Successfully built and rolled out a Machine Learning product that highlights how many employees are at high risk of leaving in the next 6 months, the product highlights what are the top 5 approached to take to stop that from happening.

Key Takeaways

  • What are the right questions to ask with engagement surveys – walkthrough of experience with finding the right data, choosing the right approaches to get it right (best source of truth)
  • Size of the data set determines the approach, the size of the company determines how quickly you can get started (especially with buy in) – for a small start up – formulating the strategy around awareness, getting the rest of the teams internally to understand what data they have, understand their own product and then to buy in to Machine Learning for the predictive piece
  • Machine Learning in People Analytics – Random Forests – Mapping variables to outcome – what outcome do we set in stone (what are we trying to achieve – first step really important here) – validation when you have small data sets – what we did and how it worked
  • Go To Market Testing – build this new data point into customer success conversations – mould it into the most affective (decision influence data point)


Speaker Bio

I’m passionate about being disruptive in my field, pushing to make a difference, finding questions we haven’t yet answered, and providing information and insight to make the most impact. Currently heading up Analytics in Talivest where we focus on the exit strategy of every employee in the Global Workforce. In work: Continuing to find problems to be solved at scale and making the unknown -> known in the data world. Outside of work: Travelling in 60 year old land rovers and re-assembling them en route to destination – in the attempt of becoming an Irish team barefoot water skier.

June 4 @ 13:30
13:30 — 14:00 (30′)

Stage 2 | Advanced People Analytics and Data Management Stage

Luke Whelan – Head of Analytics | Talivest