Videos
Welcome to our video page. Here you will find inspiring videos on HR Analytics including recordings of presentations we gave at past events, talks we had with interesting people, and information on our products and services. Subscribe to our YouTube channel for regular updates.
Most recent videos
JiGSO Listen pitch
JiGSO Listen is an innovative employee listening tool that gives teams the insights and tools to build a culture of psychological safety and team cohesion
What is JiGSO Listen?
Short explainer video introducing JiGSO Listen and how this smart platform can help your teams thrive and your organisation triumph.
HR Analytics videos: Employee Turnover
Employee churn or turnover – the rate at which employees leave a workforce and are replaced – can be a severe problem for many organisations. Even if the time and cost of investment (recruitment, hiring, training) are considered relatively low for a given workforce, it will always be non-zero. Additionally, we are all too aware of the impact on team morale and company image.
In these video series, Data Scientist Thomas Stainer explains how Survival Analysis can help you understand employee churn.
Survival analysis for employee churn – Part 2: Censoring
Censoring is an important feature in Survival Analysis that helps you take into account missing data.
Survival analysis for employee churn – Part 1: Introduction
Introducing the concept of Survival Analysis and how it can help you understand churn.
HR Analytics videos: Model Explainability
Although the fundamental concepts of Machine Learning have been around for quite a while, most people are only now beginning to become acquainted with the technology. Therefore, blindly trusting the prediction that came out of a black box model might still sound quite daunting to most.
In this video series, Data Scientist Wout Goossens opens up the black box by introducing the concept of Model Explainability.
Opening up the black box: an introduction to model explainability
What is Model Explainability and how can it give you more insight into Machine Learning predictions?