Master
2022/2023
People Analytics: Prediction of Performance & Prescription of Policy
Type:
Elective course (Management and Analytics for Business)
Area of studies:
Management
Delivered by:
Department of Management
When:
2 year, 1, 2 module
Mode of studies:
offline
Open to:
students of one campus
Instructors:
Louisa Selivanovskikh
Master’s programme:
Management and Analytics for Business
Language:
English
ECTS credits:
3
Contact hours:
24
Course Syllabus
Abstract
This practice-oriented course focuses on effective People Analytics as a source of business value creation in the context of Big data. The core objective is to explore how to efficiently integrate data analytical approaches to each stage of the strategic human resource management process, from the acquisition to the retention of qualified workers. Throughout the course, examples for each People Analytics Success stage will be provided to help illustrate the key concepts to effective HRM.
Learning Objectives
- Develop high-impact People Analytics in order to generate business value from the Big Data and little data available to the organization.
- Identify types of people analytics used in a company.
- Obtain valuable people analytics to improve the efficiency of workforce planning, hiring, placing and retaining the best employees.
- Choose relevant data science methods for specific problems in human resource (HR) management.
- Analyze outcomes of HR practices and identify their effects on both the staff members’ attitudes toward the company and the organizational performance.
- Explain how data-driven decision-making affects organizational performance and HR practices.
Expected Learning Outcomes
- Able to develop his/her intellectual and cultural level, build a trajectory of career development
- Able to identify the data required for the solution of research tasks in management; to gather data from both the field research and desk research as well as from the social and economic sources
- Able to prepare and manage the consultancy project.
Course Contents
- Workforce Planning Analytics
- Analytics for onboarding
- Employee Engagement Analytics
- Retention Analytics
- Employee Wellness, Health, and Safety Analytics.
- Qualitative comparative analysis
Assessment Elements
- Class activities
- Online test
- Presentation: Individual-based project “Examining the role of strategic HRM practices using fsQCA"
- Report: Individual-based project “Examining the role of talent management practices using fsQCA"
Interim Assessment
- 2022/2023 2nd module0.3 * Online test + 0.2 * Presentation: Individual-based project “Examining the role of strategic HRM practices using fsQCA" + 0.2 * Report: Individual-based project “Examining the role of talent management practices using fsQCA" + 0.15 * Class activities
Bibliography
Recommended Core Bibliography
- Isson, J. P., & Harriott, J. (2016). People Analytics in the Era of Big Data : Changing the Way You Attract, Acquire, Develop, and Retain Talent (Vol. 1). Hoboken: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1226538
Recommended Additional Bibliography
- Edwards, M. R., & Edwards, K. (2019). Predictive HR Analytics : Mastering the HR Metric (Vol. 2nd Edition). New York: Kogan Page. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2037089
- Fitz-enz, J., & Mattox, J. (2014). Predictive Analytics for Human Resources. Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=812792