HR Analytics and Basic Statistical Analysis (Intro)

In today’s digital economy, it is crucial for business professionals and leadership teams to be able to use analytics to manage Human Resources. With technological advancements towards a more data driven economy, it is imperative for HR professionals to understand data science and how to use techniques in data science to make sense of people data.

In this one-day program, participants will be taught the fundamentals of data science and its applications. Thereafter, we will introduce them to HR analytics, and techniques to start such a function with the HR Division.

Topics covered will be comprehensive and will include the full value chain of the data science cycle, to having hands on practice with statistics and Power BI.

Learning Objectives:

• Have a clear understanding of data science and its application
• Introduction to Analytics in general and HR Analytics
• Understand the difference between descriptive and predictive analytics
• Understand tools and techniques for building a HR Analytics function. This includes:
  • Knowing the right skillsets to start a HR Analytics function
  • Understanding the integration of the various functions to support HR Data Analytics
  • Understanding the systems and technology needed to drive the HR Analytics function
• Understand types of data sources and how to integrate HR with other business systems
• Secure knowledge about data management, protection and privacy
• Secure skills in Critical Issue Analysis to define key areas of measurement for HR
• Know how to select the right data and clean databases
• Introduction to basic statistics and techniques to perform simple data analysis for selected Human Resource questions. The techniques introduced will include:
  • Correlation analysis
  • Linear regression
  • Multiple linear regression
  • Scatterplots and Bubble Charts, Histograms, etc
  • ANOVAs
• Able to employ story-telling techniques and build dashboards to translate data into meaningful information for management decision making.