HR Analytics & Digital Workforce

Component

Marks

Description

Mapped CO

Simulations

20

Sim 1 (10M): The Attrition Predictor. Sim 2 (10M): The Recruitment Bot.

CO2, CO3

Case Study

10

"Moneyball for HR": Analysis of data-driven talent decisions.

CO1, CO4

Presentation

10

"The Analytics Dashboard": Presenting workforce insights to the Board.

CO5

Mid-Term

10

Internal written exam covering Metrics & Predictive Models.

CO1

Project

10

"Churn Analysis": Using Excel/Python to identify flight-risk employees.

CO2

Participation

10

Active involvement in analytics labs.

All

Session

Topic

Pre-Reading (Guenole et al.)

Assignment / Case Study

1

Introduction to HR Analytics

Descriptive, Predictive, and Prescriptive analytics in HR.

Ch 1: The Journey to Value

Assignment: Classify 5 HR problems into analytics types.

2

The LAMP Framework

Logic, Analytics, Measures, and Process.

Ref: Boudreau & Ramstad

Task: Apply LAMP to a training ROI problem.

3

HR Data Quality & Governance

Cleaning dirty data and ensuring privacy (GDPR/DPDP).

Ch 2: Data Management

Assignment: Audit a sample employee dataset for errors.

4

Descriptive Analytics: Metrics

Headcount, turnover, time-to-fill, and cost-per-hire.

Ch 3: Descriptive Stats

Task: Calculate the "Cost of Vacancy" for a manager role.

5

Visualizing HR Data

Creating dashboards in Excel/Power BI for executive view.

Ch 9: Visualization

Project: Build a "Diversity Dashboard" from dummy data.

6

Recruitment Analytics

Analyzing sourcing channels and funnel efficiency.

Ch 5: Acquisition Analytics

Case Study: Google’s Project Oxygen.

7

Predicting Quality of Hire

Correlating pre-hire assessment scores with performance.

Ch 5 (Contd.)

Assignment: Calculate the correlation coefficient for hire data.

8

Mid-Term Internal Exam

Assessment of metrics and data visualization.

Review: Sessions 1–7

Assessment: Written Exam (10 Marks).

9

Engagement & Sentiment Analysis

Using NLP to analyze employee surveys and feedback.

Ref: Sentiment Analysis

Task: Analyze themes from a set of exit interview notes.

10

Predictive Analytics: Attrition

Building a logistic regression model to predict turnover.

Ch 6: Retention Analytics

Assignment: Identify top 3 predictors of churn in a dataset.

11

Simulation Lab 1: Attrition Predictor

Using data to identify flight risks and intervene.

Manual: Simulation Guide

Assessment: Simulation Performance Score (10 Marks).

12

Learning & Development Analytics

Measuring ROI of training (Kirkpatrick Level 4).

Ch 7: L&D Analytics

Case Study: Accenture’s Learning ROI.

13

Performance & Compensation Analytics

Pay equity analysis and comp-ratio modeling.

Ch 8: Total Rewards

Task: Conduct a Pay Equity Audit for a mock company.

14

Organizational Network Analysis (ONA)

Mapping informal influence and communication flows.

Ref: ONA Basics

Assignment: Draw a network map of your study group.

15

AI in HR: The Digital Workforce

Chatbots, robotic process automation (RPA) in HR Ops.

Ch 11: Emerging Tech

Task: Design a conversation flow for an HR FAQ bot.

16

Simulation Lab 2: Recruitment Bot

Configuring an AI tool to screen resumes without bias.

Manual: AI Recruitment Sim

Assessment: Simulation Performance Score (10 Marks).

17

Ethics in People Analytics

Algorithmic bias, surveillance, and employee trust.

Ch 12: Ethics & Privacy

Case Study: Amazon’s AI Recruiting Tool.

18

Building the Business Case

Calculating the financial impact of HR interventions.

Ch 10: Telling the Story

Assignment: Calculate savings from a 5% reduction in attrition.

19

Capstone Presentation

Presenting the "Analytics Dashboard".

Manual: Presentation Rubric

Assessment: Group Presentation (10 Marks).

20

Course Synthesis

The future of the "Quantified Employee".

Ref: Future Trends

Submission: Final Course Portfolio.