Can you Predict Employee Turnover?
In 1997, World Chess Champion Garry Kasparov suffered one of the worst defeats of his professional career. This was no ordinary match. Instead of staring into the eyes of his opponent, Kasparov was faced with the intelligence of Deep Blue – an IBM computer created with the sole purpose to beat him.
Kasparov was dismayed by the machine’s spectacular gameplay, saying “In certain kinds of positions, it sees so deeply that it plays like God.”
How did Deep Blue do it? This godlike feat came down to one thing: prediction. The machine was able to predict how its moves would play out and examine them at a rate far quicker than Kasparov – or any human – could.
When it comes to employee turnover, who do you think would be more effective at predicting it – Kasparov or Deep Blue?
From speaking with managers and HR leaders, we’ve learned that they use a gut feeling, an instinct or observation of disengagement, to predict when someone is going to leave. But what if we could use a machine to do this work instead? It would be more accurate, less “gut” and more “fact”.
Applying Machine Learning to the Employee Experience
We now know that there’s no need to wait until that gut feeling kicks in. To solve this problem for companies, at Talivest we’ve built a Machine Learning model that can predict turnover.
We chat with Talivest CEO and Founder, Jayne Ronayne to learn more. “It has taken us over a year to develop this model,” says Jayne. “While machine learning and Artificial Intelligence are both being used extensively in financial and customer models, we’re now applying these methodologies to innovate the employee experience. The ‘Voice of the Employee’ has never been stronger when it comes to shaping the future of work.”
We’re Talking Machine Learning At the Nordic People Analytics Summit
Luke Whelan, Talivest’s Head of Analytics, will discuss machine learning in more detail onstage at this year’s Nordic People Analytics Summit 2019 in Stockholm on 4th June. Luke will give his insights on “Reducing Employee turnover with Employee Engagement Machine Learning”.
If you can’t make it to Stockholm, we’d be happy to talk about how we’re using machine learning to help companies. Contact us to schedule a demo and understand how machine learning can help you.