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Professional HR Data Analyst - Virtual Learning

Professional HR Data Analyst - Virtual Learning

Why Attend

Data is crucial for any business. This is not an argument anymore, but rather a matter of fact. Therefore, HR professionals need to develop their data analysis competency in order to inform and transform their current HR practices and most importantly, business decisions.

This course offers participants a hands-on approach on analyzing HR-related data in areas like workforce planning, performance management, diversity and inclusion, learning and development, recruitment, retention, leadership, and employee engagement.

This data-driven approach ensures that HR professionals bring high-value input to people-related decisions and shape the future of their organizations using a scientific and unbiased approach. 

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Course Methodology

This workshop is designed to be interactive and practical. It includes various learning methodologies that enable participants to immediately implement all the tools they learn during the workshop.

Case studies from the best multinational companies followed by discussion sessions dominate the learning methods in this course which aims at strengthening participants’ analytical skillset. In addition, mindset-changing will build participants’ conviction about the paramount importance of data in all aspects of HR practices. 

Course Objectives

By the end of the course, participants will be able to:

  • Demonstrate deep understanding of the use of data analytics in HR disciplines
  • Implement data analytics tools and strategies to improve recruitment decisions, and predict employee turnover
  • Analyze the impact of learning and development provision on employee motivation using linear regression
  • Predict employee performance using data from employee engagement surveys
Target Audience

This course is targeted at HR professionals from all practices: learning and development, talent management, organization development, workforce planning, performance and rewards. HR business partners, and generalists would also benefit greatly from this workshop. 

Target Competencies
  • Data analysis
  • Decision making
  • Recruitment and selection
  • Employee engagement
  • Performance management
  • Learning and development
Course Outline
  • Data-driven HR analytics
    • Definition of HR analytics
    • The analytics process – using data to influence business decisions
      • Data
      • Metrics
      • Analytics
      • Action
    • Information sources – HR data are not only found in HR departments
    • The most commonly used HR information systems and data analysis platforms
    • Basic statistics
      • Types of variables
      • Statistical significance
      • Descriptive data vs. data analysis
      • Modelling and predictive analysis
  • Data analysis of recruitment and prediction of employee turnover
    • Dependent and independent variables
    • Categorical and continuous variables
    • Logistic regression analysis methodology - building predictive models
    • Testing validity and reliability of candidate selection methods
    • Predicting rejection and shortlisting of candidates
    • Predicting employee turnover in your organization
  • Data-driven learning and development – the impact of training provision on employee motivation
    • Transforming answers of questionnaires into continuous data to expand analysis opportunities
    • Questionnaire design - testing internal consistency of questionnaires - Cronbach's alpha measure
    • Testing if your data is representative using normality test
    • Understanding the nature of relationship between business variables using Pearson's correlation  
    • Examining the impact of training provision variables on employee motivation using linear regression
    • Simulating an alternative model to Kirkpatrick's model for evaluating training impact 
  • Exploring relationships between employee performance, employee engagement, and profitability
    • How to measure employee engagement
    • Factor analysis to test the reliability of questions in an employee engagement survey
    • Analyzing data to explore the relationship between customer loyalty levels and employee engagement levels
    • Stepwise multiple regression - an effective tool to explore relationships among business variables
    • Using stepwise multiple regression to model employee performance
Schedule & Fees