Industry 4.0. Challenges for European Industry Deriving from Servitisation and Digitalisation

Abstract

A new concept of the Industry 4.0 revolution is completely different from the previous ones. At this point, it is worth reminding that mechanisation, i.e., the invention and use of the steam engine, marks the beginning of the industrial age Industry 1.0. The next step included electrification which replaced less efficient steam engines with electric engines able to continuously manufacture products at relatively low energy cost (Industry 2.0). Compared to the previous revolution, waiting for Industry 3.0 based on narrowly interpreted digitalisation (digital input of data into machines) took much longer. Over this period, we could observe the development of increasingly more powerful computers that control manufacturing processes. Machines became more productive, precise, and flexible while digitalisation enabled reaching further advancement in automation. New planning and control systems started to emerge, intended to coordinate production activities. The main components of Industry 4.0 are integration and networking taken together, dependent of each other and supporting each other via the Internet.

Taking into consideration the aforementioned issues, the Industry 4.0 revolution
has triggered clearly more economical and socially responsible use of resources to meet
consumer needs. The above-mentioned needs are identified at individual level and
in real time, which surely accelerates the meeting of individualised consumer expectations and needs. As a result, by networking and the exchange of data between products and consumers in the fourth industrial revolution, companies can make their production processes more economical, taking account of the environmental, economic, and social aspects.

Full text







AdamA.Ambroziak*
Introduction
A new concept of the Industry 4.0 revolution is completely different from the pre-
vious ones. At this point, it is worth reminding that mechanisation, i.e., the invention
and use of the steam engine, marks the beginning of the industrial age Industry 1.0.
The next step included electrification which replaced less efficient steam engines with
electric engines able to continuously manufacture products at relatively low energy
cost (Industry 2.0). Compared to the previous revolution, waiting for Industry 3.0 based
on narrowly interpreted digitalisation (digital input of data into machines) took much
longer. Over this period, we could observe the development of increasingly more power-
ful computers that control manufacturing processes. Machines became more productive,
precise, and flexible while digitalisation enabled reaching further advancement in
*
Adam A. Ambroziak, SGH Professor, PhD, SGH Warsaw School of Economics, Collegium of World Economy,
e-mail: Adam.Ambroziak@sgh.waw.pl, ORCID: 0000-0002-4618-8497.
4

72
automation. New planning and control systems started to emerge, intended to coordi-
nate production activities.
The main components of Industry 4.0 are integration and networking taken together,
dependent of each other and supporting each other via the Internet. It is considered
a new industrial scenario in which the convergence of different emerging technolo-
gies strengthened by the Internet of Things (Rong et al., 2015) results in cyber-physical
and intelligent systems that can create value for the industrial activities. Partially, it
describes a new industrial scenario dominated by information technologies and connec-
tivity, and, in consequence, it is focused on the establishment of intelligent products and
production processes by integrating modern information and communication technolo-
gies, and they emphasise different faces of the new industrial challenges (Frank, 2019).
Firstly, the point is to connect consumer behaviour, expectations, and priorities
with manufacturers’ offerings. To this end, consumers often get not only a finished
product but also a communicating device taking the form of software which enables
real time monitoring of how available options are utilised and facilitates filing orders
for new products. This solution, through de facto integration of people with available
systems, helps in current adjusting of an offered product (or service) with consumer
expectations.
Secondly, within the framework of Industry 4.0, we can identify relations between
machines through digital control over the Internet and IT technologies. That concept
leads to the Internet of Things and remote monitoring (Grubic, 2014). In this case, the
goal is to ensure the manufacturing of goods or the provision of services (also linked
with industrial products), supply and assemble indispensable components that com-
municate with one another at the manufacturing stage. A reverse flow of information
takes place between machines engaged in production and the production system of
a company (Liao et al., 2017; Reischauer, 2018; Yin et al., 2018). A more advanced level
of cooperation needs cloud computing (Wen and Zhou, 2016), big data (Opresnik and
Taisch, 2015) and predictive analytics (Ardolino et al., 2017).
Taking into consideration the aforementioned issues, the Industry 4.0 revolution
has triggered clearly more economical and socially responsible use of resources to meet
consumer needs. The above-mentioned needs are identified at individual level and
in real time, which surely accelerates the meeting of individualised consumer expecta-
tions and needs. As a result, by networking and the exchange of data between products
and consumers in the fourth industrial revolution, companies can make their produc-
tion processes more economical, taking account of the environmental, economic, and
social aspects.
It is worth noting that previous discussion on the EU industry was focused especially
on some old-fashion problems: protectionism v. interventionism, sectoral v. horizontal

 73
approach, (Ambroziak, 2014, 2017a, 2017b; Gawlikowska-Hueckel, 2016) while rarely on
new technological challenges. This is an evidence of very rapid changes in innovations
implemented in industry, including those related to digitalisation. Therefore, the goal
of this chapter is to assess the readiness of the EU and its Member States’ economies
to embrace the fourth industrial revolution in the field of digitalisation. To this end,
the engagement of European companies in digitalisation was assessed by carrying out
a multilevel analysis of: a) changes in the share of companies using the ERP software
package to share information between different functional areas, b) the use of software
solutions, such as Customer Relationship Management or Customer Relationship Man-
agement to analyse information about their clients for marketing and business pur-
poses, as well as, c) the use of cloud computing services, d) big data, and e) their digital
integration with third partners, taking into account their host Member States, size of
companies and economic activity sectors. All data were received from Eurostat.
The above listed business management packages and systems used by companies
to communicate internally or externally with their suppliers, buyers and customers, but
also to exchange information and work using cloud computing or to collect, analyse
and interpret Big Data sets received in the course of their activities, transfer business
operations into Industry 4.0 networking. Apparently, the processes should be carried
out in parallel, since, without internal integration of individual departments within
a company and external integration with other business partners (suppliers and buy-
ers) based on cloud computing, it is hard to imagine how consumer expectations and
needs, often individual and revealed through collected and examined Big Data, could
be met successfully.
1. Developmentadvancementanddynamicsofselected
sectorsandMemberStatesinthecontextofIndustry4.0
In order to more precisely identify digital integration and development advancement
of companies, groups of economic sectors have been singled out which are viewed as
components of Industry 4.0 revolution. Following an arbitrary approach, manufactur-
ing as well as service sectors have been selected for further analysis (Table 1). In 2017,
the broadly understood manufacturing sector covering electric and machine engineer-
ing and computer industry, whose specificity linked with multi-component speciali-
sation makes it uniquely placed to benefit from the Industry 4.0 revolution, reported
a rather significant share and growth compared to 2010. At the same time, the share of
industrial sectors dominated by traditional raw material suppliers started to decrease
and grew at a much slower pace over those years. Besides manufacturing sectors, the

74
analysis included some services which support industry in the period of transforma-
tion through the servitisation of finished goods but also through mutual integration
including also by communication and shared management.
Table 1
Rankingofsectorscoveredbytheresearchbyshareandincreaseofvalueadded
intheEuropeanUnionin2010–2017
 






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
   

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  

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


  
   
 
  
   

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
  




  




  
   

   



  
Source: Eurostat.
In addition, based on the outcomes of the analysis of increase in the cumulative
value added generated by sectors covered by the research over the period 2010–2017
and their importance in the total value added of individual economies, Member States
have been divided into leaders, moderate and modest Member States in terms of the

 75
importance of manufacturing and services directly linked to the Industry 4.0 concept
(Table 2).
Table 2
RankingofMemberStatesbyshareandchangeofvalueaddedofsectorsunder
researchin2010–2017
   

  
  
  
  
  
  
   
  
AT  

EE  
  
  
  
  
  
  
  
  
  
  
  

  
  
  
  
  
MT  
  
  
*) Data for 2016.
Source: Eurostat.

76
2. EnterpriseResourcePlanning(ERP)andCustomer
RelationshipManagement(CRM)
ERP systems are large-scale enterprise software packages that consist of several
integrated subsystems, enabling planning and control of resources and processes of
a company (Davenport, 1998). In consequence, ERP software provides a wide-ranging
set of capabilities across all business operations, including many modules, for exam-
ple: accounts receivable, accounts payable, sales and marketing, purchasing, human
resources, inventory management, warehouse and transportation management, product
management, planning, and production. Thus, it can cover many organisation activi-
ties: human resources, accounting, corporate governance, production, procurement,
distribution, sales and sometimes customer services to collect necessary information
on customer experiences. It should be noted that some ERP software can be more spe-
cialised and dedicated to selected sectors and activities of industries (Panorama Con-
sulting Group, 2019). It means that a company using ERP can collect and store data,
and from their interpretation get information on its activities, relations with partners
and customers that is consistent, timely and reliable across organisational units and
geographical locations (Barth and Koch, 2019).
It is worth noting that the ERP system often includes or is complemented by Cus-
tomer Relations Management (CRM). CRM was originally associated with describing
systems and tools used to automate sales processes (Payne and Frow, 2005). Being
viewed as information-enabled relationship marketing (Ryals and Payne 2001), now-
adays, CRM software is designed to focus capabilities to handle marketing and cus-
tomer management, to organise and collect appropriate data on current and potential
customers. It should ensure improving a relationship between a company and its cus-
tomer based on some communication channels, including websites, telephone, e-mail,
social media or dedicated applications – all media based on the Internet. This means
it helps in contacts with management and sales management to improve productiv-
ity (Salesforce, 2019) by increasing individual approach to customers and maximising
consumer satisfaction.
When it comes to digital integration of internal operations of European companies,
the highest share of enterprises who use ERP software package to share information
between different functional departments was declared in Belgium (54%), the Neth-
erlands, Lithuania (the highest growth), Spain, Luxembourg, Denmark, Austria, and
Portugal, with the lowest share reported in 2017 in Latvia (25%), Bulgaria, the United
Kingdom, Romania, and Hungary (Figure 1). It is noteworthy that the biggest increases
over the period covered by the research were observed for leaders of the 2017 ranking,

 77
meaning recent years had a powerful impact upon their current position. Two Mem-
ber States reported a decrease (Sweden and Romania, but also, e.g., Germany if we take
account of mid-term data).
Figure 1
Changesintheshare(minandmax)ofenterpriseswhouseERPsoftwarepackage
toshareinformationbetweendifferentfunctionalareasin2010–2017
0
10
20
30
40
50
60
BE
NL
LT
ES
LU
DK
AT
PT
FI
DE
FR
EL
IT
CY
EU28
SK
SE
SI
MT
CZ
EE
IE
HR
PL
LV
BG
UK
RO
HU
Source: Eurostat.
Figure 2
Changesintheshare(minandmax)ofenterprisesusingERPsoftwarepackage
toshareinformationbetweendifferentfunctionalareasbrokendownbysize
andsectorin2010–2017
0
10
20
30
40
50
60
70
80
90
All enterprises
SMEs
Large enterprises
ICT
C19-23
C26-33
J58-63
C24-25
D35-E39
G45-47
C10-18
M69-74
L68
G47
N77-82
H49-53
I55
F41-43
Source: Eurostat.
In 2017, more than three-fourths of large companies (compared to one-third of SMEs)
declared using the ERP software systems (Figure 2). Sector-wise, the system was used

78
mainly by companies representing sectors such as manufacture of chemicals (C19-23),
manufacture of electromachinery (C26-33), manufacture of metal products (C24-25),
and information and communication services (J58-63). They also reported the highest
growth between 2010 and 2017. On the other hand, the smallest growth dynamics and,
as a result, the lowest share of enterprises using the ERP systems was found in trans-
port (H49-53), accommodation (I55), and construction (F41-43) services.
The use of Customer Relationship Management (CMS) systems in the EU looks
slightly different if we compare it to the integration of companies within the frame-
work of ERM. The biggest share of companies using this type of software solutions was
identified in Germany, the Netherlands, Belgium, Austria, and in Cyprus (more than
40%) while the lowest share in Bulgaria, the Czech Republic, Lithuania, Hungary, and
Romania (below 20%) (Figure 3). Noteworthy, in this case the biggest growth (with the
exception of the Netherlands and Cyprus) was reported in the Member States in which
the share of such companies was close to the EU-28 (33%) average (Latvia and the UK).
Figure 3
Changesintheshare(minandmax)ofenterprisesusingsoftwaresolutionslike
CustomerRelationshipManagementin2010–2017
0
5
10
15
20
25
30
35
40
45
50
DE
NL
BE
AT
CY
LU
FI
ES
DK
SE
EU28
IE
LT
UK
IT
FR
MT
SI
EE
PT
SK
PL
EL
HR
BG
CZ
LV
HU
RO
Source: Eurostat.
Also in the case of CRM systems, the share of large enterprises using the software
clearly outnumbered the share of SMEs (62% and 32%, respectively) (Figure 4). In terms
of economic sectors, obvious leaders are IT and communication companies followed by
businesses from sectors such as accommodation, wholesale and retail trade, and pro-
fessional and science services (over 40%). Relatively the least intensive relationships
with customers were reported for companies which manufacture agri-food products or
offer transport, and construction services (below 20%).

 79
Figure 4
Changesintheshare(minandmax)ofenterprisesusingsoftwaresolutionslike
CustomerRelationshipManagementbrokendownbysizeandsectorin2010–2017
0
1
0
2
0
3
0
4
0
5
0
6
0
70
All enterprises
SMEs
L
arge enterprises
ICT
J58-63
I55
G45-47
M69-74
C19-23
C26-33
D35-E39
L68
N77-82
C24-25
C10-18
H49-53
F41-43
Source: Eurostat.
Figure 5
Changesintheshare(minandmax)ofenterprisesusingCustomerRelationship
Managementtoanalyseinformationaboutclientsformarketingpurposes
in2010–2017
0
5
1
0
1
5
2
0
2
5
3
0
35
CY
ES
NL
BE
IE
AT
DE
LT
DK
LU
FI
E
U28
UK
MT
SE
FR
IT
PT
SK
CZ
PL
EE
EL
BG
LV
SI
HR
RO
HU
Source: Eurostat.
The above-mentioned system of customer relationship management is used, to
a large extent, for marketing purposes. Leaders in this category are companies from
Cyprus, Spain, the Netherlands, Belgium, Ireland, and Germany (above 26%), while the
lowest share of companies using the CRM system exclusively for marketing purposes

80
was reported in Bulgaria, Latvia, Slovenia, Croatia, Romania, and Hungary (below 15%)
(Figure 5). We need to bear in mind, however, that using data for this purpose is a rela-
tively simple and well known way of managing consumer-related information. Much
more complex approach to the subject, also better aligned with the Industry 4.0 con-
cept, consists in collecting and using consumer data for other business goals connected
with product individualisation and the servitisation of goods. The highest share of such
companies were found in Germany, the Netherlands, Austria, Belgium, and in Cyprus
(over 40%), with the lowest and decreasing share identified in the researched period
in Croatia, Bulgaria, the Czech Republic, Greece, Latvia, Hungary, and Romania (below
20%) (Figure 6).
Figure 6
Changesintheshare(minandmax)ofenterprisesusingCustomerRelationship
Managementtocapture,storeandmakeavailableclientinformationtoother
businessfunctionsin2010–2017
0
5
10
15
20
25
30
35
40
45
50
DE
NL
AT
BE
CY
LU
FI
DK
ES
SE
LT
EU28
IE
UK
IT
FR
SI
MT
PT
EE
PL
SK
HR
BG
CZ
EL
LV
HU
RO
Source: Eurostat.
Large entrepreneurs clearly dominate in using consumer data only for marketing
purposes, as well as for other business purposes (45% and 60% respectively). In both
cases, the highest share of such companies was found in IT & communication and accom-
modation services. Further ranking positions of sectors depended on the purpose for
which data were used. In the case of strictly marketing activities, CRM systems were
used also in wholesale and retail trade and in the chemical industry while entrepre-
neurs using the CRM system for other business goals represented a rather wide range
of sectors whose performance in this area was very similar: professional and research
services, utilities supply, as well as chemical and electromachinery industries (Figure 7).

 81
Figure 7
Changesintheshare(minandmax)ofenterprisesusingCustomerRelationship
Managementbrokendownbysizeandsectorin2010–2017




0
5
10
15
20
25
30
35
40
45
50
All enterprises
SMEs
Large enterprises
ICT
J58-63
I55
G45-47
C19-23
C26-33
M69-74
N77-82
C10-18
D35-E39
C24-25
L68
H49-53
F41-43
0
10
20
30
40
50
60
70
All enterprises
SMEs
Large enterprises
ICT
J58-63
I55
M69-74
C19-23
G45-47
C26-33
D35-E39
L68
N77-82
C24-25
G47
C10-18
H49-53
F41-43
Source: Eurostat.
The above analysis leads to the conclusion that trends in using both ERP and CRM
for various marketing-related purposes and other business functions are convergent
in different Member States, as well as sectors of industry and services under research.
Member States which reported the highest and quickly growing shares of internally
integrated enterprises belong, in most cases, to group III of countries representing rela-
tively low but in recent years the most quickly growing value added in sectors included
in the study (DK, NL, CY, LU but also LT and ES). On the other hand, the poorest per-
forming countries were those in which the share of sectors covered by the study was
relatively the highest although, admittedly, they did not report any radical increases
over recent years (RO, HU from group I and LV, BG from group II). In group I of the
states leading in terms of industrial and service structure, it is worth mentioning Slo-
venia and Poland whose performance was slightly better in digitalisation of internal
processes in enterprises.
From the point of view of economic operations, the highest and growing shares of
entrepreneurs who use ERP and CRM systems at the EU-28 level were identified in the
chemical and electromachinery industries, as well as in accommodation, IT & commu-
nication, and professional and science services. Notably, these are sectors (with the

82
exception of the electromachinery industry) whose shares in total value added of all
investigated areas of business operations are relatively low but have been rather sig-
nificantly increasing in recent years. At the same time, the lowest indicator of internal
digitalisation of business processes was found in construction, transport, and admin-
istrative and support services.
3. CloudComputing
Using cloud computing services is the third indicator of the preparedness to the
fourth industrial revolution. Cloud computing is the latest in a long line/set of tech-
nologies that seek to streamline the operation of enterprises. Some might argue that it
is not a set of technologies but, rather, a set of services offered using a particular busi-
ness model and existing technologies (Ingalsbe et al., 2011). Nonetheless, cloud com-
puting represents the shift to an asset free IT provisioning model where highly scalable
hardware, software and data resources are available over a network (Hoberg, 2012). The
use of cloud computing has the following four characteristics: a) cloud computing has
a secure and dependable centre of data storage, b) it can share data between various
equipment, c) it can enable users to use the Internet infinitely, d) it does not require
high quality equipment from the user (Abdel-Basset et al., 2018).
In the case of cloud computing services, the biggest portion of companies using
them started doing so in the years 2014–2018 in countries such as Finland, Sweden,
Denmark, the Netherlands, Ireland, the United Kingdom, and Belgium (from 40% up
to 65%). These Member States occupy positions between moderate and modest from
the viewpoint of the share of sectors covered by the study in 2017 with simultaneous
stable growth in the recent period. Over the same period, the lowest indicator and the
lowest growth dynamics were reported in Greece, Poland, Romania, and Bulgaria (below
15%), i.e., in Member States with a high share of value added in these sectors and rela-
tively small changes in it throughout the study (Figure 8).
Taking account of economic sectors, the highest share of enterprises using cloud
computing services was identified in IT & communication, real estate administration,
administrative and support, as well as utilities supply services. There are sectors whose
share in the value added slowly increases, although over the investigated period it was
clearly lower compared to the leaders (with the exception of real estate administration
services). On the other hand, the smallest share of companies using cloud computing
was found in construction and transport services as well as in agri-food and metal indus-
tries (Figure 9). These sectors report a decreasing share in the value added of economic
activities covered by the study.

 83
Figure 8
Changesintheshareofenterpriseswhobuycloudcomputingservicesused
overtheInternetbrokendownbyMemberStatein2010–2018
0
10
20
30
40
50
60
70
FI
SE
DK
NL
IE
UK
BE
MT
EE
HR
CY
EU28
CZ
SI
LU
PT
IT
LT
AT
DE
ES
SK
FR
HU
LV
EL
PL
RO
BG
Source: Eurostat.
Figure 9
Changesintheshareofenterpriseswhobuycloudcomputingservicesused
overtheinternetbrokendownbysizeandsectorofactivityin2010–2018
0
1
0
2
0
3
0
4
0
5
0
6
0
70
All enterprises
SMEs
L
arge enterprises
J58-63
ICT
M69-74
L68
N77-82
D35-E39
C19-23
C26-33
G45-47
I55
C24-25
F41-43
H49-53
C10-18
Source: Eurostat.
4. BigData
Another indicator of the inclusion of companies in the Industry 4.0 concept is Big
Data management. Big Data is defined as an extremely large volume of data that are
analysed with technology to show the patterns of human development or anything
related to society since Big Data leads to more precise analysis and thus helps in more

84
accurate decision making and more efficient work (Anshari and Lim, 2016). Big Data
technologies are providing unprecedented opportunities for statistical inference on
massive analysis, but they also bring in new challenges to be addressed (Talón-Ball-
estero et al., 2018). In response to the growth in digital data, Big Data is a term intro-
duced to describe information management and information processing involving data
of increasing volume, increasing complexity, increasing variety, and increasing velocity
(Fox and Do, 2013). Finally, Big Data is the next frontier for innovation, competition
and productivity (Manyika et al., 2011).
The biggest share of companies that analyse Big Data themselves can be found
in Malta, the Netherlands, Belgium, and Ireland (above 15%) (Figure 10). In this case,
however, growth dynamics is much more important, as it provides information on Mem-
ber States in which companies have engaged in business networking and use Big Data
analyses. In this ranking, Germany is the undisputable leader reporting growth of such
companies by 9 percentage points (from a mere 6% in 2016), followed by France and
Malta (5 percentage points each). Member States with the biggest share of companies
using Big Data, with the exception of Germany, are countries in which the share of the
examined sectors in total value added was relatively low in 2017, exhibiting, however,
a clearly growing trend in the investigated period.
The smallest proportion of companies carrying out Big Data analyses was identi-
fied in Latvia, Poland, Bulgaria, Hungary, Austria, Italy, and in Cyprus (below 9%). With
the exception of the last two, in these Member States the share of sectors covered by
the study was relatively high and did not change in recent years.
Figure 10
ChangesintheshareofenterprisesanalysingBigDatafromanydatasourcebroken
downbyMemberStatein2016–2018
0
5
10
15
20
25
MT
NL
BE
IE
FI
FR
LU
DE
UK
DK
LT
EL
PT
EU28
EE
ES
RO
HR
SI
SE
SK
CZ
LV
PL
BG
IT
HU
AT
CY
Source: Eurostat.

 85
When it comes to sectors of economic activity represented by companies which
analyse Big Data, their list includes utilities supply, transport, professional and science,
accommodation, and administrative and support services. Entrepreneurs from indus-
trial sectors conduct such analyses much more rarely (Figure 11).
Figure 11
ChangesintheshareofenterprisesanalysingBigDatafromanydatasourcebroken
downbysizeandsectorofactivityin2016–2018
0
5
10
15
20
25
30
35
All enterprises
SMEs
Large enterprises
J58-63
ICT
D35-E39
H49-53
M69-74
I55
N77-82
G45-47
C26-33
F41-43
C19-23
L68
C10-18
C24-25
Source: Eurostat.
5. Digitalintegrationofcompanies
withtheirexternalpartners
The final index that helps in assessing the readiness to embrace the Industry 4.0
concept is the degree of digital integration of companies with their external partners.
The index consists of indicators which, on the one hand, address advanced collabora-
tion formats consisting in having a business automatically linked to its suppliers or
consumers and, on the other hand, electronic invoicing. The leaders with the highest
share of companies exercising business processes automatically linked with external
partners are Germany, Lithuania, Belgium, Denmark, Finland, and Poland (above 20%)
(Figure 12), with the lowest share of companies automatically linked with their busi-
ness partners reported by Greece, Hungary, Romania, and Latvia (below 10%). Thus, we
may conclude that, for this particular indicator, the division into Member States with
a high or low share in the value added in the investigated sectors is not meaningful. In
both groups, we may identify Member States with a relatively low as well as very high
share and change dynamics in the structure of value added.

86
Figure 12
DigitalintegrationofenterpriseswithexternalpartnersbyMemberStates
0
20
40
60
80
DE
LT
BE
DK
FI
PL
HR
NL
EU28
LU
BG
ES
CY
PT
AT
EE
SI
SK
FR
SE
CZ
IE
UK
IT
MT
EL
HU
RO
LV
Enterprises whose business processes are automatically linked to those
of their suppliers and/or customers (2017)
Enterprises sending eInvoices, suitable for automated processing (2018)
Enterprises sending eInvoices B2BG, suitable for automated processing (2016)
Enterprises sending only paper invoices B2BG (2016)
Source: Eurostat.
Figure 13
Digitalintegrationofenterpriseswithexternalpartnersbrokendownbysize
andsectorofactivity
0
2
0
4
0
60
All enterprises
SMEs
Large enterprises
G45-47
ICT
J58-63
C19-23
C26-33
H49-53
C25-25
D35-E39
C10-18
I55
M69-74
N77-82
F41-43
L68
Enterprises whose business processes are automatically linked to those
of their suppliers and/or customers (2017)
Enterprises sending eInvoices, suitable for automated processing (2018)
Enterprises sending eInvoices B2BG, suitable for automated processing (2016)
Enterprises sending only paper invoices B2BG (2015)
Source: Eurostat.
Speaking of sectoral classification, the biggest share of companies whose business
processes are integrated with their suppliers or consumers was found in the processing

 87
industry, while the lowest in services (administrative and support services, construc-
tion and real estate activities), i.e., in sectors where EU-28 value added is relatively the
least relevant (Figure 13).
Conclusions
The research conducted has helped in grasping some trends in the readiness of
European companies to face the Industry 4.0 revolution. First, which seems obvious,
the degree of differentiation in this area in the European Union is very high across the
Member States and sectors: from extremely well prepared and clearly willing to get
engaged in the process to extreme reduction or even refraining from any activities
in the field of digitalisation.
Second, large enterprises are much better prepared to digital integration both
internally and in connection with suppliers and customers, including consumers. The
SME sector significantly lags behind in this classification, which suggests it should be
supported by targeted actions undertaken by the Member States and the EU. The goal
is to limit negative effects of the fourth generation industrial revolution which could
quite easily lead to the exclusion of SMEs. As a result, we might expect the creation of
two big conglomerates based on rather a restrictive EU antitrust policy.
Third, the group of Member States relatively well fitting the idea of Industry 4.0
includes countries in which manufacturing does not play a major role in generating
value added. It means that entrepreneurs from these Member States focus on the pro-
vision of services to typical manufacturing enterprises. It does not mean, however, that
the sector has completely lost in its relevance, as in many cases we can observe that
its importance is significantly growing. The Industry 4.0 concept should be thus seen
in a wider perspective, taking account of all economic actors: manufacturers, service
providers, suppliers of components and raw materials, as well as consumers. Thus, it
is not an idea that would promote a widely understood re-industrialisation of the EU;
it is a concept focused on using new digital technologies in the economy intended
to stimulate sectors in Member State economies whose relevance was less prominent.
Fourth, the group of Member States which reported a relatively high share of eco-
nomic sectors included in the study, above all manufacturing, performs less impres-
sively in terms of digital integration at internal and external levels, including digital
integration with consumers. Apparently, they have given up innovation because of their
relatively stronger standing when it comes to value added creation. Yet, the structure
slowly evolves to the disadvantage of traditional sectors, which means that in situations

88
of limited engagement in digitalisation and servitisation of the product offer they might
be squeezed out from the market.
Fifth, in some cases, a low share of companies engaged in digitalisation may result
from the profile of a given industry, in particular in service sectors or from the size of
companies; nevertheless, in the face of the Industry 4.0 revolution, it seems wrong
to remain outside of the new trend. In order to more precisely grasp the preparedness
of the European industry to the fourth industrial revolution, we need to conduct fur-
ther studies at the level of individual Member States and sectors.
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