People Analytics in Excel: Employee Attrition (Interpretation Part 2: Choosing Meaningful Metrics)
Channel: People Analytics Alaska
Date: 15/12/2019

In this video we continue to interpret the results of our logistic regression that predicts employee attrition from a fictional company. In our previous video we talked about how to intepret the confusion matrix that shows what predictions our model made and where it tended to get them wrong. In this video we use our confusion matrix to talk about understanding error rates is crucial to driving business results.

The crux of the matter is this: model accuracy is often irrelevant. A model that is 90% accurate might sound good, but if it is regularly reporting the wrong answer in a category that costs the company a lot of money, it is as good as useless. Depending on the business case a false positive can be a lot more expensive than a false negative, or vice versa. Understanding this and knowing how to tweak model parameters to create better business results is crucial. In this video we demonstrate this by changing the model's cutoff score and seeing how those decisions impact financial outcomes for our fictional business.

In the world of people analytics/hr analytics/business analytics, context is king. If we understand it, we can single-handedly deliver enormous competitive advantage to our employer.