The key to success in any organization is attracting and retaining top talent. I’m an HR analyst at my company, and one of my tasks is to determine which factors keep employees at my company and which prompt others to leave. I need to know what factors I can change to prevent the loss of good people. Watson Analytics is going to help.
I have data about past and current employees in a spreadsheet on my desk top. It has various data points on our employees, but I’m most interested in whether they’re still with my company or whether they’ve gone to work somewhere else. And I want to understand how this relates to workforce attrition. Let’s see how Watson Analytics can help me figure this out.
After logging in to Watson Analytics and uploading my data, I’m ready to do some investigating.
I ask Watson Analytics what drives attrition, because it’s the most interesting to me, and I want to see how the other fields statistically relate to that target. It looks like working a lot of overtime is strongly linked to attrition.
I want an even stronger predictive model, though, so I select combination so I can see the most predictive information on how job role and performance evaluation relate to employees who have left.
I can review a word cloud that shows the top key drivers of attrition and their importance by size.
In my workbook, I can also review a decision tree to see the breakdown of employees who have left and how they differ by job role. I see that people in an HR role like me or in a management position are more likely to stay than people in sales or quality control. However, the key piece of information I see is that the employees who also work more than 15 hours of overtime each week are most likely to leave.
I can also review the tree as plain language explanations.
These are insights that may seem obvious – people who work a lot of extra hours and aren’t rewarded are going to leave. And churn and attrition in sales jobs are higher than other areas. What Watson Analytics does is quantify these insights reliably, so my company can take more focused actions based on a number of factual insights.
So to recap, I started with a spreadsheet and in moments had a list of interesting information that I could understand. Interactive visualizations guided me to statistically relevant patterns in the data that I might not have seen otherwise. Now I am confident that I can now make better decisions about employee retention.
To see my analysis in action, view this video.
If you haven’t used Watson Analytics yet, today’s a great day to get started at www.watsonanalytics.com.