SMEs need to compete with bigger corporates to acquire 
people with these skills. This is a problem of quantity mostly, as the SMEs in these 
categories understand what they need.  

This is different for SMEs in the lower maturity levels of the pyramid. Profiles required by 
ICT users become more business-oriented and project-oriented, with a strong focus on 
the design of new services and apps, and the ability to outsource/rely on standardised 
platforms and solutions237.  

Soft skills are relevant for all segments, but are perhaps even more important for 
appliers and followers. For these types of SMEs, it might be essential to be ‘connected’ to 
overcome their competitive disadvantage of having restricted resources. Instead of 
developing the necessary skills in-house, they might make use of the skills of ecosystem 
or value chain partners, technological solutions available on the market or hire expertise. 
This still requires a basic knowledge of the implications of emerging technologies and the 
solutions available. An SME needs to be aware against which criteria technological 
solutions, vendors and externals can be assessed. With regard to the latter, SMEs need 
to know the competences that they need in order to work with BIC technologies. During 
the workshops and interviews, experts confirmed the view that – especially for the group 
of followers in the segmentation model – awareness of 1) the benefits of emerging 
technologies and 2) skills  needs are still important issues that should be addre ssed. In 
many initiatives focusing on the uptake of emerging technologies, such as the German 
Mittelstand 4.0 initiative, awareness raising is still one of the core activities in their 
service portfolio.   

Competence (self-) assessment tools could be useful in this context as well, especially if 
they are related to recognised standards such as the e-Competence Framework, ISO 
standards or even (in the case of cybersecurity) to the American NIST framework.  

235 Ne wcom be, M. (2018), IPv6-only world on the horizon. Published June. Available at: 

https://www.e e tim es.com/author.asp?section_id=36&doc_id=1332655; Wright, B. (2018), How a talent 
shortage is hampering IoT development. Published March. Available at: 
https://www.idgconnect.com/abstract/29718/how-talent-shortage-hampering-iot-development  

236 Ibid. 

237 Hüsing, T., Dashja, E., Gareis, K., Korte, W. B., Stabenow, T., & Markus, P. (2015), e-Leadership skills for 

sm all and medium sized enterprises. Published O ctober. Available at: http://eskills-
le ad.eu/fileadmin/lead/re ports/lead_final_report.pdf  

80 

 
 
 
                                              
Finally, it seems SMEs are mostly in need of increasing their cyber hygiene and would 
need to embed this in their digital strategy. This addresses anyone working in the 
organisation. The SME would be helped with basic cybersecurity by design standards of 
products and services, for instance via quality labels, but at least to make transparent for 
the SME what could be done to increase cyber hygiene in a trustworthy manner.  

4.  SKILLS STRATEGIES 

As it was discussed in the previous chapters, the SME landscape is diverse, therefore the 
approach of firms to the use of technologies and the types of skills needed to use them 
vary significantly across firms. The literature review and analysed interviews  highlight 
that existing skills needs in SMEs could be grouped in three categories, namely, hard 
skills, soft skills and business expertise. The type of skills gaps, or their combination, 
depend on the level to which a company is engaged in (technological) innovation. For 
example, hard skills are especially relevant for frontrunners and developers, while soft 
skills are relevant for all segments, but are even more important for appliers and 
followers. There are multiple strategies that SMEs follow to acquire the needed skills. This 
chapter presents a variety of available strategies or ‘pathways’ and factors that 
determine the selection of a particular strategy.  

4.1.  Strategy needs  

4.1.1.  A skills strategy implies a conscious 

decision 

The company decision to explore opportunities related to the use of BIC technologies is 
(eventually) a choice that is made by SME management team or owners, based on 
business rationale. According to our interview results, as well as, the research of 
Barnard, Bakkers and Wunsche (2017)238 most SMEs understand that investing in novel 
technologies provides a competitive advantage. Paradoxically, interview results highlight 
that decision-makers in SMEs tend to lack the necessary knowledge about available, 
useful technologies and their potential. Due to dynamic changes in the market of 
technologies even the IT professionals or technology experts in SMEs struggle to keep 
track of changes in the market and to understand the use and application of particular 
technologies. Technology providers are moving towards business models whereby they 
serve as consultants that inform companies about the functionalities of particular 
technologies, however, according to some interview respondents, many providers fail to 
explain the use of technologies in simple terms, applied to the context of the company 
and their effect on business processes or on products/services in a specific company.  

Around a quarter of interview respondents emphasized that apart from the lack of 
familiarity with the market of technologies, company managers/owners do not sufficiently 
master strategic thinking and communication skills to design and successfully implement 
technology integration and skills development strategies. The absence of experience in 
creating appropriate strategies demotivates SMEs to embark on digital transformation 
and disables them in addressing skills gaps. In light of transformative effect of 
technologies in SMEs, the skills strategies should be well-designed and adjusted 
according to changes in a company. The process of adjustment is company-specific, it 
involves costs and, consequently, business risks. Many interviewees highlighted that if a 
company is successful in its business without undergoing digital transformation it is 
unlikely to take unnecessary risks. In addition, in countries or regions where there are 
fewer digitally oriented, innovative companies, SMEs are less optimistic about the 
potential of BIC technologies and are less willing to explore the market of these 

238 Barnard, C ., Bakkers, J. H., & W unsche, S. (2017), The road to the digital future of SMEs. Published 

Se pte mber. Available at: 
https://www.virginm ediabusiness.co.uk/pdf/Insights%20Guides/The%20SMEs%20changing%20the%20world
.pdf  

81 

 
 
                                              
technologies. Such observations reveal two findings: first, it confirms Everett Rogers’ 
diffusion of innovation theory (1995)239 that companies are more likely to follow a 
business trend rather than being a pioneer in the market; second, many SMEs are 
adjusting their business models based on collaboration with partners or requests of 
clients, underlining the importance of its ecosystem. If a partner or client does not 
request or is not able/willing to adjust to digital transformation, then there are fewer 
incentives or even disincentives to launch digital transformation in SMEs. Both findings 
underscore the importance of large-scale encouragement of the digital transformation to 
make it a market trend and to stimulate the use of technologies by partners and/or 
clients.   

There are three major drivers of skill development in firms. First, the ‘deciders’ or 
management should show the commitment and strategy to ensure the 
operationalisation of digital transformation; second, the organisation must ensure that 
digital transformation is driven by cross-functional work and there is a sufficient 
knowledge transfer; and third, the culture in the firm  should stimulate discussions on 
digital transformation goals and skills development needs 240. Without such a supportive 
environment, the integration of BIC technologies, as well as, development of needed 
skills for the uptake of these technologies is highly problematic in SMEs.  

According to the research conducted by the European Research Center for Information 
System241, a successful digital transformation requires systematic skill development. It is 
argued that the readiness of companies to embrace digital transformation determines the 
approach towards skills development. The digital maturity model, presented in the 
following figure, depicts the stages of digital transformation and the corresponding 
strategies towards digital skills development.  

Figure 40 Digital  maturity  model: Skill Development for Digital  Transformation 242 

239 R ogers, E. (1995). Diffusion of Innovations. Retrieved from: 

https://we b.stanford.edu/class/symbsys205/Diffusion%20of%20Innovations.htm 

240 Be rghaus, S. & Be ck , A. (2016), Stages in digital business transformation: results of an empirical maturity 
study. Available at: https://pdfs.semanticscholar.org/d416/aa50e0eb6abb3f5e6e5fa071931f9a494d28.pdf  

241 SAP (2017), Maturity model and best practice: skill development for digital transformation. Available at: 

https://www.sap.com/documents/2017/08/7630cfa8-cd7c-0010-82c7-eda71af511fa.html  

242 Ibid. 

82 

 
 
 
                                              
The first stage of the maturity model reflects the situation when SMEs do not recognise 
the potential of BIC technologies and thus do not invest in the development of 
appropriate skills. As a result, internal human resources are usually poorly managed; the 
decisions to develop skills are reactive, sporadic and lack consistenc y. From the ‘chaotic’ 
stage of digital transformation the companies enter the ad-hoc stage, where the 
development of skills is evolving depending on occasional digital projects or tasks. The 
systematic and strategic stages of digital transformation have a defined skills 
development approach, which leads to more effective and efficient use of technologies. A 
better use of technologies results in more investment for skills development and 
culminates in data-driven, adaptive formulation of skills development strategy. These 
findings are important for the initiative because the type of interventions; tools and 
methods supported by the initiative need to be selected and developed taken into 
account these different approaches to skills strategies, if one even exists.  

Many interview respondents mentioned that digital maturity of an SME is correlated with 
technological intensity in a specific industrial or service sector. For example, digital 
maturity in the IT sector is expected to be higher, on average, than in the textile sector. 
This is in line with conclusions from major research institutes, underlining that substantial 
differences exist between industries if it comes to digital maturity. Figure 4-2 provides an 
example from Capgemini’s Digital Transformation Institute.  

Figure 41 Digital  mastery  of industries243 

This observation highlights that the decisions of company managers or owners to adopt 
BIC technologies and to develop appropriate skills fundamentally depends on assessment 
of profitability of digital transformation in an SME. Thus, without a clear busines s case 
the SMEs in different industrial and service sectors do not strive to reach the highest 
stages of digital transformation.  

The analysis of existing literature on the topic and interviews conducted reveal that the 
decisions of the management team or owners in SMEs play a central role for 

243 C apgemini Digital Transformation Institute (2018), Digital Mastery Survey. Available at: 

https://www.capge mini.com/wp -content/uploads/2018/07/Digital-Mastery-DTI-report_20180704_we b.pdf 

83 

 
 
 
 
 
                                              
development of digital skills and for adoption of BIC technologies. It also acknowledges 
that SMEs tackle their skills needs on a sliding scale from ad hoc individual driven 
decisions (chaotic) to fully integrated int o the technology strategy (data driven). The 
challenge for this initiative is to identify and tailor a vision that respects these different 
approaches by SMEs in the market at the moment.  

The underlying concept requires understanding of the 
balance between an organisation’s strategy on why 
and how to adopt technology as business 
opportunity, and the required human capital to 
deliver on that  investment. It is about investing in 
building a capability at the organisational level, and 
consequently finding  the right people to build 
competences necessary for that capability. 
Employees fulfil roles associated with  those 
competences, using methods and tools to add 
specific value. 

4.1.2.  Different strategy needs for different 
users of the technologies in the SMEs 

The analysis of our interviews shows that the use of BIC technologies demands an 
upgrade of skills for all employees within the company, including the regular users of 
technologies, the IT professionals and company managers. The regular users of 
technologies are expected to improve their digital literacy, while IT professionals should 
continuously invest in their knowledge of technologies and better their communication 
skills to inform users about functionalities of technologies and to incorporate the 
feedback of users for improvement of products and services. Managers in SMEs are 
expected to possess transversal digital skills to manage all business processes, think 
strategically and creatively about the use of technologies, as well as, to guide the IT 
professionals towards innovation. Both the literature review and the opinions of experts 
emphasise that the digitalisation of economy, and consequently of business, is 
transforming the labour market and the attitude towards education by stimulating life -
long learning.  

Depending on the role that the technology is or will be playing in an SME the business 
and skills strategy will be adjusted. Using the technologies for improving or transforming 
internal business processes often requires more people within the organisation to be 
involved and consequently have the appropriate skills. For example, in addition to 
physical reorganisation of production process, a change in  ommunication and 
cooperation within the company may be needed. Using the technologies for product or 
service delivery however, has a stronger influence on external relations and may require 
a skills strategy to involve its partners in the 
value chain.  

The following section will elaborate on the choice of an appropriate strategy for skills 
development.  

4.2.  Choosing the right strategy 

4.2.1.  Size of investment 

There is a variety of strategies on digital skills development; the choice of a strategy is 
largely determined by the digital maturity stage of SMEs, which implies the willingness of 
the management team to embrace c hanges in a firm  and the assessment of the impact 
of technologies on business processes. The cost-benefit analysis is normally guiding the 
choice of a strategy and the size of investment for skills development in an SME. If a 
technology is at the core of all business processes, and consequently has a large value 
for an SME, then a company is likely to invest more resources into skills development to 

84 

 
 
 
ensure effective operation of the technology244. In such a case, the number of people who 
receive training to upgrade their skills is likely to be larger than if a technology has a 
small function in a company. Hence, the size of investment into digital skills development 
in SMEs that are frontrunners and developers, have a defined (strategic) or optimized 
(data-driven) level of digital maturity, is expected to be larger.  

Among other factors that influence the amount of investment for skills development is 
the proficiency level of needed skills that is determined by the type of technologies. In 
case of data analytics, coding and software development skills might be needed, in 
contrast to skills related to simple interaction with technologies. In light of a worldwide 
shortage of skills related to digitalisation in companies the size of investment in acquiring 
or gaining advanced skills is larger. Interviews with experts in the area of BIC 
technologies indicated that SMEs experience a greater shortage of skills, particularly 
advanced skills that are scarce, as a result of competition for talent with larger 
companies and less competitive salary offers.  

4.2.2.  Approaches to fill skills gap 

A survey conducted by Capgemini Consulting in 2013245 revealed that over 63% of 
companies are using traditional strategies to address skills gap, namely, the in-house 
solutions – training by colleagues or invited experts and recruitment, or the external 
solution – outsourcing of skills through partnerships with companies that possess needed 
skills. The latter involves the transfer of specific tasks or even business processes to a 
partner company, therefore some companies are unwilling to experience high reliance, to 
share sensitive information or the client base with a partner. The choice between internal 
versus external skills strategy is determined by multiple factors: 

  Availability of a suitable trainer and a course either within an SME 

or outside of it; 

  Ability to train employees, complexity of training; 

  Frequency of use of needed skills; 

  Potential to use needed skills in other tasks; 

  Risks if skills are not developed in-house; 

  Ease of doing business without needed skills in-house (with partners, clients); 

  Direct costs of required training versus the costs of outsourcing; 

 

Investment costs of current staff upskilling and a fear of them leaving the 
company versus the cost of finding the right provider of skills; 

  Opportunity cost for not continuing business as usual. 

Only 13% of surveyed companies are using innovative methods, such as targeted 
company acquisition (the purchasing/merging with companies that have talent in specific 
technologies) or engagement with start-ups in business incubators and accelerators (the 

244 Kane , G. C ., Palmer, D., Phillips, A. N., Kiron, D., & Buckley, A. N. (2016), Aligning the organisation for its 
digital future. Published July. Available at: https://sloanreview.mit.edu/proje cts/aligning-for-digital-future/  

245 C apgemini (2013), The digital talent gap: developing skills for today’s digital society. Available at: 

https://www.capge mini.com/wp -content/uploads/2017/07/the_digital_talent_gap27 -09_0.pdf  

85 

 
 
                                              
identification of talent or cooperation with start-ups)246. Some other successful 
approaches to closing the skills gap in companies are 247:  

  The organisation of training initiatives with firms that have similar skills gaps; 

  Apprenticeships; 

  Multi-sector partnerships with IT industries; 

  Schools and public -sector agencies to adjust and enhance existing digital skills 

programmes; 

  The encouragement of employees to join coding bootcamps; 

  Cooperation with regional business development agencies or with Chambers of 

Commerce; 

  Participation in publicly funded skills-focused programmes or initiatives. 

The approach towards skills development in a SME is strongly influenced by several 
factors, such as available human resources, type of technologies, convenience, costs 
(time, financial resources) and a maturity stage at which skills development is needed. 
For example, the ‘digitally born’ SMEs, like university spin-offs focusing on data science, 
have a higher level of hard digital skills. These firms experiment more and develop skills 
on the job. These firms collaborate with other data science firms to cooperate and learn 
from interaction. Learning-by-doing is the most prominent in-house method for skill 
development, as they lack the resources to set up formal academies or traineeships.  

4.2.3.  Providers to fill skills gap 

Aside from self-learning, there is a variety of providers to fill the skills gap, such as 
education institutions that offer more formal training to SMEs, public or publicly -funded 
organisations and private firms that are operating in the same industry or possess 
appropriate skills. According to interviews with experts, SMEs typically provide in-
house/on-the-job training by their own employees or approach education 
institutions/training centres for a short -term course to improve skills of employees. Many 
SMEs do not invest substantial amounts of time and financial resources to find the most 
appropriate external training provider. Some companies that approached education 
institutions to improve the skills of employees argue that it is not sufficient, as more 
mentoring, face-to-face learning is needed to acquire skills248. Among other common 
critical remarks is the lack of connection of traditional training with a particular industrial 
or business sector, as the current skill needs require a flexible approach to ensure 
relevance and effectiveness of an education course249.  

One of most common private initiatives for addressing the skills gap is outsourcing. SMEs 
contract specialised companies to provide tailored services without an SME having to set 
up the required infrastructure. In some cases, companies cooperate to work and develop 
skills together. According to the survey of business leaders in North America, Europe and 
APAC region, 46% of respondents are interested in outsourcing new digital skills and 

246 Ibid. 

247 ITU (2018), Digital skills toolkit. Available at: https://www.itu.int/en/ITU -D/Digital-

Inclusion/Documents/ITU%20Digital%20Skills%20Toolkit.pdf  

248 O e sch (2018), Digital skills gap: Where are  we  now? Published May. Available at: 

https://trainingindustry.com/articles/it-and-technical-training/digital-skills-gap-2018-whe re-are-we -now/  

249 Score y, J. & Jones -Evans, D. (2017), SME skills survey 2017 final re port. Published June. Available at: 
http://www.lsk ip.wales/downloads/SME%20Skills%20 Survey%202017%20-%20Final%20English.pdf  

86 

 
 
 
                                              
24% of interviewees consider outsourcing digital skills training for in-house resources250. 
The outsourcing is expected not only to fill the skills gap, but also to improve operational 
efficiency, reduce costs and contribute to business growth.  

Figure 42 Answers  of Infosys  survey respondents  on question “What is the biggest  value that you seek  
from digital  labour from partners?”   251 

Public-private-partnerships (PPP), where education providers, governments and business 
come together are less common, according to opinions of interviewees. However, several 
experts noted that some SMEs acquire skills through joining centres of excellence that 
provide networking and learning opportunities. In countries where digital skills gap is 
ineffectively or not actively addressed by private companies the public -sector actors are 
more likely to launch training initiatives, foster business linkage programmes and 
stimulate PPP in skills development 252.  

Among less likely actions taken by SMEs to fill the skills gap are listed: t he sending of 
employees to a full-time accredited MSc degree programme, the setting up of a training 
centre, a large investment in hiring a service provider or the alteration of a business 
model. All of these options are considered too expensive for SMEs.  

The choice of a skills development strategy in SMEs normally relies on rational decision-
making. There are many factors that are taken into consideration when an appropriate 
strategy is designed, however, the primary criteria for the selection of a strategy is cost-
effectiveness, efficiency and opportunity costs. Considering that only the assessment of 
costs and benefits may reveal to a specific SME the best strategy for digital skills 
development, the firms should be well aware of advantages and disadvantages of various 
strategies. The following sections zoom into those aspects.  

4.3.  External skills strategies 

External skills strategies are focused on outsourcing or hiring temporary ‘extended 
workforce’, such as experts or consultants, and forming alliance partnerships. Using 
external, short-term workers has several advantages, such as access to specialised skills 

250 Infosys (2018), Outsourcing in the age of intelligent automation. Available at: 

https://www.info sys.com/insights/digital-future/Documents/outsourcing -age-intelligent-automation.pdf  

251 Ibid. 

252 O EC D (2013), Enhancing skills through public-private partnerships in Kazakhstan’s information technology 
se ctor. Available at: https://www.oe cd.org/countries/kazakhstan/Enhancing%20Skills%20though%20Public-
Private%20Partnerships%20in%20Kazakhstan%27s%20Information%20Technology%20Sector.pdf  

87 

 
 
 
 
                                              
and flexibility of working arrangements and a lack of regular obligations on the part of an 
employer. The cost-effectiveness of hiring ‘extended workforce’ is debated, however, 
around 39% of executives in large US companies stated that the following approach 
results in saving of financial resources 253.  For SMEs, the current solution could address 
the urgent need to fill the skills gap.  

The forming of alliance partnerships is considered an external skills strategy when a 
company is dividing tasks across partners. Such a strategy is similar  to a regular 
outsourcing. The disadvantages of following external skills strategies include the loss of 
control, inability to monitor costs, performance of tasks and their quality, security risks 
associated with the use of available or accessible data, increasing reliance on partners 
and instability risks, transaction costs associated with communication and management 
of business processes254.   

4.4. 

Internal skills strategies 

Internal skills strategies boil down to two options, namely upskilling employees or hiring 
professionals with demanded skills. Fundamentally, the internal skills strategies are 
concentrated on building skills capabilities within an SME. Such strategies, particularly 
internal company training and mentoring of employees, have undeniable advantages, 
such as increased skills transfer, greater satisfaction of employees, better tailoring of 
training towards skills needs and matching of a course with roles and responsibilities 255. 

Despite the seeming benefits of such strategies, only the analysis of costs, benefits, 
effectiveness and efficiency of investments into skills of employees can reveal whether 
the chosen strategy is profitable for a particular SME. For example, the amount of time 
and financial resources spent on finding or training an employee, the identification or 
design of an appropriate education course, the intensity and use of acquired skills will 
determine to what extent the investment was expedient. The investment in employees 
may quickly turn into pure costs if an employee decides to leave an SME. Hence, internal 
skills strategies do not add more stability nor reduce risks for a company.  

Among the tools for upskilling  existing employees are listed Massive Open Online Courses 
(MOOCs), short courses via higher education institutes or private companies, in-house 
learning from colleagues, training within the company network and test & trial innovation 
investments. 

(1)  One of most popular formats for addressing the digital skills gap is MOOCs. The 

pacing of MOOCs can often be tailored to the individual, and the mode of training 
is virtual/online. Hence, employees can access any course at a convenient time 
and location256. Many employees prefer MOOCs to other types of training, 
however, as a result of non-interactive format their effectiveness is lower 
compared to other forms of training257. A significant number of MOOCs are free of 

253 Acce nture  (2014), How to m anage an extended work force  for business agility. Published March. Available at: 

https://www.acce nture .com/in-en/insight-outlook-managing-the-extended-workforce-talent  

254 R iggins, N. (2017), 20 advantages and disadvantages of outsourcing from your small business. Published 

Fe bruary. Available at: https://smallbiztre nds.com/2017/02/advantages -and-disadvantages-of-
outsourcing.html  

255 He athfield, S. M. (2018), Tap the powe r of internal training. Published May. Available at: 

https://www.the balancecare ers.com/tap-the-powe r-of-internal-training-1919298  

256 O EC D (2016), Innovating education and e ducation for innovation: the powe r of digital technologies and 

sk ills. Available at: http://www.oe cd.org/education/ceri/GEIS2016 -Background-document.pdf  

257 R adford, A. W ., R obles, J., Cataylo, S., Horn, L., Thornton, J., & W hitfild, K. (2014), The employer potential 

of MO OCs: A m ixed-methods study of human re source  professionals’ thinking on MOOCs. Available at: 
https://files.eric.ed.gov/fulltext/EJ1045984.pdf  

88 

 
 
                                              
charge; the exception are specialised, tailored courses, which charge a fee to 
receive a certificate of completion. Taking tailored courses require that an SME is 
aware of the types of skills needed. Since this is not always the case the benefit of 
MOOCs is questioned at times. 

(2) 

(3) 

A growing number of academic institutions, education centres and private 
companies offer short courses, open summer schools to assist firms in addressing 
the digital skills gaps. The attendance of a course by an employee requires an 
investment of time and finance. In contrast to MOOCs, short courses have a more 
intensive approach to study and many of them are provided only in classes. The 
advantage of such types of training is the ability to interact with other students 
and trainers/coaches, however, many existing courses are not specifically 
adjusted to skills needs of particular employees. Hence, their use depends on 
flexibility and relevance of curriculum, successful diagnostic of needed skills and 
effective communication with the trainer258. 

The in-house learning from other colleagues could be a very effective method of 
training if needed skills are already available in an SME, the transfer of skills does 
not require significant investment of time and other resources, and if colleagues 
possess good teaching/mentoring skills. In addition, training by colleagues can be 
effective in building relationships with a new employee 259. Training within the 
company network implies involvement of partners, which enables access to a 
greater number of specialists/trainers and other resources for learning. The 
usefulness of such type of training depends on the same factors as in in-house 
learning from colleagues.  

(4) 

The test & trial innovation include a variety of training investments that are 
beyond the list of conventional methods. These more innovative methods include 
games, self-directed online learning and interaction with technologies260.  

When the decision is made to hire new staff rather than train current staff, SMEs tend to 
combine the skills requirements of new technologies with other tasks required in the 
organisation rather than hire a specific professional. As a result, there is an abundance of 
staff profiles for the three technologies in SMEs that include both the technology need 
and another company-specific need. This approach makes a one-size-fits-all approach for 
skills strategies of SMEs rather inappropriate, and also makes it a challenge for job-
seekers with the right technology skills to identify these positions as appropriate to them.  

To be able to fulfil the specific company need, it is not rare for SMEs to attract talent 
through their network of partners in their economic value chain and partners in regional 
initiatives such as traineeships. Although with the current high demand for digital talents, 
it is becoming more common to recruit from outside of the country and even outside of 
Europe.  

To find the right staff to fit these rather company-specific criteria, SMEs currently often 
compete with higher salaries and/or more attractive working conditions offered by large 

258 EC O R YS UK (2016), Digital skills for the UK economy. R eport prepared for the Department of C ulture , Media 

& Sport. Published January. Available at: 
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/492889/
DC MSDigitalSkillsReportJan2016.pdf  

259 He athfield, S. M. (2018), Tap the powe r of internal training. Published May. Available at: 

https://www.the balancecare ers.com/tap-the-powe r-of-internal-training-1919298  

260 O EC D (2016), Innovating education and e ducation for innovation: the powe r of digital technologies and 

sk ills. Available at: http://www.oe cd.org/education/ceri/GEIS2016 -Background-document.pdf  

89 

 
 
 
                                              
companies. This will remain a challenge for SMEs as long as there remains a skills 
shortage. 

4.5.  Conclusion 

Strategies of SMEs to approach skills needed for the three technologies at hand are 
motivated by a wide range of company specific factors. SME managers/owners 
embracing digital transformation are rare but are a step ahead in their approach towards 
digital skills development. Hence, the stage of digital maturity is associated with the skills 
development strategy chosen by an SME. The lack of knowledge and skills of 
managers/owners in SMEs prevents them from understanding the potential of these 
technologies and discourages investment in digital skills development.  

Traditional digital skills development strategies, such as t raining, recruitment and 
outsourcing are most popular in companies – both large and small. The choice of the 
right strategy for an SME depends on an assessment of needed skills, available 
resources, amount of various types of investments and costs and use of acquired digital 
skills through cost-benefit, cost-effectiveness, efficiency and opportunity cost analyses. 
Both internal and external skills strategies have advantages and disadvantages, therefore 
neither of them secures an SME from business risks nor ensures that skills gaps in a 
company will be addressed.  

Figure 43 Strategies  for developing big data, IoT and cybersecurity  skills 

5.  KEY STRATEGIES AND POLICIES 

The shortage of digital skills relevant for IoT, big data and cybersecurity in the European 
workforce has not gone unnoticed. Initiatives to combat this issue are abundant, and can 
be found at an EU, national, regional and sectoral level. However, the goals, methods 
and scope of these initiatives vary substantially. Broadly speaking, the initiatives can be 
divided into three overarching categories based on the aim of the initiatives. The first 
category is upskilling  the current workforce and aimed at improving the expertise in a 

90 

 
 
 
particular domain to avoid obsolescence of skills 261. The second category is reskilling  the 
current workforce and has the goal of changing people from one domain of expertise to 
another. Both these approaches are for the short to medium-long term and are generally 
more relevant to SMEs. The third category is a more structural approach and aimed at 
educating the future workforce. This ensures that future generations possess digital skills 
once they enter the labour market. 

The goal of this initiative is to stimulate the development of specialised skills for SMEs in 
Europe. It is therefore important to acknowledge that this initiative does not exist in a 
vacuum. This section discusses the initiatives that emerged during the desk research a nd 
interviews. First, the state-of-play will be discussed. This is followed by a more detailed 
discussion of the initiatives segmented by the type of initiator or funder. We distinguish 
between initiatives funded by or operating at the EU level, the level of member states, 
regional initiatives, private sector organisations, public-private-partnerships (PPPs) and 
the US. For each section, several initiatives relevant to SMEs will be highlighted to 
provide opportunities for learning from best practices. The f inal section will briefly discuss 
the three overarching categories of upskilling, reskilling and educating the future 
workforce.   

5.1.  Overview of relevant initiatives 

The study collected over 50 skills-initiatives262 relevant for boosting digital skills, which 
include basic interpersonal, communicative skills, as well as, advanced technical skills. 
The identification of initiatives was based on the Internet search of major European, 
national, regional and private digital skills programmes addressing (elements of ) BIC 
skills development, announced on websites of public organisations or in public reports 
and research studies. Complementary to the desk research, interviewees were asked 
whether they were aware of relevant initiatives, and a call was placed upon the w ebsite 
of the European Digital SME Alliance inviting stakeholders to submit initiatives not 
already mapped by the research team. The results of the search are not exhaustive, but 
rather indicative of the diversity of available programmes. Around one -third of identified 
initiatives specifically focus on addressing skills needs in SMEs. This already highlights 
that most public, private digital skills development programmes do not specifically target 
small companies. 

For a selection of good practices, covering public policies, academia and 
industry-led initiatives, the study provides a more detailed project descriptions 
in Annex E. These good practices provided for excellent insights that hugely 
supported the design of the vision and roadmap. 

Fifteen European examples: 

  Skillnet Ireland by the government of Ireland (Ireland) 

  Cybersecurity Skills Initiative (CSI) by an Irish nationwide public -private coalition 

(Ireland) 

  SME Datalab by Jheronimus Academy of Data Science (JADS) (the Netherlands)  

  PROMPT by RISE Research Institutes of Sweden (Sweden) 

  Cyber Resilience Centre by Brainport Eindhoven region (the Netherlands) 

  ASTER by Emilia-Romagna region (Italy) 

261 C e defop (2018), Insights into skill shortages and skill mismatch: learning from C edefop’s European skills and 
jobs survey. Luxembourg: Publications O ffice. Available at: http://data.europa.eu/doi/10.2801/645011%0AA  

262 Anne x C lists these initiatives as part of the toolbox (further described in chapter 7) 

91 

 
 
                                              
  Recognising skills in data science by the Big Data Value Association (BDVA) 

(European) 

  Community knowledge platform by VOICE (association of IT -using SMEs) 

(Germany) 

  SMESEC by the SMESEC consortium for the European Commission (European) 

  Make_SME_Digital (Blueprint skills training SMEs) by consortium for the European 

Commission (European) 

  Mittelstand 4.0 Centres of Excellence by the Federal Ministry for Economic Affairs 

and Energy (Germany) 

  Les Digiteurs by CCI Paris Ile-de France (France) 

  SEnDIng by the University of Patras for the European Commission (European) 

  Modern Enterprises Programme by the Hungarian Chamber of Commerce 

(Hungary) 

 

Innovation vouchers by Business Finland (Finland) 

Three examples from outside of Europe: 

  Cybersecurity support rangers by The Ministry of Economy, Trade and 

Industry (Japan) 

  Cyber NYC by the New York City (USA) 

  Skillsfuture initiative by Singapore government (Singapore) 

5.2. 

Initiatives led and/or funded by the EU 

There are several initiatives funded by the EU that focus on digital skills, of which seven 
large initiatives are analysed here. Five of those focus specifically on upskilling the 
current workforce. These five (IT Professionalism, Digital Skills and Jobs Coalition, ENISA 
Network, Digital Innovation Hubs and makes_me </digital>)  are also particularly 
relevant to SMEs. 

IT Professionalism has the goal to better understand how strategies for IT competences 
for SMEs could be developed263. This initiative is tailored towards SMEs, but is more 
focused on developing knowledge about these processes than actually providing tools 
SMEs could use.  

The Digital Skills and Jobs Coalition brings together firms, education providers and non-
profit organisations in EU member  states 264. Within each member state, several projects 
are executed with a diverse set of goals. Some of these projects focus on developing 
digital skills for SMEs. The objective of the coalition is to support the upskilling and 
retraining of the workforce and in particular support measures that help SMEs in 
attracting and retaining digital talents.  

ENISA is the European Union Agency for Network and Information Security265. It acts as 
the center of expertise for cybersecurity. In this role, it provides information about 
technologies like IoT, big data and IT infrastructure. Since 2008, ENISA has provided 
cybersecurity training material for specialists that cover technical, operational and legal 
domains. Each domain has several topics and courses. For each topic, the target 

263 http://ictprofessionalism.eu  

264 Europe an C ommission (2014), The digital skills and jobs coalition.  Published October. Available at: 

https://ec.europa.eu/digital-single-market/en/digital-skills-jobs-coalition  

265 https://www.e nisa.europa.eu/about-enisa  

92 

 
 
                                              
audience is defined and handbooks, toolsets are provided free of charge. ENISA has 
developed several tools and training material specifically for SMEs, such as the Cloud 
Security Guide for SMEs266. 

Digital Innovation Hubs is the EU initiative within the Digital Single Market package that 
aims to complement national initiatives for digitizing industry and to support digital 
industrial revolution in the EU. Digital Innovat ion Hubs are one-stop-shops that assist 
companies, both small and large, to develop more competitive products and services 
using digital technologies. These Hubs provide knowledge, expertise, financing support 
and technology to companies that are willing t o assist their customers, clients in 
experimenting with digital innovations. 267  

Makes_me </digital>  is commissioned by the European Commission and managed by a 
consortium of BluSpecs, Civitta and UPTC268. It has a budget of 400.000 EUR and should 
be used in improving  the digital skills of SME employees in Europe. This is done by 
choosing two regions in Europe with high unemployment rate and designing training 
programs to upskill  the workforce. The next steps in this project are aimed at upscaling 
the initiative to other EU Member States.   

The fifth initiative is Rethinking Education, a program set up in 2012 to meet the demand 
for higher skills and reduce unemployment 269. For each of the EU Member States a 
country analysis was performed to function as a benchmark for evidence-based 
policymaking. This results in specific and tailor-made policies that will rethink the 
educational system per country to better align with the anticipated labor market needs of 
the next decade. The goals include reduction of early school leavers, promoting lifelong 
learning and more cooperation between educational institutions and training providers.  

The European Union funded all initiatives. Some are financed through calls for tenders 
and managed by a consortium of partners, while others like ENISA and the Digital Skills 
and Jobs Coalition are agencies associated with the European Commission. The budget or 
amount of resources available to the initiatives varies, as a direct result of this structure. 
The initiatives that are outsourced have a fixed budget available. IT Professionalism and 
makes_me </digital>  aim to study and design programs for digital skills but are not 
focused on European-wide upskilling. The run-time of these initiatives is therefore 
shorter. 

The Digital Jobs and Skills Coalition, on the other hand, stimulates several programs 
related to the transforming of the economy and subsequent impact on skills needs. These 
programs include public, private and public -private partnerships to upskill, reskill  and 
educate the workforce. Each program has different initiators and partners, and therefore 
different governance structure and budget.  

In sum, the initiatives on the European level are currently deepening the understanding 
of the skills needs and piloting solutions to solve these issues. Practical and easy to find 
tools SMEs can use in their current needs are still in development.  

Existing EU initiatives vary in terms of focus areas, target groups and approach/method 
for addressing skills gap, even if they are seeking to reach the same aim. To illustrate 

266 https://www.e nisa.europa.eu/publications/archive/training-material-SMEs 

267 Europe an C ommission (2018), Digital Innovation Hubs. Available at: 

http://s3platform.jrc.ec.europa.eu/digital-innovation-hubs 

268 Europe an C ommission (2017), C ommission launches pilot proje ct to design dedicated digital skills training 

programmes for small businesses. Published June. Available at: https://ec.europa.eu/digital-single-
m ark et/en/news/commission-launches-pilot-proje ct-design-dedicated-digital-skills-training-programmes-small  

269 https://ec.europa.eu/education/policy/multilingualism/rethinking-education_en  

93 

 
 
                                              
this, the tables below present four EU initiatives that specifically focus on upskilling the 
current workforce. 

5.2.1.  Blueprint for sectoral cooperation on 

skills 

As it  discussed earlier, technological intensity and associated skills  needs have sectoral 
patterns. This allows policy-makers to form  sector-based initiatives in  addressing skills 
gaps. Among the major  advantages of the sectoral approach are the stimulation of skills 
development in the entire industry/sector, and the building of cooperation between several 
stakeholders. Since some  companies require  a  tailored approach to address their skills 
needs, the sector-based initiatives might not always be flexible enough to accommodate 
to their needs.  

One of the major current initiatives that have a sectoral approach in responding to skills 
gaps in industries is the Blueprint for Sectoral Cooperation on Skills. This initiative is part 
of the new Skills Agenda, therefore it is funded the European Commission. The Blueprint 
for Sectoral Cooperation on Skills provides a framework for strategic cooperation between 
key stakeholders, such as businesses, trade unions, and education and training institutions, 
aiming  is to support a sectoral strategy for development of concrete actions in addre ssing 
skills needs in the short and medium terms270. Within the Blueprint for Sectoral Cooperation 
on Skills, there are five sector-oriented initiatives currently carried out 271, as described in 
Table 6, with more initiatives in other sectors to be launched towards the end of 2018 and 
in 2019 

Sector 

A utomotive 

Maritime 
technology 

Space geo 
information 

Initiative name 

Initiative website 

De ve lopment and research on innovative 
vocational e ducation skills (DRIVES) 

https://www.proje ct-
drive s.eu/en/home  

Maritim e alliance for fostering the European 
blue  e conomy through a marine te chnology 
sk illing strategy (MATES) 

Towards an innovative strategy for skills 
de ve lopment and capacity building in the 
space  geo information sector supporting 
C opernicus User Uptake (EO 4GEO) 

https://projectmates.eu/  

http://www.e o4geo.eu/  

Textile/clothing/
leather/footwear 

Sk ills 4 smart TCLF industries 2030 
(S4TC LF) 

http://www.s4tclfblueprint.eu/  

Tourism 

The  next tourism generation alliance  (NGT)  https://nexttourismgeneration.eu/  

Table 3 Blueprint  initiatives  per sector 

5.3. 

Initiatives funded by Member States governments 

The governments of the EU Member States recognise the importance of digital skills for 
the national and the EU economy, therefore individual countries introduce various 
training programmes for different population groups to reach specific national goals in 
digital transformation. The local SMEs take advantage of those initiatives, due to 
proximity, accessibility of trainings, better awareness about those programmes, and 
availability of training in local languages. Furthermore, companies will benefit from well-
tailored training programmes  and this is more likely to be the case when the initiative is 

270 Europe an C ommission (n.d.), Blueprint for sectoral cooperation on skills. Available at: 

http://ec.europa.eu/social/main.jsp?catId=1415&langId=en   

271 Europe an C ommission (2017), Erasmus+: C ooperation for innovation and the exchange of good practices 

(KA2). Ava ilable at: https://eacea.ec.europa.eu/sites/eacea-
site /files/compendium_ssa_blueprint_2017final.pdf  

94 

 
 
 
 
                                              
offered by a local government that is aware of the specific needs of ‘their’ local SMEs, 
and related digital maturity levels and resources. Some nationally funded initiatives are 
indirectly contributing to digital skills development in the country through awareness-
raising campaigns, knowledge-sharing programmes, setting-up of organisations that 
connect training providers and companies.  

Thus far, this study has found a total of 26 initiatives funded by national governments in 
the EU28 Member States. Germany and Denmark  account for seven and five initiatives 
respectively, with France coming third with three initiatives. However, while these three 
countries together account for over half of the national initiatives found thus far, we also 
acknowledge that this mapping exercise is not exhaustive, and many more initiatives 
exist. Our findings could be interpreted as a signal of the differences in awareness and 
action among the Member States. Five initiatives are presented in more detail further 
below, illustrating the diversity in terms of services offered and approach taken. 

The national initiatives vary in relevance to SMEs. The relevance is determined by the 
actions or goals of the initiatives aimed at the upskilling or reskilling  current workforce 
and which groups are targeted within this workforce. In total, 16 initiatives want to 
upskill the working population in terms of digital skills. However, digital literacy and 
inclusion are considered as key in the digital transformation as well. This is represented 
by the six initiatives that target the general population. Examples of these initiatives are 
Developing Digital Literacy in Estonia272, the Good Things Foundation in the UK273 and 
Cybervolunteers in Spain274. These projects aim to educate people in order for them to 
use computers and the Internet. In turn, this will enable them to participate in a digital 
society.  

The remaining 10 initiatives that upskill the workforce are targeting professionals in 
general and sometimes SMEs in particular. Examples include helping SMEs to establish 
an online presence275, to provide cybersecurity training276 and to incorporate digital 
technologies into their businesses277. However, rarely any of the initiatives provide 
advanced digital skills. This indicates that the basic skills are perceived to be lacking by 
the initiatives. Public initiatives are likely to be general and basic due to their nature. 
Targeting more advanced digital skills is only probable if this serves the public good. 
Right now, this is not the case.  

At the national level, there are no initiatives only focusing on reskilling the workforce. 
Reskilling  is part of the Grande école du numérique in France 278 and INCoDe.2030 in 
Portugal279. However, upskilling and educating the future workforce are also goals of 
these initiatives. The idea to move people from one industry to another is therefore not 
popular. This can be explained by the nature of public initiatives too. Predicting the 

272 Ge rm an Federal Ministry for Economic Affairs and Energy (2016), Avoiding skills shortages and mismatches 

– Ne w strate gies for meeting companies’ skilled labour needs. Published April. Available at: 
https://www.bm wi.de /Redaktion/EN/Publikationen/avoiding-skills-shortages-and-
m ismatches.pdf?__blob=publicationFile&v=2   

273 https://www.goodthingsfoundation.org  

274 https://www.cibe rvoluntarios.org/es  

275 http://transition-numerique.fr/centre-de-re ssource s/les-digiteurs-paris-ile-de-france/  

276 https://www.incibe .es/formacion/ciberseguridad -para -micropymes-y-autonomos  

277 https://hellofuture.org/case/digilyft/  

278 http://www.grandeecolenumerique.fr/  

279 http://www.incode2030.gov.pt  

95 

 
 
                                              
likelihood, timing and jobs that will disappear as a result of the digital transformation is 
very difficult. This could be a reason reskilling is not a major  part of the public initiatives 
yet. 

The identified German initiatives have a strong focus on Industry 4.0 and related 
(advanced) skills. Among seven mapped initiatives in Germany, five of them focus on 
SMEs in particular. Some of these initiatives represent the competenc e centers that 
function as network organisations. The so-called competence centers are not providing 
skills trainings themselves but bring SMEs in contact with funding and experts in relevant 
fields that can provide training. Similar competence centers are also found in Ireland 
(Skillnet)280 and in France (Transition Numérique Ile-de-France)281. The latter initiative 
provides a network of consultants to SMEs that assists in using digital technologies. 

Some miscellaneous approaches include the Human Capital Agenda ICT in the 
Netherlands, the initiatives that are focused on increasing the availability of open data by 
the Government of Denmark282  and on utilizing libraries for knowledge sharing and skill 
development in Romania283.   While these initiatives are relevant to combat the skills 
shortage through awareness raising on importance of digital skills and encouraging the 
use of digital technologies, they do not directly address the digital skill gaps of SMEs.  

5.3.1.  Regional initiatives 

In addition to national governments, there are several regional and city level initiatives to 
support digital skills relevant to the three technologies in Europe. The regional initiatives 
have the advantage of involving local actors, building learning communities in cities, 
stimulating local knowledge sharing, analyzing local labour markets and supporting 
regional SMEs through tailored strategies. Below we have provided a selection of several 
initiatives. 

In the Ile-de-France region, les Digiteurs focus solely on SMEs, providing them with an 
online resource centre and dedicated training to help enterprises develop their digital 
capacity and offer. The programme does not target specific sectors or types of skills. 
Training is provided through educational programmes and in-situ counselling. A 
coworking space and a showroom have also been installed for SMEs willing to try new 
equipment and technologies. This initiative was put in place by the Chamber of 
Commerce and Industry (CCI) of Paris-Ile-de-France in 2017, and is part of the national 
digital transition strategy. In February 2018, the CCI started a new partnership with les 
Echo-NetExplo, Google and SoLocal Group, called Le Coach Digital, which aims to provide 
fee-based training and business development to SMEs. 

In Emilia-Romagna, the Clust-ER associations adopted a mid-way solution, by bringing 
together SMEs, students and developers of educational programs (research laboratories 
and centers for innovation belonging to the High Technology Network). Although the 
initiative is not directly aimed at upskilling, it helps building soft skills. As the whole 
supply chain meets at both managerial and IT level, SMEs can identify their needs in 
terms of skills but also in terms of new services that need to be provided in the region. IT 
staff can also share their experiences and advices. By working with education providers, 
they also get a chance to frame future programs in which their staff could enroll. The 

280 https://www.sk illnetire land.ie  

281 http://transition-numerique.fr/centre-de-re ssource s/les-digiteurs-paris-ile-de-france/  

282 Ge rm an Federal Ministry for Economic Affairs and Energy (2016), Avoiding skills shortages and mismatches 

– Ne w strate gies for meeting companies’ skilled labour needs. Published April. Available at: 
https://www.bm wi.de /Redaktion/EN/Publikationen/avoiding-skills-shortages-and-
m ismatches.pdf?__blob=publicationFile&v=2   

283 https://www.m e dgidiacity.ro/  

96 

 
 
                                              
programme is run by ASTER, the Consortium for innovation and technology transfer of 
Emilia-Romagna. 

In the Walloon region of Belgium, digital education is provided through a wider support to 
apprenticeship and in-situ training. The Wallonia Marshall plan 4.0 includes support to 
educational programmes, training for tutors in companies, an online matchmaking 
platform for prospective trainees and interested companies, financial assistance for 
trainees and companies welcoming them. The Wallonia Marshall plan 2.0 was launched in 
2015 with a budget of 304.5 million  EUR, and it will last for four years 284.  

Some regional initiatives are not specifically focusing on SMEs or on employees, but 
rather on larger population groups. In Ghent, the e-inclusion programme aims to give all 
citizens the opportunity to develop digital skills. The project being about digital inclusion, 
it mainly covers initial skills. The programme, which was launched in 2006, is managed in 
cooperation between the City of Ghent, the Public Centre for Social Welfare Ghent and 
Digipolis Ghent. Already in 2012, the programme was identified as a best practice for 
multi-stakeholder involvement for digital inclusion. Key to its success was its capacity to 
regularly launch innovative pilot -projects to keep up with new developments, the 
integration of digital initiatives across all local policies, and the active involvement of 
citizens.285 

At the regional level, some initiatives have been ongoing for long enough to get 
interesting conclusions. See the example of Ghent (although the evaluation is already 
old: 2012). For most initiatives, it is too early to say if one has been more efficient than 
another. Most programmes try to combine several activities to fit the demand: from 
online resources for all to tailored consulting services for companies. As a result, the 
initiatives do not try to target a specific set of skills, but leave the possibility to 
companies taking part in the programme to ask for customised support.    

5.4. 

Initiatives funded by the private sector in Member States 

5.4.1.  Insurance companies and 

accountancies can play a key role in 
making SMEs more cyberproof 

The role of insurance companies and accountancies, especially in the field of 
cybersecurity, should not be underestimated.  

Accountancies are in regular contact with SMEs and advise them on business continuity 
matters. Most accountants are SMEs themselves and hence can understand SMEs. They 
are well positioned to make SMEs aware of the threats (and opportunities) of 
cybersecurity, and trigger them to action. Accountancies across Europe are already 
developing initial points of view and checklists to support SMEs in this challenge (some 
can be found here).  

Insurance companies on the other hand carry part of the societal risk of SMEs being 
impacted by cyber incidents. Increasingly insurance companies are moving to pro -active 
prevention policies to make SMEs aware about the risks and about easy steps to become 

284 Plan Marshall 4.0. Accueillez un stagiaire  en alternance. Available at: 

http://planmarshall.wallonie.be/mesure s/accueillez -un-stagiaire-en-alternance  

285 Marië n, I. & Van Audenhove, L. (2012). Towards a Multi-Stakeholder Approach for Digital Inclusion: A case 

study of Ghent’s Digitaal Talent policy program. Published July. Available at: 
https://cris.vub.be/en/publications/towards-a-multistakeholder-approach-for-digital-inclusion-a-case-study-
of-ghents-digitaal-talent-policy-program(0d1bda13-06b5-4f1d-bf73-523a039e0663).html  

97 

 
 
                                              
more secure and resilient. Via their insurance policies they have a financial lever to 
trigger SMEs to action.  

5.4.2.  Various private sector led training 

activities 

Several other private sector-led skills development initiatives were found. These 
initiatives are provided and funded by a variety of private organisations, which include 
education organisations (schools, colleges, universities), professional training centers, 
private associations/clubs and companies that have digital skills experts that provide 
training. The private sector has the capacity to accommodate to different skills needs, 
therefore the variety of training specialisations (type of skills, skills level, sector 
orientation) and available modes of study (period of study, group/individual training, 
type of a trainer) is usually broader than of initiatives that are provided or funded by 
public organisations. The private sector initiatives can also be effective in fostering 
business collaboration with trainers/education providers and other companies that face 
similar  skills gaps. Considering the diversity of available public and private sector digital 
skills initiatives it is difficult to make broad generalisations and find large distinctions 
between public and private sector programmes.  

In our study, various private sector-led initiatives were found. These initiatives all aim to 
upskill the digital competencies of firms and SMEs in particular. Like all the other 
initiatives, they have a horizontal approach, meaning that they do not target specific 
sectors. The initiatives do place skill development in the larger context of growing 
businesses. For example, Facebook’s initiative was launched in 2018 and aims to train 1 
million  people by 2020. It does this by collaborating with loc al organisations in, for the 
time being, Spain, Italy, Poland and France to educate people in digital literacy and 
media skills. In turn, this should enable people to effectively grow their businesses by 
enabling access to the online community.  

The three other relevant initiatives are firms providing courses in digital skills  (Coursedot, 
OAK3 Academy and General Assembly). Prices vary and depend on the courses. 
Coursedot allows the user to search for relevant courses based on a search term. The 
search term “data analysis” returns 223 hits, all courses on different software packages 
and levels286. The software producers often provide these courses. Microsoft has 
courses on data analysis in Excel in Germany that run for three days and cost 1,400 
EUR287. On the higher end are courses by EMC on Big Data Science that take six days in 
the UK and cost 4,670 EUR288. An online data analysis short course provided by General 
Assembly costs 1,250 USD per learner and its duration is 10 weeks 289. For SMEs it is 
difficult to discern the differences and quality between these courses. 

However, all three firms do provide training in specialist roles and could provide training 
both online and on-campus. The fact that more specialised training is available is unique, 
in comparison to the other initiatives we found. However, sending people to train for 
multiple days on-location could pose problems for SMEs that cannot afford to send an 
employee to training for so long.  

There are also course providers that are somewhat less relevant to SMEs. These courses 
are more generic (e.g. marketing courses by Google Digital Garage) or focused on 
reskilling  the workforce (e.g. Udacity & Google Developer Scholarships Challenge in the 

286 https://coursedot.com/catalogsearch/result/index/?p=2&q=analyzing+data  

287 https://coursedot.com/20779a-analyzing-data-with-excel.html  

288 https://coursedot.com/emc-data-science-and-big-data-analytics.html  

289 https://generalassemb.ly/education/learn-data-analysis-online  

98 

 
 
                                              
EU). The least relevant initiatives focus on digital inclusion, reskilling or diversity. These 
issues are very important, but in the context of providing practical skills to SMEs on the 
short term not very relevant.  

Technology companies are providing a large share of all the initiatives. Eight initiatives 
involve technology firms like Google, Facebook, and Samsung. Google is the most 
prolific, as it is involved in the Udacity & Google Scholarship, Codepact in the 
Netherlands, Google Analytics Academy, Google Growth Engine for Europe and Google 
Digital Garage. It often partners with local organisations to provide training, scholarships 
and courses to individuals. Many of the courses Google provides relate to marketing, data 
analysis and many other digital skills that people need to succeed. Many courses are free 
and used as an introduction to certain topics and can be taught online and offline 
depending on the initiative and the course.  

5.5. 

Initiatives funded  by public-private collaborations in  Member 
States 

We have also come across 27 collaborations between public and private organisations. 
Many of these take the form of network organisations, competence centres and 
knowledge-sharing networks. These could involve educational institutions like 
universities, (large) firms and branches of local ministries to provide training, education 
and knowledge about digital skills and technologies. Some initiatives also foster 
innovation by enabling partners to work together on projects and research. In turn this 
should lead to practical knowledge and the upskilling of the workforce. The initia tives that 
are based on public -private collaborations are usually promoted by one party, either 
public or private organisations, that is seeking support or engagement with other actors. 
Such initiatives could be an effective solution for building synergies, improving 
cooperation between public and private organisations and for reaching common 
objectives in terms of digital skills development. Many public private partnerships achieve 
faster results, reduce risks and costs of individual actors and, as a result, achieve higher 
efficiency. The disadvantages of such approaches are associated with complexity of 
collaboration between public and private organisations, such as mutual dependence, 
which can slow down the decision-making process, unbalanced risks of one party, market 
distortion through exclusion of companies/organisations that did not join the public -
private initiative.290  

Geographically speaking, the PPPs are very diverse. In our sample, many countries have 
two PPPs, but there is not one country with more than two. Examples include Austria, 
Denmark, Belgium,  Sweden, Germany and Poland. The goals of these PPPs are also more 
diverse. Instead of focusing solely on upskilling, there is also more attention to reskilling 
and educating the future workforce compared to the public or private initiatives. As a 
result, initiatives are either relevant to SMEs now or they are not.  

Examples of relevant initiatives include the Digital Hub in Denmark, The Big Data Value 
Association in Europe and PROMPT in Sweden. The Digital Hub brings together SMEs and 
digital talent through an online platform focused on emerging digital technologies. By 
bringing knowledge in the form of human capital and SMEs together, the digital skills of 
SMEs could be improved. The goal of PROMPT is similar,  as firms  develop courses in 
cooperation with universities to provide software competencies to the workforce that are 
relevant to businesses. These courses can also be followed online. The Big Data Value 
Association focuses on big data technologies and brings together data users, providers 
and researchers to enhance the ecosystem and foster innovation.  

Crescere in Digitale from Google gives SMEs access to digital marketing skills, by 
matching SMEs with trainees. Google provides the training and the Italian government 

290 R odriguez, J. (2018), Public Private Partnership Pros and Cons. Available at: 

https://www.the balancesmb.com/public-private-partnership-pros-and-cons-844713 

99 

 
 
                                              
pays for the traineeships. They provide a monthly fee of 500 EUR for the duration of six 
months to the trainees; saving the SMEs money and letting them use the knowledge of 
the trainees. Furthermore, the SMEs build up a network and have contact with young 
professionals that might be interested in working for the SME after graduation. The entire 
program runs until the end of June in 2020 and aims to have paid for 5000 internships by 
that time.  

The mapped public -private initiatives give an impression that collaborations between 
public and private organisations are aimed at fostering innovation by sharing knowledge 
and valorisation. This valorisation can be in the form of help for employee upskilling. 
However, they do risk providing very specialised courses that not all SMEs can benefit 
from. Furthermore, the involvement of SMEs that lack digital skills is not always clear. 
This too could result in the issue of other organisations pushing their own agenda and 
perceived needs, without corresponding to the needs of some SMEs that require either 
general or specific training. 

Initiatives that are less relevant include checklists for cybersecurity and GDPR 
compliance, certification of digital excellence for schools and providing coding classes to 
students from primary  to high school. The first set provides practical tools SMEs could 
use, but does nothing for skills development. The latter category is mainly involved in 
promoting the appeal of coding and digital skills to students and laying the foundation of 
digital skills of the future working generation.  

5.6.  Examples of initiatives in US 

5.6.1.  Overview of US support 

The US traditionally invests little in active labour policies, explaining the limited number 
of public initiatives to support the uptake of digital skills among its businesses. Indeed, 
investment in this domain has halved in total funds allocated in the past 30 years 291. 
Under the Obama administration, a number of public initiatives were launched at the 
national level. They usually involve grant s from the Department of Commerce, but also 
from the Department of Defence (for cybersecurity programmes), which are then 
completed by State or other local public funds and public -private partnerships. The 
programmes usually focus on support to educational programmes and matching tools for 
job seekers and employers. As such, upskilling of employees is not a priority, since one 
of the key objectives is to reduce unemployment. However, some elements can be found 
in cybersecurity.  

One example is the CASCADE (California Advanced Supply Chain Analysis and 
Diversification Effort) initiative funded by the Department of Defence and the State of 
California, launched in 2017 to develop cybersecurity-related education curricula, 
training, and apprenticeship programs292. The programme focuses on hard cybersecurity 
skills, but also entrepreneurial and other business skills (commercialization, supply chain 
outreach, etc.), and provided support and innovation vouchers for the acquisition of 
cybersecurity capacity by companies293. 

291 C ouncil of Economic Advisers (2016) Active labor market policies: theory and e vidence for what work s. C EA 

issue Brie f. Published December. Available at: 
https://obamawhitehouse.archives.gov/sites/default/files/page/files/20161220_active_labor_market_polic ies_
issue_brief_cea.pdf  

292  C ASC ADE (n.d.), California advanced supply chain analysis and diversification e ffort. Available at: 

http://business.ca.gov/Programs/Innovation-and-Entrepreneurship/Cybersecurity/CASCADE  

293 State  of C alifornia O ffice  of the Governor (2018), Program summary. Published January. Available at  : 

http://business.ca.gov/Portals/0/Files/CASCADE/CASCADE--ProgramSummary.pdf  

100 

 
 
                                              
The largest public programme launched in the US in the past years is TechHire, which 
supported the development of local initiatives that mostly focused on education and 
reskilling, often targeting specific communities, such as workers with non-traditional 
backgrounds, veterans, and deprived areas. The aim of the programme  was to provide 
workers with the needed skills for well-paying, middle- and high-skilled, and high-growth 
jobs, through fast-track training organised via public -private partnerships. 

The programme was not restricted to any sector or type of skills, but several initiatives 
launched under its umbrella focused on digital and IT skills. Initiatives were implemented 
in universities and community colleges, but also in other environments such a s coding 
boot camps and online courses. Towards the end of the programme, more than 70 
communities and 1500 employers were involved in diverse sectors (figures for digital 
skills were not available). 

Cybersecurity has been a key focus of digital skills programme in the US. At the national 
level, the Department of Commerce launched NICE, the National Initiative for 
Cybersecurity Education. It aims to create an ecosystem of cybersecurity education, 
training, and workforce development. The initiative is still ongoing294. A successful 
example can be found in the State of Virginia, which combined both NICE and TechHire 
programmes to develop cybersecurity education for students and veterans295. The Cyber 
Vets Initiative includes two training programmes for the reskilling of veterans. The first 
one is a pilot public -private partnership consisting of a free online cybersecurity course to 
200 veterans. The second one is a scholarship-based programme offering advanced 
technical training and contact with cybersecurity firms to veterans and spouses of active 
military workers296.  

As presented above, the TechHire and NICE programmes have supported the 
development of educational programmes in digital skills. As part of the NICE programme, 
1 million  USD was released in grants for the development of local and regional training 
cybersecurity programmes. In Virginia, t he cybersecurity education initiative led to 
concrete results, with a multiplication by six of the number of students enrolled in the 
cybersecurity programme in 2016, compared to 2014297. Under the CyberVirginia label, 
all cybersecurity curricula can be found online by prospective students, who can also 
apply for a number of scholarships298.  

In the US, public funds are used to set up public -private partnerships to provide local, 
community-based initiatives. Most of them focus on education and reskilling, with the 
central objective of reducing unemployment. Direct support to companies – and SMEs 
specifically - per se is rare. Instead, many American companies rely on existing training 
courses, often provided by larger technology companies.  

The US benefits from its leading IT companies. However, although several of them have 
set up grants and support for non-profit organisations (see for example Google’s 
initiatives299), direct support to businesses is only offered as a paid-for service. Indirect 

294 https://www.nist.gov/itl/applied -cybersecurity/nice/about  

295 Andre ws, B. & C olangelo, M. (2016) Investing in Cybersecurity W orkforce of Tomorrow. Available at: 

https://www.com m erce .gov/news/blog/2016/12/investing -cybersecurity-workforce-tomorrow  

296 https://www.cybe rve ts.virginia.gov/  

297Andre ws, B. & C olangelo, M. (2016) Investing in C ybersecurity Workforce of Tomorrow. Available at:  

https://www.com m erce .gov/news/blog/2016/12/investing -cybersecurity-workforce-tomorrow  

298 https://www.cybe rva.virginia.gov/education/   

299 https://www.google.org/our-work /economic-opportunity/ 

101 

 
 
                                              
support can be received via non-profits. For example, some of Google funded initiatives 
support free-lance workers and business managers.  

5.6.2.  Comparing the US and the EU 

To compare with the situation in the European Union, the United States follows a rather 
similar  approach: the federal level has made public funds available (at least under 
Obama administrations), to support the development of digital skills. Most of it was used 
at a more local level, with States and local communities organising the set -up of specific 
initiatives.  

Regarding the level of support, it must be noted that the federal level has decreased its 
financial support and that recent programmes do not seem to have been continued under 
the Trump administration, which contrasts with the EU ongoing effort to support digital 
skills. At the State level, as between European Member states, the involvement of the 
public administration in supporting digital skills programmes varies from one state to 
another, depending on their wealth, political orientation, but also on t he strength of the 
existing IT sector. Unsurprisingly, California offers a very complete support, including to 
businesses.  

As in the EU, most initiatives are not designed specifically for SMEs. The difference is 
mostly in discourse: while the EU and some Member States strongly insist on SMEs in 
their industrial policy, the US in general does not differentiate between companies of 
different sizes. Although we can expect smaller American businesses to benefit more 
from support initiatives, they are not targeted per se, while initiatives targeting the 
population are often tailored for specific groups and communities.  

In term of sectors, cybersecurity is getting more attention in the US than in the EU, due 
to ongoing involvement of the US Department of Defense. In terms of the variety of 
offered skills trainings, both in the US and the EU the range of initiatives is very broad, 
and it includes everything from hard to soft skills, from coding to managing an IT 
business.  

5.7.  Learnings from the good practices 

5.7.1.  Upskilling the current workforce 

The need for digital expertise is growing as IT departments move from facilitating roles 
inside organisations towards more strategically oriented roles. As one interviewee stated: 
“IT is becoming more important for the business and thus requires expertise in 
translating the needs of the market”. This does not only require ‘hard’ IT skills, but also 
‘soft’ business skills300.   

Initiatives tackling this issue typically teach basic IT skills to the general (working) 
population. This is not directly relevant to SMEs, however. In terms of upskilling the 
current workforce of SMEs, private training institutions and education providers, such as 
universities, offer courses to enrich the expertise of employees. Several interviewees 
pointed out that the relevance of these courses is difficult for an SME to assess. On top of 
that, courses should be given in self-paced format during non-working hours to allow 
SMEs and their employees to attend them. One interviewee stated: “The learning 
outcomes of courses should be aligned with the needs of SMEs. This requires 
communication between firms and education providers”. Thus, to make courses relevant 
to SMEs, education providers and firms have to collaborate in curriculum development. 

300 Be rge r, T., & Fre y, C . B. (2016), Digitalization, Jobs, and Convergence  in Europe: Strategies for C losing the 

Sk ills Gap. Procedia - Social and Behavioral Sciences, 64(4), 441–454. 
https://doi.org/10.1177/0002764217701217  

102 

 
 
                                              
Some universities already design courses with the community in mind  and, as a result, IT 
course curricula should become more business-oriented301.  

Some interviewees called into question the necessity of developing digital skills for all 
SMEs. They acknowledge the likelihood and importance of data-driven firms and 
economies, but foresee a model in which the market will provide data services for firms. 
As one interviewee explained: “SMEs are not capable of doing anything with data 
themselves. Most of the time, both large and small  firms will be buying data solutions 
from the market”. One of these initiatives is Coursedot302, an online marketplace that 
connects trainers and firms. Trainers can provide upskilling to firms both off - and online, 
tailored to the needs of the SME. 

5.7.2.  Reskilling the current workforce 

The approach of reskilling the current workforce, is to quickly react to the shortage of IT 
professionals. People are encouraged to leave their current industry and to become IT 
professionals. Four initiatives in particular focus on retraining unemployed individuals. 
These initiatives are Social Builder (France), The Digital Academy (Czech Republic), ICT 
Professionals (Spain) and Code for All (Portugal). All of these initiatives are run by 
private organisations, but are not necessarily tailored to skills needed by SMEs.  

In short, reskilling appears to be a small part of the initiatives we found. If it is included 
in an initiative, it is often privately run and focuses on unemployed people. Most 
initiatives that focus on reskilling are short and provide basic rather than advanced skills, 
as professional or long-term education is needed to reach a high level of digital 
proficiency. Many of these basic reskilling courses are sponsored by a third party 
(government or a private organisation), thereby reducing the fee for the participants. In 
this sense, reskilling enables people to acquire starting qualifications and enhance their 
position in the labour market. At the same time, it offers an opportunity to reduce the 
number of people in ‘redundant’ jobs once the digital transformation kicks in303. Hence, 
reskilling  could be a solution only in case basic digital skills are in demand in the EU 
Member States. 

5.7.3.  Educating the future workforce 

Formal education is the cornerstone of acquiring skills304. A long-term solution to closing 
the digital skills gap requires therefore adaptation of the current educational system. As 
mentioned under upskilling the current workforce, course curricula have to be made 
more relevant to SMEs. However, the curricula have to be adapted in primary and 
secondary schools as well.  

301 W amba, S. F. (2017), Big data analytics and business process innovation. Business Process Management 

Journal, 23(3), 470–476. https://doi.org/10.1108/09574090910954864  

302 https://coursedot.com/ 

303 Dolphin, T. (2015), Technology, globalisation and the future  of work  in Europe: Essays on employment in a 
digitised e conomy. Available at: http://www.ippr.org/files/publications/pdf/technology-globalisation-future-of-
work _Mar2015.pdf?nore direct=1  

304 Be rge r, T., & Fre y, C . B. (2016), Digitalization, Jobs, and Convergence  in Europe: Strategies for C losing the 

Sk ills Gap. Published January. Available at: 
https://www.ox fordmartin.ox.ac.uk/downloads/reports/SCALE_Digitalisati on_Final.pdf  

103 

 
 
 
                                              
Logical thinking, critical analysis, coding, algorithms and data-literacy should be taught in 
schools from an early age305. Coding became part of the curriculum in some British 
schools from the age of five306. Initiatives like ProgeTiger (Estonia), Coding Class 
(Denmark), Samsung Innovation Camp (Italy) and Codepact (The Netherlands) are 
aiming  to familiarize children and students with coding and programming. These 
initiatives are often in partnerships with technology companies like Samsung, Google and 
Accenture, to provide training to children at no cost to the schools.  

Crescere in Digitale (Italy) is an initiative in partnership with Google, providing paid 
internships to students. Students learn IT-related skills while doing an internship at 
SMEs. Students get a monthly allowance from the initiative and the SMEs get in contact 
with students that can help their businesses.  

While the need to update or reform the educational system in Europe is mentioned often, 
one participant during the first expert workshop in Brussels said: “firms complain about 
educational institutions that their graduates do not possess the relevant hard skills”. The 
explanation he gave was that the duration of educational programs is too long, meaning 
that skills acquired during that time are outdated when a student graduates. This is an 
argument for the idea of lifelong learning. As Cedefop points out, t his should be the 
responsibility of both the individual and the firm, as both benefit from keeping skills and 
knowledge up-to-date307.  

Short-term initiatives cannot address the current and future digital skills gap, therefore 
there is a need for the greater focus on digital skills in formal education institutions at all 
level, from schools to universities. Existing initiatives recognise their limited potential in 
addressing skills gaps, therefore they serve only as temporary, immediate solutions. The 
future workforce needs to possess both knowledge, skills and life-learning mindset to 
quickly adapt to market needs and technological advances.  

5.7.4.  Conclusions 

The definition of digital skills varies to a large extent. When digital skills are clearly 
defined, normally it is a narrow set of skills related to coding, programming or online 
marketing. These skills are important, but hardly cover the whole spectrum of  digital 
skills.  Hence, there is a need for a greater focus on combination of technical skills with 
the 21st century skills, such as critical thinking, communication, creativity.  

The scale and variety of the digital skills gaps across the EU has given rise to an equally 
complex landscape of initiatives, projects and players that try to deal with the challenge. 
This challenge is tackled by increasing the availability of digital skills trainings for the 
workforce that focus on either upskilling, reskilling or by including digital skills in the 
curricula of formal education institutions. Digital skills initiatives that focus on upskilling 
are more common than those on reskilling, as upskilling is needed for a continuous 
improvement of skills and catching-up with technological progress, while reskilling is 
typically offered as a basic introduction into the ICT profession for unemployed. The 
education of future workforce is of utmost importance for addressing the digital skills 

305 Be ck er, T., C urry, E., Jentzsch, A., & Palmetshofer, W. (2016), Ne w horizons for a data-driven economy: A 

roadmap for usage and e xploitation of big data in Europe. Springer O pen. Available at: 
https://doi.org/10.1007/978-3-319-21569-3_16  

306 Dolphin, T. (2015), Technology, globalisation and the future  of work  in Europe: Essays on employment in a 
digitised e conomy. Available at: http://www.ippr.org/files/publications/pdf/technology-globalisation-future-of-
work _Mar2015.pdf?nore direct=1  

307 C e defop (2018), Insights into skill shortages and skill mismatch: learning from C edefop’s European skills and 
jobs survey. Luxembourg: Publications O ffice. Available at: http://www.ce de fop.europa.eu/en/publications -
and-resources/publications/3075 

104 

 
 
                                              
gaps in the EU. The current short -term initiatives cannot replace in full capacity the lack 
of digital education at schools and higher academic institutions.  

Considering the diversity of existing initiatives (e.g., type of training, skills levels), few of 
them are directly targeting skills gaps of SMEs. The majority of existing initiatives do not 
have a specific target group or a sector in which digital skills are being promoted. The 
generic approach in addressing skills gaps does not exclude SMEs, as they still benefit 
from trainings that are provided for the general population or for all companies and 
employees, but it might not address their particular needs and prevent access to training 
due to high competition for participation in an initiative. Nevertheless, currently, across 
the EU there are several digital skills  initiatives on national, regional, EU levels that are 
specifically designed for SMEs, hence, various actors recognise particular needs and 
challenges in small organisations/companies. 

The digital skills initiatives are provided at the regional, national and EU levels, and they 
are implemented by special agencies, consortia, PPPs or private sector organisations. 
Both public and private organisations offer digital skills trainings, however, the diversity 
of trainings provided by private companies is larger, due to market adjustment to specific 
company needs. The European level initiatives are more focused on understanding skills 
needs and offering easy-to-use online tools and basic trainings. The sectoral, regional 
and national initiatives allow to build cooperation between participants and other 
stakeholders, however, due to a narrower target group the sectoral approach might lead 
to a better alignment of digital skills training to needs of a particular sector. Among the 
major advantages of national and regional initiatives are availability of training in a local 
language, easy accessibility, involvement of local actors and conformity of training with 
national/regional digitalization strategies.  

The private-public partnerships c ould be an effective solution for building synergies, 
improving cooperation between public and private organisations, pooling resources and 
for reaching common objectives in digital skills  development. However, the disadvantage 
of such arrangement lies in complexity of collaboration between public and private 
organisations, such as long decision-making process. Our analysis shows that many of 
existing public -private initiatives are aimed at fostering innovation by sharing knowledge 
and valorization. 

Since our study has not mapped all existing digital skills initiatives across the EU it is 
difficult to assess in what areas, sectors and geographical regions there is a lack of 
particular skills initiatives for SMEs. In contrast to the US, the EU seems to be lac king 
initiatives on cybersecurity, however, similarly to the EU, the US also uses the generic 
approach in addressing digital skills gaps. The majority of mapped digital skills initiatives 
are provided either across the EU or by Western European countries, particularly 
Germany, Denmark  and France. This signals that at least the visibility of digital skills 
initiatives launched in Western Europe is higher than in Eastern Europe.  

To combat the digital skills gap, a coordinated approach is needed. First, the digital skills 
need to be clearly defined. With a clear definition it is possible to identify specific needs 
of SMEs and how to address them. A structural change in the training and education of 
people in Europe is necessary to close the gap, but also to keep the skills up-to-date. 
Children need to be educated in the basic digital skills, so by the time they choose 
studies or careers they have basic digital skills and knowledge. From there, lifelong 
learning is needed to maintain these skills and keep them relevant in a changing 
environment.  

To provide SMEs with digital skills in the short term, people can be upskilled or reskilled. 
However, prior to training, the education has to be aligned with the skills needs and 
expectations of SMEs. This includes clear and easy to understand learning outcomes. If 
employees are trained, the format has to be adjusted to the context of SMEs as well. This 
could include self-paced online courses and training on location or during the evenings.  

105 

 
 
106 

 
 
 
 
PART II: THE WAY FORWARD 

107 

 
 
 
6.  A FIVE-YEAR STRATEGY ON SKILLS DEVELOPMENT FOR SMES 

As illustrated in Part I of this report, the adoption of BIC technologies is of crucial 
importance for SMEs, primarily because of two main reasons: 1) ensuring business 
continuity, and 2) ensuring growth opportunities. At the same time, a lack of skills is one 
of the top barriers that holds SMEs back from adopting BIC technologies. There is a clear 
mismatch between supply and demand when it comes to BIC skills, both from a 
qualitative and a quantitative perspective. From a qualitative perspective, there is a need 
to ensure that the skills portfolio of current and future employees better match SME 
needs. As illustrated in section 4, skills required for adopting BIC depend on the maturity 
and type of an SME, but often involves a combination of hard skills, soft skills and 
business expertise. Too often, the type of skills that current and future employees 
possess are not in line with SMEs’ needs. From a quantitative perspective, one needs to 
resolve the current scarcity on the market, especially with regards to hard skills. Europe 
needs to ensure that a sufficient number of people is qualified for working with BIC 
technologies – not only for the big corporates, but equally for SMEs.  

Apart from labour market issues, SMEs encounter other barriers in their efforts to upskill 
their existing workforce and to attract talents, inter alia, limited financial and human 
resources, a mismatch between their skills needs and training offerings, and a lack of 
awareness. SMEs hardly provide training to their employees. Addressing these barriers is 
key for fostering SME skills development, and hence facilitating them in their journey to 
embrace BIC technologies.  

This chapter presents a holistic strategy for addressing these barriers and is developed in 
close collaboration with relevant stakeholder groups.   

6.1.  Design principles  

The development of a common vision for supporting specialised skills development for 
SMEs was guided by a number of design principles.  

  The vision is evidence-based - the vision has to be based on an empirical 

analysis of the current state of play with regards to BIC skills developments for 
SMEs, in terms of a thorough assessment of SMEs’ needs versus what is available, 
and barriers faced by SMEs. The approach taken in this initiative consists in 
extensive desk research, complemented by expert interviews and an online 
survey. Findings were then validated during expert workshops. This approach 
justifies the call for action as outlined further on in this section.  

  The vision is forward-looking – as the BIC skills gap will not disappear from one 
day to the other, adopting a long-term and forward-looking approach is essential. 
Up- and reskilling the current and future workforce requires a consistent approach 
over years, in which 2023 should be considered as an intermediate milestone 
rather than a final destination.  

  The vision is demand-driven – SMEs have some unique characteristics as 

compared to larger enterprises. These particularities should be taken into account 
in order for the vision and related actions to be effective. In addition, skills needs 
from SMEs change rapidly, as a result of the rapidly evolving BIC landscape. Both 
factors require involvement of SMEs, not only during the design phase but also 
during the implementation. 

  The vision offers a direction for development – as the pace of change in the 

technological domains under consideration is tremendous, the vision sets out the 
general direction, from which actions can be distilled. However, as the 
technological landscape is evolving fast, it might be needed to tweak the timing, 
content and scope of actions over time, while the more general direction for 
development remains consistent.  

108 

 
 
  The vision is action-oriented – as described under the previous bullet, the vision 

sets out the general strategic direction. But as highlighted during the interviews, 
SMEs are best helped by concrete actions and solutions. Therefore, the vision 
should offer opportunities to derive concrete actions from it, for various relevant 
stakeholder groups.   

  The vision is supported by main stakeholder groups – the problem analysis 

revealed that many different stakeholders have a role to play, so addressing the 
problem requires a shared vision that reflects the interest of key stakeholders at 
EU, national and regional levels, representing different backgrounds (public, 
private, PPP’s).  

  The vision is international – as the BIC skills gap is multi-country problem, with 
dependencies between countries (eg international talent sourcing), effectively 
addressing the BIC skills gap requires a multi-country approach and cross-border 
collaboration. Building on both European and US experiences, the vision primarily 
addresses the EU Member States.  

  The vision addresses a multilevel stakeholder field – several stakeholders on 
several levels have a role to play in addressing BIC skills development for SMEs. 
Therefore, the vision should facilitate the identification of roles and concrete 
actions at different levels – European, national, regional - for different stakeholder 
groups. The latter can include public authorities, private actors, educational 
institutions and public -private partnerships.    

  The vision acknowledges the diverse SME landscape – the vision acknowledges 
at the one hand the broad and diverse SME landscape, but on the other leaves 
enough room for action to derive from the vision that are targeted to specific SME 
categories and (industry-) specific.  

6.2.  Vision statement 

The activities conducted led to the formulation of the following vision statement, which is 
supported and validated by a broad variety of relevant stakeholder groups that were 
consulted in the process:  

Enabling  an  increased adoption of  cybersecurity, big  data, and  internet of  things  by  
European SMEs  via  supporting measures that strengthen ecosystems and  structurally 
enhance the supply of necessary skills and facilitate organisational development. 

In this vision statement, the following elements are important: 

  SMEs are part of a value chain of companies, which allows them to share, 
collaborate, learn and grow. Measures should strengthen these ecosystems, as 
they are the most effective driving force of increasing the adoption of big data, 
internet of things and cybersecurity.  

  Advancing the digital maturity of SMEs starts with a strategy to adopt 

technology to create business value: understanding the skills a company 
requires, starts with an understanding of how the technology contributes to the 
company’s strategy. Measures should be aimed at increasing awareness of how to 
embrace and embed these technologies in the digital strategy of the enterprise, 
and from that direction derive the competences and roles and skills involved to 
deliver on that strategic objective. Measures should also include concrete tools 
and instruments that facilitate capability development in the organisation 
(especially from an HR function point of view – which is often lacking or minimally 
organised in SMEs). 

  Technology adoption requires the right skillset. Measures should be aimed 

towards increasing the supply of the necessary skills on the labour market, via 
upskilling programmes of employees in the company and by increasing the 
number of graduates in the relevant educational fields (universities, business 
schools, VET). 

109 

 
 
6.3.  Supporting  measures  to  be  considered  to  boost  skills 

development 

In order for this vision to become effective, it needs to be operationalised and translated 
into concrete supporting measures to tackle the variety of barriers as presented in the 
root-cause analysis in section 2.5.3.  

The underlying concept to design a roadmap with supporting measures stems from the 
understanding of the balance between an organisation’s strategy on why and how to 
adopt technology as business opportunity, and the required human capital to deliver on 
that investment. It is about the decision to invest in building a capability at the 
organisational level (‘decide’), to systematically plan for delivering on that decision 
(‘plan’), and consequently finding the right people to build competences necessary for 
that capability (‘execute’). Employees fulfil roles associated with those competences, 
using methods and tools to add specific value. We used this step-wise approach to 
structure the roadmap with supporting measures, building from the barrier’s analysis. 
Besides these three generic steps of technology adoption, the fourth factor is the direct 
environment or ecosystem. 

Figure 44 Step-wise  approach for organisations  to adopt new technologies  for creating  value  

The supporting measures are consequently clustered into four thematic streams: 

(1)  Strengthening ecosystems: Being connected and embedded in regional or 
sectoral support structures – ‘ecosystems’ - is essential for SMEs’ skills 
development. In every corner of Europe, SMEs need to be embedded in networks 
and have access to nearby support (knowledge, guidance and learning).  

(2)  Strategic outlook development (‘decide’): Aimed to Increase the 

understanding of the strategic business opportunity of adoption of BIC. Starting 
with raising awareness and creating a strategic outlook. Also requiring 
strengthening of direct business environment and facilitation of collective action. 

(3)  Structured skills development (‘plan’): From vision to plan: support SMEs 

with the implementation of structured skills development, enhance capabilities for 
assessment, monitoring and decision-making (the business case!) & increase 
transparency and access to funding. 

(4) 

Tailoring training to SMEs’ needs (‘execute’): Increase education and training 
offers: build sustainable training offers that match SMEs needs (content, form, 
set-up). Develop training capacity. Collect intelligence to increase understanding 
of needs. Reduce direct costs. 

110 

 
 
 
 
Figure 45 Visualisation  of the roadmap’s  main streams of action 

6.3.1.  Stream A - Strengthening the 

ecosystem 

Strengthening of the ecosystem revolves around the improvement of access for SMEs to 
knowledge, guidance and learning within their current and other ecosystems. As 
mentioned earlier, being connected and being embedded in regional or sectoral support 
structures – ‘ecosystems’ - is essential for SMEs’ skills development. However, SMEs 
often lack access to such networks, to tacit and explicit knowledge and/or to facilities 
that help accelerate skills development. It can be difficult for them to organise shared 
services – which is easier in an ecosystem -, and the managerial capabilities to become 
anchored in ecosystems are sometimes lacking. Lastly, the availability of BIC skills 
support structures throughout the EU is currently fragmented, with some regions having 
sufficient and adequate services in place, whereas in others no services were found at all 
when it comes to BIC skills. 

Being connected and having access to knowledge, guides in the area of BIC, education 
and facilities is key for SMEs. As an interviewee put it: “for SMEs, it is either link or die. 
In every corner of Europe, SMEs need to be embedded in networks and have access to 
nearby support”. In this respect, it is encouraging that the European Commission 
foresees a crucial role for the Digital Innovation Hubs (DIH) in providing SME support, 
with the goal of having one hub in every region by 2020308. DIHs are one-stop-shops 
where companies can access and test digital innovations, gain the required digital skills, 
get advice on financing support and ultimately accomplish their digital transformation. As 
stated by the EC Commissioner on Digital Economy and Society: “All companies should 
benefit of a DIH  in their region to support the digital transformation. By ensuring a 
strong pan-EU network of DIHs with an investment of €100 min  per year btw 2016-2020 
we make sure everyone is included, in all regions”309.  

The measures for strengthening of the ecosystem (and initiatives) are clustered along 
three sub-goals: 

308 https://ec.europa.eu/digital-single-market/en/blog/digital-innovation-hubs-joining-forces-accelerate-digital-

transformation-european-industry  

309 https://twitter.com/GabrielMariya/status/1027330339734253569   

111 

 
 
 
                                              
A1.  Mapping of ecosystems; 
A2.  Strengthening and expanding existing ecosystems; 
A3.  Boosting the effectiveness of the ecosystems. 

A1.  Mapping of ecosystems 
The mapping of ecosystems is aimed at determining the current state of play by mapping 
of existing ecosystems, identifying their strengths & weakness and increase tra nsparency 
thereof. The overall aim of this sub-goal is to contribute to the availability of and access 
to regional support structures and facilitate the access of SMEs to concrete guidance, 
education and training in the area of BIC skills development offered by these regional 
support structures. 

In order to gather the necessary intelligence on the ecosystems to meet these sub-goals, 
two measures are proposed. The first measure is the investment in research to 
understand the state of play & existing capacities. This includes, for example, the 
mapping of access points/hubs to improve transparency, undertake gap analysis, and the 
take-up of shared services centres.  

The measures described include an assessment of stakeholder involvement for each of 
the measures; and relevant sources, like handbooks, guidance notes or examples of 
successful initiatives. 

Stakeholder involvement is classified in the following categories: 

  Lead: central coordinator, monitors actions undertaken 

  Act: main responsible for implementation of key actions 

  Support: responsible for non-key actions feeding into key actions or participating 

in a non-leading role in key actions 

  Encourage: incentivize participation of other stakeholder groups 

Subject 

Stream / 
Sub-goal 

Measure 

Short 
description 

A. Strengthening the ecosystem > 1. Mapping of ecosystems 

Description 

Invest in research to understand the state of play and 
existing capacities 

Desired output of the research includes, inter alia, a mapping of 
access points/hubs to improve transparency, and the take-up of 
shared services centers. Based upon the research, a gap analysis, 
exploring the difference between current and desired future state 

Stakeholder 
involvement 

  European Commission: Lead & Act – conduct or 

commission research 

  National governments: Support European Commission – 

provide input 

  Education: Support European Commission – provide input 

 

Industry: Support European Commission – provide input 

  Associations: Support European Commission – provide input 

  Other: - 

112 

 
 
 
 
 
The second measure is the creation of shared databases and tools to make information 
accessible to stakeholders. This allows more efficient distribution of information and 
insights, most notably best practices, among stakeholders 

Subject 

Stream 
Sub-goal 
Measure 

Short 
description 
Stakeholder 
involvement 

/ 

A. Strengthening the ecosystem > 1. Mapping of ecosystems 

Description 

Created shared databases and tools to make information 
accessible to stakeholders 

Online available information, accessible to the public, on  

  European Commission: Lead & Act - exchange best practices 

  National governments: Act - database and tool development 

  Education: Support national government – provide input, 

dissemination 

 

Industry: -  

  Associations: -  

  Other: Intermediaries – support national government – provide 

input, dissemination 

A2.  Strengthening and expanding existing ecosystems 
The strengthening and expansion of the existing ecosystems aims to support existing 
networks, hubs and initiatives to reach a more comprehensive coverage which will allow 
them access to every SME.  

Three measures are proposed to achieve these aims. Firstly, policies and funding 
programmes that help to support SME communities, networks and ecosystems should be 
develop and supported. This measure is geared towards providing every SME in EU with 
a nearby hub where they can benefit from information, training, guidance on skills 
development. In particular, support to the Digital Innovation Hubs should be prioritised 
as good example of a hub that has enabled SMEs communities.  

The digital innovation hub initiative seeks to build synergies with already ongoing 
relevant initiatives. A wealth of expertise already exists in Europe, with competence 
centres in several areas already being operational. In addition to 660 cybersecurity 
competence throughout the EU, over 200 so called Digital Innovation Hubs 310 
throughout the EU are providing support to companies in their respective regions. Digital 
Innovation Hubs are one-stop-shops that support companies to become more 
competitive by using digital technologies. They are based upon technology infrastructure 
(competence centre) and provide access to the latest knowledge, expertise and 
technology to support their customers with piloting, testing and experimenting with 
digital innovations. As proximity is considered crucial, they act as a first regional point of 
contact, a doorway. A DIH is a regional multi-partner cooperation and can also have 
strong linkages with service providers outside of their region supporting companies with 
access to their services. Figure 6-2 illustrates the functioning of Digital Innovation Hubs.  

310 http://s3platform.jrc.e c.europa.eu/digital-innovation-hubs  

113 

 
 
 
 
 
                                              
Figure 46 The functioning  of Digital  Innovation  Hubs311 

The present initiative seeks to leverage the wealth of competence centers already 
operational, as DIH’s address several of the barriers identified in this initiative: findability 
and availability of guidance, education and training, and limited financial resources. 
Moreover, the target group and technologies covered by DIH’s are in line with the 
present initiative, as DIH’s have a particular focus on SMEs – although their support is 
not limited to SMEs – and the use of digital technologies such as big data, IoT and 
cybersecurity. 

/ 

A. Strengthening the ecosystem > 2. Strengthening and expanding 
existing ecosystems 

Description 

Develop and support policies & funding programmes that 
help to support SME communities, networks and ecosystems 

Leverage existing Digital Innovation Hubs or stimulate the creation 
of new ones by stimulating downstream actors (CoCs, business dev 
agencies, regional business clusters etc.) to organise/create such 
hubs, offering every SME in Europe to benefit from a nearby support 

Subject 

Stream 
Sub-goal 

Measure 

Short 
description 

311 Ibid. 

114 

 
 
 
 
 
                                              
center. Key here is to stimulate existing or new DIHs  to explicitly 
address the topic of skills development. 

Purpose 

Addressing B1, B2, B3, F2, F3, F5, G1, G2, G5.  

Stakeholder 
involvement 

  European Commission: Lead & Act – develop policies and 

funding programmes 

  National governments: Support European Commission – roll-

out of policies and programmes 

  Education: -  

 

Industry: -  

  Associations: - 

  Other: -  

Secondly, research on the existing policies and initiatives landscape is required to identify 
and promote good practices. This allows to leverage lessons learned from successful 
initiatives instead of reinventing the wheel 

Subject 

Stream / 
Sub-goal 

Measure 

Short 
description 

Description 

A. Strengthening the ecosystem > 2. Strengthening and expanding 
existing ecosystems 

Research the existing policy & initiatives landscape to 
identify and promote good practices  

Successful initiatives in the area of BIC skills development for SMEs 
exist, but are fragmented and not equally available in the EU. Their 
availability tends to be skewed towards Western and Northern 
Europe. Europe should investigate the development of a mechanism 
to: 

  Sustain successful practices in this area; 

  Transfer lessons learned to other regions; 

Scale successful practices where possible 

Stakeholder 
involvement 

  European Commission: Lead & Act – promotion of practices 

  National governments: Act – collect information; Support – 

promotion of practices 

  Education: - 

 

Industry: -  

  Associations: Support national governments – collection, 

promotion  

  Other: - 

As part of this measure, clarifying the business case for SMEs may be an important step 
to make SMEs understand the importance of investment in BIC skills. 

Subject 

Description 

115 

 
 
 
 
 
 
Stream 
Sub-goal 

Measure 

/ 

A. Strengthening the ecosystem > 2. Strengthening and expanding 
existing ecosystems 

Clarify the business case to illustrate ROI and support 
informed decision making 

Short 
description 

Provide examples of positive business cases for SMEs. Preferably 
supported by a simple tools to support SMEs in calculating the BIC 
skills investment 

Stakeholder 
involvement 

  European Commission: Lead / Act – clarify business case, 

promote 

  National governments: Support - promote 

  Education: Support - promote 

 

Industry: -  

  Associations: Support - promote 

  Other: Intermediaries - Support - promote 

Thirdly, policies which help to mobilise accelerators/downstream actors need to be 
extended and, where no specific policies are in place yet, developed. In this measure, 
special attention needs to me given to ensure involvement of SMEs themselves to make 
sure policies are aligned with SME needs 

Subject 

Stream 
Sub-goal 

Measure 

Description 

/ 

A. Strengthening the ecosystem >  2. Strengthening and expanding 
existing ecosystems 

Extend  and  develop  policies  which  help  mobilising 
accelerators/downstream actors 

Short 
description 

Getting  accelerators/downstream  actors  mobilized  by  means  of 
interpersonal communication and peer-to-peer exchange with a focus 
on joint goals.  

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead/Act - develop policies 

  Education: - 

 

Industry: Support national governments – provide input 

  Associations:  

  Other: Downstream - Support national governments – 

provide input 

A3.  Boosting the effectiveness of the ecosystems 
The boosting of the effectiveness of the ecosystems is aimed at ensuring that the support 
offered by the ecosystem to SMEs is optimally focused on achieving the overarching goal 
of e-skills development within SMEs. To this aim, two measures are proposed.  

Firstly, EU and national programs that facilitate knowledge sharing should be initiated. 
Knowledge sharing allows stakeholder within the ecosystem to learn from others about 

116 

 
 
 
 
 
the optimal method to support SMEs in their understanding of the need of investment in 
BIC skills and the ways in which to obtain these skills. 

Subject 

Stream / 
Sub-goal 

Measure 

Short 
description 

Description 

A. Strengthening the ecosystem > 3. Boosting the effectiveness of 
the ecosystems 

Initiate EU and national programs that facilitate knowledge 
sharing 

The development of programs that aim to connect and mobilize 
people and resources within the ecosystem with a focus on 
knowledge sharing and mutual learning. Important to ensure any 
exchange of knowledge is based upon information that is relevant 
and up-to-date. 

Stakeholder 
involvement 

  European Commission: Lead/Act – EU level 

  National governments: Act – national level 

  Education: Support – contribute input for knowledge sharing 

 

Industry: Support – contribute input for knowledge sharing 

  Associations: - 

  Other: -  

Secondly, a collaboration between hubs and education is expected to improve the match 
between demand for information and skills  from the side of SMEs and its supply as 
offered by education. A better match ensures a more effective adaption of BIC by SMEs. 
One such example is the JADS MKB Data-lab in the Netherlands, which offers tools and 
solutions to SMEs that allow them to integrate data science into their business by means 
of PoCs. 

Subject 

Stream 
Sub-goal 

Measure 

Description 

/ 

A. Strengthening the ecosystem > 3. Boosting the effectiveness of 
the ecosystems 

Stimulate collaboration between hubs and education system 
to better tailor to needs 

Short 
description 

Information available at hubs on skills  needs of SMEs can strengthen 
the adaption of BIC within SMEs 

Stakeholder 
involvement 

  European Commission: - 

  National governments:  Lead 

  Education: Act – improve curriculum 

 

Industry: Act – transfer information on needs 

  Associations: Support industry – stocktaking of needs 

  Other: Intermediaries – Support industry – stocktaking 

of needs 

117 

 
 
 
 
 
6.3.2.  Stream B - Strategic outlook 

development 

Being connected and having access to knowledge, guides in the area of BIC, education 
and facilities is key for SMEs. As an interviewee put it: “for SMEs, it is either link or die. 
In every corner of Europe, SMEs need to be embedded in networks and have access to 
nearby support”. In this respect, it is encouraging that the European Commission foresee 
a crucial role for the Digital Innovation Hubs (DIH) in providing SME support, with the 
goal of having one hub in every region by 2020312. DIHs are one-stop-shops where 
companies can access and test digital innovations, gain the required digital skills, get 
advice on financing support and ultimately accomplish their digital transformation. As 
stated by the EC Commissioner on Digital Economy and Society: “All companies should 
benefit of a DIH  in their region to support the digital transformation. By ensuring a 
strong pan-EU network of DIHs with an investment of €100 min  per year btw 2016-2020 
we make sure everyone is included, in all regions”313.  

B1.  Raise awareness within SMEs 
B2.  Strengthen the direct business environment of SMEs 
B3.  Facilitate collective action 

B1.  Raise awareness within SMEs 
Instead of jumping into developing BIC skills, SMEs first need to be able to articulate 
their skills  need: what are exactly the roles needed, and which skills do these roles need 
to have to work with BIC technologies? Information of SME managers and/or owners on 
the potential of the BIC technologies is an important first measure. 

Subject 

Stream 
Sub-goal 
Measure 

/ 

B. Strategic outlook development > 1. Raise awareness within SMEs 

Description 

Inform  SME  managers/owners about  the  potential  of  BIC 
technologies and encourage innovation 

Short 
description 

Improve awareness and facilitate the implementation of 
cybersecurity requirements and standards – that includes adaptation 
of the standards for SMEs. The latter is already initiated in various 
initiatives, among which the “Info sec for SMEs Guide” by Digit al 
SME Alliance. This assists SMEs in setting up ISO / IEC 27001 on 
information security management.  

An investigation of what is already being developed, such as the 
aforementioned guide, should lead to the identification of blind 
spots. Within these blind spots, action should be taken. This should 
be combined with a promotion and awareness campaign, making 
SMEs aware of cybersecurity requirements and standards and the 
existence of such guides.  

Stakeholder 
involvement 

  European Commission: Lead 

  National governments: Act - develop/encourage policies 

312 https://ec.europa.eu/digital-single-market/en/blog/digital-innovation-hubs-joining-forces-accelerate-digital-

transformation-european-industry  

313 https://twitter.com/GabrielMariya/status/102 7330339734253569  

118 

 
 
 
 
                                              
  Education: - 

 

Industry: -  

  Associations: Support national governments – promotion of 

insights 

  Other: - 

Info sec for SMEs  

Relevant 
resources 

Specialised HR departments are often lacking in SMEs and a slow adoption of existing 
competence frameworks in existing trainings further contribute to a lack of awareness 
and difficulties in pinpointing the skills to be developed to benefit from BIC technologies. 
To address this challenge, the ecosystem of the SMEs can play a supportive role in 
raising awareness among SMEs by offering information. 

Subject 

Stream  Sub-
goal 
Measure 

Short 
description 

Stakeholder 
involvement 

B. Strategic outlook development > 1. Raise awareness within SMEs 

Description 

Support  organisations, initiatives and  platforms  that  foster 
collaboration and knowledge sharing 

Nearby support for SMEs is essential, as they tend to have a regional 
focus. Regional  training  programmes  have the  potential of  linking 
SMEs to other SMEs that follow the same  training, thus facilitating 
sustainable networks, knowledge sharing and peer-2-peer learning. 
Effective existing training  mechanisms offer a  portfolio of  services, 
addressing the several stages of maturity, from awareness to action: 
starting with best practices and company visits, to business model 
redesign, actual experimenting, testing, etc. 

  European Commission: - 

  National governments: Lead/Act – develop support policies 

  Education: - 

 

Industry: -  

  Associations: Support initiatives 

  Other: Intermediaries - Act - develop initiatives 

Relevant 
resources 

Mittelstand 4.0 

Intermediaries can also play an important role in the adaption of BIC technologies within 
SMEs. Furthermore, if SME owner/managers do not know what they need, they are not 
able to assess whether it is more beneficial to internalise certain skills or to hire them on 
the market. 

Intermediaries like accountants have a trusted relationship with SMEs, meaning they can 
also act as trusted advisor in relation to BIC adoption. Similarly, other stakeholders in the 
ecosystem may play a similar  role in advising SMEs on BIC. Insurance companies are in 
frequent contact with SMEs and have a similar  interest as the SMEs to prevent SMEs 
being exposed to societal risks (e.g. cyberattacks targeting the SME).  

119 

 
 
 
 
 
Subject 

Stream 
Sub-goal 
Measure 

/ 

B. Strategic outlook development > 1. Raise awareness within SMEs 

Description 

Involve intermediaries that can act as advisors in adoption of 
BIC  technologies  – in  particular  engage accountancies and 
insurance companies to increase (cybersecurity) awareness 
and prevention  

Short 
description 

Stimulate intermediaries to (further) extend their role as advisor to 
also include advisory services on BIC technologies. 

Accountancies are in regular contact with SMEs and advise them 
on business continuity matters. Most accountants are SMEs 
themselves and hence can understand SMEs. They are well 
positioned to make SMEs aware of the threats (and opportunities) of 
cybersecurity, and trigger them to action. Accountancies across 
Europe are already developing initial points of view and checklists to 
support SMEs in this challenge (some can be found here).  

Insurance companies on the other hand carry part of the societal 
risk of SMEs being impacted by cyber incidents. Increasingly 
insurance companies are moving to pro-active prevention policies to 
make SMEs aware about the risks and about easy steps to become 
more secure and resilient. Via their insurance policies they have a 
financial lever to trigger SMEs to action. 

Stakeholder 
involvement 

  European Commission: Stimulate – Uptake by associations at 

European level 

  National governments: Stimulate – Uptake by associations at 

the national level 

  Education: - 

 

Industry: -  

  Associations: Intermediaries associations – support 

intermediaries 

  Other: Intermediaries - Act - offer advisory services on 

BIC adoption  

An alternative and more pressing route to raise awareness consists of legal obligation. 
Most notably, cybersecurity is an area with potential negative externalities in the form of 
network infection throughout a broader ecosystem. Consequently, there may be ground 
to consider legislation related to cybersecurity. 

Subject 

Stream 
Sub-goal 

Measure 

Description 

/ 

B. Strategic outlook development > 1. Raise awareness within 
SMEs 

Investigate the feasibility of legal enforcement of 
cybersecurity 

Short 
description 

Our analysis shows that awareness of cybersecurity is still an issue 
for many SMEs, while cyberattacks may impact the whole value 

120 

 
 
 
 
chain. Therefore, the feasibility of a legal enforcement of 
cybersecurity should be investigated, including accompanying 
cybersecurity assessments to support organisations in their uptake 
of cybersecurity. Penalties and tax credits can be considered. 

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead 

  Education: - 

 

Industry: Support national government – feasibility 
assessment 

  Associations: Support national government – feasibility 

assessment 

  Other: - 

B2.  Strengthen the direct business environment of SMEs 
The technological savviness of SME owner/managers depends on a multitude of factors, 
of which one is age. Overall, SME owner/managers have difficulties understanding the 
impact of BIC technologies, or realising the urgency to act on it. A long-term vision on 
adopting BIC is lacking, and the focus is rather on operational matters. In addition to this 
internal perspective, also the technological maturity of the environment plays a role, as 
an environment stimulating for instance open data fosters the uptake of big data. To 
address the above portrayed relatively low ‘tech maturity’, both internal and external, 
several measures are proposed. 

First, collaboration with researchers can be stimulated to improve SMEs possibilities in 
the field of BIC. One such example is the cooperative research centres program in 
Australia.314 

Subject 

Stream 
Sub-goal 

Measure 

/ 

B. Strategic outlook development > 2. Strengthen the direct 
business environment of SMEs 

Description 

Stimulate collaborative projects between SMEs and 
researchers 

Short 
description 

The technological maturity of SME manager/owners can be 
improved, and SMEs can be supported in the adoption of BIC by 
working together with technology experts, such as researchers. To 
this end, research schemes can be developed specifically aimed at 
starting joint projects between SMEs and researchers on the topic of 
skills development for SMEs. Moreover, data labs may enable SMEs 
to explore the potential of BIC.  

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead/Act - Encourage uptake 

  Education: Act – engage with SMEs 

 

Industry: Act – engage with Education 

314 

https://www.business.gov.au/assistance/cooperative-research-centre s-programme/cooperative-research-

ce ntre s-projects-crc-ps  

121 

 
 
 
                                              
  Associations: Support industry – engagement with Education 

  Other: - 

Second, continues investment in infrastructure will remain important as necessary 
condition to allow SMEs to build up a business case on investment in BIC.  

Subject 

Description 

Stream 
Sub-goal 

/ 

B. Strategic outlook development > 2. Strengthen the direct 
business environment of SMEs 

Measure 

Continue to invest in infrastructure that enables technology 
adoption 

Short 
description 

Efforts to improve framework conditions such as open data, open 
APIs, the data sharing economy, should be continued and sustained 
to facilitate the adoption of big data and IoT. But also investment 
into the main physical infrastructure (broadband, 5G) will warrant 
continued attention. 

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead/Act – develop infrastructure 

policy, stimulation of investment  

  Education: - 

 

Industry: -  

  Associations: - 

  Other: Infra providers - Act –Invest in infrastructure 

Third, a matchmaking platform can catalyse SMEs in their steps into BIC.  

Subject 

Stream 
Sub-goal 

Measure 

Description 

/ 

B. Strategic outlook development > 2. Strengthen the direct 
business environment of SMEs 

Design a matchmaking platform that links technology 
solutions in the area of BIC with SME needs 

Short 
description 

Development of platforms at local/regional level with a specific focus 
on (IT-using) SMEs. To ensure optimal platform impact, 
transparency on quality of services and prices of services offered 
should be ensured. Possibly, the platform may also facilitate in joint 
procurement and shared services (described under B3). 

Stakeholder 
involvement 

  European Commission: Act – Exchange of best practices 

  National governments: Support local regional governments – 

platform development stimulation 

  Education: Support Intermediaries – provide technology 

solutions 

 

Industry: -  

  Associations: - 

122 

 
 
 
 
  Other: Intermediaries – Lead/Act – develop platforms; 

Local/regional government – Support - platform development 

As fourth and final measure, national cybersecurity frameworks can strengthen SMEs’ 
business environment. 

Subject 

Stream 
Sub-goal 

Measure 

Short 
description 

/ 

B. Strategic outlook development > 2. Strengthen the direct business 
environment of SMEs 

Description 

Stimulate  the  development  of  national  Cybersecurity 
frameworks for SMEs 

The development of a national framework helps to create a common 
language to compare the business practices to prevent and  tackle 
cyber risks. The framework may  help an enterprise to plan a cyber 
risk  management strategy, developed over the time according to its 
business, size and other distinguishing and specific elements of the  
enterprise.  Adoption  of  the  framework  can  be  mandatory  or 
voluntary, and can be  accompanied by for instance checklists, and 
self-assessments. Interviewees  also  suggested  to  investigate  the 
feasibility of cybersecurity audits under the framework. In the init ial 
audit phase (first years), financial support from the government could 
be  required,  while  after  some  time  communities  should  be  self-
supporting with regards to the auditor. 

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead/Act – stimulation of 
developments, promotion of the frameworks 

  Education: - 

 

Industry: -  

  Associations: Support national government - promotion of 

the frameworks 

  Other: Intermediaries – Support national government - 
promotion of the frameworks, ENISA – support national 
governments – inform on developments 

Facilitate collective action 

B3. 
One common challenge for SMEs is overcoming the small scale of the company, resulting 
in diseconomies of scale. Investment that are partly fixed, that is similar  for each 
company, weight relatively heavier on small firms in comparison to large firms. To 
overcome this challenge, collective actions with other SMEs or with partners within the 
value chain may be used. 

123 

 
 
 
 
Most notably, SMEs may want to explore joint procurement and shared services. By 
sharing the burden among more parties, the (financial) barriers for SMEs reduce. One 
such example is the Cyber Resilience Center Brainport initiative in the Netherlands. 315 

315 

https://www.brainport.nl/nieuws -ontwikkelingen/primeur-brainport-eindhoven-voor-ketenwe erbaarheid-

cybe rse curity 

124 

 
 
 
 
                                              
Subject 

Stream / 
Sub-goal 
Measure 

Short 
description 

B. Strategic outlook development > 3. Facilitate collective action 

Description 

Promote and facilitate joint procurement and shared services 

SMEs alone might not have the financial resources to effectively 
ensure cybersecurity or to work with big data/IoT but organising 
shared services with other SMEs (or joint procurement) might enable 
them to work with BIC. Such cooperation can also be achieved with 
large companies in the value chain. Further investigation into the 
conditions and success factors and the proven instruments to drive 
shared services is recommended. 

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead/Act - review blocking regulation 

  Education: - 

 

Industry: -  

  Associations: Support national government - promotion of the 

frameworks 

  Other: Intermediaries – Support national government - 

promotion of the frameworks 

6.3.3.  Stream C - Structured skills 

development 

The technological savviness of SME owner/managers depends on a multitude of factors, 
of which one is age. Overall, SME owner/managers have difficulties understanding the 
impact of BIC technologies, or realising the urgency to act on it. A long-term vision on 
adopting BIC is lacking, and the focus is rather on operational matters. In addition to this 
internal perspective, also the technological maturity of the environment plays a role, as 
an environment stimulating for instance open data fosters the uptake of big data.  

To address the above portrayed relatively low ‘tech maturity’, both internal and external, 
the following sub-goals are identified.  

C1.  Support implementation of structured skills development  
C2.  Enhance capabilities for monitoring & decision-making in SMEs 
C3. 

Increase transparency and access to funding 

C1. Support implementation of structured skills development 
Professionals possessing the specialised skills needed to work with BIC technologies are 
scarce. SMEs face several challenges in this regard, within the context of an ageing 
European workforce. SMEs compete with big corporates to attract and retain talents that 
possess the required combination of skills. And it is not just about attracting and 
retaining talents; also, continuous development of skills and knowledge is essential for 
the growth of their company. To overcome these challenges, this initiative fo resees the 
following measures.  

Existing initiatives form an important starting point. Plenty of blueprints, framework and 
tools are available that can support in their structured skills development. Examples in 
Europe include the e-Competence framework (e-CF) and the EDISON program for data 
science. In the United States, the NIST cybersecurity framework, can serve as an 
example. 

125 

 
 
 
 
Subject 

Stream / 
Sub-goal 

Measure 

Short 
description 

Description 

C. Structured skills development > 1. Support implementation of 
structured skills development 

Promote blueprints, practical frameworks and tools that 
support SMEs to build a smart (HR) strategy 

The blueprints, frameworks and tools identify which competences 
are necessary to be able to develop specific capabilities; and which 
roles are involved into achieving these capabilities. Preferably, the 
blueprints, frameworks and tools also offer a self-assessment that 
allows SMEs to obtain a clear insight into any gaps between available 
and required competences. 

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead 

  Education: Act - identify tools 

 

Industry: Act - express needs 

  Associations: Act - tailoring tools to SME needs 

  Other: Downstream - support Industry – identification 

of needs 

Key insights from the various blueprints, frameworks and tool may be bundled into a 
single, easily accessible starters guide for SMEs. 

Subject 

Description 

Stream 
Sub-goal 

/ 

C. Structured skills development > 1. Support implementation of 
structured skills development 

Measure 

Develop ‘how to start’-guidance for SMEs 

Short 
description 

Consolidation of information from blueprints, frameworks and tools 
into a single source. Tailoring the information for different company 
size classes. Explore improvement on accessibility of the document, 
including editorial and the location (e.g. a single web-portal). 

Stakeholder 
involvement 

  European Commission: Lead/Act – develop 

materials, promotion 

  National governments: Support European 

Commission – promotion 

  Education: - 

 

Industry: -  

  Associations: Support European Commission – promotion 

  Other: - 

Also within value chains, various examples of actions supportive to SMEs skills 
development, most notably in cyber resilience, are available. One such example is the 

126 

 
 
 
 
cyber resilience centre Brainport in the Netherlands.316 In this initiative, the larger firms 
support SMEs with respect to their cybersecurity to improve the overall resilience of the 
entire value chain.  

Subject 

Stream 
Sub-goal 

Measure 

/ 

C. Structured skills development > 1. Support implementation of 
structured skills development  

Description 

Promote examples of value chains supporting SMEs to 
become cyber resilient 

Short 
description 

Similar  to joint procurement and shared services, as discussed under 
stream B3, cooperation within the value chain can offer benefits to 
SMEs to improve cyver resilience  

Stakeholder 
involvement 

  European Commission: Lead 

  National governments: Support Associations - Encourage 

associations 

  Education: - 

 

Industry: Initiate practices to strengthen the value chain  

  Associations: Act - collect examples 

  Other: Downstream - support associations – collect examples 

Structured skills development is bound to be more successful if a proper stocktaking of 
the skilsl potential within the company is properly assessed, for example by means of an 
aptitude test. One such a successful example is Skillnet Ireland, where a significant 
untapped potential for cyber skills turned out to be present. 

Subject 

Stream 
Sub-goal 

Measure 

Description 

/ 

C. Structured skills development > 1. Support implementation of 
structured skills development  

Tap into talent and involve staff in the development of a 
company HR strategy 

Short 
description 

Test for latent skills already present within the company by means 
of an aptitude test.  

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead 

  Education: Support industry – offer insights 

 

Industry: Act - amend HR strategy 

  Associations: Support industry – encourage action 

  Other: Downstream- Support Industry – offer insights, 

encourage action 

316 https://cwbrainport.nl 

127 

 
 
 
                                              
To make attraction of qualified external staff easier, a recognition mechanism for BIC 
skills. An important initiative to recognise informal learning is presented by the BDVA 
Skills Task Force317.  

Subject 

Stream 
Sub-goal 

Measure 

Short 
description 

/ 

C. Structured skills development > 1. Support implementation of 
structured skills development  

Description 

Design an EU-wide mechanisms to recognise skills acquired 
through informal and non-formal training 

Various mechanisms are available, like accreditation, academic 
degrees, certificates, labels, and badges. Especially badges, 
supported by online verification of their authenticity and ownership, 
are a low-threshold method to support skill recognition. 

Stakeholder 
involvement 

  European Commission: Lead/Act - create mechanism 

  National governments: - 

  Education: - 

 

Industry: -  

  Associations: - 

  Other: -  

C2.  Enhance capabilities for monitoring & decision-making in SMEs 
Monitoring will support SMEs in understanding and strengthening their process of skills 
development. It will also allow to better assess where further strengthening is most 
needed and decide to invest.  

One important measure for monitoring is the facilitation to self -assessment. 

Subject 

/ 

Stream 
Sub-goal 
Measure 

Short 
description 

Stakeholder 
involvement 

Description 

C. Structured skills development > 2. Enhance capabilities for 
monitoring & decision-making in SMEs 
Facilitate self-assessments to enable SMEs to detect skills 
gap in their organisation 
Building  on the work conducted in this initiative (first concept of a 
self-assessment), a new European initiative should be launched 
specifically focusing on the development of a self-assessment, taking 
into account regional and sectoral particularities and the various 
types of SMEs that exist.  

  European Commission: Lead 
  National governments: - 
  Education: Act - develop assessment 
Industry: -  
 
  Associations: - 
  Other: Downstream actors – Support European Commission - 

promote 

317 https://www.digitalsme.eu/digital/uploads/20190412_4th-Workshop_2nd-ppt_Pre sentation-BDVe.pdf 

128 

 
 
 
 
                                              
To ensure any investment into skills  training  is  effective, quality of trainings should  be 
clear. For this purpose, quality labels for BIC trainings should be considered. Examples can 
be found is, inter alia, Germany318 and the Netherlands319 

Subject 

Stream 
Sub-goal 

/ 

C.  Structured  skills  development  >  2.  Enhance  capabilities  for 
monitoring & decision-making in SMEs 

Description 

Measure 

Research the possibility of quality labels for BIC-trainings 

Short 
description 

Stakeholder 
involvement 

The use standardised competence frameworks and certificates allows 
SME manager/owners to assess the value of trainings and  provides 
them with insights in the competences professionals have. This makes 
it easier for them to 1) assess the value of trainings when considering 
sending  their  employees  to  training,  and  2)  in  case of  recruiting 
professionals,  to  assess  the  value  of  the  trainings  they  have 
conducted. To this end, it should be investigated to what extent it is 
possible to develop standardised certificates throughout the EU. This 
allows SME manager/owners in  country A to better understand the 
quality of training in country B.   

The  specific  target  group  of  SMEs  should  be  considered  when 
investigating such certificates. They need to be adapted for the scale 
and affordability to SMEs – as there will be specific competences and 
skills  needed to implement BIC technologies (both by SMEs, but also 
by the “consultants” to the SMEs. 

  European Commission: Lead/Act - arrange mutual recognition 

  National governments: Act - explore/develop regulatory labels 

  Education: Act - explore/develop voluntary labels 

 

Industry: -  

  Associations: - 

  Other: -  

Further enhancement of monitoring can be achieved in the form of stocktaking of market 
trends. As example, the market insights reporting initiative of VOICE, an association for 
IT-using SMEs, can be mentioned.320 

Subject 

Stream 
Sub-goal 

/ 

C.  Structured  skills  development  >  2.  Enhance  capabilities  for 
monitoring & decision-making in SMEs 

Description 

318 Trusted Cloud Initiative (https://www.truste d-cloud.de/). 

319 https://mkb.nl/nieuws/bedrijfsleven -ontwikkelt-risicomodel-en-keurmerk-cyberbeveiliging 

320 https://voice-ev.org/wissensplattform/ 

129 

 
 
 
 
 
                                              
Subject 

Description 

Measure 

Monitor market trends to inform SMEs 

Short 
description 

Collect information  on,  inter  alia,  market  developments like  new 
services, new suppliers, and conditions of service (to prevent lock-in). 
The  monitor  can  also  help  to  decrease  dependency  on  external 
providers  by  stimulating 
in 
networks/ecosystems/value  chains.  Such  networks  improve  SMEs 
access to knowledge and facilitate peer-to-peer learning. Networks 
can either be regional or sectoral (or both). 

the  anchoring  of  every  SME 

Stakeholder 
involvement 

  European Commission: Lead/Act – monitoring 

EU/global trends 

  National governments: Act - monitoring national trends 

  Education: - 

 

Industry: Support – formation of value chains, 
knowledge transfer 

  Associations: Act – Stimulate value chain knowledge transfer 

  Other: Intermediairies – support national governments – 

monitor trends 

C3.  Increase transparency and access to funding 
As for all investments, financing plays an important role.  

Subject 

Description 

Stream 
Sub-goal 

/ 

C.  Structured skills  development  >  3.  Increase transparency and 
access to funding 

Measure 

Increase funding for skills development in SMEs 

Short 
description 

A successful example comes from Ireland, where Skillnet  Ireland acts 
as a broker between education and companies. Companies that want 
to participate in  Skillnet  need to form  a  network (based on  region 
and/or industry) with which they need to cooperate and propose to 
Skillnet explaining their need for skills development. If Skillnet accepts 
their proposal, Skillnet provides a grant of 50%. The other 50% comes 
from the network of  companies itself. In addition to financial support, 
Skillnet matches the skill need with their network of educators, they 
provide mentoring and coaching, ongoing enablement and strategic 
support,  and  they  conduct  an  independent  evaluation  of  every 
program.  

This  approach is  quite  successful, and  it  is  worthwhile  exploring 
further its success factors and conditions for upscaling/replicating this 
initiative in other EU countries. 

Stakeholder 
involvement 

  European Commission: Support national governments - 

funding 

  National governments: Lead/Act - funding 
  Education: - 
Industry: -  
 

130 

 
 
 
  Associations: - 
  Other: -  

Description 

/ 

C.  Structured skills  development >  3.  Increase transparency and 
access to funding 

Promote and scale successful funding mechanisms that foster 
skills development 

Subject 

Stream 
Sub-goal 

Measure 

Short 
description 

Identify which mechanisms have proven to be successful, identify the 
success factors driving  this  success and  apply  these, taking  into 
account local circumstances. 

Stakeholder 
involvement 

  European Commission: Lead/Act – promote 

funding mechanisms 

  National governments: Support European 

Commission - promotion 

  Education: Support European Commission - promotion 

 

Industry: -  

  Associations: Support European Commission - promotion 

  Other: Intermediaries - Support European 

Commission - promotion 

6.3.4.  Stream D - Tailoring training to SMEs’ 

needs 

Currently, too often available trainings in the area of BIC skills  are not in line  with SMEs’ 
needs. Specific trainings in the area of BIC are scarce (focus is often on digital skills in the 
broadest sense), the form in which trainings are provided are not ideal for SMEs and too 
often, trainings are too expensive. Another problem is that the trainings that exist are not 
part of widely accepted framework. This results in difficulties with assessing the value of 
trainings. To address the current mismatch between available training offerings and SME’s 
needs, the following measures contribute to ensuring a  better match between available 
training offerings and training needs of SMEs. 

Embarking  on BIC technologies requires investments in several elements, of which one is 
training of personnel. Having restrained financial resources, SMEs need to prioritise their 
investments. An  indirect  return  on  investment may  lead  to  the  fact that training  of 
personnel in the area of BIC is not among the top priorities. External funding is required 
but is not always available or is not easily accessible by SMEs.  

The technological savviness of SME owner/managers depends on a multitude of factors, of 
which one is age. Overall, SME owner/managers have difficulties understanding the impact 
of BIC  technologies, or realising the urgency to act on it. A long-term vision on adopting 
BIC  is lacking, and the focus is rather on operational matters. In addition to this internal 
perspective, also  the  technological  maturity  of  the  environment  plays  a  role,  as  an 
environment stimulating for instance open data fosters the uptake of big data.  

Professionals possessing the specialised skills needed to work with BIC  technologies are 
scarce. SMEs  face several challenges in  this  regard,  within  the  context of  an  ageing 
European workforce. SMEs compete with big corporates to attract and retain talents that 
possess the required combination of skills. And it is not just about attracting and retaining 

131 

 
 
 
talents: also for SME owner/managers, continuous development of skills and knowledge is 
essential for the growth of their company. 

The following sub-goals enable the tailoring of training needs. 

D1.  Increase education and training offers 
D2.  Develop training capacity 
D3.  Collect intelligence 
D4.  Reduce direct costs for SMEs 

D1.  Increase education and training offers 
Trainings are essential for skills development. For trainings to be optimally effective, they 
need  to  be  closely  aligned  with  the  training  needs.  Further  improvement  of  the 
understanding of training needs by education providers can support this alignment. 

Subject 

Stream 
Sub-goal 

Measure 

Short 
description 

/ 

D.  Tailoring  training  to SMEs’  needs >  1.  Increase education and 
training offers 

Description 

Increase  understanding  of  education  providers  on  how  to 
identify training needs, target groups & tailor offers 

Making sure that teachers and professors continuously advances skills 
and knowledge based on the latest insights from industry. Think of 
teacher exchange schemes, training programmes or the development 
of new (standardised) modules that teachers and professors can use 
in the area of BIC. 

Stakeholder 
involvement 

  European Commission: Lead/Act – develop 

guidance, promotion 

  National governments: Support European Commission - 

promotion 

  Education: - 

 

Industry: -  

  Associations: Support European Commission - promotion 

  Other: - 

Although seemingly contradictory to the previous measure, trainings should make use of 
certain key principles to ensure optimal knowledge transfer. 

Subject 

Description 

Stream 
Sub-goal 

/ 

D.  Tailoring  training  to  SMEs’  needs  >  1.  Increase education and 
training offers 

Measure 

Promote  use  of  standard  approaches  and  frameworks  to 
increase effectiveness in training courses 

Short 
description 

Training offerings should be newly set up or restructured both in form 
and content so that they are tailored to the needs of SMEs and go 
beyond ‘generic’ digital skills, and rather focus specifically on BIC:  
  Modular, blended, not necessarily during business hours. 
Innovative methods (eg gaming) should be explored.  

  Focus specifically on BIC 

132 

 
 
 
 
  Trainings are practical, include whole chain, and include 

concrete examples 

  Trainings are provided in a plain language and in the mother 

language of the SME 

Easy  participation by  SME  should  be  the leading  guiding  principle 
when developing the trainings. Both owners as well as skills specialists 
should be targeted with the trainings. 

Stakeholder 
involvement 

  European Commission: Lead/Act - develop standards 
  National governments: Act – promotion of standards 
  Education: - 
Industry: -  
 
  Associations: - 
  Other: - 

The development of BIC skills throughout the company may go beyond just targeting the 
specialists (see  the  description of  the  previous  measure).  Especially  inclusion  of  BIC 
modules in non-technical curricula will help to ensure broad support and understanding for 
the usefulness of BIC skills throughout the entire organisation. 

Subject 

Stream 
Sub-goal 

/ 

D.  Tailoring  training  to SMEs’  needs >  1.  Increase education and 
training offers 

Description 

Measure 

Integrate BIC modules in non-tech curricula 

Short 
description 

Embedding technical modules in general non-technical (e.g. business 
administration) courses. Integrate technical skills in  existing or  new 
courses addressing the current workforce; and embed these technical 
modules  in  curricula  aimed  at  addressing  the  future  workforce 
(students). An example could be a module on cybersecurity. 

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead 

  Education: Act - amend curricula 

 

Industry: -  

  Associations: - 

  Other: -  

Existing  frameworks and  blueprints can offer a  solid  and efficient basis for  the further 
development of  education and  training  offers. One  example  of  such  a  source  is  DG 
Connect’s Makes-me-digital initiative.321 

Subject 

Description 

Stream 
Sub-goal 

/ 

D.  Tailoring  training  to  SMEs’  needs  >  1.  Increase education and 
training offers 

321 https://makesmedigital.eu 

133 

 
 
 
 
                                              
Subject 

Measure 

Description 

Build  on  existing  co-ooperation  frameworks  between 
education and industry, and existing blueprints for training for 
SMEs 

Short 
description 

Frameworks  and  blueprints  to  both  develop,  but  also  upscale 
education and training offers. 

Stakeholder 
involvement 

  European Commission: - 

  National governments: Lead/Act – identify blueprints, 

promotion  

  Education: Support national government – identify blueprints; 

Act - tailor training programmes 

 

Industry: -  

  Associations: - 

  Other: -  

To stimulate the attractiveness of BIC skills  within education, enough internships should 
be ensured. 

Subject 

Stream 
Sub-goal 

/ 

D.  Tailoring  training  to  SMEs’  needs >  1.  Increase education and 
training offers 

Description 

Measure 

Stimulate internships 

Short 
description 
Stakeholder 
involvement 

Create internships for students with BIC relevant skills 

  European Commission: - 

  National governments: - 

  Education: Support - offer interns 

 

Industry: Act - create BIC internships 

  Associations: Lead 

  Other: -  

D2.  Develop training capacity 

Currently, too often available trainings in the area of BIC skills  are not in line  with SMEs’ 
needs. Specific trainings in the area of BIC are scarce (focus is often on digital skills in the 
broadest sense), the form in which trainings are provided are not ideal for SMEs and too 
often, trainings are too expensive. Another problem is that the trainings that exist are not 
part of widely accepted framework. This results in difficulties with assessing the value of 
trainings. To address the current mismatch between available training offerings and SME’s 
needs, the following measures contribute to ensuring a  better match between available 
training offerings and training needs of SMEs. 

134 

 
 
 
Increase in mobility of scarce experts was achieved in Sweden.322 

Subject 

Stream 
Sub-goal 
Measure 

Description 
D. Tailoring training to SMEs’ needs > 2. Develop training capacity 

/ 

Increase mobility of scarce experts 

Short 
description 

Stakeholder 
involvement 

Most notably, increasing the possibility to combine two (or more) part-
time positions, for example one in academia and one in business, will 
improve the availability of high-level expert to business.  

  European Commission: - 

  National governments: Support education 

  Education: Lead/Act – explore possibility for part-time 

contracts for key experts 

 

Industry: Act – explore possibility for part-time contracts for 
key experts 

  Associations: - 

  Other: -  

For  an  effective  out-roll  of  training,  sufficient  training  facilities  suitable  should  be 
available.323 

Subject 

Stream 
Sub-goal 
Measure 

Short 
description 

/ 

D. Tailoring training to SMEs’ needs > 2. Develop training capacity 

Description 

Invest in facilities to support training programmes 

Investment in  facilities concerns physical location. Typically, these 
may be avialable at hubs of within the local ecosystem (e.g. Digityser 
in Brussels). Test labs may be needed for cybersecure IoT devices.  

Stakeholder 
involvement 

  European Commission: - 

  National governments: Act – stimulate investment 

  Education: Lead/Act - develop facilities 

 

Industry: -  

  Associations: - 

  Other: -  

D3.  Collect intelligence 

322 Malin Rosqvist, Driving innovation and  improving competence s in Swe dish SMEs ; 

https://www.digitalsme.eu/digital/uploads/3rd -Work shop_1st-ppt_2019-02-08_MalinRosqvist.pdf 

323  Se e ,  for  e x ample,  R e commendation  from   the sis  IoT  matchmaking  platform  for  SMEs   (TU  De lft); 
https://repository.tudelft.nl/islandora/object/uuid:e31a8e50-8f7c-4601-ad97-27a292092554/datastream/OBJ 

135 

 
 
 
                                              
Training development may be supported by data on SME trainings needs and participation 
motives. 

Subject 

Stream 
Sub-goal 

Measure 

Short 
description 

/ 

D. Tailoring training to SMEs’ needs > 3. Collect intelligence 

Description 

Promote data-driven approaches in SME support programmes 

Achieve better insight  into  SME training  needs to  align  policy and 
training  offers  by  collecting SME  consumption levels  of  trainings. 
Aggregation of data, either at regional level and/or national level, may 
provide insightful patterns to identify SME needs. 

Stakeholder 
involvement 

  European Commission: Lead/Act - Specify information 

needs programmes 

  National governments: Stimulate Education 

  Education: Act - Information collection 

 

Industry: -  

  Associations:  

  Other: 

Subject 

Stream 
Sub-goal 
Measure 

/ 

D. Tailoring training to SMEs’ needs > 3. Collect intelligence 

Description 

Research motives of SMES to participate in training 

Short 
description 

While  this  study  offers  much  insights  into  reasons  for  non-
participation of SMEs, more research into the positive drivers is useful. 

Stakeholder 
involvement 

  European Commission: Lead/Act – research motives 

  National governments: Stimulate Industry 

  Education: - 

 

Industry: Act - Provide insights 

  Associations: Stimulate Industry 

  Other: -  

D4.  Reduce direct costs for SMEs 

Embarking  on BIC  technologies  requires  investments  in  several  elements, 
of which one is training  of personnel.  Having  restrained  financial  resources, 
SMEs need to prioritise  their  investments. An indirect  return  on investment 
may  lead  to the  fact  that  training  of  personnel  in  the  area  of  BIC  is  not 
among the top priorities.  Funding  has  been discussed  in  stream C3. Here, 
the focus lies  on reduction  of the direct  costs. The following  measures can 
be considered. 

136 

 
 
 
 
Innovation voucher scheme have proven their worth in, inter alia, Finland, the Netherlands 
and Lithuania.324 

/ 

D. Tailoring training to SMEs’ needs > 4. Reduce direct costs for SMEs 

Description 

Subject 

Stream 
Sub-goal 
Measure 

Short 
description 

Stakeholder 
involvement 

Stimulate innovative voucher schemes for fostering BIC skills 
development 

In  order  to  foster  SME  skills  development  and  to  stimulate 
experimenting  with  BIC,  voucher  schemes  can  be  put  in  place. 
Voucher schemes have proven to be effective in different contexts, 
and already exist with regard to innovation etc. (see examples further 
below). The challenge is to integrate a skills dimension with regards 
to emerging technologies within those schemes.  

European policymakers should investigate an approach to: 

  Sustain successful voucher schemes and to integrate the 

skills dimension in schemes; 

  Transfer lessons learned to other regions; 
  Scale successful practices where possible and stimulate the 
development of voucher schemes in case they do not yet 
exist.  

As a primary  funding vehicle, the ESF can be used. In this case, it is 
important to include a focus on educational purposes, and to specify 
for a range of technologies.  

Besides dedicating the voucher schemes to skills 
development/training (educational purposes), one should also 
investigate the option of dedicating vouchers to the implementation 
of cybersecurity standards. The best way to develop personal skills 
is by aligning them to the organizational improvements. For 
instance, it is not by coincidence that Agile (SCRUM) is implemented 
by “coaching”, which is “learning by doing it” – The same principle 
holds ground for SMEs with regard to the implementation of 
cybersecurity standards.  

  European Commission: - 
  National governments: Lead/Act – develop, stimulate 

schemes 
  Education: - 
Industry: -  
 
  Associations: - 
  Other: - 

6.3.5.  Governance: Creating overarching 

governance for skills 

There is a need to create a stronger partnership between the public and the private 
sector in order to offer leadership and vision for digital skills  and jobs in Europe. This 

324 

https://www.businessfinland.fi/en/for-finnish-customers/services/funding/sme/innovation-voucher/; 

https://www.ve rslilie tuva.lt/paslaugos/kompetenciju -vauceris/  

137 

 
 
 
                                              
entails a specific commitment from all the stakeholders in order to pursue common 
objectives and make investments to achieve them.  

Build  and further develop public -private partnerships on ICT skills and jobs, including 
industry and trade associations, national, regional and local governments, companies, 
education institutions, research and ICT professionals. Our recommendation is for the 
establishment a European Public Private Partnership (PPP) for Skills and Jobs, as 
such entity is perfectly suited to enable a long-term, strategic approach and reduce 
uncertainties by allowing for long-term commitments.  

In addition, this PPP needs to be accompanied by close collaboration with research and 
universities as well as industry to develop an evidence-based approach to skills 
development, that can help identify future skills needs for the digital transformation. 

This strategic and evidence-based approach to skills development needs to consider 
market needs, thus laying the basis for innovation in Europe. It is important differentiate 
between the different types of new technologies or skills. For instance, cybersecurity is a 
horizontal topic, but big data or IoT depend very much on the specific business model of 
a company. Thus, there is a need to distinguish measures according to market demands 
and needs, and therefore, to base action on evidenc e and research on market demands. 

138 

 
 
 
 
7.  TOOLBOX 

7.1.  Purpose of the toolbox 

The purpose of the toolbox is to facilitate knowledge sharing and to encourage 
stakeholders to engage in (new) initiatives that will support SMEs in adopting new 
technologies and developing the required skills. It aims to point stakeholders towards 
tools that have demonstrated a certain added value and that can help others in setting-
up or scaling up initiatives.  

The toolbox is created primarily for stakeholders involved in the organisation of skills 
initiatives for SMEs. Some of the tools can also be of use for SMEs themselves, but it is 
much more likely SMEs will look for support in their direct environment and ecosystem. 
These tools are most likely to reach SMEs via dissemination by for instance policymakers 
and associations. 

7.2.  Design of the toolbox 

There are various ways to design and structure a toolbox. In this approach, the tools are 
mapped to the streams in the roadmap. This should allow for an intuitive understanding 
of ‘what’ to find ‘where’. As an example, assumeing a stakeholder is planning to develop 
an initiative aimed at supporting SMEs with structured skills development (stream 3), 
he/she will find relevant materials mapped to that stream.  

Figure 47 Meta-model of the toolbox 

The toolbox consists of the following types of tools: 

  Good practices: skills-initiatives that have contributed to one or more of the 
action streams in the roadmap. These were further categorised as support 
programme/strategy, training programme, or network/collaboration initiative. 

  Frameworks: recognised overviews, outlines or skeletons that can guide SMEs in 

deciding on an approach to plan for developing the human capital that is needed 
to implement the digital strategy (i.e. following adoption of big data, IoT or 
cybersecurity in the enterprise’s strategy). In particular, frameworks that support 
competence development (such as the e-CF, NIST, EDISON). 

  Self-assessments: assessments that either support (employees of) SMEs in 

determining their level of competence for a role in cybersecurity, big data or IoT, 
or support the organisation in assessing their level of maturity regarding these 
technologies.  

139 

 
 
 
 
  MOOC’s: Massive Open Online Courses (MOOCs) aim at unlimited participation 

and open access via the web. In addition to traditional course materials, such as 
filmed lectures, readings, and problem sets, many MOOCs provide interactive 
courses with user forums to support community interactions among students, 
professors, and teaching assistants, as well as immediate feedback to quick 
quizzes and assignments.  

  Guides & others: this category consists of guides, white papers, reports and 

various other materials that inform users about the topics relevant for this study. 

Throughout the study, relevant ‘tools’ were collected to grow the knowledge base. The 
toolbox is not exhaustive, though via the EU-wide research, interviews, surveys and 
workshops at least covers most of the relevant items. 

The toolbox itself is a list created in excel (presented in Appendix C), whereby each tool 
is mapped to the most relevant action stream and most relevant sub-goal per stream. 
Complementary to the toolbox, a selection of good practices is further detailed in 
Appendix E.  

The toolbox will become available in an online mode via our partners of the European 
DIGITAL SME Alliance.  

140 

 
 
 
 
 
PART III: MONITORING  SKILLS DEVELOPMENT 

141 

 
 
 
 
 
 
 
 
8.  PROVIDE  A  COMPARISON  WITH  THE  US  AND  PROPOSE  INDICATORS  AND 

MONITORING MECHANISMS FOR INTERNATIONAL COMPARISONS 

8.1.  Overview this task 

The monitoring mechanism for digital skills  is  presented in four sections as described in 
Figure 8-1. 

8.2

8.3

8.4

8.5

•Underlying conceptual considerations

•Monitoring mechanism proposed

•Monitoring mechaism indicators explained

•Synergies with other existing framework

Figure 8-1.  Content creation path towards the Final Report 

8.2.  Conceptual  considerations  accounted  for  in  the  proposed  monitoring 

mechanism 

The suggested monitoring mechanism is developed based on the following considerations:  

 

 

 

 

It is based on an ICT specific Supply and Demand indicator framework. The 
framework relies on traditional data sources from providers of consolidated 
data across multiple countries (and meeting the SMART criteria), in view of 
allowing international comparison with the US and other countries at the level of 
ICT for which data availability is greater compared to the thematic areas in focus.  
It is intended for international comparison accounting for extra and intra EU 
coverage; the first layer looks at a wider geographical scale and focuses on 
baseline indicators that rely on internationally harmonised data sources, or 
possible to be harmonised with a good degree of accuracy, especially looking at 
the US. The second layer focuses on the EU by including specific sub-dimensions 
that are mostly relevant and available at EU level.  
Its indicator framework design accommodates for Big data, Internet of 
Things and Cybersecurity specific indicators. These mostly rely on alternative 
data sources and available reports; thus, the country availability is at times 
scattered, and replicability could be limited. An assessment of the indicators 
showing potential to be further monitored and to be compared at international 
level is provided.  
In recognition of the needs of policy making in terms of anticipating future 
demand and supply for skills and act to reduce the gap between supply and 
demand it has been considered important to also  highlight critical  indicators 
which can provide signals of future skills supply and demand  in the 
thematic areas but also in comparison to the US.  

  It builds on existing frameworks, in view to limit/avoid the parallel existence 
of multiple monitoring mechanisms of skills at EU level and capitalise on the 
synergies.  

142 

 
 
 
 
8.3.  The Monitoring mechanism  

The digital skills  monitoring mechanism proposed is grounded on a skills  Supply -Demand 
framework making use of ICT specific indicators for which data availability is richer.  

The supply and demand framework is further split into training and labour indicators. The 
ICT indicators extend to the three thematic areas (Big Data, IoT and Cybersecurity) for 
which indicators deemed critical for the needs of policy making are propose d.  

The rationale behind this choice is that ICT is the closest conceptual framework to Big Data, 
IoT, and Cybersecurity. In terms of existing statistical data and indicators it allows for a 
comprehensive monitoring framework to be built for the EU.  

To inform a monitoring mechanism for each of the thematic areas substantial original work 
would be needed using new data sources or extensive surveys with industry/labour force 
(see Table 8-3 and Table 8-6 for suggestions on extending the conceptual framework from 
ICT to the thematic areas). In recognition of the urgency for policy makers to monitor the 
gap between the current supply and demand and anticipate the future demand for skills, 
indicators that provide signals and can be monitored regularly are proposed.  

For an international comparison with the US even at the ICT level very limited indicators 
are available. For this reason and in consideration of the need for the EU to monitor digital 
skills not just within its core but also with international competitors a selection of indicators 
serving this purpose are proposed. 

The monitoring  mechanism  in  its practical application is  expected to be  utilised as  the 
indicator framework upon which basis analytics can be performed, namely forecasting and 
foresight exercises. 

Figure 8-2 shows our proposed Demand-Supply monitoring framework. 

143 

 
 
Figure 8-2 Supply-demand framework for the monitoring mechanism 

8.3.1. 

Sources 

Indicators are sourced from Eurostat (as a primary source) and other sources such as the 
WEF, the European Cluster Collaboration Platform and others. The availability of data by 
company size (SMEs versus large companies) is also part of the monitoring mechanism. 
As explained in more detail in the box below, the OECD is the main source for data at non-
EU level, and notably for the comparison with the US. 

The comparison with the US 

Official US data seem not to have the same coverage and richness than EU data, and do 
not have indicators that one can directly map against data for Europe. The OECD is the 
source that mostly has comparable data with the EU, but for some OECD indicators, US 
data are not available. The data availability for the US is  detailed in the demand  and 
supply indicators overview tables (tables 8 and 10 further below).  

We detail below other sources explored for the US, together with the limitations to use 
them in a comparison with the EU:  

  World Bank: It has data on Higher Education Information System (HEI), but the 
classification of programs is quite broad and does not specify ICTs. The closest 
program type to look at would be “sciences programs”. 

144 

 
 
 
 
 
 
  UNESCO Institute for Statistics (UIS): UNESCO’s data covers basic ICT skills of 
the general population (e.g., % youth and adults who have used basic arithmetic 
formulae in a spreadsheet), but no advanced skills and no focus on employees or 
enterprises are included. 

  World Inequality Database on Education (WIDE): As in the UIS data, it only 

covers basic ICT skills of the general population. 

  The National Center for Education Statistics (NCES) does not provide data on 
tertiary, vocational education, nor training in enterprises. They seem to focus on 
younger students. The highest level is “high-school graduates”. 

  US Census: It provides data on number of tertiary education students in general, 
but not per field. It seems not to contain data of employees being trained in ICT or 
enterprises investing in ICT training.  

  Eurostat: A few Eurostat indicators contain data on the U.S. This is, nevertheless, 

in very limited cases, and not for the indicators covered in this project.  
  Pew Research: Although no relevant quantitative data could be found, Pew 

Research studies provide somewhat related qualitative anecdotal evidence: (i) The 
Future of Jobs and Jobs Training (2017); (2) The State of American Jobs (2016); 
(3) What the Public Knows about Cybersecurity (2017). 

  Mimeo report325, The State of Learning and Development in 2016: It provides a 
general overview of learning and training programs and systems in the US, but 
without focus on ICT. It is based on the answers of 425 learning and development 
professionals. 

  2016 Training Industry Report:326 It provides figures on the skills training 

industry in the US. It is based on 644 survey responses. No focus on advanced ICT 
skills. 

  ASTD’s State of the Industry Report (2013, 2016): General information on the 
investment of US companies on staff learning and development without specific 
focus on ICT skills. It is based on a survey of 475 organisations. 

325 https://www.insynctraining.com/pages/The_State_of_Learning_and_Development_in_2016.pdf  

326 https://trainingmag.com/sites/default/files/images/Training_Industry_Report_2016.pdf 

145 

 
 
 
 
 
                                              
8.4.  Monitoring mechanism indicators explained 

This section presents the indicators collected on supply and demand of skills.  The main 
observation drawn is that while there is good data coverage for ICT -related indicators on 
skills, with different available sources that apt to be used for comparisons a t international 
level (and with the US), the data potentially available to construct the indicators selected 
for the three areas (Big  Data, IoT, Cybersecurity) are not readily available and require 
substantial original work. At the same time, we found existing initiatives that are moving 
forward to extend the scope of existing statistics to cover new types of works and related 
skills.  

In  what follows, we  provide  a  summary  table  introducing the  indicators at  ICT  level 
currently available. For each indicator we specify the years available, the source, the 
prospected continuity in the future, and the availability for the US and for SMEs. We then 
also provide a set of indicators following the proposed framework that could be collected 
in the future on the three thematic areas and an indication of one indicator for supply and 
one for demand that could be used to provide signals at EU level and the US and can be 
collected now and regularly in the future. 

8.4.1. 

Supply 

ICT  - PROPOSED MONITORING  FRA MEWORK A ND CORRESPONDING  INDICA TORS   

The logic behind  the selection of the indicators for skills  supply under  training and  the 
labour market is described below. 

Sub-dimension  Pillars suggested 
Training 

IC T training at HEIs  
IC T vocational training 
IC T training by e nterprises - 
to spe cialists 
IC T training by e nterprises - 
to non-specialists 
IC T specialists employed 
Usage  of  IC T  sk ills  by 
e nte rprises 
IC T innovation 

Labour market 

(Demand  and 
Supply 
indicator) 

Pre sence of ICT companies 

Explanatory notes 
Training categories cover the three m ain sources of supply, 
thus, Higher Education Institutes (HEIs), vocational training 
providers and businesses.   Account is m ade for training 
provided to specialists and non-specialists. 

In re cognition of the  digital transformation pre sent across 
m ultiple professions labour supply looks at not only the ICT 
spe cialists e mployed but also m ore broadly the  use of ICT 
sk ills by e nterprises.   
A  note  with re spe ct to the  labour classification de finition 
should be m ade: The IC T specialist work force  is a broader 
cate gory  than  IC T  profe ssionals,  which  are   a  se t  of 
occupations  corre sponding  to  a  su b-group  of  the   ICT 
spe cialist  work force .  Data  colle cted  so  far  re fe r  to  ICT 
spe cialists. ILO ISCO codes are  the standard classification 
for occupations, together with ESCO at European  level. 
The  two  can  be  harm onised (converted). ILO  ISC O data 
available online only use the first level of the taxonomy (1-
digit), howe ver raw data until 4-level can be retrieved under 
re que st. More information on the ISCO codes can be  found 
in Error! Reference source not found., in the  context of 
its use  in the  study Digital O rganisational Frameworks and 
IT Professionalism EASME/COSME/2016/016.  
The  pre sence of companies or clusters can be considered a 
prox y of supply of specific skills (i.e. ICT skills). 

Table 8-1 framework of supply and assessment for ICT 

Figure 8-3 and Table 8-2 visualise and summarise  the indicators collected for Supply of 
ICT-related skills.  

146 

 
 
 
 
Figure 8-3 Summary of indicators on ICT Supply 

Dimensio
n 

Sub-
dimen
sion 

Indicator 

Years 
availabl
e 

Training 

Training 

IC T 
training 
by HEIs 

Enrolm ent by field  
(% in total) 
Graduates by field  
(% in total) 

-

2012 
2016 
2005, 
2010, 

Source  Notes on 
continuity 
in the 
future 
Uncle ar 

Eurosta
t 
Eurosta
t 

Uncle ar 

US 
availabilit
y 
(source) 
2015  only 
(O EC D) 
2015  only 
(O EC D) 

A vailabilit
y by size 
(SMEs) 

No 

No 

147 

 
 
 
 
Dimensio
n 

Sub-
dimen
sion 

Indicator 

Years 
availabl
e 

Source  Notes on 
continuity 
in the 
future 

US 
availabilit
y 
(source) 

A vailabilit
y by size 
(SMEs) 

Training   

Training   

Training   

Training   

Labour 

Labour 

Labour 

Labour 

Labour 
(supply  & 
demand) 

IC T 
vocatio
nal 
training 
IC T 
training 
by 
e nte rpri
se s - to 
spe ciali
sts 
IC T 
training 
by 
e nte rpri
se s  

IC T 
training 
by 
e nte rpri
se s - to 
non-
spe ciali
sts 
IC T 
spe ciali
sts 
e m ploy
e d 
Usage 
of 
ICT 
sk ills by 
e nte rpri
se s 

IC T 
innovati
on 

IC T 
spe ciali
sts with 
cross-
function
al sk ills 
IC T 
com pan
ie s 

2012, 
2013 
2014, 
2015 
2016 
2005, 
2010, 
2015 

2012-
2017 

Main sk ills targeted 
by C VT courses  
(% e nte rprises) 

Ente rprise provided 
training  to  ICT/IT 
spe cialists 
to 
de ve lop/upgrade 
the ir IC T skills 
(% all e nterprises) 

Eurosta
t 

Eve ry 
ye ars 

5 

No 

Ye s 

Eurosta
t 

Ye arly 

No 

Ye s 

all 

all 

of 

of 

Ente rprise provided 
training  to  other 
pe rsons  e m ployed 
to  de ve lop/upgrade 
the ir IC T skills  
(% 
e nte rprises) 
Ente rprise provided 
training  to 
their 
pe rsonnel (not ICT 
spe cialists) 
to 
de ve lop/upgrade 
the ir IC T skills  
(% 
e nte rprises) 
Pe rsons  Em ployed 
with  IC T  Spe cialist 
Sk ills 
(Thousands 
individuals) 
Fre quency of use of 
inform ation 
and 
com m unication 
te chnologies 
work  
(Estim ated average 
pe rce ntage 
and 
standard e rror) 
R e search/innovatio
n:  Participation  to 
re le vant the m es in 
FP7, H2020 
(% budget allocated 
ove r 
FP7 
total 
budget) 
IC T specialists with 
cross-functional 
sk ills 
(% range ) 

of 

at 

2012-
2018 

Eurosta
t 

Ye arly 

No 

Ye s 

2012-
2019 

Eurosta
t 

Ye arly 

No 

Ye s 

2004-
2017 

Eurosta
t 

Ye arly 

No 

Ye s 

2012-
2015 

O EC D 

Ye arly 

No  

Same   as 
for 
EU 
(O EC D) 

2007-
2020 

C ordis 

No 

According 
to 
FP 
programmi
ng pe riod 

Until  2013 
through 
C orda 
database 

2017 

W orld 
Econo
m ic 
Forum  
(W EF) 

Ye arly 
(ne w 
re le ase 
Se pt 2018) 

No 

Ye s (not all 
EU 
countrie s) 

 2010-
2016 

Eurosta
t 

Ye arly 

IC T 
e nte rprises: 
Industrial  structure  
- supply of ICT skills 
the  
prox ied  by 
pre se nce  of 
ICT 
com panies 
(Num ber 
e nte rprises; 
Num be r of pe rsons 
e m ployed) 

of 

Ye s 

No 
(for US the  
the  
Econom ic 
C e nsus 
Industry 
C lassificati
on  R eport 
include s 
se ctor, but 
IT 
is 
aggregated 
with  Le gal, 

148 

 
 
Dimensio
n 

Sub-
dimen
sion 

Indicator 

Years 
availabl
e 

Source  Notes on 
continuity 
in the 
future 

Labour 
(supply  & 
demand) 

 IC T 
com pan
ie s 

Pre sence 
re le vant clusters  
(Num ber 
cluste rs) 

of 

curre nt 

of 

C luster 
collabor
ation 
pla tfor
m  

Updated 
online on a 
re gular 
basis 

US 
availabilit
y 
(source) 
Adve rtising 
and 
Accounting
)  
No 

A vailabilit
y by size 
(SMEs) 

No 

Table 8-2 framework of supply for ICT level - available indicators 327 

BIG  DA TA,  IOT  A ND  CYBERSECURITY  PROPOSED  MONITORING  FRA MEWORK  A ND 
CORRESPONDING  INDICA TORS 

Initiatives to set the ground for the design of indicators at the thematic level come from 
traditional and new data sources. One of them is led by ILO, who carries out a thorough 
monitoring and assessment of the ISCO codes in view of keeping them up to spe ed with 
the changing dynamics of the job market and relevant occupations. Piloting projects using 
new data are also taking place such as the work in the exploratory big data report of the 
European Innovation Scoreboard on skills supply from university websites.328 

Key findings on Big Data, IoT and Cybersecurity skills supply are summarised below. From 
the indicators listed we propose in the short term to regularly monitor the availability of 
specialists with skills in big data, cybersecurity, IoT using LinkedIn. The representativeness 
of Linkedin, corrections for biases in the data, the limitations in terms of what it captures 
(e.g.  skills  quoted in  education, experience or  skills  of  users’  profiles)  and  how  the 
indicators constructed with this database should be interpreted are  important aspects to 
understand before utilising the indicator for analytics and policy recommendations.  

SUPPLY 
Sub-dimension 

Pillars 
suggested 

Training 

Training 
HEIs 

at 

A ssessment (from the 
review of data) 
Big 
data 
 

Cyber 
security 
 

IoT 

 

Notes 

O nly possible by crawling undergraduate, 
graduate,  post-graduate  study  portals. 

 

 

O nly possible by crawling online courses 

Vocational 
training 

Training 
by 
e nte rprises  - 
to spe cialists 

 

 

Ye s   

na 

na 

na  

Training 
by 
e nte rprises  - 
to 
non-
spe cialists 

Be st captured by surve ys  
Included for IoT in the Eurostat ICT usage 
in e nte rprises (isoc_e) through “access to 
and use of the Internet and other network  
te chnologies for connecting objects and 
de vice s (Inte rnet of  Things)”, but  raw 
data  are   ne e ded  from   Eurostat.  Data 
available  until  2017,  ye arly  update, 
bre akdown  by  size   class  and  se ctor 
(NAC E).  
Not applicable for non-specialists. 

327  W he n different sources are  used be twe en the  EU and the  US it  is be cause not all EU countrie s are  OECD 
m e mbers, thus the priority for EU cove rage is given to Eurostat whe n available. In addition, 2015 is the starting -
ye ar for the O ECD, while  Eurostat has longer time-series.  

328 

Available 

https://ec.europa.eu/docsroom/documents/30362/attachments/1/translations/en/renditions/native  

at: 

149 

 
 
 
 
 
 
                                              
SUPPLY 
Sub-dimension 

Pillars 
suggested 

Labour market 

Spe cialists 
(e m ployed) 

A ssessment (from the 
review of data) 
Big 
data 
 

Cyber 
security 
 

IoT 

 

Usage  of  ICT 
sk ills 
by 
e nte rprises 

Ye s 

Ye s   

Innovation 

Ye s 

Ye s 

Ye s 

Notes 

of 

individuals 

Num be rs 
with  
corre sponding  sk ills  on  the ir  LinkedIn 
profile  (Curre ntly developed by DG GROW 
in 
for 
the   Advanced  Te chnologies 
Industry  proje ct  and  included  by  the  
W orld  Economic  Forum  in  the ir  re port 
“The  Global Human Capital Report 2017”, 
available ye arly since  2013 329, data not 
available for the US.  
-C ommunity Survey on ICT usage and e-
com m erce in enterprises - Module G: Big 
data analysis (data availability overview 
and details in the overview re port).  
-C ommunity Survey on ICT usage and e-
com m erce in e nterprises - Module D: Use 
of  cloud  com puting  se rvice s  (data 
availability ove rview  and de tails in  the  
ove rvie w re port). 
-  C ollecting  quantitative  Data  on  the  
State  of play of Artificial Intelligence and 
othe r  Ne w  Te chnolog ies  -  SMART 
2019/0019 
-  Included in  the   surve y of  this  study 
the 
unde r  the   que stion  “What 
to 
relationship  of  your 
cybersecurity/IoT/Big 
O ur 
com pany… 1) Is (potential) user of this 
te chnology,  2)  Is  producer  of  this 
te chnology, 3) Is both user and producer 
of this te chnology, 4) Doe s not use  nor 
produce this technology 
Data is available for Europe (2007-2017) 
through Fp7, H2020 C ordis and E-corda 
databases. The matic are as ne e d to  be  
chose n.  

is 
company 
Data? 

Table 8-3 framework of supply and assessment for thematic areas  

Notes 
: requires substantial original work as indicators are not readily available but is feasible. 

8.4.2.  Demand 

ICT  - PROPOSED MONITORING  FRA MEWORK A ND CORRESPONDING  INDICA TORS 

The logic behind the selection of the indicators for skills  demand under training and the 
labour market is described below.  

Sub-dimension  Pillars suggested 
Training 

De m and 
formal 
for 
m e thods of ICT training 
De m and  for  informal 
m e thods of ICT training 

Labour market  R e cruitment  of 

ICT 
spe cialists in business  
Planned investments in 
IC T 
Trade   in  IC T  se rvices 
(by partner country) 
Pre sence 
com panies 

ICT 

of 

(Demand  and 
Supply 
indicator) 

Explanatory notes  
De m and of training is covered by specific statistics collected by 
Eurostat and the  W EF looking at the  demand for acquisition of 
spe cific sk ills, at form al and informal le ve l. Sk ills de mand is 
prox ied by the completion of computer courses or other training 
course s (through formalized education or self-study). 
De m and of (ICT) labour is proxied by the  pre sence of hard-to-
fill vacancies, re cruitment statistics for spe cific task s/skills, as 
we ll as by inve stment plans in the (ICT) field. Trade in services 
prox ied by the demand of ICT services by partner country is also 
considered as a proxy for labour demand.  

The  pre sence  of companies or clusters and the change in the  
cluste r com position can be  considered a prox y of demand of 
spe cific skills (i.e. ICT skills). 

329 Data are  only available on PDF ve rsion, thus extraction should run by scraping if no raw data provided by the  

W EF.  

150 

 
 
 
 
                                              
Table 8-4: framework of demand and assessment for ICT 

Figure 8-4 and Table 8-4 visualise and summarise the indicators collected for Demand on 
ICT-related skills. 

Figure 8-4 Summary of indicators on ICT Demand 

Dimensio
n 

Sub-
dimension 

Indicator 

Source 

Years 
availabl
e 

Training 

De m and 
for 
formal 
m e thods of 

of 

W ay 
obtaining 
e -sk ills: 

2005 
2006 

Eurostat 

Notes on 
continuit
y in the 
future 
Irre gular 

US 
availability 
(source) 

A vailabilit
y by size 
(SMEs) 

No 

No 

151 

 
 
 
 
 
Source 

Notes on 
continuit
y in the 
future 

US 
availability 
(source) 

A vailabilit
y by size 
(SMEs) 

Eurostat 

Irre gular 

No 

No 

Years 
availabl
e 

2007 
2011 

2005 
2006 
2007 
2011 

2018 

W EF 

Unsure 

Ye s (WEF) 

No 

1960-
2014 

1960-
2018 

2012-
2017 

2012-
2017 

2007-
2017 

Eurostat 

Ye arly 

ESIF 

Ye arly 

Ye s  (W orld 
Bank /OEC D
) 

No 

Ye s  (O ECD 
inve stments
) 

No 

Eurostat 

Ye arly 

Ye s 
C e nsus) 

(US 

Ye s 

Eurostat 

Ye arly 

No 

Ye s 

W EF 

Ye arly 

No 

No 

Dimensio
n 

Sub-
dimension 

Indicator 

IC T 
training 

Training 

De m and 
for informal 
m e thods of 
IC T 
training 

Training 

De m and 
for informal 
m e thods of 
IC T 
training 

Labour 

Labour 

in 

Trade  
IC T 
se rvice s 
(by partner 
country) 
Planned 
inve stment
s in IC T 

Labour 

Labour 

Labour 

R e cruitmen
t  of 
ICT 
spe cialists 
in business 

R e cruitmen
t  of 
ICT 
spe cialists 
in business 

R e cruitmen
t  of 
ICT 
spe cialists 
in business 

of 

Individuals 
who  have  
obtained IT 
sk ills 
through 
form alize d 
e ducation 
(school, 
unive rsity, 
colle ge, 
e tc.) 
W ay 
obtaining 
e -sk ills: 
Individuals 
who  have  
obtained IT 
sk ills 
through 
training 
course s, 
se lf-study 
(books, 
C D-R OMs, 
e tc. 
& 
le arning by 
doing) 
Individuals 
who  have  
tak en 
a 
com puter 
course  
m ore   than 
3 years ago 
or 
have  
ne ve r 
tak e n any 
Trade  
in 
IC T 
se rvices by 
partne r 
country 
Planned 
IC T 
inve stment
under 
s 
ESIF 
(by 
country, by 
re gion,  by 
op prog) 
Ente rprises 
that 
re cruited or 
trie d 
to 
re cruit  ICT 
spe cialists 
Businesses 
having 
hard-to-fill 
vacancies 
for 
ICT 
spe cialists 
Ente rprises 
whe re  
e x te rnal 
suppliers 
pe rformed 
(fully 
or 
partly)  ICT 
functions 

152 

 
 
Dimensio
n 

Sub-
dimension 

Indicator 

Source 

Years 
availabl
e 

Notes on 
continuit
y in the 
future 

US 
availability 
(source) 

A vailabilit
y by size 
(SMEs) 

Labour 
(supply  & 
demand) 

IC T 
com panies 

Labour 
(supply  & 
demand) 

 IC T 
com panies 

re quiring 
IC T/IT 
spe cialists 
IC T 
e nte rprises
:  Industrial 
structure   - 
supply  of 
sk ills 
IC T 
prox ied  by 
the  
pre sence of 
IC T 
com panies 
Pre sence of 
re le vant 
cluste rs 

2012-
2017 

Eurostat 

Ye arly 

No 

Ye s 

2013 

C luster 
collaboratio
n platform 

Updated 
online  on 
a  re gular 
basis 

No 

Ye s 

Table 8-5: framework of demand for ICT level - available indicators330 

BIG  DA TA,  IOT  A ND  CYBERSECURITY  PROPOSED  MONITORING  FRA MEWORK  A ND 
CORRESPONDING  INDICA TORS 

Initiatives to set the ground for the design of indicators at the thematic level come from 
traditional and new data sources. One of them comes from Cedefop constructing demand 
indicators using online job vacancies currently using ISCO codes which could how ever be 
tailored given the use of  big data. 

Key findings on Big Data, IoT and Cybersecurity skills supply are summarised below. From 
the  indicators  listed  we  propose  in  the  short  term  to  regularly  monitor  online  job 
advertisements requiring  skills  in  big  data, cybersecurity, IoT.  This  can  be  done  via 
coordination with the work cedefop is currently conducting or using LinkedIn data.  The 
jobs data of LinkedIn includes both jobs posted directly on LinkedIn via LinkedIn Jobs as 
well  as jobs  ingested from  over 40,000  sources including company websites, applicant 
tracking  systems,  job  boards,  aggregators  and  job  feeds.  LinkedIn  has  developed 
algorithms to identify and remove duplicate job posts from ingested sources.  

DEMA ND 
Sub- 
dimension 

Training 

Pillars suggested  Asse ssment 

(from  

the  

Notes on sourcing data 

re vie w of data) 

Big 
data  
 

IoT 

 

C ybe r 
se curity 
 

 

 

 

for 
De m and 
form al m ethods of 
IC T training 
De m and 
for 
inform al m ethods 
of IC T training 

W e bcrawling  of  Unive rsity  we bsite s  for 
e nrolments  in  IC T  courses  by  the matic 
are a 331 
W e bcrawling of ICT vocational we bsites for 
e nrolments 
Sk ills type of LinkedIn m embers, by age 
and de gree of specialization, W EF Global 
Hum an  C apital  R e port  2017,  updated 

330  W he n different sources are  used be twe en the  EU and the  US it  is be cause not all EU countrie s are  OECD 
m e mbers, thus the priority for EU cove rage is given to Eurostat whe n available. In addition, 2015 is the starting -
ye ar for the O ECD, while  Eurostat has longer time-series. 

331 

Pilot 

the  
file :///Users/eleonora/Downloads/EIS%20Exploratory%20Report%20B-Big%20data%20(1).pdf  page 5 

Score board 

Innovation 

Europe an 

NESTA 

run 

for 

by 

2018, 

153 

 
 
 
 
 
 
 
 
                                              
DEMA ND 

Labour 
market 

 

 

 

R e cruitment 
the m atic 
spe cialists 
business 

of  
area 
in 

Use   of  Big  Data 
analysis 
by 
business 

Ye s 

 

 

Ye s 

Ye s 

Ye s 

Planned 
inve stments 
the  
are as 

in 
thematic 

i.e . 

Notes on sourcing data 
ye arly, since 2013. Not available for the 
US332.  
O nline Job vacancies: 
C e defop, due  in  March  2019: curre ntly 
assessing which data will be covered. Only 
EU) 
Te chnopolis group in the context of Digital 
C itie s C hallenge (number of jobs in ICTs, 
only for lim ited number of European cities, 
only for 2018)  
Inde x calculated as ratio of the number of 
re cruite r  outre ach  via 
InMails 
Link e dIn’s ne twork  se nt on ave rage over 
the  last 12  m onths to unique members 
with the  spe cific skill as a proxy of demand 
of sk ills. C apGemini re port “Digital Talent 
Gap  –  Are   com panies  doing  e nough? 
2017 333”. European and US data.  
DG GR O W  is curre ntly designing LinkedIn 
based Indicators for  de m and using the  
available jobs data within the   Advanced 
Te chnologies for Industry proje ct. 
Pe rce ntage of total e nterprises; with own 
e m ployees,  with 
se rvice  
providers, with both own e m ployees and 
e x te rnal se rvice providers. O EC D, 2016. 
Not available for US. 
C runchbase - Availability of ve nture capital 
in  total  IC T;  Num ber  of 
inve stors, 
re gularly updated online.  

e x te rnal 

Table 8-6: framework of demand and assessment for thematic areas indicators  

: requires substantial original work as indicators are not readily available but is feasible  

8.5.  Building on existing frameworks – towards a single monitoring framework 

Other  existing  frameworks  and  initiatives at EU-level have  been scrutinised to assess 
synergies with our monitoring mechanism and the indicators collected. More specifically, 
we checked:  

  additional relevant indicators,  
  alternative data collection methodologies and,  
 

the extendibility of the alternative approach and data to the three areas (Big 
Data, IoT and Cybersecurity).  

The  assessment of  the  existing  frameworks  was  done  having  in  mind  the  following 
questions:  

  What are the commonalities between the indicators collected and the ones collected 
in the scope of the other monitoring framework, for ICT and prospected the three 
thematic areas?  

  To what extent the other approaches can be used and adapted for the collection of 

indicators on the three thematic areas?  

  Ultimately, what should we retain and what should we discard? How the other 

frameworks could use our proposed framework as reference?  

332 Note : R aw Data by country are only available through the report. They need to be extracted by scarping.  

333  R e port 

link :  https://www.capgemini.com/news/capgemini-and-linkedin-release-new-report-on-the-digital-talent-gap-

employees-are-investing-their-own-resources-to-remain-competitive/ 

154 

 
 
 
 
                                              
Figure 8-5 summarises  the assessment of the other existing initiatives and frameworks 
under  observation, further  developed  below.  Potential additions  and  changes  to  the 
currently proposed set of indicators will be discussed with the European Commission.  

Figure 8-5 Monitoring framework proposed and synergies with other  frameworks and initiatives  

Source: Author’s elaboration 

E-SKILLS  A ND E-LEA DERSHIP SKILLS  IN  EUROPE, DIGITA L  ORGA NISA TIONA L  FRA MEWORKS 
A ND IT  PROFESSIONA LISM  EASME/COSME/2016/016 (EMPIRICA ) 

 

In the context of the project e-Skills and e-Leadership Skills in Europe, Demand 
and Supply Forecasts (2016-2020) (Digital Organisational Frameworks and IT 
Professionalism EASME/COSME/2016/016), for e-Skills, Empirica builds a Supply-
Demand framework to run a forecast with two scenarios. Differently from our 
approach based on Training and Labour indicators for both Supply and Demand, 
the Empirica’s Supply framework can be split into two groups of indicators: 1) 
Labour and 2) Training, while the demand side is based on 1) Labour (vacancies 
and, jobs).  

  A relevant indicator for international comparisons is the one on immigration-

emigration, that is similar  to our “trade in services by partner country indicator”. 
Alternative formulations and sources could eventually be considered as for 
example the cross-border trade in employment (for which OECD indicators could 
be used). This extension would only be relevant for ICTs and not for the other 
three areas because of data aggregation limitations.  

  Other useful indic ators proposed under the Supply side would be Lateral entry and 

Category change, however, novel work of data collection (as well as more 
information on Empirica’s sources and method) should be accounted for.  

  Concerning the demand side, vacancies are a relevant indicator. 
  The e-Skills Empirica framework uses a definition of ICT Specialists and ICT 
Profession based on ISCO codes. In view of extending these codes to create 
relevant indicators on employment (occupations) for Big Data, IoT and 
Cybersecurity, we appreciate that ILO ISCO codes are the best reference 
and the most widely used one, in terms of detailed workforce topologies.  
To use ISCO codes would create a solid base for further monitoring and for 
replicability. However, from a conceptual point of view, additional workforce type 
codes should be considered on top of the ones used for ICTs, as the applications 
of these three areas are broader than ICT only. Ultimately, raw data from ILO 
should be assessed to further explore this hypothesis. More information can be 
found in Error! Reference source not found. 

155 

Consider ILO ISCO codes to extend ICT definition to the three areas to create indicators using ILO data and workforce categories. Overall very limited extendibility to the three areas  Empirica/IDC  Similar indicators on HEI and Vocational trainingCross-border trade in employment indicator possible inclusion for intl. comparisonsIt includes time-dynamic indicators of possible inclusion for forecast analyses = possibly consider ICTAvailable ICT specialists indicator by country in the section "OccupationAvailable ICT services indicators on employment --> however very aggregated  Skills PanoramaEurofound toolsBig DataCybersecIoTData collection based on webscraping or at a higher level of aggregation for the restructuring event monitor. Job monitor needs further investigation  EurostatOECDCluster Collab platformEcordaWEFICT data sourcesEurostatOECDCluster Collab platformEcordaWEFCEDEFOPEurostatOECDEurostatWeb-crawlingToo aggregated to extend to the three areas Low adaptability assumed - but further investigation could be done.  
 
 
 
 
While  Empirica’s approach provides a good granularity for the ICT area it has not an 
immediate  application  to  the  other  three  areas.  Further  analysis  can  be  done, 
nonetheless, on  the  usability  of  ILO  ISCO  codes (as  done  by  Empirica)  to  create 
workforce categorisations for the other areas. 

THE  SKILLS  PA NORA MA   

The Skills  Panorama is  the online platform  for skills  monitoring  and anticipation by the 
European Commission and powered by CEDEFOP. Indicators are presented by:  

  Source 
  Dataset 
  Alphabetical order 
  Policy theme (European skills index, People and skills, matching skills and jobs, 

future jobs, labour market context)  

  Country (EU28) 
  Occupation. The skills panorama occupation type (i.e. workforce) is in line with 

ILO ISCO codes, thus largely also in line with our proposed typologies structure. 
Associate professionals include ICT technicians. Statistics available cover i) future 
employment growth, ii) occupations employed in the sector iii) employment 
shares, iv) employment by level of education v) by age and future employment 
openings (from the CEDEFOP database). 

  Sector. The sectors include ICT services with statistics on i) future employment 
growth, ii) occupations employed in the sector iii) employment shares, iv) 
employment by level of education v) by age (all data from Labour Force Survey)  

Key EU trends to 2030 also includes a section on Demand  for and Supply of Skills, with 
two reported indicators 1) Share of job openings by level of education 2016-2030 and 2) 
Labour force share by level of qualification 2011-2030. Overall the following considerations 
can be made:  

  The data aggregation reported by the Skills Panorama website is quite high, thus 
not allowing making further considerations on the use of the data for additional 
areas (i.e. big data, etc.).  

  The codes used by CEDEFOP are always ISCO or ESO, and in all cases, translated 

in one of the two so to be able to make international comparisons.  

  Similarly  to Empirica, there is a forecast aspect (skills anticipation, at ISCO codes 

3-digit) 

  The study team has contacted CEDEFOP to assess details about the granularity of 
the data collected by them, and to confirm with them if there is any planned 
activity on specifically the areas covered by this study (ICT, Big data, IoT, 
Cybersecurity). CEDEFOP has confirmed that for the quasi totality of the data 
collected, data granularity would not allow us to extract information and indicators 
at the level of the thee areas under observation. An exception to keep monitored 
for the future is about “online vacancies” for which data collection will potentially 
reach ISCO 4-digit level. ICT occupations will be covered for sure. The project will 
deliver the first results for seven EU countries in March 2019, to reach EU28 
coverage by mid-2020.  

  For some occupations (high-tech occupations, vacancies) CEDEFOP reported 

difficulties to use ISCO codes, at 3-4 digit, and mentioned that further adaptations 
at higher-level (ILO level) are needed to accommodate for the changing nature of 
occupations in the high-tech area.  

EUROFOUND TOOLS 

156 

 
 
 
 
 
The Eurofound  European  Monitoring Centre on  Change  –  EMCC  includes  two relevant 
monitors accounting for skills and/or jobs by sector/area: 1) the European Restructuring 
Monitor and the 2) European Jobs Monitor. After a review of the resources available online, 
the following can be concluded:  

  Restructuring Monitor: the information reported in the restructuring events 

database is gathered by a network of correspondents carrying out a wide -ranging 
screening of daily and business press and online sources. The events covered 
concern only large-scale companies in the EU28 countries as well as Norway. An 
event is included if it entails the announced destruction or creation of at least 100 
jobs, or at least 10% of the workforce at sites employing more than 250 people. 
In view of our study’s objectives and scope, a weak linking potential is envisaged 
given that data refer only to large-scale companies, and that the highest sectoral 
disaggregation goes to the level of “information/communication” business area 
(industry classification not specified). 

  European Job Monitor: it focuses on structural change statistics, using proxies 
of job quality like wages and skills levels. Further investigation would be needed 
to assess more in-depth the type of data used, sectors, and occupations covered 
as the full dataset seems not accessible online.  

157 

 
 
 
 
 
De puty director general 

Tillväxtverket 

APPENDIX  A: LIST OF INTERVIEWEES 
 Expert interviewees round 1 (February – June 2018) 

First Name 

Name 

Title/Role 

1 

C ristina  

Barros 

2 

3 

Maria  

Bas 

Be ck  

Bosm a 

4 

Agata  

Boutanos 

5 

Jiri 

Brank a 

6 

7 

8 

Le na  

Joris 

Mary 

C arlsson 

C astermans 

C le ary 

9 

Thomas 

C ooney 

10  R aphaël 

C rouan 

11  Ans 

De  Vos 

12  Danilo  

13 

Yuri 

D'Elia  

De m chenko  

14 

Pavlin 

Dobre v 

15  Branim ir 

Dze nopoljac 

C oordinator SMEs 
dim e nsion  

Ge schäftsstellenleiterin 
Digital in NR W 
Assistant Professor of Data 
Scie nce  and 
Entre pre neurship 
Dire ctor of the 
R e presentation to the 
Europe an Union 
Ex pe rt De partment for 
Sk ills and Labour Market 

Business developer IoT  

De puty C hief Ex ecutive 
O ffice r; Coordinator of Irish 
Digital Skills and Jobs 
C oaltion  
Profe ssor in 
Entre pre neurship 
Founder & C EO; board 
m e mber & chair for SMEs 
Profe ssor 

Se nior Policy Manager 

C oordinating partner at 
EDISO N 
C onsortiumUniversity of 
Am ste rdam 
R e search and development 
m anager 
Advisor 

18  R ichard 

Foggie 

Advisor  

19  Mark o 

Grobe lnik 

C oordinator of Digitalna 
Slove nija 

20 

Paul  

21  Vale ntin 

He aly 

Hue ber 

22  Mara  

Jak obsone 

23  Gábor 

Kism ihók 

C hie f Executive 

Engine ering and 
Te chnology C onsulting 
(IC T) De legate 
C oordinator of E-prasmju 
partrne rība (E-skills 
partne rship), vice-presiden 
R e search Group Leader 

24 

Elzbie ta 

Ksiazek 

De puty Director 

Organisation 

Portuguese National 
Initiative for Digital 
C om petences (INCoDe)  
Mitte lstand 4.0 

Jhe ronimous Academy of 
Data Scie nce (JADS) 

Union of Entrepre neurs 
and Em ployers  

C EDEFO P  

Slim design; Twe nte 
Unive rsity 
Irish C omputer Society & 
C EN W ork shop on ICT 
Sk ills 

Dublin Institute of 
Te chnology 
Startupbootcamp IoT 
Program; AIOTI 
Antwe rp Management 
School 
EC SO  

EDISO N C onsortium 

Bosch Software 
Innovation 
IC T C luster of C entral 
Se rbia  
Sm artified 

Innovate UK (knowle dge 
transfer network ) 
the  Slovenian Chamber of 
C om merce  and the 
Ministry of Public 
Adm inistration 
Sk illnet 

Synte c Num érique 

LIKTA 

Te chnische 
Informationsbibliothek 
(TIB) 
Poznan Science and 
Te chnology Park 
C hamber of Commerce 

Aste r 

16 

Patrick  

17  Ande rs 

Farlang Slavenburg 

C o-founder 

Flodstrom 

Educational Director 

EIT Digital (EIT ICTLabs) 

25  R uud 

Mannaart 

26 

Lucia  

Mazzoni 

27 

Erne stina  

Me nasalvas 

28 

Le o 

29  Me re te  

Mrsic 

Nørby 

Advisor, product manager, 
innovation, data and re tail 
IC T R egional Technology 
Platform C oordinator 

C hair of the TF on Skills 
and Education 
Profe ssor 

Big Data Value 
Association 
Alge bra University 

Inte rnational Senior 
C onsultant, Ph.D 

MADE 

158 

 
 
  
First Name 

Name 

Title/Role 

Organisation 

30  Agis 

Papantoniou 

C EO  

31  Andre a  

Parola 

Ge ne ral Manager 

32  Ke nny 

Pool 

33  Nicolò 

Pranzini 

C hairman Big Data 
Innovation Hub 
ASTER  - High Competences 
and Startup Unit 

34 

Luigi 

R e buffi 

C EO  and founder 

35 

Paul 

36  Nie ls Pe ter 

R oe vens 

R ønmos 

37  Ste fan 

Schum acher 

Dire ctor 

C hie f Special advisor Digital 
Unit/ Data scientist in 
ce nte r for digital innovation 
Dire ctor 

38  Bo 

Se je r Frandsen 

C EO  

39  Ge orge 

Shark ov 

He ad 

C ognizone 

Europe an e-Skills 
Association 
De ll Te chnologies  

ASTER  - High 
C om petences and Startup 
Unit 
Europe an Cyber Se curity 
O rganisation (ECSO) 
Le ad-IT 

Danish Business 
Authority 

Voice  e .V. (Association of 
the  IT Using SMEs) 
IT Forum (Digital SME 
national member) 

C ybe rsecurity Bulgarian 
Gove rnment 

40 

Egbe rt-Jan 

Sol  

C TO  and professor 

TNO , R adboud University 

41  R ichard 

Ste ve ns 

42  Ste fano 

43  Staffan  

Tirati 

Truvé  

C onsulting Director, IDC 
Europe an Government 
C onsulting 
Vice  Pre sident 

IDC  Italy 

EFVET 

C TO  and professor 

R e corded Future 

44  C onstantinos 

Tsiourtos 

Ex e cutive Director 

45  Hans 

46  Arthur 

Van Bragt 

Van de r W ees 

47 

Philippe 

van Im pe 

Proje ctle ider 

Founder 

Dire cte ur 

48  R ob 

Van Kranenburg 

Founder IOT council 

49  Andre a  

Zapparoli Manzoni 

50 

Thilo  

Zim m ermann 

Me m ber of Board of 
Dire ctors 
Proje ct Manager Future 
W ork  Lab 

C yprus Cybersecurity 
O rganization 
Big Data Value C enter 

Arthur's Le gal 

Digityser 

IO T council 

C LUSIT 

Fraunhofer 

Expert interviewees round 2 (June - November 2019) 

First Name 

Name 

Title/Role 

Organisation 

1  Ge e rt  

Asse lbergs 

Se nior proje ct lead 

2  Maria  

Be ck  

3  Marco 

Bianchini 

Ge schäftsstellenleiterin Digital in 
NR W  
Policy Analyst 

4  C hristiaan 

Boite n 

Advisor 

Stichting 
Bè tate chniek 
Mitte lstand 4.0 

Platform 

C e ntre for  Entre pre neurship, 
SMEs,  R e gions  and  C ities, 
O EC D 
Eurocom merce 

5  Laure ntiu 

Bune scu 

C EO  

All Digital 

6  Danilo  

d'Elia  

Se nior policy analyst 

7  Ge rard 

Doyle  

8  Dave  

Fe e nan 

9  Sam uel 

Frick e r 

10 

Jörg 

Frie drich 

11  Ele na  

Garrido  

Ne twork  m anager, C ybersecurity 
Sk ills Initiative 
Ne twork  m anager 

Ph.D.,  Profe ssor  at 
FHNW  
Unive rsity  of  Applie d  Scie nces 
and  assistant  profe ssor  at 
Ble k inge Institute of Technology 
He ad of De partment Educational 
Policy 
C luster m anager 

Europe an  C ybe r  Se curity 
O rganisation (ECSO) 
Te chnology 
Sk illnet 
Te chnology 
Sk illnet 
SMESEC  (ATO S contributing) 

Ire land 

Ire land 

ICT 

ICT 

VDMA 

AER TIC 

159 

 
 
  
 
 
12  Paul 

Gisby 

Se nior manager 

Accountancy Europe 

13  Poul-Erik 

Hansen 

14  Margot 

15  Danny  

16  Youssef 

17  Gordon  

18  Daan 

19  Tim o 

Hol 

Jaspers 

Kalad 

Kirste in 

Kolk man 

Kos 

20  Katarzyna  

Koziol 

21  Anne  

Lidgard 

Dire ctor 

Analyst 

Business lead C yber 

C ENSEC  

Achm e a 

Achm e a 

C TO -office , C yber initiatives 

Ne w York  C ity 

C EO  

Initiator 

Ex e cutive  Dire ctor  Ex tension 
School 
Ente rprise  and  Single   Market 
Advise r 
Dire ctor, Se nior Advisor 

Move Tech 

JADS SME Datalab 

Te chnical University Delft 

SME Unite d 

Swe dish 
Age ncy VINNO VA 

Innovation 

22  R obert Jan 

Marringa 

23  Fabio  

Massimo 

Le ad 

Proje ct 
De ve lopment 
C hair, board member 

Brainport 

Two For Innovation 

TC 428, Digital SME Alliance 

24  Ste ffe n 

Maure r 

C hie f Information Security Officer  Move Tech 

25  Erne stina 

Me nasalvas 

26  Guido 

O ngena 

Le ad of BDVA Task Force 9: Skills 
and Education 
Se nior re searcher HU Data Lab 

27  Nicolò  

Pranzini 

Advisor 

28  Pe tra  

Püchner 

C om missioner for Europe  

29  Pascal 

R ave steijn 

30  Ste fan 

Schum acher 

Profe ssor in Process Innovation & 
Information Systems  
Dire ctor 

31  Franziska 

Se im ys 

Policy support 

32  Bo 

Se je r Frandsen  C EO ,  board  m e mber,  vice -

33 

Josine 

34  Arjan 

van de  Ven 

pre sident 
Dr. Ing. 

Van de n Born 

R e search Institute Director 

35  C saba 

Virag 

He ad  

36  R ainer 

W e ndt 

Me m ber  of  W G  SKILLS:  digital 
sk ills, social dialogue, movement 
of  work e rs, com petence ce nters 
at DIGITAL SME 

Big  Data  Value   Association, 
and University Madrid 
Unive sity of Applied Sciences 
Utre cht 

ASTER   -  High  C ompetences 
and Startup Unit 
Minister of Econom ic Affairs, 
Labour and Housing of Baden-
W ue rttemberg, Ge rmany 
HU  Business School Utre cht, 
Unive rsity of Applied Sciences 
Voice  e .V. (Association of the 
IT Users SME)  
VDMA 

IT-forum,  AIO TI,  European 
DIGITAL SME Alliance  
TNO    

of 

Institute 

Tilburg 
Gove rnance 
C ybe rsecurity  C ompetence 
C e nter Hungary 
BITMi, IIBA, PMI 

Alignment meetings with related initiatives (February 2018 – August 2018) 

Name 

Project/Initiative 

1  Svatopluk Štolfa 

2  Lucía Fraga Lago 

3  Milva C arbonaro  

4  Silvia Barbone 

Innovative 

De ve lopment  and  R e search  on 
Vocational Education Skills (DRIVES) 
Maritim e Alliance for fostering the  European Blue  
e conomy  through  a  Marine  Te chnology  Sk illing 
Strate gy (MATES) 
Towards  an 
sk ills 
de ve lopment and capacity building in the space geo 
inform ation  se ctor  supporting  C ope rnicus  User 
Uptake (EO 4GEO) 
The  Ne xt Tourism Ge neration Alliance (NGT) 

innovative  strate gy 

for 

5  C hristine Simon, Katarzyna Szumielewicz  

Mak es_me_digital 

6  Mayte  C arrecedo 

I4MS  

APPENDIX  B: METHOD  AND SOURCES OF THE ANALYSIS OF 
TECHNOLOGICAL TRENDS 

160 

 
 
 
 
 
For the analysis of the technology trends and market developments described in section 
2.3, 25 research articles from leading research firms were compared and analysed. The 
following criteria were used to identify technological trends:  

  Publications are max. 2 years old; 

  Trends identified are documented by at least three separate sources; 

  Trends are related to or impact big data, IoT and/or cybersecurity; 

  They are disruptive technologies, according to the definition provided by 

McKinsey334, meaning that they are rapidly advancing, they have a broad potential 
scope of impact, may affect significant economic value, and they can dramatically 
change the status quo of the market; 

 

For the search process, the following keywords were used: IoT, big data, 
cybersecurity, movements, trends, market developments, technology, outlook, 
2018 

(1) 

(2) 

Acce nture  (2018), Accenture Technology Vision. Available at: 
https://www.acce nture .com/t20180227T215953Z__w__/us -en/_acnmedia/Accenture/next-gen-
7/te ch-vision-2018/pdf/Accenture-TechVision-2018-Tech-Trends-Report.pdf#zoom=50  

Atom ico (2017), State of European Tech Report 2017. Available at: 
https://2017.stateofeuropeantech.com/  

334 Manyika, J., Chui, M., Bughin, J., Dobbs, R ., Bisson, P., & Marrs, A. (2013), Disruptive technologies: 

Advances that will transform life, business, and the global e conomy. Published May. Available at: 
https://www.m ck insey.com/business-functions/digital-mckinsey/our-insights/disruptive-technologies  

161 

 
 
 
                                              
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
(3) 

(4) 

(5) 

(6) 

(7) 

(8) 

(9) 

(10) 

(11) 

(12) 

(13) 

(14) 

(15) 

(16) 

(17) 

(18) 

(19) 

(20) 

(21) 

(22) 

(23) 

(24) 

Bain & C ompany (2017), Finding Europe's Edge in the Internet of Things. Available at: 
http://www.bain.com/publications/articles/finding-europes-edge-in-the-internet-of-things.aspx  

C apgemini (2017) Technovision Parallel Digital R ealities 2017. Available at: 
https://www.capge mini.com/wp -content/uploads/2017/07/technovision_2017_-
_parallel_digital_re alities.pdf  

C apgemini (2017) Trends in C ybersecurity 2017. Available at: https://www.capgemini.com/nl-nl/wp-
conte nt/uploads/sites/7/2017/11/1b-085-17-tre nds-in-cybersecurity_we b.pdf  

C apgemini (2018) 2018 Pre dictions: Disruptive Technologies. Available at: 
https://www.capge mini.com/gb-en/2018/01/2018-predictions-disruptive-technologies/#  

C apgemini (2018) 2018 predictions: cybersecurity. Available at: https://www.capgemini.com/gb -
e n/2018/01/2018-predictions-cybersecurity/  

C isco Systems (2018), Annual C ybersecurity Report. Available at: 
https://www.cisco.com /c/m/en_au/products/security/offers/cybersecurity-reports.html  

De loitte (2018), Technology Industry O utlook. Navigating toward the future: Leveraging technology 
advance s in the digital transformation e ra. Available at: 
https://www2.de loitte.com/content/dam/Deloitte/us/Documents/technology-media-
te le communications/us-tmt-2018-technology-industry-outlook.pdf  

De loitte (2018), Tech Trends 2018. The symphonic e nterprise. Available at: 
https://www2.de loitte.com/content/dam/insights/us/articles/Tech-Trends-2018/4109_TechTrends-
2018_FINAL.pdf  

De loitte (2015), Five questions about social media analytics in the energy and re source s industries. 
Available at: https://www2.de loitte.com/us/en/pages/finance/articles/five-questions-about-social-
m e dia-analytics-in-energy-and-resources-industries.html 

Enisa (2017) ENISA Threat Landscape R eport 2017. Available at: 
https://www.e nisa.europa.eu/publications/enisa-threat-landscape-report-2017  

Europe an Commission (2017), The Digital Economy and Society Index. Available at: 
https://ec.europa.eu/digital-single-market/en/desi 

EY (2018), Is the next e volution of big data, big judgmen t? Available at: 
http://www.e y.com /Publication/vwLUAssets/EY -data-analytics-in-hospitality/$FILE/EY -data-analytics-
in-hospitality.pdf  

Gartne r (2017), Top 10 Strategic Technology Trends for 2018. Available at: 
https://www.gartne r.com/doc/3811368?refval=&pcp=mpe 

Gartne r (2018), The Top Security Trends for Midsize Enterprises. Available at: 
https://www.gartne r.com/we binar/3690017  

Gartne r (2017), 100 Data and Analytics Predictions for 2021. Available at: 
https://www.gartne r.com/imagesrv/media-products/pdf/tealium/Tealium-1-47GUGIN.pdf  

IBM (2017), Top 5 IoT tre nds transforming business in 2018. Available at: 
https://www.ibm .com/blogs/internet-of-things/top-5-iot-trends-in-2018/ 

IDC  (2017), Worldwide IT Industry 2018 Predictions. Available at: 
https://www.idc.com /getdoc.jsp?containerId=US43171317 

McKinse y & C ompany (2017), What’s Now and Ne xt in Analytics, AI, and Automation. Available at: 
https://www.m ck insey.com/global-themes/digital-disruption/whats-now-and-next-in-analytics-ai-and-
automation# 

McKinse y & C ompany (2017), Fueling growth through data monetization. Available at: 
https://www.m ck insey.com/business-functions/mckinsey-analytics/our-insights/fueling-growth-
through-data-monetization 

McKinse y & C ompany (2016), Digital Europe: Pushing the frontier, captu ring the benefits. Available at: 
https://www.m ck insey.com/~/media/McKinsey/Business%20Functions/McKinsey%20Digital/Our%20I
nsights/Digital%20Europe%20Pushing%20the%20frontier%20capturing%20the%20benefits/Digital -
Europe -Full-report-June-2016.ashx 

Price wate rhouseCoopers (2018), Tech breakthroughs megatrend: how to pre pare for its impact. 
Available at: https://www.pwc.com /gx/en/issues/technology/tech-breakthroughs-megatre nd.html 

Price wate rhouseCo opers (2017), Emerging tre nds 2017. W hat’s ahead on the global cybersecurity and 
privacy landscape? Available at: https://www.pwc.com /us/en/cybersecurity/assets/cybersecurity-
tre nds.pdf 

(25) 

Saviant Consulting (2018), IoT and Data Analytics Predictions for 2018. Available at: 
http://www.saviantconsulting.com/blog/iot-data-analytics-pre dictions-2018.aspx  

APPENDIX  C:  TOOLBOX OVERVIEW 

162 

 
 
 
 
Good practices - 
various skills 
initiatives 

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

1  Digital Skills for 

SMEs 

http://www.glbulgar
ia.bg/en/digisme 

Training 
program 

1. 
Stre ngthening 
e cosystems 

1.  C re ated share d databases and 
tools to make information 
acce ssible to stakeholders 

Support 
programme/ 
strate gy 

2. Support 
strate gic 
outlook 
de ve lopment  

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2  SME:Digital 

https://investindk.c
om /-/media/invest-
in-
de nmark/files/danis
h-digital-growth-
strate gy2018.ashx?l
a=e n&hash=8F378
A9E64FAD29D4453
0C 3238D9720DA44
EC 3C A 
https://eng.em.dk/
m e dia/10554/digital
-strate gy-fact-
she et.pdf  

3  Num e ricALL & 

Fit4coding – 
training 
jobse ekers into 
we b de ve lopers 
in Lux embourg 

4  Digitaal.Talent@
Ge nt – Unlocking 
the  Digital 
Pote ntial of all 
C itize ns in 
Be lgium 

https://www.num e ri
call.fr/ 

Training 
program 

4. Tailor 
e ducation and 
training offers  

4. Innovate e ducational 
programmes (co-creation, 
badging) to stimulate 
collaboration betwe en SMEs and 
e ducation 

https://stad.gent/sa
m e nleven-we lzijn-
ge zondheid/alle-
ge ntenaars-digitaal 

Training 
program 

1. 
Stre ngthening 
e cosystems 

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

5  W allonia 

Marshall Plan 
4.0. 

http://planmarshall.
wallonie .be/le-plan-
0 

Ne twork  / 
collaboratio
n 

3. Stre ngthen 
structure d skills 
de ve lopment  

6  Grande  
é cole  du 
num érique in 
France  

7  Sam sung 

Innovation 
C am p in Italy 

http://www.grandee
cole numerique.fr/ 

Training 
program 

4. Tailor 
e ducation and 
training offers  

https://www.innova
tioncamp.it 

Training 
program 

8 

IT Talents 
Training Camp 

http://ittalents.bg/h
om e  

Training 
program 

3. Prom ote blueprints, practical 
fram ework s and tools that support 
SMEs to build a smart (HR) 
strate gy (incl. tools to support 
re cruitm ent, hiring, dvlpment) 

4. Innovate e ducational 
programmes (co-creation, 
badging) to stimulate 
collaboration betwe en SMEs and 
e ducation 

4. Tailor 
e ducation and 
training offers  

4. Incre ase understanding of 
e ducation providers on h2 identify 
training needs, target groups & 
tailor offers 

4. Tailor 
e ducation and 
training offers  

4. Prom ote and scale succe ssful 
funding mechanisms that foster 
sk ills development (e.g. cost-
sharing models) 

9  C oding Class in 
De nm ark 

10  The  Digital 

Acade my 

https://itb.dk/article
s/fre mtidens-
k om petencer/coding
-class 

Training 
program 

4. Tailor 
e ducation and 
training offers  

https://www.cze chit
as.cz/en/portfolio/di
gital-academy 

Training 
program 

4. Tailor 
e ducation and 
training offers  

11  IT for SHE 

http://www.itforshe
.pl/ 

Training 
program 

12  Proge Tiger 

Training 
program 

http://www.hitsa.ee
/it-
e ducation/education
al-
programmes/progeti
ge r 

4. Tailor 
e ducation and 
training offers  

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non-
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Incre ase mobility of scarce  
e x perts (in Edu & Edu-Industry) 

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

163 

 
 
 
Good practices - 
various skills 
initiatives 

13  SMESEC  

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

https://smesec.eu/a
bout.html 

Guide / 
toolbox 

1. 
Stre ngthening 
e cosystems 

1.  C re ated share d databases and 
tools to make information 
acce ssible to stakeholders 

14  Big Data Value 
Association 

http://www.bdva.eu  Ne twork  / 

collaboratio
n 

1. 
Stre ngthening 
e cosystems 

Training 
program 

1. 
Stre ngthening 
e cosystems 

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

Ne twork  / 
collaboratio
n 

4. Tailor 
e ducation and 
training offers  

4. Prom ote existing blueprints for 
training for SMEs 

http://we bacademie
.org/ambitionFemini
ne  

Training 
program 

4. Tailor 
e ducation and 
training offers  

Guide / 
toolbox 

3. Stre ngthen 
structure d skills 
de ve lopment  

4. Innovate e ducational 
programmes (co-creation, 
badging) to stimulate 
collaboration betwe en SMEs and 
e ducation 

3. Prom ote blueprints, practical 
fram ework s and tools that support 
SMEs to build a smart (HR) 
strate gy (incl. tools to support 
re cruitm ent, hiring, dvlpment) 

15  Digital Transition 
programme 

16  Le s Digiteurs. 
Transition 
Num é rique Ile-
de -France 

http://www.e uroco
m m erce .eu/media/1
43276/European%2
0SME-
Action%20Program
m e .pdf  

http://transformatio
n-digitale-tpe-
pm e .cci-paris-
idf.fr/sommaire/ 
https://www.le sdigit
e urs.cci-paris-
idf.fr/notre-
am bition-votre-
e ntre prise 

17  W e b@cademie 

W om en ambition 
– A se cond-
chance  coding 
school! in France 

18  Kom petenzzentr

um  
Fachk räftesicher
ung (KO FA) 
(“one-stop-
shop” 

19  C odepact 

20  Go-Digital 

21  Alliance  for 
Initial and 
Furthe r Training 
2015–2018 

22  Mitte lstand 
Digital 

23  C re sce re in 
Digitale 

https://www.bm wi.
de /R edaktion/EN/Pu
blik ationen/avoiding
-sk ills-shortages-
and-
m ismatches.pdf?__
blob=publicationFile
&v=2 

https://www.bm wi.
de /R edaktion/EN/Pu
blik ationen/avoiding
-sk ills-shortages-
and-
m ismatches.pdf?__
blob=publicationFile
&v=2 

http://www.bm wi.d
e /R edaktion/DE/Arti
k e l/Digitale-
W e lt/foerderprogra
m m -go-digital.html 

https://www.bm wi.
de /R edaktion/EN/Pu
blik ationen/avoiding
-sk ills-shortages-
and-
m ismatches.pdf?__
blob=publicationFile
&v=2 

http://www.bm wi.d
e /R edaktion/DE/Dos
sie r/mittelstand-
digital.html 

http://www.cre sce r
e indigitale.it/ and 
http://foodinnovatio
nprogram.org/googl

Ne twork  / 
collaboratio
n 

4. Tailor 
e ducation and 
training offers  

4. Innovate e ducational 
programmes (co-creation, 
badging) to stimulate 
collaboration betwe en SMEs and 
e ducation 

Support 
programme/
strate gy 

1. 
Stre ngthening 
e cosystems 

Training 
program 

4. Tailor 
e ducation and 
training offers  

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

4. Stim ulate internships to 
provide students with practical 
e x perience  and SMEs with 
pote ntial employees 

Support 
programme/
strate gy 

1. 
Stre ngthening 
e cosystems 

1.  Stim ulate collaboration 
be twe e n hubs and e ducation 
syste m to better tailor to needs 

Training 
program 

4. Tailor 
e ducation and 
training offers  

4. Innovate e ducational 
programmes (co-creation, 
badging) to stimulate 

164 

 
 
 
Good practices - 
various skills 
initiatives 

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

24  Ge rm an-Italian 
C ooperation on 
Industry 4.0 

e -partners-with-
italian-government-
to-launch-made-in-
italy-and-crescere-
in-digitale/ 

https://www.plattfo
rm -
i40.de/I40/Redaktio
n/EN/Downloads/Pu
blik ation-
ge samt/german_ital
ian_cooperation.pdf
?__blob=publication
File &v=2 

Ne twork  / 
collaboratio
n 

1. 
Stre ngthening 
e cosystems 

25  Mitte lstand 4.0  http://www.m itte lst

and-
digital.de/DE/Foerd
e rinitiativen/mittelst
and-4-0.html 

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

collaboration betwe en SMEs and 
e ducation 

1.  Initiate EU and national 
programs that facilitate 
k nowle dge sharing and cre ate 
platforms whe re 3rd parties and 
SMEs can acce ss re levant 
m ate rials (single multi-sector 
portal at EU level) 

2.  Support organisations, 
initiatives and platforms tht foster 
collaboration and knowle dge 
sharing amongcompany 
m anagers/owne rs for adoption of 
BIC  te chnologies and new 
business models (e.g. business 
clubs/associations/clusters, buddy 
support schemes, training 
programs for a group of company 
m anagers) 

26  The  Mittelstand 
4.0 C ompetence 
C e nter 
e Standards 

https://www.k om pe
te nzzentrum-
e standards.digital/ 

Guide / 
toolbox 

1. 
Stre ngthening 
e cosystems 

1.  Stim ulate collaboration 
be twe e n hubs and e ducation 
syste m to better tailor to needs 

27  Digitales 

Handwe rk 

http://www.handwe
rk digital.de/ 

Ne twork  / 
collaboratio
n 

3. Stre ngthen 
structure d skills 
de ve lopment  

3. Facilitate self-assessments to 
e nable SMEs to detect skills gap in 
the ir organisation 

28  Sk illnet Ireland  https://www.sk illnet

ire land.ie 

Ne twork  / 
collaboratio
n 

1. 
Stre ngthening 
e cosystems 

29  SMEs trainings 
for digital 
te chnologies and 
innovation 
de ve lopment in 
Latvia  

http://www.m m u.lv
/  

Training 
program 

4. Tailor 
e ducation and 
training offers  

30  Sam sung Digi 

Pass 

http://www.sam sun
gdigipass.ee/ee 

Training 
program 

4. Tailor 
e ducation and 
training offers  

31  AMETIC  ICT 

Profe ssionals 

http://ametic.es/es/
FTI  

Ne twork  / 
collaboratio
n 

4. Tailor 
e ducation and 
training offers  

32  Sk ills Plus 

33  INC oDe.2030 

https://www.k om pe
tansenorge.no/Engli
sh/Basic-
sk ills/Competencepl
us/ 

http://www.incode 2
030.gov.pt 

Support 
programme/
strate gy 

4. Tailor 
e ducation and 
training offers  

Support 
programme/
strate gy 

1. 
Stre ngthening 
e cosystems 

34  C ybe rvolunteers

: 
C ibe rvoluntarios 

https://www.cibe rv
oluntarios.org/es 

Ne twork  / 
collaboratio
n 

4. Ta ilor 
e ducation and 
training offers  

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

4. Prom ote existing blueprints for 
training for SMEs 

4. Innovate e ducational 
programmes (co-creation, 
badging) to stimulate 
collaboration betwe en SMEs and 
e ducation 

4. Stim ulate innovative voucher 
sche mes for fostering BIC skills 
de ve lopment that do not have a 
high burden (Go Digital Germany) 

4. Prom ote existing blueprints for 
training for SMEs 

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

4. Incre ase mobility of scarce  
e x perts (in Edu & Edu-Industry) 

165 

 
 
 
Good practices - 
various skills 
initiatives 

prom oting 
te chnological 
volunteering in 
Spain 

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

35  Sk illsfuture  

Singapore  

http://www.sk illsfut
ure .sg/AboutSkillsF
uture  

Support 
programme/
strate gy 

4. Tailor 
e ducation and 
training offers  

4. Incre ase funding for skills 
de ve lopment in SMEs  

36  Digital Skills and 
Jobs C oalition 
Ple dge Viewe r 

37  SMAR T071 

http://pledgeviewe r.eu 

1. 
Stre ngthening 
e cosystems 

1.  C re ated share d databases and 
tools to make information 
acce ssible to stakeholders 

https://www.e cono
m ie 071.nl/proje cten
/sm art071/ 

Support 
programme/
strate gy 

4. Tailor 
e ducation and 
training offers  

38  EC SO ’s 

Europe an 
Hum an 
R e sources 
Ne twork  for 
C ybe r 
(EHR 4C YBER) 
Task Force 

https://www.digitals
m e .eu/digital/uploa
ds/3rd-
W ork shop_2n-
ppt_EH4C YBER_pre
se ntation0802019.p
df 

Ne twork  / 
collaboratio
n 

4. Tailor 
e ducation and 
training offers  

39   BDVA Sk ills 

Task Force and 
the  BDVe Proje ct 

http://www.bdva.eu
/task -force-
ove rvie w 

Ne twork  / 
collaboratio
n 

1. 
Stre ngthening 
e cosystems 

Guide /toolb
ox  

1. 
Stre ngthening 
e cosystems 

40  “From  volume to 
value  The big 
data strategy" of 
Em ilia R omagna 

https://formazionel
avoro.regione.emilia
-rom agna.it/alta-
form azione-
rice rca/allegati/emili
a-rom agna-big-
data -
com m unity__we b.p
df/@@download/file
/EMILIA%20ROMAG
NA%20BIG%20DAT
A%20C OMMUNITY_
_W EB.pdf 

41  JADS MKB 

Datalab 

www.jadsm k bdatala
b.nl 

C ounselling  4. Tailor 

e ducation and 
training offers  

42  Digital 

C hampions BE 

www.digitalcham pio
ns.be 

Ne twork  / 
collaboratio
n 

1. 
Stre ngthening 
e cosystems 

4. Innovate e ducational 
programmes (co-creation, 
badging) to stimulate 
collaboration betwe en SMEs and 
e ducation 

4. Incre ase understanding of 
e ducation providers on h2 identify 
training needs, target groups & 
tailor offers 

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

4. Stim ulate internships to 
provide students with practical 
e x perience  and SMEs with 
pote ntial employees 

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

4. Prom ote existing blueprints for 
training for SMEs 

http://www.prom pt
e du.se/ 

Training 
program 

4. Tailor 
e ducation and 
training offers  

43  PR O MPT, 

Profe ssional 
Maste r in 
Software  
Engine ering 

44  C ybe r Sk ills 

Initiative (CSI) 

https://www.ictsk ill
ne t.ie /news/cyberse
curity-sk ills-
initiative-launch-at-
cybe rconf/ 

Ne twork  / 
collaboratio
n 

2. Support 
strate gic 
outlook 
de ve lopment  

2.  Stim ulate the development of 
national C ybersecurity 
fram ework s for SMEs  

45  SEnDIng 

http://sending-
proje ct.e u 

Training 
program 

4. Tailor 
e ducation and 
training offers  

4. Prom ote use of standards and 
fram ework s to incre ase uniformity 
in training courses 

166 

 
 
 
Good practices - 
various skills 
initiatives 

46  Mode rn Business 

Program 
(Hungary) 

www.vallalk ozzdigit
alisan.hu 

Typology 

Most relevant 
stream of 
roadmap 

Support 
programme/
strate gy 

2. Support 
strate gic 
outlook 
de ve lopment  

47  C ybe r R esilience 
C e ntre Brainport 

https://cwbrainport.
nl/ 

Ne twork  / 
collaboratio
n 

2. Support 
strate gic 
outlook 
de ve lopment  

48  Innvation 

vouche rs Finland 

https://www.busine
ssfinland.fi/en/for-
finnish-
customers/services/
funding/research-
and-
de ve lopment/innova
tion-voucher/ 

Training 
program 

4. Tailor 
e ducation and 
training offers  

Most relevant sub-goal of that 
stream 

2.  Support organisations, 
initiatives and platforms tht foster 
collaboration and knowle dge 
sharing amongcompany 
m anagers/owne rs for adoption of 
BIC  te chnologies and new 
business models (e.g. business 
clubs/associations/clusters, buddy 
support schemes, training 
programs for a group of company 
m anagers) 

2.  Support organisations , 
initiatives and platforms tht foster 
collaboration and knowle dge 
sharing amongcompany 
m anagers/owne rs for adoption of 
BIC  te chnologies and new 
business models (e.g. business 
clubs/associations/clusters, buddy 
support schemes, training 
programs for a group of company 
m anagers) 

4. Incre ase funding for skills 
de ve lopment in SMEs  

49  VO IC E C yber 

se curity platform 

https://voice-
e v.org/wissensplattf
orm / 

Support 
programme/
strate gy 

3. Stre ngthen 
structure d skills 
de ve lopment  

3. R e search the possibility of 
quality labels so SMEs re cognise 
value  of a training   

50  C ybe r security 
R angers (jpn) 

https://www.m e ti.g
o.jp/e nglish/press/2
019/0611_002.html 

C ounselling  2. Support 

strate gic 
outlook 
de ve lopment  

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

51  C ybe r Ne w York 
C ity (C yber NYC) 

https://www.cybe r-
nyc.com / 

Support 
programme/
strate gy 

1. 
Stre ngthening 
e cosystems 

1.  Stim ulate collaboration 
be twe e n hubs and e ducation 
syste m to better tailor to needs 

52  Innovation 

vouche rs 
Fle voland 

https://voucherrege
lingflevoland.nl/ 

Training 
program 

4. Tailor 
e ducation and 
training offers  

4. Incre ase funding for skills 
de ve lopment in SMEs 

Frameworks 

Typology   Most relevant 

stream of 
roadmap 

Most relevant sub-goal of that 
stream 

1  DigC omp 

https://ec.europa.e
u/jrc/e n/digcomp 

http://ictprofessiona
lism .eu 

https://makesmedig
ital.e u 

2 

IT 
Profe ssionalism: 
Digiframe 

3  m ak es_me 
</digital> 
(Digital Skills: 
Ne w Profe ssions, 
Ne w Educational 
Me thods, Ne w 
Jobs - 
Sm art2016/1006
) 

Fram e work  4. Tailor 

e ducation and 
training offers  

Fram e work  4. Tailor 

e ducation and 
training offers  

Fram e work  4. Tailor 

e ducation and 
training offers  

4. Prom ote use of standards and 
fram ework s to incre ase uniformity 
in training courses 

4. Prom ote use of standards and 
fram ework s to incre ase uniformity 
in training courses 

4. Incre ase funding for skills 
de ve lopment in SMEs  

167 

 
 
 
  
  
  
  
  
  
  
Good practices - 
various skills 
initiatives 

4  EDISO N Data 
Scie nce  
Fram e work 

5  A lightwe ight 
C ybe rsecurity 
fram ework  for 
thorough 
prote ction 

6  National 

Initiative for 
C ybe rsecurity 
Education 
(NIC E) 

https://ec.europa.e
u/digital-single-
m ark et/en/news/edi
son-training-
scie ntists-today-
and-tomorrow 

https://smesec.eu/i
nde x.html  

Typology 

Most relevant 
stream of 
roadmap 

Fram e work  4. Tailor 

e ducation and 
training offers  

Most relevant sub-goal of that 
stream 

4. Prom ote use of standards and 
fram ework s to incre ase uniformity 
in training courses 

Fram e work  4. Tailor 

e ducation and 
training offers  

4. Prom ote use of standards and 
fram ework s to incre ase uniformity 
in training cours es 

https://www.nist.go
v/itl/applied-
cybe rse curity/nice  

Fram e work  3. Stre ngthen 

structure d skills 
de ve lopment  

Self-assesments 

Typology   Most relevant 

1  R e adiness for 

Innovation Self-
assessment Tool  

http://www.sircon.c
o.uk /afrcinnovation
assessment/ 

2 

Finding your 
C ybe rsecurity 
C are er Path 

3  SME C loud 

Se curity Tool 

4  Entre prises, les 
clé s d'une 
application 
ré ussie du GDPR 

5  C ybe r R isico 

Scan 

https://www.e dx .or
g/course/finding-
cybe rse curity-
care e r-path-
uwashingtonx-
cyb004x 

https://www.e nisa.e
uropa.eu/topics/clou
d-and-big-
data/cloud-
se curity/security-
for-smes/sme-
guide-tool  

http://www.cigre f.fr
/wp/wp-
conte nt/uploads/20
17/11/CIGREF-GT-
AFAI-C IGREF-TIF-
Donnees-
Pe rsonnelles-et-
Syste m es-d-
Informations-GDPR-
2017.pdf 

https://veiligzakelijk
inte rne tten.cybersta
tus.nl/  

Se lf-
assesments 

stream of 
roadmap 

2. Support 
strate gic 
outlook 
de ve lopment  

Se lf-
assesments 

2. Support 
strate gic 
outlook 
de ve lopment  

Se lf-
assesments 

2. Support 
strate gic 
outlook 
de ve lopment  

Se lf-
assesments 

2. Support 
strate gic 
outlook 
de ve lopment  

Se lf-
assesments 

2. Support 
strate gic 
outlook 
de ve lopment  

6  C ybe rsecurity 

C om petence 
C e nter 

https://voice-
e v.org/wissensplattf
orm /  

Se lf-
assesments 

2. Support 
strate gic 
outlook 
de ve lopment  

3. Prom ote blueprints, practical 
fram ework s and tools that support 
SMEs to build a smart (HR) 
strate gy (incl. tools to support 
re cruitm ent, hiring, dvlpment) 

Most relevant sub-goal of that 
stream 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

168 

 
 
 
  
  
  
  
  
  
  
  
  
  
  
  
  
Good practices - 
various skills 
initiatives 

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

Guides & others 

Typology   Most relevant 

stream of 
roadmap 

Most relevant sub-goal of that 
stream 

1  Avoiding skills 
shortages and 
m ismatches – 
Ne w strate gies 
for m e eting 
com panies’ 
sk illed labour 
ne e ds 

2  EU GDPR  

C he cklist for 
C orporate 
Im plementation 

3  C om munity 

Boost EU 
Face book 

4  Digital Schools 
of Distinction in 
Ire land 

5  Digital skills gap 

in Europe  

https://www.bm wi.
de /R edaktion/EN/Pu
blik ationen/avoiding
-sk ills-shortages-
and-
m ismatches.pdf?__
blob=publicationFile
&v=2  

http://www.bm wi.d
e /R edaktion/DE/Pub
lik ationen/Digitale-
W e lt/datenschutzgr
undve rordnung.html 

https://newsroom.f
b.com /news/2018/0
1/com munity-boost-
e urope/ 

http://www.digitalsc
hools.ie/ 

Support 
programme/
strate gy 

4. Tailor 
e ducation and 
training offers  

4. Stim ulate internships to 
provide students with practical 
e x perience  and SMEs with 
pote ntial employees 

Guide / 
toolbox 

3. Stre ngthen 
structure d skills 
de ve lopment  

3. Facilitate self-assessments to 
e nable SMEs to detect skills gap in 
the ir organisation 

Training 
program 

4. Tailor 
e ducation and 
training offers  

4. Prom ote existing blueprints for 
training for SMEs 

Ne twork  / 
collaboratio
n 

4. Tailor 
e ducation and 
training offers  

http://ec.europa.eu
/ne wsroom/dae/doc
um e nt.cfm?doc_id=
47880  

Guide /toolb
ox  

2. Support 
strate gic 
outlook 
de ve lopment  

2.  De sign a matchmking platform 
that links technology solutions in 
the  are a of BIC with SME needs  

6 

The  Additional 
Q ualifications for 
Digital 
C om petences 
Programme 

https://media.nesta
.org.uk/documents/
R e adie_Digital_Skill
s_booklet_online.pd
f 

Support 
programme/
strate gy 

4. Tailor 
e ducation and 
training offers  

4. Prom ote existing blueprints for 
training for SMEs 

7  C ontinuous 
Profe ssional 
De ve lopment for 
IC T&L in Ire land 

8  Hum an Capital 
Age nda ICT 

9  Data P itch 

10  C om mit2Data 

https://www.ics.ie /
ne ws/what-is-
continuous-
profe ssional-
de ve lopment-  

https://www.bm wi.
de /R edaktion/EN/Pu
blik ationen/avoiding
-sk ills-shortages-
and-
m ismatches.pdf?__
blob=publicationFile
&v=2  

https://datapitch.eu
/  

https://www.dutchd
igitaldelta.nl/upload
s/pdf/Commit2data-
DDD-Flye r-
nove mber-
17_171116_100106
.pdf  

Training 
program 

3. Stre ngthen 
structure d skills 
de ve lopment  

3. De cre ase dependency on 
e x te rnal providers 

Support 
programme/
strate gy 

3. Stre ngthen 
structure d skills 
de ve lopment  

3. Monitor m arket trends to 
inform  (esp. IT-using) SMEs 

Support 
programme/
strate gy 

1. 
Stre ngthening 
e cosystems 

1.  De ve lop policies which help 
m obilising 
acce le rators/downstre am actors  

Support 
programme/
strate gy 

2. Support 
strate gic 
outlook 
de ve lopment  

2.  Stim ulate collaborative 
proje cts betwe en SMEs and 
re se archers 

11  IT in Bank, in 

Poland 

http://itnabank.pl/   Training 
program 

12  C ode for All 

http://www.academ
iade codigo.org  

Training 
program 

3. Stre ngthen 
structure d skills 
de ve lopment  

3. R e search how care er switche s 
can be  facilitated to increase the 
tale nt pool (esp. in cyber security) 
and scale good practices  

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

169 

 
 
 
  
  
Good practices - 
various skills 
initiatives 

13  O pe ning 

O pportunities in 
R om ania 

Typology 

http://openingoppor
tunitie s.ro/  

Training 
program 

14  Social Builder 

https://socialbuilder
.org  

Training 
program 

Most relevant 
stream of 
roadmap 

4. Tailor 
e ducation and 
training offers  

4. Tailor 
e ducation and 
training offers  

15  Find “hidden” 

jobs among 
SMEs – m atch 
with job se ekers 

16  R e thinking 
Education 

https://www.bm wi.
de /R edaktion/EN/Pu
blik ationen/avoiding
-sk ills-shortages-
and-
m ismatches.pdf?__
blob=publicationFile
&v=2  

https://europa.eu/r
apid/press-
re le ase_IP-12-
1233_e n.htm  

Ne twork  / 
collaboratio
n 

2. Support 
strate gic 
outlook 
de ve lopment  

Support 
programme/
strate gy 

4. Tailor 
e ducation and 
training offers  

17  Digilyft Kick start  https://hellofuture.o

C ounselling  4. Tailor 

rg/case/digilyft/  

18  Good Things 

Foundation 

https://www.goodth
ingsfoundation.org 

Ne twork  / 
collaboratio
n 

e ducation and 
training offers  

2. Support 
strate gic 
outlook 
de ve lopment  

Most relevant sub-goal of that 
stream 

4. Innovate e ducational 
programmes (co-creation, 
badging) to stimulate 
collaboration betwe en SMEs and 
e ducation 

4. Innovate e ducational 
programmes (co-creation, 
badging) to stimulate 
collaboration betwe en SMEs and 
e ducation 

2.  De sign a matchmking platform 
that links technology solutions in 
the  are a of BIC with SME needs  

4. Incre ase understanding of 
e ducation providers on h2 identify 
training needs, target groups & 
tailor offers 

4. Incre ase funding for skills 
de ve lopment in SMEs  

2.  Support organisations, 
initiatives and platforms tht foster 
collaboration and knowle dge 
sharing amongcompany 
m anagers/owne rs for adoption of 
BIC  te chnologies and new 
business models (e.g. business 
clubs/associations/clusters, buddy 
support schemes, training 
programs for a group of company 
m anagers) 

19  O AK3 Academy  http://www.oak 3.be   Training 
program 

4. Tailor 
e ducation and 
training offers  

4. Stim ulate innovative voucher 
sche mes for fostering BIC skills 
de ve lopment that do not have a 
high burden (Go Digital Germany) 

Training 
program 

4. Tailor 
e ducation and 
training offers  

4. Prom ote existing blueprints for 
training for SMEs 

20  BSI Group BIM  https://www.bsigro
up.com/en-GB/our-
se rvice s/training-
course s/BIM-
training-courses/  

21  Unionlearn 

https://www.unionl
e arn.org.uk  

Ne twork  / 
collaboratio
n 

2. Support 
strate gic 
outlook 
de ve lopment  

2.  Involve intermediaries in an 
SME that can act as advisors for 
SME m anagers/owne rs in 
adoption of BIC te chnologies (e.g. 
accountants, insurance 
com panies, ICT interns) 

1.  De ve lop policies & funding 
programmes that help to support 
SME com m unities, network s and 
e cosystems (clusters), such as 
Digital Innovation Hubs 

2.  De sign a matchmking platform 
that links technology solutions in 
the  are a of BIC with SME needs  

22  Digital 

Innovation Hubs 

http://s3platform.jr
c.e c.e uropa.eu/digit
al-innovation-hubs 

Ne twork  / 
collaboratio
n 

1. 
Stre ngthening 
e cosystems 

23  LEAD-IT 

www.le ad-it.be  

C ounselling  2. Support 

strate gic 
outlook 
de ve lopment  

24  IoT De vice 

Se curity Lab 

https://www.digitals
m e .eu/digital/uploa
ds/2nd-
W ork shop_Skills-
for-SMEs_3rd-

Ne twork  / 
collaboratio
n 

4. Tailor 
e ducation and 
training offers  

4. Inve st in facilities to support 
training programmes (eg labs) 

170 

 
 
 
Good practices - 
various skills 
initiatives 

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

ppt_Khani_IoT_Sec
_lab_Short1_7-Dec-
18.pdf 

25  Southampton 
Data Scie nce 
Acade my 

26  Knowle dge 
Transfer 
Partne rships for 
data science in 
SMEs 

27  Digital C ities 

https://southampto
ndata.science/ 

Training 
program 

1. 
Stre ngthening 
e cosystems 

4. Incre ase funding for skills 
de ve lopment in SMEs  

https://www.ncl.ac.
uk /m aths-
physics/business/kt
p/ 

Support 
programme/
strate gy 

4. Tailor 
e ducation and 
training offers  

4. Prom ote existing blueprints for 
training for SMEs 

https://www.de lle m
c.com /en-
us/industry/digital-
citie s/index.htm  

Guide /toolb
ox  

1. 
Stre ngthening 
e cosystems 

1.  Initiate EU and national 
programs that facilitate 
k nowle dge sharing and cre ate 
platforms whe re 3rd parties and 
SMEs can acce ss re levant 
m ate rials (single multi-sector 
portal at EU level) 

28  C ybe r W elfare 

https://www.cybe rw
e lfare.it/ 

Guide /toolb
ox  

1. 
Stre ngthening 
e cosystems 

1.  C re ated share d databases and 
tools to make information 
acce ssible to stakeholders 

29  Digital Learning 

C e ntre 

http://www.softwar
e m anager.eu/  

Training 
program 

3. Stre ngthen 
structure d skills 
de ve lopment  

30  C ybe r R eady 

https://certification.
com ptia.org/why-
ce rtify/cyber-ready 

Training 
program 

4. Tailor 
e ducation and 
training offers  

31  IT-R eady 

https://www.cre atin
gitfutures.org/ 

C ounselling  3. Stre ngthen 

structure d skills 
de ve lopment  

32  Datafabriek/ The 
Data Factory  

33  Bronne n: wie  

he lpt mij ve rder 
m e t data? 

https://onlinetouch.
nl/villay/ingovernm
e nt-04-
2018/16;Essay#/16 
(dutch re ad) 

https://www.k vk .nl/
download/20173047
_invulbare-
pdf_databronnen_1
71215-
proe f2_tcm 109-
452575.pdf  

Training 
program 

4. Tailor 
e ducation and 
training offers  

Ne twork  / 
collaboratio
n 

2. Support 
strate gic 
outlook 
de ve lopment  

34  Big data: 

groe ikansen 
voor 
onde rnemers 

Guide / 
toolbox 

https://www.k vk .nl/
download/Whitepap
e r-Big-
Data_tcm 109-
408602.pdf  

2. Support 
strate gic 
outlook 
de ve lopment  

35  Be st Practices 
for Statistical 
Data Analysis  

http://data.library.v
irginia.edu/statlab/b
e st-practices-for-
statistical-data-
analysis/  

Guide / 
toolbox 

4. Tailor 
e ducation and 
training offers  

3. Prom ote blueprints, practical 
fram ework s and tools that support 
SMEs to build a smart (HR) 
strate gy (incl. tools to support 
re cruitm ent, hiring, dvlpment) 

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

3. R e search how care er switche s 
can be  facilitated to increase the 
tale nt pool (esp. in cyber security) 
and scale good practices  

4. Inve st in facilities to  support 
training programmes (eg labs) 

2.  Support organisations, 
initiatives and platforms tht foster 
collaboration and knowle dge 
sha ring amongcompany 
m anagers/owne rs for adoption of 
BIC  te chnologies and new 
business models (e.g. business 
clubs/associations/clusters, buddy 
support schemes, training 
programs for a group of company 
m anagers) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

4. Inte grate BIC modules in non-
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

36  Training material 
ope n data 

https://www.e urope
andataportal.eu/en/

Guide / 
toolbox 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 

171 

 
 
 
Good practices - 
various skills 
initiatives 

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

re sources/more-
training-materials 

37  E-Book  Big Data  http://kvk.instantm

agazine.com/e-
zine s-kvk/big-data 

Guide  
/toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

38  Digital Journey 

Track e r 

https://www.sirris.b
e /digitaljourneytrac
k e r 

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

Guide  
/toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

fre e , to incre ase potential talent 
pool 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

39  Informationspool  https://www.allianz

-fue r-
cybe rsicherheit.de/A
C S/DE/Informations
pool/_function/Infor
m ationspool_Formul
ar.htm l?nn=996065
4  

https://www.allianz
-fue r-
cybe rsicherheit.de/A
C S/DE/_/partner/Pa
rtne rbe itrag_ISPs_G
e faehrdungsmatrix_
2016.pdf?__blob=p
ublicationFile&v=4 

https://www.e nisa.e
uropa.eu/publicatio
ns/cloud-security-
guide-for-smes  

40  Konsolidierte 

Ge fährdungsmat
rix  m it 
R isik obewe rtung 
2016 

41  C loud Se curity 
Guide  for SMEs 

42  SME Guide  for 

the  
Im plementation 
of ISO /IEC 
27001 on 
Information 
Se curity 
Management 

43  Be sche rm je 
be drijf te gen 
cybe rcrim e! 

https://www.digitals
m e .eu/digital/uploa
ds/SME-Guide-for-
the -
im plementation-of-
ISO IEC-27001-on-
inform ation-
se curity-
m anagement.pdf  

https://veiliginterne
tte n.nl/bescherm-
je -be drijf-tegen-
cybe rcrim e/  

44  Digitale fraude: 
pre ve ntie door 
m k b kan beter 

45  De  5 

basisprincipes 
van ve ilig 
digitaal 
onde rnemen 

https://www.k vk .nl/
download/Infograph
ic%20Pre ventie%20
door%20het%20mk
b%20te gen%20digit
ale%20fraude%20d
e finitief_tcm 109-
449038.pdf  

https://www.digitalt
rustce nter.nl/de-5-
basisprincipes-van-
ve ilig-digitaal-
onde rnemen 

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

172 

 
 
 
Good practices - 
various skills 
initiatives 

Typology 

46  C ybe r R esilience 

Lab 

https://cyre slab.org
/  

Training 
program 

Most relevant 
stream of 
roadmap 

4. Tailor 
e ducation and 
training offers  

47  Privacy in 

Te chnology: 
Standards and 
Practice s for 
Engine ers and 
Se curity and IT 

48  Privacy Program 
Management 

https://my.iapp.org
/NC __Product?id=a
191a000000QL2eAA
G  

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

https://iapp.org/res
ource s/article/privac
y-program-
m anagement/  

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

49  Practitioner's 

toolk it for PES 
Building C areer 
Guidance  and 
Life long Learning 

50  Publicatie 

Inte rnet of 
Things 

http://ec.europa.eu
/social/main.jsp?lan
gId=e n&catId=89&
ne wsId=9060&furth
e rNe ws=ye s  

https://www.k vk .nl/
download/KvK%20I
oT%20Publicatie_tc
m 109-399524.pdf 

51  Inte rnet of 
Things: 
k ansrichtingen 

52  Businesskansen 

m e t IoT 

https://www.k vk .nl/
download/KvK%20I
nte rne t%20of%20T
hings%20-
%20A3%20we rkbla
de n_tcm 109-
399525.pdf  

https://kvk.instant
m agazine.com/e-
zine s-kvk/internet-
of-things# 

Guide  
/toolbox 

3. Stre ngthen 
structure d skills 
de ve lopment  

Guide  
/toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

Guide  
/toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

Guide / 
toolbox 

2. Support 
strate gic 
outlook 
de ve lopment  

53  Business is 

Gre at Britain 

http://www.gre atbu
sine ss.gov.uk/domo
re online/  

Guide /to  
olbox 

2. Support 
strate gic 
outlook 
de ve lopment  

Most relevant sub-goal of that 
stream 

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

3. Prom ote blueprints, practical 
fram ework s and tools that support 
SMEs to build a smart (HR) 
strate gy (incl. tools to support 
re cruitm ent, hiring, dvlpment) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

2.  Stim ulate e xisting and new 
policy initatives that inform SME 
m anagers/owne rs about the 
pote ntial of BIC technologies and 
e ncourage innovation (e.g. 
programmes, campaigns, e vents) 

54  C loud W atch 

HUB 

http://www.cloudwa
tchhub.eu/SMEs  

Guide /to  
olbox 

1. 
Stre ngthening 
e cosystems 

1.  C re ated share d databases and 
tools to make information 
acce ssible to stakeholders 

Massive Open 
Online Courses 
(MOOCs) 

1  Udacity & 

Google 
De ve loper 
Scholarships 
C hallenge in the 
EU 

Typology   Most relevant 

MO O C 

https://blog.udacity
.com /2017/09/anno
uncing-60000-
challe nge-
scholarships-
udacity-google.html  

stream of 
roadmap 

2. Support 
strate gic 
outlook 
de ve lopment  

Most relevant sub-goal of that 
stream 

2.  Support organisations, 
initiatives and platforms tht foster 
collaboration and knowle dge 
sharing amongcompany 
m anagers/owne rs for adoption of 
BIC  te chnologies and new 
business models (e.g. business 
clubs/associations/clusters, buddy 
support schemes, training 
programs for a group of company 
m anagers) 

173 

 
 
 
  
  
  
  
  
  
  
Good practices - 
various skills 
initiatives 

2  Sk illm an 

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

http://learn.skillma
n.e u  

MO O C 

1. 
Stre ngthening 
e cosystems 

1.  C re ated share d databases and 
tools to make information 
acce ssible to stakeholders 

3  Analytics 
Acade my 
(Google) 

https://analytics.go
ogle .com/analytics/
academy/  

MO O C 

4. Tailor 
e ducation and 
training offers  

4  Google Growth 
Engine  for 
Europe  

https://grow.google
/intl/e urope  

MO O C 

2. Support 
strate gic 
outlook 
de ve lopment  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

2.  Support organisations, 
initiatives and platforms tht foster 
collaboration and knowle dge 
sharing amongcompany 
m anagers/owne rs for adoption of 
BIC  te chnologies and new 
business models (e.g. business 
clubs/associations/clusters, buddy 
support schemes, training 
programs for a group of company 
m anagers) 

5  C ybe rsecurity for 

Sm all 
Businesses 

6 

Incibe  

7  Google Digital 

Garage 

8  Studyportals 

https://www.sba.go
v/course /cybersecur
ity-sm all-
businesses/  

https://translate.go
ogle .com/translate?
hl=nl&sl=e s&u=http
s://www.incibe .e s/f
orm acion/cibersegur
idad-para-
m icropymes-y-
autonomos&prev=s
e arch  

https://learndigital.
withgoogle.com/digi
tale we rk plaats 

https://www.shortc
ourse sportal.com/se
arch/#q=di-282|lv-
short|tc-
EUR &start=0&order
=re le vance  

MO O C 

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

MO O C 

MO O C 

1. 
Stre ngthening 
e cosystems 

1.  C re ated share d databases and 
tools to make information 
acce ssible to stakeholders 

1. 
Stre ngthening 
e cosystems 

1.  C re ated share d databases and 
tools to make information 
acce ssible to stakeholders 

9 

LoR a Academy  https://lora-

MO O C 

10  Aan de  slag met 

big data. Denk 
groot, start k lein 

11  Microsoft 

Introduction to 
Big Data  

12  Big Data 

C apstone Project  

de ve lopers.semtech
.com /resources/lora
wan-academy/  

http://bigdata.movi
e trader.tv/clipcard2
/bigdatamooc?hd=tr
ue  

https://www.e dx .or
g/course/microsoft-
profe ssional-
program-big-data-
m icrosoft-dat229x 

https://www.e dx .or
g/course/big-data-
capstone-project-
ade laidex-datacapx 

13  Big Data 

Fundamentals 

14  Microsoft 

Profe ssional 

https://www.e dx .or
g/course/big-data-
fundamentals-
ade laidex-bigdatax 

https://www.e dx .or
g/course/microsoft-
profe ssional-

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Prom ote existing blueprints for 
training for SMEs 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 

174 

 
 
 
Good practices - 
various skills 
initiatives 

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

C apstone: Big 
Data  

capstone-big-data-
m icrosoft-dat230x-0 

fre e , to incre ase potential talent 
pool 

15  Knowle dge 

Management 
and Big Data in 
Business  

16  Big Data 

Analytics Using 
Spark   

17  Big Data 

Analytics  

18  SLQ  Tutorial 

19  Analytics 

De cision Making  

20  Introduction to 
Data Analytics 
for Managers 

21  Introduction to 

Data Analysis 

22  Intro to Data 
Scie nce  

23  A/B Te sting by 

Google 

24  Em e rging 

Te chnologies: 
from  
Sm artphones to 
IoT to Big Data 
Spe cialization 

https://www.e dx .or
g/course/knowledge
-m anagement-big-
data -business-
hk polyux-ise101x-3  

https://www.e dx .or
g/course/big-data-
analytics-using-
spark -uc-san-
die gox-dse230x 

https://www.e dx .or
g/course/big-data-
analytics-adelaidex-
analyticsx  

https://www.w3sch
ools.com/sql/default
.asp  

https://www.e dx .or
g/course/analytics-
de cision-making-
babsonx-bpet-statx-
0  

https://www.e dx .or
g/course/introductio
n-data-analytics-
m anagers-
m ichiganx-ds120x 

https://eu.udacity.c
om /course/intro-to-
data -analysis--
ud170  

https://eu.udacity.c
om /course/intro-to-
data -science--
ud359  

https://eu.udacity.c
om /course/ab-
te sting--ud257 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non-
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

https://www.course
ra.org/specialization
s/e merging-
te chnologies 

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

25  MicroMasters Big 

Data  

https://www.e dx .or
g/m icromasters/big-
data  

MO O C 

4. Tailor 
e ducation and 
training offers  

26  Data 

W are housing for 
Business 
Inte lligence 
Spe cialization 

27  Le arn Python 

https://www.course
ra.org/specialization
s/data-ware housing 

MO O C 

4. Tailor 
e ducation and 
training offers  

https://www.code ca
de m y.com/learn/lea
rn-python 

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

175 

 
 
 
Good practices - 
various skills 
initiatives 

Typology 

28  Ex ploratory Data 

Analysis  

https://www.course
ra.org/learn/explora
tory-data-analysis  

MO O C 

Most relevant 
stream of 
roadmap 

4. Tailor 
e ducation and 
training offers  

29  Visualize 

Business Data 
with Tableau  

https://www.course
ra.org/specialization
s/data-visualization  

MO O C 

4. Tailor 
e ducation and 
training offers  

30  Data 

Visualization  

https://www.course
ra.org/learn/datavis
ualization 

MO O C 

4. Tailor 
e ducation and 
training offers  

Most relevant sub-goal of that 
stream 

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

31  Data Scie nce for 
Ex e cutives  

32  Data Scie nce 
Spe cialization 

33  Applie d Data 
Scie nce  
Spe cialization 

34  Be com e a Data 

Analyst 

35  Pre dictive 

Analytics for 
Business 

36  C ybe rsecurity 
Fundamentals 

37  Information 
Se curity 
Management 

38  C ybe rsecurity 

R isk  
Management 

39  C ybe rsecurity 
C apstone  

40  Introduction to 

C ybe rsecurity 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

https://www.e dx .or
g/professional-
ce rtificate/data-
scie nce -executives 

https://www.course
ra.org/specialization
s/jhu-data-science 

https://www.course
ra.org/specialization
s/applied-data-
scie nce  

https://eu.udacity.c
om /course/data-
analyst-
nanodegree--nd002 

https://eu.udacity.c
om /course/predictiv
e -analytics-for-
business-
nanodegree--nd008 

https://www.e dx .or
g/course/cybersecur
ity-fundamentals-
ritx -cybe r501x-1 

http://www.e cfallian
ce -
training.org/course/i
nde x.php?categoryi
d=5&lang=nl  

https://www.e dx .or
g/course/cybersecur
ity-risk -
m anagement-ritx-
cybe r503x 

https://www.e dx .or
g/course/rit-
cybe rse curity-
capstone 

https://www.e dx .or
g/course/introductio
n-cybe rsecurity-
uwashingtonx-
cyb001x 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Tailor 
e ducation and 
training offers  

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

41  C ybe rsecurity 
Basics – a 
Hands-on 
Approach  

https://www.e dx .or
g/course/cyber-
se curity-basics-a-
hands-on-approach  

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

42  Building a 

C ybe rsecurity 
Toolkit  

https://www.e dx .or
g/course/building-
cybe rse curity-

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 

176 

 
 
 
Good practices - 
various skills 
initiatives 

Typology 

Most relevant 
stream of 
roadmap 

Most relevant sub-goal of that 
stream 

47  C ybe rsecurity 
Spe cialization 

https://www.course
ra.org/specialization
s/cybe r-security 

MO O C 

4. Tailor 
e ducation and 
training offers  

toolk it-
uwashingtonx-
cyb003x 

https://www.future l
e arn.com/courses/in
troduction-to-cyber-
se curity/9  

https://www.incibe .
e s/formacion/cibers
e guridad-para-
m icropymes-y-
autonomos 

http://scholarship-
positions.com/open-
unive rsity-fre e-
online-course-on-
cybe r-
se curity/2015/08/0
5/  

https://www.course
ra.org/learn/cyber-
se curity-domain 

43  Introduction 

to C ybe rsecurity 

44  C ibe rseguridad 

para 
m icropymes y 
autónomos 

45  C ybe rsecurity 

46  C ybe rsecurity 

and its Ten 
Dom ains 

48  Esse ntials of 

C ybe rsecurity 

49  The  Business of 

C ybe rsecurity 
C apstone 

50  MicroMasters 

C ybe rsecurity  

51  C ybe rsecurity 

De ve loping 
Program for your 
Business 
Spe cialization 

52  C ybe rsecurity 
Mobility  

https://www.e dx .or
g/professional-
ce rtificate/uwashing
tonx -essentials-
cybe rse curity  

https://www.course
ra.org/learn/busines
s-of-cybersecurity-
capstone 

https://www.e dx .or
g/m icromasters/ritx
-cybe rsecurity  

https://www.course
ra.org/specialization
s/cybe rsecurity-
de ve loping-
program-for-
business 

https://www.course
ra.org/learn/cyberse
curity-m obility# 

programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

MO O C 

MO O C 

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

MO O C 

4. Tailor 
e ducation and 
training offers  

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

MO O C 

MO O C 

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

53  Ne twork  
Se curity  

http://online.stanfor
d.e du/course/netwo
rk -se curity 

MO O C 

4. Tailor 
e ducation and 
training offers  

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

4. Stim ulate development of 
practical cybersecurity training 
programmes (eg in VET), SMEs’ 
ne e ds based, using labs  

54  Ne twork  

Fore nsics 
Training 

https://www.e nisa.e
uropa.eu/topics/trai
nings-for-
cybe rse curity-
spe cialists/online-
training-
m ate rial/technical-
ope rational#buildin
g  

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

177 

 
 
 
Good practices - 
various skills 
initiatives 

55  Enabling 

Te chnologies for 
Data Scie nce 
and Analytics: 
The  Internet of 
Things 

56  Ge tting Started 
with the  Internet 
of Things  

57  The  Internet of 

Things  

58  De ve loping IoT 

Solutions with 
Azure  IoT  

59  Fog Ne twork s 

and the Internet 
of Things  

60  Inte rnet of 
Things: 
R oadmap to a 
C onnected World 

https://www.e dx .or
g/course/enabling-
te chnologies-data-
scie nce -columbiax-
ds103x-1 

https://www.e dx .or
g/course/getting-
starte d-with-the-
inte rne t-of-things-
iot-4  

https://www.class -
ce ntral.com/course/
future learn-the-
inte rne t-of-things-
3820  

https://www.e dx .or
g/course/developing
-iot-solutions-azure-
iot-m icrosoft-
de v225x-0 

https://www.class -
ce ntral.com/mooc/2
731/coursera-fog-
ne twork s-and-the-
inte rne t-of-things 

https://mitxpro.mit.
e du/courses/course-
v1:MITProfessionalX
+IO Tx+2016_T2/ab
out 

Typology 

MO O C 

Most relevant 
stream of 
roadmap 

4. Tailor 
e ducation and 
training offers  

Most relevant sub-goal of that 
stream 

4. Inte grate BIC modules in non-
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

61  Inte rnet of 
Things 
Spe cialization 

https://www.course
ra.org/specialization
s/inte rnet-of-things  

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

62  A De ve loper's 

Guide  to the 
Inte rnet of 
Things 

63  An Introduction 
to Programming 
for the  Internet 
of Things  

64  Software  

Archite cture  for 
the  Internet of 
Things  

65  Em be dded 

Hardware  and 
O pe rating 
Syste m s  

66  W ire le ss 

C om munities 
Em e rging 
Te chnologies  

67  C ybe rsecurity 

and the Internet 
of Things 

https://www.m ooc-
list.com/course/dev
e lopers-guide-
inte rne t-things-iot-
course ra 

https://www.course
ra.org/specialization
s/iot 

https://www.course
ra.org/learn/iot-
software -
archite cture 

https://www.course
ra.org/learn/embed
de d-operating-
syste m  

https://www.course
ra.org/learn/wire les
s-communication-
te chnologies 

https://www.course
ra.org/learn/iot-
cybe r-security 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

MO O C 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non-
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Tailor 
e ducation and 
training offers  

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

4. Inte grate BIC modules in non -
te ch curricula, even offer it for 
fre e , to incre ase potential talent 
pool 

178 

68  Digital Business 
Acade my 

https://digitalbusine
ssacademy.technati
on.io/ 

MO O C 

4. Tailor 
e ducation and 
training offers  

 
 
 
179 

 
 
 
 
 
APPENDIX  D: DETAILED  ASSESSMENT OF THE EMPIRICA 
APPROACH 
The table below summarizes the Empirica framework for e-Skills focused on ICT, the type 
of indicators collected and the considerations in light of our proposed monitoring 
mechanism. 

A ssigned 
macr0-area 

Indicator 
collected 
Empirica/IDC 

Considerations in 
comparison with the 
proposed monitoring 
mechanisms for ICT 

Extendibility 
to IoT, Big 
Data, and 
Cybersecurity 

A ctions/suggestions 

SUPPLY 

Labour  

IC T HE 
graduates 

Training 

IC T vocational 
training 
graduates 

Data source not 
m e ntioned.   

Corresponding 
indicators in the 
proposed monitoring 
framework: Enrolment 
by fie ld % and Graduates 
by fie ld % 

Corresponding 
indicators in the 
proposed monitoring 
framework: Main skills 
targe ted by C VT courses 
(% e nte rprises) 

Ne w data to be 
colle cte d 

Sam e  angle 
approached by our 
fram ework  

Ne w data to be 
colle cte d 

Sam e  angle 
approached by our 
fram ework  

Labour  

STEM (scie nce, 
te chnology, 
e ngineering, 
m athematics) 
e ntrie s 

Corresponding 
indicators in the 
proposed monitoring 
framework: Not 
considered in our 
fram ework . 

Too broad to be 
adapted to the 
thre e  areas. 

C ould be included for 
IC T 

Labour 
(inte rnal 
m obility)  

Late ral e ntries 

Labour  

C ate gory change 

Data source: not 
available; assumed 
e stim ated. 

Missing  information on 
late ral entry definition 
spe cification: i.e. Does it 
cove r passing from a 
non-ICT department to 
an IC T department? 

Corresponding 
indicators in the 
proposed monitoring 
framework: Not 
considered in our 
fram ework .  

Tim e -dynamic indicator 

Data source: not 
available.  

Missing  information on 
de finition specification 
with re fe re nce to 
“cate gory”. 

Corresponding 
indicators in the 
proposed monitoring 
framework: Not 

De pe nding on 
data source .  

Ex pe cte d novel 
work  to be  
done  for data 
colle ction.  

Inte re sting indicator 
about internal 
m obility, relevant for 
SMEs, howe ver, novel 
work  to be  done for 
data collection. 

More  
inform ation is 
ne e ded to 
assess.  

Ex pe cte d novel 
work  to be  
done  for data 
colle ction. 

Inte re sting indicator, 
howe ve r, novel work  
to be  done for data 
colle ction. 

180 

 
 
A ssigned 
macr0-area 

Indicator 
collected 
Empirica/IDC 

Considerations in 
comparison with the 
proposed monitoring 
mechanisms for ICT 

Extendibility 
to IoT, Big 
Data, and 
Cybersecurity 

A ctions/suggestions 

Labour 

Business 
m anagement 
e ntrie s 

Labour 
(C ross-
borde r trade 
in 
e m ployment) 

Em i- 
im m igration 

DEMAND 

Labour 

Vacancies 

considered in our 
fram ework . 

Tim e -dynamic indicator 

Corresponding 
indicators in the 
proposed monitoring 
framework: Not 
considered in our 
fram ework . 

Tim e -dynamic indicator 

More  re levant in a time 
dynamic growth m odel.  

In a static m odel, 
re le vant indicator can be 
the  OECD indicators on 
Trade in Employment 
(TiM)  – e .g. Domestic 
Em ployment embodied in 
fore ign final demand (by 
partne r) , distinguishing 
by Source  Industry. The 
re le vant sector is SIC 
code  C 72 Computer and 
R e lated activities. 

Data source: not 
available.  

Corresponding 
indicators in the 
proposed monitoring 
framework: we  do not 
consider vacancies.  

W e  consider “Recruitment 
of IC T specialists”, 
“planned investments in 
IC T” and “trade in ICT 
se rvice s”.   

Labour 

Jobs 

Data source: not 
available. 

More  
inform ation is 
ne e ded to 
assess. 

Data 
aggre gation 
doe s not allow 
e x te nsion to 
the  three areas.  

O EC D indicators on 
Trade  in Em ployment 
(TiM) could be 
e x plored (missing 
data, country 
cove rage) for ICT.  

It provides a supply 
indicator of labour in 
an inte rnational 
dim e nsion. 

Adaptable, 
de pending on 
the  data 
colle ction 
m e thod (for 
e x ample 
through we b-
scraping) 

Possible to look at 
vacancies, howe ver 
not sure  if the two 
indicators would differ 
significantly.  

Nove l work  ne eds to 
be  done for data 
colle ction.  

Adaptable, 
de pending on 
the  data 
colle ction 
m e thod (for 
e x ample 
through we b-
scraping) 

NA 

Table 7 Detailed review of ISCO codes  for ICT, Big Data, IoT  and Cybersecurity workforce definition   

E-Skills - ICT definition and applicability to Big Data, IoT and Cybersecurity 

Another relevant element that we have reviewed in the scope of e -Skills Empirica 
framework is the definition of ICT Specialists and ICT Profession based on ISCO codes, in 
view of assessing the possibility to extend those categories to Big Data, IoT and 
Cybersecurity to create relevant indicators on employment.  

181 

 
 
 
 
Empirica refers to ICT specialist and ICT profession workforce of the ILO International 
Standard Classification of Occupations 2008 (ISCO-08). ICT is one of the ‘thematic 
views’ (or focuses) of ISCO-08, together with and among others Agriculture, Health and 
Tourism. ISCO-08 thus contains an expansion and update of the categories for these 
occupations.  

We reviewed both ILO ICT thematic view and the slightly adapted Empirica ICT 
specialist workforce definition in view of assessing its degree of replicability within the 
monitoring mechanism proposed and more specifically, the relevance of the workforce 
types for both ICT and the three areas (IoT, Cybersecurity and Big Data).  

Looking at the professional categories proposed by our study, thus i) Managers, ii) 
Professionals and iii) Advanced Users, the ILO ISCO categories cover ‘Professionals’ and 
‘Technicians and Associates’, plus a number of additional relevant codes (i.e. codes in 
ISCO 7 and ISCO 1). Empirica takes a step further to include the Manager (ISCO 1) 
category and to suggest some adaptations among which the category Mechanics and 
Servicers.  

As ILO ISCO codes are broadly used as reference (also by the EU Skills Panorama for 
example), we propose the following workforce types for ICT for this study, compatible 
with the ILO ISCO proposed classification and the Empirica one: 

1.  ILO  ISCO categories 

‘ICT thematic view’ 

2.  Empirica ICT workforce 
definition categories 

3.  Proposed final 
categories 

4.  Professionals 

5.  Manager 

6.  Manager 

7.  Technicians and 

8.  Professionals 

9.  Professionals 

Associates 

10.  

13.  

11. Technicians/Associates 

12. Technicians/Associates 

14. Mechanics and Servicers 

15. Advanced Users (includes 
Mechanics and Services) 

Table 8 Review of ISCO  ICT codes, Empirica  approach  and proposed professionals  (workforce) definition  

In terms of the adaptability of ILO ISCO codes to IoT, Cybersecurity and Big Data, the 
ICT codes are not directly usable, and further analysis, considerations and assumptions 
should be made in view of exploring their use.  

ILO ISCO codes are the best reference available in terms of workforce topologies details. 
To use ISCO codes would create a solid base for further monitoring and for replicability.  

From a conceptual and technological point of view, additional workforce type codes 
should be considered on top of the ones used for ICTs, as the applications of these three 
areas are broader than ICT only. Following ILO ISCO codes, these could be, for example, 
2149 Engineer profession not elsewhere specified, 4-digit codes from 8 Plant and 
Machine Operators and Assemblers, 216 Architects, planners, surveyors and designers, 
etc. 

Different degrees of relevance can be assumed for each code depending on the specific 
area, thus, a matrix of weights (or any other alternative that allows to assess the codes 
relevance) should be created to select the relevant codes, for each area.  

Raw data from ILO would be needed to assess to what degree one could go further down 
in typologies granularity. ILO uses a coding system that assigns words to specific codes 
when collecting data through the survey to create 4-digit ISCO codes. In its report on the 
status of implementation of ISCO (2015), the ILO mentions that “There may, for 
example, be a need to determine whether an increasing number of jobs in ICT referred to 
as "architects" (enterprise architect, solutions architect, software architect, network 
architect, systems architect ...) are adequately covered by the existing unit groups or 
reflect new or emerging occupations. Similarly, there may be a need to determine 
whether new social media occupations are emerging at the boundary between ICT and 

182 

 
 
 
 
the world of marketing and advertising (search engine optimization (SEO) specialist, SEO 
strategist, online community manager) or whether these are specializations of existing 
occupations”335. The extension of the codes to new types of occupations, as well as a 
further code update for the ICT occupations, is thus hypothetically possible, however, it 
would require aligning with the ILO.   

In absence of raw ILO sources, we summarize below a proposed workforce types list, 
following ILO ISCO codes and Empirica. 

ICT, Big Data, IoT and Cybersecurity workforce 

Managers (1) 

IC T service managers 

ISCO-08 
code 

1330 

Professionals  Syste m s analysts 

Core ICT practitioners - professional level  

Software  developers  

W e b and multimedia developers  

Applications programmers  

Software   and  applications  de ve lopers  and 
analysts n.e.c. 

Database designers and administrators 

Syste m s administrators 

C om puter network  professionals 

Database and network professionals n.e.c. 

Other ICT practitioners - professional level 

Ele ctronics engineers 

Te le communications e ngineers  

Graphics and Multimedia Designers 

Information te chnology trainers  

IC T sales professionals 

Technicians 
and A ssociates 

ICT 
Core 
associate/technician level 

practitioners 

IC T operations technicians 

IC T user support te chnicians 

C om puter network  and systems te chnicians 

W e b technicians 

Other 
ICT 
associate/technician level 

practitioners 

Ele ctronics engineering technicians 

Broadcasting and audio-visual technicians 

Te le communications e ngineering technicians  

- 

- 

2511 

2512 

2513 

2514 

2519 

2521 

2522 

2523 

2529 

2152 

2153 

2166 

2356 

2434 

3511 

3512 

3513 

3514 

3114 

3521 

3522 

A dvanced 
users 

Craft 
related 
workers (1) 

and 
trade 

Mechanics and servicers 

Ele ctronics mechanics and servicers  

IC T installers and servicers 

7421 

7422 

Other 
advanced 
users 

(Considered  as  users  also  when  they  are 
indicated  under  Professional  activities  by  the 
specific code) 

Table 9 Detailed review of ISCO codes  for ICT, Big Data, IoT  and Cybersecurity workforce definition  

Source : authors’ elaboration based on ILO ISCO codes and Em pirica 
Note s: 
(1) Em pirica definition 

335 Hunte r, D. (ILO) (2015), The status of implementation and plans for future re vision of the International  

Standard Classification of Occupations, 2008 (ISCO-08), ESA/STAT/AC.289/34 

https://unstats.un.org/unsd/classifications/expertgroup/egm2015/ac289-34.PDF 

183 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
                                              
184 

 
 
 
 
APPENDIX  E: DETAILED DESCRIPTION OF GOOD RACTICES 
Good practices further detailed below: 

  Skillnet Ireland by the government of Ireland 

  Cybersecurity Skills Initiative (CSI) by an Irish nationwide public -private coalition 

  SME Datalab by Jheronimus Academy of Data Science (JADS) 

  PROMPT by RISE Research Institutes of Sweden 

  Cyber Resilience Centre by Brainport Eindhoven region 

  ASTER by Emilia-Romagna region 

  Recognising skills in data science by the Big Data Value Association (BDVA) 

  Community knowledge platform by VOICE (association of IT -using SMEs) 

  SMESEC by the SMESEC consortium for the European Commission 

  Make_SME_Digital (Blueprint skills training SMEs) by consortium for the European 

Commission 

  Mittelstand 4.0 Centres of Excellence by the Federal Ministry for Economic Affairs 

and Energy Germany 

  Les Digiteurs by CCI Paris Ile-de France 

  SEnDIng by the University of Patras for the European Commission 

  Modern Enterprises Programme by the Hungarian Chamber of Commerce 

 

Innovation vouchers by Business Finland 

  Cybersecurity support rangers by The Ministry of Economy, Trade and Industry 

Japan 

  Cyber NYC by the New York City  

  Skillsfuture initiative by Singapore government  

Name good practice 

Skillnet Ireland 

Responsible organisation(s) 

Business support agency of the Government of Ireland 

Duration (start/end) 

Since  2013 

Funding 

Budget 

Public (by the Minister for Education and Skills)  

Total investment of €36.27m (€17.7 (Skillnet Ire land funding) + 
€18.57m (Enterprise contributions) 

Targeted skills 

A range  of Sk illnet Ireland funded programmes that deliver a wide  
range  of skills 

Objectives of the initiative 

Concise description 

 

 

Advance the competitiveness, productivity and innovation of 
Irish businesses through enterprise-led workforce 
de ve lopment 
Facilitate increased participation in e nterprise training and 
work force  le arning in Ireland. 

Sk illnet Ireland is a business support agency of the Government of 
Ire land. It focuses on funding support, promoting of upskilling, 
business networking, career development, developing future  skills and 
policy.  

A Sk illne t Ne twork  is a collection of private-sector businesses that 
collaborate to address skills needs within their sector or re gion. There 
are : 

185 

 
 
 
Name good practice 

Skillnet Ireland 

 

Single  Sector Ne twork s: these Skillnet Ne twork s work  with 
businesses in specific sectors, developing bespoke solutions to 
m e e t existing and emerging skills needs within those sectors. 

  Multi Se ctor Ne tworks: These Skillnet Ne tworks work  with 

businesses in specific re gions, developing bespoke solutions to 
m e e t existing and emerging skills needs within specific 
re gions. 

The  65+ Skillnet Learning Network s assist businesses, small and large, 
to ide ntify the skills needed to develop their businesses and to support 
the ir te ams. The Skillnet model has particular appeal for SMEs as the 
cost of training is subsided by Sk illnet Ireland. In addition, the design, 
sourcing and delivery of training is all coordinated by the Sk illnet 
Ne twork  itse lf, e nabling e asy acce ss to training but also m oving much 
of the  administrative burden away from the firm. 

Results 

68 Ne twork s. Support over 16.000 business nationwide and provide a 
wide  range of valuable learning experiences to over 55.000 trainees. 
441.846 total training days, 56.182 total people trained 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons 
roadmap and/or scaling up 

learned 

for 

Website(s) initiative 

https://www.sk illnetireland.ie/about/funding-for-upskilling/ 

Name good practice 

Cybersecurity Skills Initiative (CSI) Ireland 

Responsible organisation(s)  A national public-private coalition lead by Technology Ire land ICT Skillnet 

and Sk illnet Ireland  

Duration (start/end) 

2018 

Funding 

Budget 

Public-private 

Unk nown 

Targeted skills 

C ybe r security skills  

Objectives of the initiative 

The  programme has a cle ar structure  to achieve success (the ‘road to 
e x ce llence’) which builds on five objectives: 

 

C ybe rsecurity Skills Pathways,  

  O rganic growth (broaden the skills base by fostering internal 

m obility),  

 

 

 

C ybe rsecurity is a Business issue not just an IT issue 

Ne w Entrants (attract and re tain young people),  

C ontinuous professional development (CPD). 

Concise description 

The  C ybersecurity Sk ills Initiative (C SI) is a dire ct re sponse to the  most 
consistent need of companies across all sectors and of all sizes – how to 
ade quately protect the ir business in the face of the escalating cyber threat.  

186 

 
 
 
 
 
 
Name good practice 

Cybersecurity Skills Initiative (CSI) Ireland 

C e ntral to  this  ne e d is  the  growing  shortage of  sk illed cybe rsecurity 
pe rsonnel to protect against and re spond to se curity bre aches.  And this 
is happening at a time whe n unemployment is rapidly decreasing and the 
com petition for the available technically skilled personnel is intense. 

The   C SI  contains  a  com pre hensive  plan  to  train  5,000  pe ople  in 
cybe rse curity skills and help 4,000 companies to tackle the cybersecurity 
sk ills issue over the next thre e years. 

O ne  interesting course is the C yber Aptitude Test which facilitates career 
change into cybe rse curity and has proven to tap  into ne w  supply of 
re sources to fill the skills gap/tackle e xisting mismatch.  

Results 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Strengthening  ecosystems: 

Strategic outlook development: 

Structured  skills development: 

Tailoring training to SME’s needs  

Lessons learned for roadmap 
and/or scaling up 

Website(s) initiative 

https://www.ictsk illnet.ie/cyber-security-skills/, 
https://www.ictsk illnet.ie/wp -content/uploads/2019/04/C SI -Brochure -
2019.pdf 

Name good practice 

SME Datalab 

Responsible organisation(s) 

JADS 

Duration (start/end) 

6 till 10 we e k s per project 

Funding 

Budget 

Public-Private partnership 

Day charge an additional fee of €2.500 for e ach proje ct that they do, half 
of this budget goes to the student that did the job 

Targeted skills 

Big data  

Objectives of the initiative 

  He lping organizations to cre ate value with data. 

Concise description 

JADS MKB Datalad helps organisation to cre ate value with data. They do 
this by  doing short te rm  proje ct with  data scie ntists (that are  still in 
colle ge). In case the students get stuck, the e xperienced professionals or 
scie ntists will be  the re  to he lp or guide them. JADS MKB Datalab mainly 
focusses on proje cts that can cre ate cost re duction or re ve nue increase. 
In some cases, the client wants m ore than just one project, in cases like 
that, the re will be m ultiple proje ct to get to the re quire d re sult.  

Results 

More  than 70 com panies (in different sizes and industries) are helped in 
with totally different issues 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

Stre ngthening e cosystems: 

187 

 
 
 
 
 
 
 
 
Name good practice 

SME Datalab 

 

 

 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for roadmap 
and/or scaling up 

Website(s) initiative 

https://jadsmkbdatalab.nl/about-us/ 

Name good practice 

PROMPT 

Responsible organisation(s)  R ISE 

Duration (start/end) 

Unk nown 

Funding 

O wne d by Swe dish State and work in collaboration with and on behalf of 
the  private and public sectors and academia.  

Budget 

Unk nown 

Targeted skills 

Cybersecurity, big data & IoT skills  

Objectives of the initiative 

 

Products, technologies, processes and materials that contribute 
to a sustainable future  and a competitive Swe dish business 
com m unity. 

Concise description 

R ISE is Swe den’s research institute and innovation partner. Through our 
inte rnational collaboration programmes with industry, academia and the 
public sector, we  e nsure  the competitiveness of the Swe dish business 
com m unity on an international level and contribute to a sustainable 
socie ty. 

O ur 2,800 employees e ngage in and support all types of innovation 
proce sses. RISE is an independent, State-owne d re search institute, 
which offe rs unique e xpertise and over 100 te stbeds and demonstration 
e nvironments for future-proof technologies, products and services. 

Results 

O ur turnove r was approximately SEK 3 billion. O wne r of and partner in 
60% of Swe den’s total test and demonstration environments 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://www.ri.se /e n/better-future-and-those-who-take-us-there  

Name good practice 

Cyber resilience centre 

Responsible organisation(s)  Brainport, Eindhoven re gion 

188 

 
 
 
 
 
 
 
 
Duration (start/end) 

Funding 

Budget 

Public-Private partnership 

Targeted skills 

C ybe rsecurity 

Objectives of the initiative 

 

Incre ase the re silience  of high industries firms in the 
Ne the rlands against cyber attacks 

Concise description 

Achie ve  a higher cyber re silience  by offering a trusted e nvironment on 
participants whe re they share knowle dge, information, and best practices 
with e ach other 

Results 

Unk nown 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for roadmap 
and/or scaling up 

Website(s) initiative 

https://cwbrainport.nl/  

Name good practice 

ASTER 

Responsible organisation(s) 

Em ilia -Romagna 

Duration (start/end) 

Since  1985 ASTER  has shaped and defined pathways and tools for 
innovation, industrial re search, technology transfer and for the 
im provement of high-quality skills and care ers on innovation 

Funding 

Budget 

Targeted skills 

Public and private organisations  

Unk nown 

Big data  

Objectives of the initiative 

 

Foste r the re gion’s sustainable growth by developing innovation 
and k nowle dge, attractiveness and internationalisation of the 
re gion... 

Concise description 

ASTER  is the C onsortium for innovation and technology transfer of the 
Em ilia -Romagna re gion of Italy 

ASTER  promotes industrial re search as the m ain driver of sustainable 
e conomic development and collaborates with company associations to 
de ve lop joint re search and corporate strategies and actions, facilities and 
se rvice s for industrial re search, and the e nhancement of human capital 
work ing in these areas. 

ASTER  m anages the Emilia-Romagna High Technology Ne twork , 
consisting of industrial re search laboratories and Innovation C entres, 
providing re search, e xpertise, tools and re source s to business and 

to he lp drive innovation in companies 

189 

 
 
 
 
 
 
Name good practice 

ASTER 

Results 

The  High Technology Ne twork  currently involves: 82 laboratories, 14 
Innovation Centres, 10 Technopoles 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://www.ub-cooperation.eu/pdf/cases/S_C ase_Study_Aster.pdf  

Name good practice 

Recognising Skills in Data Science  

Responsible organisation(s)  BDVA 

Duration (start/end) 

The  BDV PPP was launched in 2014, but its operationalization has been 
e specially pushed forward with the launch of the LEIT work  programme 
2016/2017 The obje ctives of the Association) are  to boost European 
Big Data Value re search, development and innovation and to foster a 
positive perception of Big Data Value. 

Funding 

Budget 

Public 

Unk nown 

Targeted skills 

Big data  

Objectives of the initiative 

 

Positioning Europe as the world leader in the cre ation of Big 
Data Value. 

Concise description 

The  Big Data Value Association (BDVA) is an industry-driven 
inte rnational not–for-profit organisation with 200 members all over 
Europe  and a we ll-balanced composition of large, small, and medium-
size d industries as we ll as re search and user organizations. BDVA is the 
private  counterpart to the EU C ommission to implement the Big Data 
Value  PPP program. 

The  m ission of the BDVA is to develop the Innovation Ecosystem that 
will e nable the data and AI-driven digital transformation in Europe 
de live ring maximum eco nomic and societal benefit, and, achieving and 
sustaining Europe’s leadership on Big Data Value cre ation and Artificial 
Inte lligence 

Results 

Unk nown 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

190 

 
 
 
 
 
 
Name good practice 

Recognising Skills in Data Science  

Name good practice 

VO IC E C ommunity Knowle dge Platform 

Responsible organisation(s) 

The  Fe deral Association 

Duration (start/end) 

The  Fe deral Association emerged at the end of 2011 from the merger 
of the  organizations C IOcolloquium and CIO-Circle. VOICE is organized 
as a re gistered association with he adquarte rs in Berlin and office s in 
C ologne, Munich and Hamburg. 

Funding 

Budget 

Public 

Unk nown 

Targeted skills 

C ybe rsecurity  

Objectives of the initiative 

 

Furthe r e nhance the competitiveness of member companies 
through the use of digital technologies - with a targeted 
e x change on the top issues of digitization and by safeguarding 
the  inte rests  of user companies in national and European 
policie s and in IT. provider shaft. 

Concise description 

Results 

Voice  offers its clients a competent, attractive and dynamic platform. 
VO IC E is today the largest re presentation of digital decision-makers on 
the  user side in German-speaking countries. They represent a cross 
se ction of DAX, MDAX and medium-sized companies. 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://voice-ev.org/wissensplattform/ 

Name good practice 

SMESEC 

Responsible organisation(s) 

Various org 

Duration (start/end) 

The  SMESEC  suite will be  developed in 36 months by a strong 
consortium of 12 partners from 7 countries 

Funding 

The  consortium is le d by ATOS, with m any years of e xperience  in 
proje ct m anagement and cyber-security, and involves large companies, 
SMEs, re search ce nters, and universities. While supported by research 
ce nte rs and universities, SMESEC  is an industry-oriented project, 
whe re  the  private companies will cove r more than 73% of the total 
proje ct costs. 

This project has re ceived funding from the European Union’s Horizon 
2020 re search and innovation programme under grant agreement No 
740787 (SMESEC ) 

Budget 

Targeted skills 

C ybe rsecurity 

191 

 
 
 
 
 
 
Name good practice 

SMESEC 

Objectives of the initiative 

 

 

 

High-quality cybersecurity solutions attractive to SMEs with a 
re stricte d budget 

Provide cybersecurity training and awareness for SMEs and all 
type  of employees 

Te st and validate our solution with four initial use cases and 
have  an open call whe n the solution is more m ature 

 

R e ady to market solution 

Concise description 

SMESEC  is a proje ct proposed by an international group of e xperts as a 
re sponse  to  the   cybe r-se curity  challe nges  of  SMEs  with  a  lim ited 
back ground on cyber-security and a restricte d budget 

Results 

Rationale for selection 

The  initiative shows a successful approach that contributes to: 

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://www.sm e sec.eu/about.html 

Name good practice 

Blueprint skills training SMEs 

Responsible organisation(s) 

M akes me digital c onsortium for the European C ommission 

Duration (start/end) 

D es igning a s hared vision for s kills development for SMEs on Big D ata, Internet of 
T hings and Cybersecurity for the c oming years until 2 023 

Funding 

Budget  

P ublic 

€ 4 00.000 

Target ed skills 

C ybersecurity, I oT and big data  

Objectives of  the initiative 

Concise  description 

 

 

T he main objective of this initiative is to research, identify, design, test 
and validate s pecific measures s upporting specialised s kills 
development related to Big Data, I nternet of T hings (IoT) and 
C ybersecurity for s mall and medium-sized enterprises in E urope 

T he aim of the project is to provide the European Commission with a 
s tructured programme for the training of SME employees and 
unemployed persons with digital skills that are required in the modern 
work place. 

T he European Commission and EASME took the initiative to analyse and support 
SM Es’ s kills development for Big D ata, I nternet of T hings and Cybersecurity. This 
initiative is managed by a consortium of Capgemini Consulting, T echnopolis Group 
and the E uropean D IGITAL SME Alliance. 

Results 

C ourses developed on full stack, data analytics, cybersecurity and digital marketing 

Rationale f or selection 

T he initiative s hows a s uccessful approach that contributes to: 

 

 

 

 

Strengthening ecosystems: 

Strategic outlook development: 

Structured skills development: 

T ailoring training to SME’s needs 

Lessons learned f or roadmap 
and/or  scaling up 

Website(s) initiative 

https://makesmedigital.eu  

192 

 
 
 
 
 
 
 
Name good practice 

Mittelstand 4.0 

Responsible organisation(s) 

Fe de ral Ministry for Economic Affairs and Energy Germany 

Duration (start/end) 

2015 - ungoing 

Funding 

Budget 

Public 

Unk nown 

Targeted skills 

Cybersecurity, big data, IoT skills or combination  

Objectives of the initiative 

Concise description 

 

 

 

To raise aware ness among SMEs about the technological and 
e conomic potential of digitialisation, including industrie 4.0 
and about challenges involved 

To support the development of needs -oriented, secure, and 
m ark et-re ady solutions for SMEs by providing opportunities to 
vie w and te st these out in practice 

To provide k ey information and knowle dge for e stablished 
transfer agencies and multipliers  

R e gional ‘Mittelstand 4.0 ce ntres  of e xcellence’ that re ceive funding from 
the  Fe deral Ministry for Economic Affairs and Ene rgy, and the Centre  of 
Ex ce lle nce for the  ‘Digitalisation of Sk illed C rafts’ he lp Ge rman SMEs 
be come m ore aware of Industry 4.0, and provide them with information, 
training  and  opportunities  to  te st  the ir  Industry  4.0  applications. 
De m onstration and learning factories help companies try out new things 
–  unde r  the   close   e ye   of  industry  e x perts  –  and  put  the ir  own 
te chnologies, product or customer inte rface s to the te st before making 
an inve stment. These service s are supplemented by the  work  done by 
the  Mitte lstand 4.0 agencies: These agencies use multipliers to answer 
com panies’  que stions  on  a  host  of  transversal  issue s  link e d  to 
digitalisation  –  such  as  cloud  com puting ,  digital  com m unication, 
proce sses, trade, etc.. 

Results 

Planned annual investment of 40 billion EUR  by Ge rm an Industry in 
Industry 4.0 applications by 2020 

153 billion EUR additional growth cre ated through Industry 4.0 by 2020 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

Name good practice 

SEnDIng Project 

Responsible organisation(s)  Unive rsity of Patras 

Duration (start/end) 

1st De ce mber 2017 - 30th November 2020 

Funding 

Budget 

Co-funded by the Erasmus+ Programme of the European  Union   

€982.537 

Targeted skills 

Big data and IoT skills  

193 

 
 
 
 
 
Name good practice 

SEnDIng Project 

Objectives of the initiative 

 

 

 

 

 

To address the skills gap of DS and IoT professionals by 
targe ting the IT sector and other e conomy’s sectors (e.g. 
banking, e nergy, and logistics) that have demands for high -
qualified DS and IoT professionals. 

To provide DS and IoT professionals with sk ills and 
com petence s, that meet the needs of e mployers, are 
transferable and recognized among European countries. 

To de sign a common reference  scheme of competence s, skills, 
k nowle dge and proficiency le vels for DS and IoT professionals 
in accordance with European frameworks (e.g. eCF and 
ESC O ). 

To de sign and provide two m odular learning outcome oriented 
VET programs, one targeting DS and another IoT. 

To de sign a mechanism for the ce rtification of skills and 
com petence s provided to le arners  

Concise description 

The  SEnDIng project has developed a VET program which is based on 
m odular  and  le arning  outcomes-oriented  curricula  that  combine 
te chnical k nowledge and sk ills at Data Scie nce and Internet of Things 
dom ains with transversal skills and competence s. 

Results 

Phase 1: 103 hours asynchronous online training (10 hours pe r week  
from  November 2019 to January 2020). 

Phase 2: 20 hours face  to face  training during February 2020 that will be 
he ld in Athens, Nicosia and Sofia during 2 we ekends. 

Phase 3: 4 months on-the-job tra ining in the period from March 2020 to 
August  2020.  O n-the-job  training  will  tak e   place   at  your  business 
pre m ises and there is the possibility to support you in defining the case 
studies your e m ployees will work  on, so that the y are  re lative to your 
business activities. 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

http://sending-proje ct.eu/index.php/en/ 

Name good practice 

Modern Enterprises' Program 

Responsible organisation(s)  Hungarian Chamber of Commerce 

Duration (start/end) 

08/2015 untill 2021 

Funding 

Public (Hungarian Chamber of Commerce & European Fund for Regional 
De ve lopment – EU) 

Budget 

18.077.000 Euro  

Targeted skills 

Cybersecurity, big data, IoT skills or combination  

194 

 
 
 
 
 
 
Name good practice 

Modern Enterprises' Program 

Objectives of the initiative 

  O ffe r personalized and knowledgeable assistance and not-

re stitutable advice for business IT-developments.  

 

He lp firms and guide them in their digital transformation 

Concise description 

The  program conducts surve ys, suggest IT -developments, solutions, 
offe rs discounts, brings together e vents  

Results 

16.733 m ember firms, 1.948 discounts, 264 events 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://vallalkozzdigitalisan.hu/index.html 

Name good practice 

Innovation vouchers Finland 

Responsible organisation(s)  Business Finland 

Duration (start/end) 

C re ated on 1ste January 2018 by the merger of two organizations: Finpro 
and Tekes.  

Funding 

Budget 

Public 

Targeted skills 

Cybersecurity, big data, IoT skills or combination  

Objectives of the initiative 

  W e  e nable companies to grow inte rnationally and also cre ate 
world-class business e cosystems and a competitive business 
e nvironment for Finland... 

Concise description 

Business Finland offers Finnish companies a unified customer journey for 
innovation  activitie s,  inte rnationalization,  inve stments,  and  tourism 
prom otion. 

Results 

958M Funding applied, 2906 new products, services or other innovations 
ge nerated, 1303 patents and 816 theses.  

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://www.businessfinland.fi/en/for-finnish-customers/about-
us/re sults-and-impact/ 

Name good practice 

Digityser 

195 

 
 
 
 
 
 
Responsible organisation(s)  DigitYser is the  Digital Innovation Hub of Brussels whe re  communities 
gather to boost digitalskills, e mpowe r  e ntrepreneurship and facilitate 
digital transformation. 

Duration (start/end) 

Unk nown 

Funding 

Budget 

Un 

Targeted skills 

Cybersecurity, big data, IoT skills or combination  

Objectives of the initiative 

 

C ontribute to a better society 

Concise description 

Results 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://digityser.org/ 

Name good practice 

Cybersecurity Support Ranger 

Responsible Organization(s 

The  Ministry of Economy, Trade and Industry Japan 

Duration (start/end) 

Unk nown 

Funding 

Budget 

Public 

Unk nown 

Targeted skills 

C ybe rsecurity  

Objectives of the initiative 

Concise description 

 

 

Aim ing to raise aware ness on cybersecurity among SMEs and 
popularize cybersecurity measures tailored to the curre nt 
situations of SMEs. 

Supporting SMEs in taking cybersecurity e fforts in  
collaboration with re gional associations and companies 

The  Ministry of Economy, Trade and Industry (METI) and the 
Information-technology Promotion Agency, Japan (IPA) have been 
advancing the Project for Demonstrating Measures for Supporting SMEs 
in C onducting Post-Accident Measures Involving Cybersecurity 
(C ybe rsecurity Support Ranger), aiming to raise aware ness on 
cybe rse curity among SMEs and popularize cybersecurity m easures 
tailore d to the curre nt situations of SMEs 

Results 

Unk nown 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

196 

 
 
 
 
 
 
 
 
 
Name good practice 

Cybersecurity Support Ranger 

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://www.m e ti.go.jp/english/press/2019/0611_002.html 

Name good practice 

Cyber NYC 

Responsible organization(s)  Ne w York  C ity Economic Development Corporation 

Duration (start/end) 

Established in 2018 

Funding 

Budget 

Public-Private partnership 

100 m illion 

Targeted skills 

Cybersecurity, big data, IoT skills or combination  

Objectives of the initiative 

  Mak e Ne w York C ity a global leader in cyber innovation and to 

catalyse 10,000 jobs 

Concise description 

A suite  of strategic investments to grow Ne w York  C ity’s cybe rsecurity 
work force , he lp com panies drive  innovation, and build ne tworks and 
com m unity spaces 

Results 

unk nown 

Rationale for selection 

The  initiative shows a successful approach that contributes to:  

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://www.cybe r-nyc.com/ 

Name good practice 

SKILLSFUTURE 

Responsible organisation(s)  Singapore  Government 

Duration (start/end) 

Unk nown 

Funding 

Budget 

Public 

Unk nown 

Targeted skills 

Cybersecurity, big data & IoT skills / all kind of skills  

197 

 
 
 
 
 
 
Name good practice 

SKILLSFUTURE 

Objectives of the initiative 

 

A national movement to provide Singaporeans with the 
opportunities to develop their fullest potential throughout life, 
re gardless of their starting points. 

Concise description 

No m atte r whe re you are  in life – schooling years, early career, mid-
care e r or silver years – you will find a variety of resources to help you 
attain mastery of skills. Sk ills mastery is more  than having the righ t 
paper qualifications and being good at what you do curre ntly; it is a 
m indset of continually striving towards greater e xcellence through 
k nowle dge, application and experience 

Results 

Unk nown 

Rationale for selection 

The  initiative shows a successful approach that contributes to: 

 

 

 

 

Stre ngthening e cosystems: 

Strate gic outlook development: 

Structure d skills development: 

Tailoring training to SME’s needs 

Lessons learned for 
roadmap and/or scaling up 

Website(s) initiative 

https://www.sk illsfuture.sg/ 

198 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
HOW TO OBTAIN EU PUBLICATIONS 

Free publications: 

•  one copy: 

via EU  Bookshop (http://bookshop.europa.eu); 

•  more than  one copy or posters/maps: 

from the  European Union’s representations (http://ec.europa.eu/represent_en.htm);   
from the delegations in non-EU countries (http://eeas.europa.eu/delegations/index_en.htm);  
by contacting the Europe Direct service (http://europa.eu/europedirect/index_en.htm) or calling 
00 800  6 7 8 9 10 11  (freephone number from anywhere in the EU)  (*). 

(* )  T he information given is free, as are most c alls (though s ome operators, phone boxes or hotels may char ge you). 

Priced publications: 

•  via EU  Bookshop (http://bookshop.europa.eu). 

Priced subscriptions: 

•  via one of the sales agents of the Publications Office of the European Union 

(http://publications.europa.eu/others/agents/index_en.htm ). 

199 

 
 
 
 
 
 
 
 
 
E
A
-
0
4
-
2
0
-
0
0
7
-
E
N
N

-

doi: 10.2826/772332 

 ISBN  978-92-9202-778-0