HR Analytics for Human Resource Management

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What Will You Learn?

  • Learn how to use Microsoft Excel to design and automate the calculation of key HR metrics.
  • Develop interactive HR dashboards and gain a clear understanding of various chart types available in Excel.
  • Build strong proficiency in Excel data management tools such as sorting, filtering, data validation, and data import techniques.
  • Leverage Pivot Tables along with filtering and sorting features to summarize HR data and extract meaningful insights.
  • Apply predictive machine learning techniques, including simple and multiple linear regression, to solve real-world HR challenges.
  • Gain a solid understanding of essential Excel formulas commonly used in HR Analytics.
  • Master widely used lookup functions in Excel, including VLOOKUP, HLOOKUP, INDEX, and MATCH, to efficiently retrieve and analyze data.

Course Content

HR Analytics Introduction

  • Introduction to HR Analytics
  • What is HR Analytics
  • What you will Learn in this Course – Overview

Basic Excel Knowledge

Different HR Metrics
measures such as employee turnover rate, time-to-hire, cost-per-hire, employee engagement, absenteeism, and performance metrics. Learn how to analyze and interpret these indicators using real-world data to identify trends, improve productivity, and support strategic HR planning. By mastering these metrics, you will be able to make data-driven decisions that enhance overall organizational effectiveness.

Importance of Excel Charts & Dashboard

Excel Dashboard – Case Study
An HR dashboard is a visual tool that consolidates key workforce data into a single, easy-to-understand view. It helps track important metrics such as recruitment, employee performance, attrition, and attendance in real time. By presenting data through charts and summaries, HR dashboards enable quick analysis and informed decision-making. They play a crucial role in improving transparency, monitoring trends, and supporting strategic HR initiatives efficiently.

Understanding Pivot Table and Pivot Charts
Learn how to use Pivot Tables and Pivot Charts to quickly analyze and summarize large HR datasets. Pivot Tables help you organize data, calculate totals, averages, and percentages, and identify patterns with ease—without complex formulas. You can filter, sort, and group data to gain meaningful insights. Pivot Charts complement this by visually representing the summarized data through graphs, making it easier to interpret trends and comparisons. This skill is essential for HR professionals to transform raw data into actionable insights and create dynamic, interactive reports for better decision-making.

Case Study – HR Dashboard
HR Dashboard Formatting

Case Study for Problem Statement
Problem Statement Example, designing Solution to IT and performing Analysis.

Predictive Analysis & Types of Statistics
Gain a foundational understanding of predictive analysis and key statistical concepts used in HR analytics. This module introduces how historical data can be used to forecast future outcomes such as employee turnover, hiring success, and performance trends. Learn essential statistical methods including descriptive, inferential, and predictive statistics, along with concepts like mean, median, correlation, and regression. By understanding these techniques, you will be able to interpret data accurately, identify patterns, and make informed, data-driven decisions that support strategic workforce planning and business growth.

Making Data Ready for Regression Analysis
Learn how to prepare and structure data effectively for regression analysis. This module covers key steps such as data cleaning, handling missing values, removing duplicates, and transforming variables into the right format. Understand the importance of selecting relevant features, encoding categorical data, and checking for outliers and assumptions. By making your data analysis-ready, you ensure more accurate models and meaningful predictions, enabling better decision-making in HR analytics.

Creating Final Regression Model using the Data
Learn how to build a robust final regression model using prepared data to generate accurate predictions and insights. This module guides you through selecting the right variables, splitting data into training and testing sets, and applying regression techniques such as simple and multiple linear regression. Understand how to evaluate model performance using metrics like R-squared, adjusted R-squared, and error measures. You will also learn to check key assumptions, avoid overfitting, and refine the model for better accuracy. By the end, you will be able to interpret results confidently and use your regression model to solve real-world HR problems, such as predicting employee attrition, performance outcomes, and workforce trends for smarter decision-making.

Final Quiz and Certification

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