## 1 Introduction  
The current business environment determined by globalization and the advent of the Industry 4.0 concept [1; 2; 3; 4; 5], where key changes are mainly related to systems, inter-machine relationships, and machine-people relationships [6; 7; 8; 9; 10], requires a high degree of focus on the development of disposable human resources and their competences [11; 12; 13] in an effort to ensure competitiveness. Industry 4.0 systems are primarily based on new supporting technologies such as adaptive robotics [14], cybernetic physical systems (CPS) [15], cloud technologies [16], virtualization technologies, etc. [17]. The importance of the integrated enterprise concept in terms of competitiveness and sustainability is increasing in connection with the implementation of the Industry 4.0 concept and the emergence of both inter-company networks and open and knowledge-based systems in organizations [18; 19; 20; 21], where the effective acquisition, processing, storage, and sharing of key information is a predictor of success. The creation of such a knowledge database is then the basis for a quick search and obtaining of variables. However, we must be careful when entering the data, and confidentiality must be taken into account before any addition to the database. At the time of digitization, the potential of big data analysis [22; 23; 24; 25; 26] is a topic of expert discussions of the human resources community, because organizations have a wealth of information at their disposal, including employee demographic data, recruitment data, key performance indicator (KPI) metrics, etc. Based on a knowledge database, human resource professionals can make more objective recruitment decisions, reduce adverse effects from employee performance, support employees with a higher likelihood of loyalty to the company, or effectively train employees in line with current needs. In an effort to meet the expectations of customers and employees, businesses are deploying intelligent features into all internal systems to create the necessary flexibility and capacity. Simple and monotonous processes are automated, while other processes become more complex and interrelated. As a result, the requirements for the competence profile of available human capital are changing. In connection with the advent of Industry 4.0, changes in the requirements for both professional and personal characteristics necessary to perform work tasks can, thus, be expected [27]. Surveys carried out to this effect indicated a priority focus on areas for _personal competencies_ (ability to act autonomously on specific incentives), _social/interpersonal competences_ (ability to communicate and collaborate with other employees and groups), _competencies necessary for immediate realization of ideas_ (ability to translate ideas into practice), _professional competencies_ (ability to find and use specific knowledge at work, process understanding, information technology (IT) security understanding) [28], _methodological competencies_ (e.g., creativity, problem solving, analytical thinking), and _personality competences_ (e.g., flexibility, motivation to learn, ability to work under pressure) [29]. The concept of so-called learning organization and the associated effective knowledge sharing seem to be an ideal approach to acquiring key competences of disposable human resources, while digitization itself and digital systems and applications provide optimal tools that can be used for this purpose. The solution for remote storage and data availability is provided by the cloud computing system [30]. The role of knowledge workers in the use of IT tools in an effort to remove the boundaries between firmly defined organizational units for the benefit of the overall information flow is becoming increasingly important. In this context, digitization has a significant impact in alternative work regimes, especially when working from home with connections to business systems.