Human Resources (HR) Analytics

26 - 28 August 2019 | Kuala Lumpur
Book Your Seat Today!

Kindly advise me your company detail and our consultant will contact you soonest!

Course Objectives

  • Uncover data-driven insights using analytics skills that aid in strategic decision making & reporting
  • To raise the level of competency of HR professionals in the use of analytics
  • Measuring key parameters throughout the HR function across all metrics
  • How to apply HR analytics to a broad spectrum of human capital activities and linking them to workforce analytics
  • Make HR analytics part of your HR strategy to predict pr anticipate the changes
  • End to end value proposition of HR Analytics and key stages of HR Analytics project
  • How to build interactive dashboard for better illustration and engagement with key business metrics
  • How to use statistical concepts for problem solving and decision making. Also solve various HR and Business challenges using analytics techniques

Description

  • Distinct source of competitive advantage
  • Optimize organizational performance & delivery
  • Faster turnaround time & improved decision making
  • Empowering managers & functional needs
  • In-depth insights through metrics that matter using interactive dashboards

Target Audience

HR Directors, HR Managers, CHROs, Senior Management Staff, HR Business Partners and all those HR professionals who want to solve various HR problems by leveraging HR analytics for data driven decision making.

Training Outline

Day 1

Getting Started to Human Resource (HR) Analytics

Introduction:

  • HR Analytics Maturity Model
  • Employee Lifecycle (ELC) Model
  • People Analytics Cycle
  • Data Analytics

Be Friend with Data Set

Data Understanding and Data Cleaning:

  • Data and Variables
  • Data Errors, Missing Values and Outliers

Discover the Data Set

Exploratory Data Analysis:

  • Data Visualization
  • Interaction between Variables – Which recruitment source is better?
  • Hypothesis Testing between Groups – Why is employee engagement low?

Integrate with Data Set

Regression Analysis:

  • Dummy Variables
  • Linear Regression – Analyze the employee salary
  • Models Selection
  • Results Interpretation
Day 2

Meeting More Data Sets

Data Merging and Data Transformation:

  • Getting Data Together – Join Data
  • Revise: Exploratory Data Analysis

Predict using Data Set

Classification – Logistic Regression:

  • Data Validation
  • Logistic Regression – Study the employee performance
  • Performance Evaluation
  • Result Interpretation
Day 3

Solve HR Issues using Data Set

Classification – More Models and Case Studies

  • Factor Analysis – Causes of employee attrition (retention)
  • Cross Validation
  • Tree-based Methods
  • Bayes Classifier
  • Neural Network
  • Other Models

More to Go

Extend Exploration:

  • Clustering Analysis
  • Principal Component Analysis
  • Text Analytics
  • Towards Automation

Prerequisite

No prior analytics or statistics knowledge is required
Basic proficiency in Microsoft Excel would be an advantage