Digital hr and analytics
A.A. 2023/2024
Obiettivi formativi
The course Digital HR and Analytics aims to contribute to the MSc Management of Human Resources goals by offering research-grounded and practice-connected models to understand and manage the intersection of Human Resources Management (HRM) and technology. As the importance of digital technologies in people management has increased, so has the research on tools, processes, and theories related to digital HRM. Similarly, the relevance of advanced data analysis and techniques to enhance strategic decisions has also increased. However, in such a rapidly evolving scenario, developing a critical mindset toward the adoption of technologies is crucial in order to better understand the risks and benefits associated with digital HRM. Therefore, by engaging in this course, students will develop a comprehensive understanding of both the positive and negative impacts of digital technologies and HR analytics on HRM systems. They will also have the opportunity to critically reflect on the evolving role of the HR function in addressing the managerial challenges posed by these transformative changes.
Risultati apprendimento attesi
At the end of this course, students will be able to:
1) Illustrate the main perspectives in the research on technology and HRM (tool, proxy, and ensemble view of technology)
2) Critically debate the relationship between e-HRM and the strategic role of the HRM function by adopting a resource-based view approach.
3) Identify success factors and steps in the implementation of digital HRM systems processes
4) Distinguish between descriptive, predictive, and prescriptive HR analytics
5) Apply the Job Characteristics Model to analyze how the adoption of information technology affects job design.
6) Describe the impact of social media and Artificial Intelligence adoption on the main HRM practices (e.g., attraction, recruitment and selection, training and development).
7) Illustrate virtual teams' challenges and related possible solutions
8) Recognize sources and mechanisms of digital leadership
9) Examine workforce data and use that information to design adequate HRM initiatives
10) Identify the various types of HR analytics useful for measuring the effectiveness of HRM practices implementation.
1) Illustrate the main perspectives in the research on technology and HRM (tool, proxy, and ensemble view of technology)
2) Critically debate the relationship between e-HRM and the strategic role of the HRM function by adopting a resource-based view approach.
3) Identify success factors and steps in the implementation of digital HRM systems processes
4) Distinguish between descriptive, predictive, and prescriptive HR analytics
5) Apply the Job Characteristics Model to analyze how the adoption of information technology affects job design.
6) Describe the impact of social media and Artificial Intelligence adoption on the main HRM practices (e.g., attraction, recruitment and selection, training and development).
7) Illustrate virtual teams' challenges and related possible solutions
8) Recognize sources and mechanisms of digital leadership
9) Examine workforce data and use that information to design adequate HRM initiatives
10) Identify the various types of HR analytics useful for measuring the effectiveness of HRM practices implementation.
Periodo: Terzo trimestre
Modalità di valutazione: Esame
Giudizio di valutazione: voto verbalizzato in trentesimi
Corso singolo
Questo insegnamento non può essere seguito come corso singolo. Puoi trovare gli insegnamenti disponibili consultando il catalogo corsi singoli.
Programma e organizzazione didattica
Edizione unica
Responsabile
Periodo
Terzo trimestre
Programma
The Digital HR & Analytics course is structured around three main modules. The first module focuses on the digital transformation of the HR function and describes how technology affects the work performed within HR and its role within the company. It will present the main theoretical approaches to explain the changes and challenges affecting digital HR.
The second module covers various e-HRM functional areas, such as e-recruitment, e-selection, e-learning, and e-performance management. It will explore the success factors for designing and managing these areas effectively.
Finally, the last module introduces the main managerial challenges in digital HR including e-leadership, and managing virtual teams. Throughout the course, analytics concepts and methodologies will be integrated into the three modules to provide practical examples and applications to real digital HR problems.
The second module covers various e-HRM functional areas, such as e-recruitment, e-selection, e-learning, and e-performance management. It will explore the success factors for designing and managing these areas effectively.
Finally, the last module introduces the main managerial challenges in digital HR including e-leadership, and managing virtual teams. Throughout the course, analytics concepts and methodologies will be integrated into the three modules to provide practical examples and applications to real digital HR problems.
Prerequisiti
Preliminary knowledge of Human Resource Management, Human Resources Information Systems, and Organizational Behavior is recommended.
Metodi didattici
The course is conducted through traditional lectures, small group activities, problem-based learning, case studies, and testimonials from HR professionals or managers
Materiale di riferimento
Required Course Materials for attending and non-attending students: Due to the fast-evolving nature of the subject taught in this course, an updated list of references for attending students and recommended further readings for non-attending students will be provided at the beginning of the course. This will enable students to gain a deeper awareness and understanding of each topic.
Modalità di verifica dell’apprendimento e criteri di valutazione
For attending students, the achievement of the expected learning outcomes will be assessed through:
1) a group project work on network analysis in a workplace setting and the design of HR activities to solve issues emerging from the analysis. Through the project work, each group will receive a mark from 0 to 30 cum laude.
2) a written test consisting of 15 multiple-choice questions (MCQs) and 3 open-ended questions. Regarding the MCQs, there will be only one correct answer, and one point will be awarded for each correct answer (zero points for each wrong or missing answer). For each open-ended question, the student will receive a grade from 0 to 5. The final grade of the test (sum of the grade in the MCQs test + grade of the open-ended questions) will range from 0 to 30 cum laude. The student will have 1.5 hours to complete the test.
The final mark will be the weighted average between the group project work evaluation (30%) and the individual final test (70%).
For non-attending students, the achievement of the expected learning outcomes will be assessed through a written test as described above.
1) a group project work on network analysis in a workplace setting and the design of HR activities to solve issues emerging from the analysis. Through the project work, each group will receive a mark from 0 to 30 cum laude.
2) a written test consisting of 15 multiple-choice questions (MCQs) and 3 open-ended questions. Regarding the MCQs, there will be only one correct answer, and one point will be awarded for each correct answer (zero points for each wrong or missing answer). For each open-ended question, the student will receive a grade from 0 to 5. The final grade of the test (sum of the grade in the MCQs test + grade of the open-ended questions) will range from 0 to 30 cum laude. The student will have 1.5 hours to complete the test.
The final mark will be the weighted average between the group project work evaluation (30%) and the individual final test (70%).
For non-attending students, the achievement of the expected learning outcomes will be assessed through a written test as described above.
Docente/i
Ricevimento:
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