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Digitalization is one of the fundamental pillars of Industry 4.0. Within smart factories, Big Data Analytics systems play a key role in supporting the decision-making process of various stages of business processes. In this context, this research aims to identify solutions able to process large volumes of data from digital business processes with the final goal of adding value to the organisation. More specifically, the research deals with the implementation of a digital manufacturing tool able to digitize the workforce management process. The research has been applied in the case study of an Italian manufacturing company operating in the leather goods sector through the digitalization of the workforce management by a cloud-based platform. The implementation of the tool increases the efficiency of the production process, provides efficient management and integrates workforce data into one system. The implemented tool generates a large volume of data, the final goal is to make data user-friendly to support business decisions. Digitisation provides an exchange of information to support managers to make confident decisions. [ABSTRACT FROM AUTHOR]

Organizational policy that governs promotion, retention, and hiring practices is critical to a firm's human resource management strategy. The policies implemented by firms will vary based on the available supply of qualified employees. As organizations become increasingly reliant on technology and data, their need for specialized and skilled employees also increases. Further, the market for technologically skilled workers continues to become more competitive and in turn, hiring and retaining qualified, skilled, and experienced employees becomes increasingly difficult. Organizations will likely have to alter their human resources management strategy to maintain their required talent pool. Analyzing the hiring, retention, and promotion structures within an organization, this research investigates the effects of limiting the population of low-density, skilled employees available for an organization to hire. Representing a more competitive talent marketplace and talent pool, the goal of this research is to understand how employee retention strategies, incentives, and internal promotion policy can be altered to achieve desired manning levels within these highly skilled disciplines. Leveraging a system dynamics model, this study builds an interactive simulation tool allowing policy makers to view the potential outcomes of their policy decisions. System dynamics models the underlying system structure providing insight into variable interaction, causal relationships, and system behavior. The outcomes of this simulation will allow policy makers to identify differences in policy outcomes, reveal potential policy leverage points, and make more informed policy decisions. [ABSTRACT FROM AUTHOR]

This paper presents the importance of the human factor in digital transformation. More specifically, it presents this on the case of Southeastern European telecommunications company. Modern age brought customers with highest expectations ever, but also new and agile competitors. Existing companies have to adopt modern technologies and train their employees to use them in the most efficient way possible, in order to keep their step in a competitive market. [ABSTRACT FROM AUTHOR]

Workforce management is one of the most important factors in the success of any company that provides its customers with services. Hence, in order for the company to achieve objectives like customer satisfaction and maximum resource utilization, there is a need to have a reliable means of efficiently managing the company workforce and making sure that the produced plan always gives a good choice when it comes to assigning the available technicians to the given jobs. As the quantity of services and the workforce grow, the use of an automated workforce management system becomes inevitable. However the automated workforce management system should allow full transparency to allow the user to interact with the generated plans. In addition, the workforce management systems face high levels of uncertainties when dealing with real-world scenarios, which necessitates employing systems, which are able to handle the linguistic and numerical uncertainties available in the real-world scenarios. Fuzzy Logic Systems (FLSs) are credited with providing transparent methodologies that can deal with the imprecision and uncertainties. However the vast majority of the FLSs employ the type-1 FLSs, which cannot directly handle the high levels of uncertainties. Type-2 FLSs which employ type-2 fuzzy sets can handle such high levels of uncertainties to give very good performances. In this paper, we will present a type-2 FLS based workforce management system that is being developed for a delivery unit in British Telecom (BT). We will show how the presented system was able to handle the faced uncertainties to give very good performance that outperformed the automated non-intelligent system and the type-1 FLSs based system. [ABSTRACT FROM PUBLISHER]