Foundation Data Science for HR Professionals

Programme Outline

Learning Objectives

1. Equip participants with the foundational understanding of the HR Analytics Function within an organisation
2. Train participants with the ability to understand the data cycle, from developing the business question to data cleaning, data selection, data analysis and data visualisation
3. Plan and develop the Strategic Workforce Model, and link it to performance and potential through the use of Excel Modelling Techniques and the use of Pivot Tables
4. Equip participants with skills to perform analysis, ranging from Financial HR to Correlation, Regression and ANOVA techniques
5. Train participants on the use of Visualisation Tools such as Power BI to develop dashboards for Data Storytelling.

Day 1

• Key technological trends happening in Industry 4.0 and importance of analytical skills
• Introduction to Data Science and types of HR Analytical Skills
• Introduction to Strategic Workforce Planning and data-driven decision making
• Performance Modelling using Excel Visualisation
• Introduction to the Balance Scorecard and HR Scorecard for developing KPIs
• Hands-on exercises

Day 2

• Data Analysis in Excel – Descriptive Statistics, Correlation, Regression, Multiple Linear Regression. Hands-on exercises using excel formulas to solve HR problems
• Introduction to the Linear Equation for predicting future costs
• Financial HR – ROI – Ratios for calculating payback period, cost of absenteeism, cost of turnover
• Utility Models for calculating ROI of recruitment tools

Day 3

• Data management
• Identify sources and different ways for data collection
• Execute data acquisition
• Perform data cleansing
• Prepare and transform data
• Project briefing

Day 4

• HR reporting and dashboards
• Introduction to storytelling
• Steps to data storytelling
• Different types of data visualisation
• Introduction to Power BI
  • Basic understanding of Power BI
  • How to create basic visualisation
  • Putting together a dashboard

Day 5

• Project Consultation – Half day
• Final Project Presentation – Half day

Assessment

• Short quizzes at the end of each class
• Class assignment from curating of data and to final presentation

Subject Credits

Upon completion and satisfying the requirements of passing this course, learners will be awarded 12 subject credits.