HR ANALYTICS AND DIGITAL TRANSFORMATION
Syllabus
EN
IT
Learning Objectives
This course, "HR Analytics and Digital Transformation," explores the integration of HR data analysis with digital transformation strategies to enhance organizational performance. Over six weeks, students will learn key concepts in HR Analytics, data collection and management, and advanced analysis techniques. The course also covers digital tools for talent acquisition, workforce planning, and optimizing HR processes. Emphasis will be placed on measuring the impact of HR initiatives and effectively communicating insights.
EDUCATIONAL OBJECTIVES:
The course aims to introduce the topic of HR analytics, understood both as an organizational variable that guides and influences people's behaviour and as a component of the technological assets available to companies. Students will be provided with interpretative models to appreciate this dual dimension.
KNOWLEDGE AND UNDERSTANDING:
By the end of the course, students will understand what is meant by HR Analytics, the tools available, and how they are used in a descriptive, predictive, and prescriptive perspective. They will also understand how HR Analytics integrates into human resource management and the trends in digital transformation. In a constantly innovating context, students are expected to understand the topics discussed, rather than memorize tools and concepts, which could quickly become obsolete. Consequently, a deep understanding of HR Analytics will enable students to tackle complex problems, even in a continuously changing environment.
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING
Through the acquired knowledge and understanding, students should be able to develop the skills and abilities necessary to undesratnd how HR Analytics integrates into human resource management and how they can enrich the task without depersonalizing it. By the end of the course, students will be able to plan, implement using appropriate tools, and use data analysis tools related to human resource management in various areas where they can contribute to HR management.
AUTONOMY OF JUDGMENT:
Students will be able to critically reflect on the role of HR Analytics systems and understand that such tools are not neutral but should be evaluated within a broader framework of organizational design. In particular, by the end of the course, students will be able to understand how the design of the HR Analytics system supports the design of human resource management. They will critically evaluate different tools and their impact on the organization.
COMMUNICATION SKILLS:
By the end of the course, students will be able to address the topic of HR analytics in written and oral form, using technical language appropriate to the interlocutors and the reference context. They will also demonstrate the ability to analyze even complex problems.
LEARNING SKILLS:
Students will achieve autonomy in learning about the evolution of HR analytics, using a study and research method suitable for deepening the knowledge acquired.
EDUCATIONAL OBJECTIVES:
The course aims to introduce the topic of HR analytics, understood both as an organizational variable that guides and influences people's behaviour and as a component of the technological assets available to companies. Students will be provided with interpretative models to appreciate this dual dimension.
KNOWLEDGE AND UNDERSTANDING:
By the end of the course, students will understand what is meant by HR Analytics, the tools available, and how they are used in a descriptive, predictive, and prescriptive perspective. They will also understand how HR Analytics integrates into human resource management and the trends in digital transformation. In a constantly innovating context, students are expected to understand the topics discussed, rather than memorize tools and concepts, which could quickly become obsolete. Consequently, a deep understanding of HR Analytics will enable students to tackle complex problems, even in a continuously changing environment.
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING
Through the acquired knowledge and understanding, students should be able to develop the skills and abilities necessary to undesratnd how HR Analytics integrates into human resource management and how they can enrich the task without depersonalizing it. By the end of the course, students will be able to plan, implement using appropriate tools, and use data analysis tools related to human resource management in various areas where they can contribute to HR management.
AUTONOMY OF JUDGMENT:
Students will be able to critically reflect on the role of HR Analytics systems and understand that such tools are not neutral but should be evaluated within a broader framework of organizational design. In particular, by the end of the course, students will be able to understand how the design of the HR Analytics system supports the design of human resource management. They will critically evaluate different tools and their impact on the organization.
COMMUNICATION SKILLS:
By the end of the course, students will be able to address the topic of HR analytics in written and oral form, using technical language appropriate to the interlocutors and the reference context. They will also demonstrate the ability to analyze even complex problems.
LEARNING SKILLS:
Students will achieve autonomy in learning about the evolution of HR analytics, using a study and research method suitable for deepening the knowledge acquired.
Prerequisites
None
Program
The course will be organized around six main topics. Each topic will be covered in one of the weeks of the course, progressively.
Week 1: Introduction to HR Analytics and Digital Transformation
We begin by defining HR Analytics and digital transformation, discussing their significance in modern organizations. We'll explore how HR Analytics integrates with digital transformation efforts, covering key concepts, terminology, and an overview of relevant tools and technologies.
Week 2: Data Collection and Management
In week two, we focus on types of HR data and sources, differentiating between qualitative, quantitative, structured, and unstructured data. We'll emphasize the importance of data quality, integrity, and ethics. Additionally, we'll discuss how digital tools and technologies can enhance data collection and management processes.
Week 3: Data Analysis Techniques
Week three delves into descriptive, predictive, and prescriptive analytics. Students will also learn the most important tools and HR analytics software. We'll also explore how digital transformation impacts data analysis, introducing advanced analytics and machine learning applications in HR.
Week 4: Talent Acquisition and Management
We will explore recruitment analytics, performance management, and factors affecting employee engagement and retention. Digital transformation's role in these areas will be examined, including the use of AI-driven recruitment tools, performance tracking software, and digital engagement platforms. Succession planning with a focus on future digital leadership needs will also be covered.
Week 5: Workforce Planning and Optimization
In week five, we analyze workforce composition, demographics, and labor market trends. Topics include strategic workforce planning, aligning workforce strategies with organizational goals, and ensuring optimal workforce levels through capacity planning. We'll also discuss how digital tools can optimize workforce planning and enhance decision-making processes.
Week 6: Measuring and Demonstrating Impact
The final week centers on measuring the impact of HR initiatives and digital transformation efforts. We will talk about key performance indicators (KPIs). Also we will focus on how to communicate data insights.
Week 1: Introduction to HR Analytics and Digital Transformation
We begin by defining HR Analytics and digital transformation, discussing their significance in modern organizations. We'll explore how HR Analytics integrates with digital transformation efforts, covering key concepts, terminology, and an overview of relevant tools and technologies.
Week 2: Data Collection and Management
In week two, we focus on types of HR data and sources, differentiating between qualitative, quantitative, structured, and unstructured data. We'll emphasize the importance of data quality, integrity, and ethics. Additionally, we'll discuss how digital tools and technologies can enhance data collection and management processes.
Week 3: Data Analysis Techniques
Week three delves into descriptive, predictive, and prescriptive analytics. Students will also learn the most important tools and HR analytics software. We'll also explore how digital transformation impacts data analysis, introducing advanced analytics and machine learning applications in HR.
Week 4: Talent Acquisition and Management
We will explore recruitment analytics, performance management, and factors affecting employee engagement and retention. Digital transformation's role in these areas will be examined, including the use of AI-driven recruitment tools, performance tracking software, and digital engagement platforms. Succession planning with a focus on future digital leadership needs will also be covered.
Week 5: Workforce Planning and Optimization
In week five, we analyze workforce composition, demographics, and labor market trends. Topics include strategic workforce planning, aligning workforce strategies with organizational goals, and ensuring optimal workforce levels through capacity planning. We'll also discuss how digital tools can optimize workforce planning and enhance decision-making processes.
Week 6: Measuring and Demonstrating Impact
The final week centers on measuring the impact of HR initiatives and digital transformation efforts. We will talk about key performance indicators (KPIs). Also we will focus on how to communicate data insights.
Books
The reference materials will be included directly in the online platform.
Bibliography
The additional materials will be included directly in the online platform.
Teaching methods
The course will be delivered as a distance learning course on an online platform. The course will include:
• Live and recorded lectures
• Case discussions and videos
• Talks with industry experts
• Live and asynchronous interactions on the course platform
• Assignments for students
• Q&A sessions
The course will be structured over six weeks, each organized around a main theme. There will be a total of at least six hours of teaching through web conference lectures (Instructional Teaching), and at least six hours of interactive teaching (participation in discussions, collaborative activities, and case studies). These discussions will be organized both synchronously and through asynchronous forum discussions. In particular, the interactivity of online discussion forums allows for in-depth learning, replacing seminar activities with the advantage of being organized iteratively and interactively, achieving better depth than a frontal seminar with limited possibilities for interaction between the instructor and each student.
Through personalized interaction and the possibility of asynchronous forum interaction, each student can engage in the most inclusive manner, even considering situations where the digital medium can prevent potential exclusion phenomena.
The teaching materials will be made available online in three main ways, depending on the type of material:
• Materials necessary for self-learning will be made available online at the beginning of the course.
• Support materials for interactive and instructional teaching will be made available weekly.
• Materials for in-depth case discussions will be made available during the course, with specific timings for each task, always allowing ample participation time for each student. For example, in the case of group work with an online presentation, the material may be made available online on day X, the presentation will be required 4 days later, and after another 4 days, further interaction will be required where different groups will act as discussants for each other, and so on.
• Live and recorded lectures
• Case discussions and videos
• Talks with industry experts
• Live and asynchronous interactions on the course platform
• Assignments for students
• Q&A sessions
The course will be structured over six weeks, each organized around a main theme. There will be a total of at least six hours of teaching through web conference lectures (Instructional Teaching), and at least six hours of interactive teaching (participation in discussions, collaborative activities, and case studies). These discussions will be organized both synchronously and through asynchronous forum discussions. In particular, the interactivity of online discussion forums allows for in-depth learning, replacing seminar activities with the advantage of being organized iteratively and interactively, achieving better depth than a frontal seminar with limited possibilities for interaction between the instructor and each student.
Through personalized interaction and the possibility of asynchronous forum interaction, each student can engage in the most inclusive manner, even considering situations where the digital medium can prevent potential exclusion phenomena.
The teaching materials will be made available online in three main ways, depending on the type of material:
• Materials necessary for self-learning will be made available online at the beginning of the course.
• Support materials for interactive and instructional teaching will be made available weekly.
• Materials for in-depth case discussions will be made available during the course, with specific timings for each task, always allowing ample participation time for each student. For example, in the case of group work with an online presentation, the material may be made available online on day X, the presentation will be required 4 days later, and after another 4 days, further interaction will be required where different groups will act as discussants for each other, and so on.
Exam Rules
The exam is the same for attending and non-attending students. It consists of a written exam, which focuses on theory questions, their applications, and discussions of short cases. The use of any source (notes, diagrams, books) or electronic media is not allowed during the exam. Study materials will be distributed on the course's platform
The grade will be communicated through the exam booking platform (Delphi). Moreover, the week following the exam, before the finalization of the records, a review session will be organized.
The grade will be communicated through the exam booking platform (Delphi). Moreover, the week following the exam, before the finalization of the records, a review session will be organized.