Predicting Tall Poppies

A company is only as good as the employees it keeps.

For a long time, the world of analytics has focused on understanding the lifetime value of a customer to help organisations understand which ones are worth fighting for, and of those, which are at high risk of taking their money elsewhere.

Which begs the question, why aren’t we using the same techniques to understand the value an employee will bring to the organisation over the course of their career, and which of those tall poppies are at highest risk of leaving the organisation?

The trickiest part of this problem is being able to measure the value an individual brings to the organisation. This will of course vary depending on the nature of the business – for a sales organisation, individuals can be tracked against their sales quota. For a government agency, it might be captured in the form of performance reviews and 360-degree evaluations.

Once we have a method of measuring value – whether numeric or textual – we can use IBM SPSS Predictive Analytics to uncover the hidden characteristics and patterns to predict the value an employee is likely to bring to the organisation over the course of their career.

Identifying which of those employees are at high risk of leaving the organisation is arguably quite simple. In the age of social media, there is a wealth of information available that can give insight into an employee’s state of mind – Facebook, LinkedIn, Twitter to name a few. With the help of social media analytics, we can identify and track sentiment in employee attitudes, coupled with other factors such as length of employment, market factors etc. to predict the risk of attrition.

With this knowledge, we can take action to retain our most valuable employees who are at highest risk of taking their skills elsewhere.

There is a common saying: “People by from people“. Doesn’t it then translate, that we should do whatever it takes to identify and retain the best people?