HR Analytics

Paper Code: 
MBB 425
Credits: 
4
Contact Hours: 
90.00
Max. Marks: 
100.00
Objective: 

Course Objectives: The objective of this course is to

  1. Develop data driven skills in students. The course will
  2. Enable students to apply analytical tools in understanding the employee behavior.

 

Course Outcomes (COs):

 

Course

Course outcome (at course level)

Learning and teaching strategies

Assessment Strategies

Paper Code

Paper Title

CLO 174.Apply analytics in problems related to human resource management.

CLO 175.Compare HR metrics and types of analytics in HR.

CLO 176.Analyse the HR effectiveness and its impact on employee life cycle & experience using analytics

CLO 177.Communicate data driven insights of HR analytics using data visualization techniques.

CLO 178.Implement predictive models and dashboards in HR

CLO 179.Evaluate the performances of predictive models.

 

Approach in teaching:

Interactive Lectures, Group Discussion, Tutorials, Case Study

 

Learning activities for the students:

Self-learning assignments, presentations

Class test, Semester end examinations, Quiz, Assignments, Presentation

MBB 425

 

HR Analytics

 

 

18.00

Introduction to HR Analytics: Evolution of HR analytics, challenges with HR Analytics, strategic focus on HR Analytics; Common pitfalls of HR Analytics; HR analytics process and skill-set needed in HR analytics team, LAMP framework.

18.00

Approaches to Data Analytics: Current approaches to measuring HR; Strategic HR metrics versus Bench marking; HR scorecards & workforce scorecards; Types of analytics in HR- descriptive, predictive and prescriptive; HR analytics framework

18.00

Dynamics of HR Metric: People analytics cycle, employee lifecycles and employee experiences, performance- and succession management; Agile framework; HR value chain; Metrics to measure HR effectiveness; Factors driving employee turnover, link between engagement and performance; Competitive edge and HR analytics.

18.00

Data Mining Techniques: Data analysis, data visualization techniques and effective utilization using tools; Common pitfalls associated with data visualization; Driving insights out of HR analytics.

18.00

Decision Making Based on Analytics: Data driven culture in an organization; Implementation of predictive modelling; Importance of predictability in fulfilling strategic objectives; Effective HR dashboards.

Essential Readings: 

*Case studies related to entire topics are to be taught. Hands on Training on the application of analytics in the areas of recruitment, performance management, compensation management, competency building; learning and development; employee motivation / satisfaction; employee attrition/ separation.

 

 

References: 

  • Edwards, M. & Kirsten Edwards, K. (2016). Predictive HR Analytics: Mastering the HR Metric. Kogan Page.
  • Isson, J.P. Harriott& J.S. (2016). People Analytics in the Era of Big Data: Changing the Way You Attract, Acquire, Develop, and Retain Talent. John Wiley & Sons.
  • James, E.R. (2017). Business Analytics. UK: Pearson Education Limited
  • Van, Wieren S. (2017). Quantifiably Better: Delivering Human Resource (HR) Analytics from Start to Finish. Technics Publications LLC

 

 

Academic Year: