Course outcome |
Learning and teaching Strategies |
Assessment Strategies |
On completion of this course, the students will be able to; CO 1.Apply analytics in problems related to human resource management. CO 2.Compare HR metrics and types of analytics in HR. CO 3.Analyse the HR effectiveness and its impact on employee life cycle & experience using analytics CO 4.Communicate data driven insights of HR analytics using data visualization techniques. CO 5.Implement predictive models and dashboards in HR CO 6.Evaluate the performances of predictive models. |
Approach in teaching: Interactive Lectures, Group Discussion, Tutorials, Case Study |
Class test, Semester end examinations, Quiz, Assignments, Presentation |
Learning activities for thestudents: Self-learning assignments, presentations |
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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.
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.
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.
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.
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.