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The work performed by controllers changes over time, and due to technological evolution. Consequently, the controller competencies and academic formation to work change too. Therefore, this research aim was to answer: What is the required level of preparation of accounting and controlling graduates to handle the controller's role and tasks? To answer this question was realized an empiric research, where 32 graduates answered a survey, and it was collected 359 job advertisements. The job advertisement was analyzed using data mining applying phyton, and it was used descriptive statistics for the survey, both data set were compared using data visualization. The result demonstrated that a controller requires a set of controlling, interdisciplinary, methodological, socio-personal, and digital competencies. Obtaining these competencies are through business administration study or vocational training in business. digital competencies are not yet in demand by employer, except for business intelligence. The graduates do not master digital competencies. These findings can serve as a basis for the improvement of the curricula on which the controller training process is based.
Artificial Intelligence and Data Science are transforming the businesses of today, and it is contributing significantly in Human resource management as well. Data science has paved the way to workforce analytics or people analytics, and Artificial Intelligence is supporting the HR department in various human resource management processes. Through this study, the author is exploring the impact of Artificial Intelligence and Data Science in Human Resource Management by analysing the underlying opportunities, challenges, and threats. It also focuses on recommending the skills, competencies, and capabilities that will be required by the HR department in the future to implement AI and Data Science systems. The review of the literature and expert interviews form the base for the research findings and recommendations. Furthermore, the study covers insights about the application of AI and Data Science tools and techniques in processes such as recruitment and selection, onboarding, performance management, employee engagement, training and development, and strategic decision making. Finally, the thesis concludes by addressing the practical implications, limitations, and the scope for future research.
The purpose of this research was to provide a list of the most relevant competencies that Supply Chain and Operations managers would need to effectively lead their employees in times of the Digital Transformation. To determine these competencies, interviews were conducted with 15 subject-matter experts, who were also asked to answer a questionnaire, and results were triangulated with information gathered though a job-ad analysis consisting of a sample of 260 job ads. The results showed twelve competencies to be most important: Managing change, Interpersonal skills and emotional capabilities, Effective communication, Technological savvy, Analytical thinking, Big picture and strategic thinking, Leading others, Teamwork and collaboration, Talent development, Critical thinking and problem-solving, Creativity, and Negotiation and persuasion skills.