*4.2.3 The recruitment, retention, and attraction of new talents*

The fourth revolution required a highly-skilled workforce to be implemented, developed, used and maintained. As a result, a wide range of industries needs a certain level of cooperation between machines and workers. If Industry 4.0 implies this tendency, it also underlines the growing trend of Google, Apple, Facebook, Amazon, Microsoft (GAFAM) to conquer traditional industries in which they have the necessary knowledge and capacities to become undisputable competitors in multiple fields [49]. As an example, we can remember the creation of the Google autonomous car, the collaboration between the Volkswagen group with Amazon web services to collect and analyze its industrial data and becoming a major global leader of the automotive industry, and even the collaboration between Apple and General Electric (GE) to create new applications for the internet of things (IoT) platforms that benefit to GE industries purposes thanks to IOS (exploitation system owned by Apple) opportunities. Industry 4.0 increases competition, in traditional industries and markets (but not only), which seems to be overwhelmed regarding the fast spread of the fourth industrial revolution. To overcome these challenges, companies must recruit high skilled workers, implementing continuous reskilling, learning, and training programs in their HR policies [44]. Besides, one of the major HR issues is constituted by the launch of retention practices which will reduce the diffusion of confidential business information and enhance efficiency and profitability by staying competitive at the same time. We can understand that the rise of high skilled workers' demand would create a danger if it is not associated with HR policies to enhance workforce abilities to work in a new smart and autonomous workplace.

#### *4.2.4 The adaptation to change*

One major issue to face urgently for HR function is the resistance to change. According to Deloitte [50] report, 17% of their interviewees are ready to manage working environments composed of people, robots, and AI interacting together when 60–70% will fail because they do not manage the adaptation to change properly. Also, Dhanpat et al. [35] confirmed this problem. They have shown that some employees can be resistant to change by being afraid of losing their jobs and being replaced by machines. Bonekamp et al. [51] also agree on the fact that the introduction of Industry 4.0 led to the suppression of standardized tasks by smart and autonomous systems. As a consequence, strong pressure is put on HR managers who require highly skilled people, to train employees and manage to dismiss workers for whom their tasks will be replaced by smart technologies to gain efficiency and competitiveness in the global market. In 2016, The World Economic Forum (WEF) already raised awareness by making an announcement before the opening of the Davos forum: around 5 million jobs in 5 years will be suppressed within 5 years in the main global economies [52]. It is necessary for the HR function globally to answer and react to the exponential expectations of the fourth industrial revolution by taking into account its effect on the global workforce demand and its impact on the global economy and competitiveness.

#### **4.3 Big data challenges (storage, RGPD, societal challenge)**

The fourth industrialization reveals new challenges in business activities such as the management of Bigdata and cybersecurity. Multiple obstacles to Industry 4.0 remain redundant: The constraints are numerous because the digitization of the industry poses formidable problems of standardization and cybersecurity [52].

Indeed, through their researches, one of the major challenges implied by this concept in the working environment is the deployment of Big Data, which creates a growing need to provide a legal framework for the protection of personal data and private life. Among the different cyber issues reported in Industry 4.0, the Deloitte report [50] identifies the top 10 cyber threats and their major data protection concerns.

Indeed, if legal restrictions increase to manage big data challenges, the different issues persist. In terms of an international legal framework, the ISO norm ISO/IEC 27001 defines the data security management for sensitive subjects such as financial, intellectual proprietary, employees, or even data entrusted to another company in the context of business activities. This norm is also called "Management systems of Information security" [53]. In addition, the European Union has implemented the General Data Protection Regulation (GDPR) to mitigate different kinds of challenges affiliated with the management of Big Data. GDPR regulations refer to "imposing a legal framework on the processing of personal data" [54].

However, despite the willingness to build an international legal framework to reduce risk related to Big data cybersecurity, there are still a long-ways to go for a proper framework of Industry 4.0. For instance, Deloitte report has shown that one out of four firms is not developing, implementing, or documenting the industrial cybersecurity (ICS) specific policies and procedures, and more than 33% of manufacturers have not performed any cyber risk assessments specifically focused on the ICS operating on their shop floors, resulting in a potentially significant risk to their operations [55].

In terms of internal management, other issues can arise when a company starts using big data analytics in order to grow. The challenges to take into account include the lack of proper understanding of big data, and therefore, proper usage of the latter; data growth issues, or, "what do I do with this much information?" because

*Evolution of Industry 4.0 and Its Implications for International Business DOI: http://dx.doi.org/10.5772/intechopen.101764*

the collection of such an amount of data must be useful for something. But what, exactly? Another issue is the confusion when selecting a Big Data tool. There is an increasing number of tools available on the market for firms to have reports and data concerning their businesses. However, it is often not very precise and easy when one is not really aware of what is best for them. This last point brings us to another issue which is the lack of professional expertise in the field of Big Data. Indeed, more and more companies are recruiting professionals and experts in the field of data, such as data scientists, engineers, and analysts. These professions are rare, and as the demand and supply rule confirms, it is quite costly for a firm to recruit, though it is a must when expecting to grow, especially in our current globalized market.
