22 Jan Retain Your Employees With HR Analytics
The world economy is booming and the unemployment rate is still declining. This means that great talent has a lot of options to choose from. Companies that do not do their best to retain their employees eventually lose out to competitors. Why should you try to retain your employees? Well, that is because replacing them is very expensive. Some studies predict that every time a company replaces a salaried employee, it costs 6 to 9 months’ salary on average. In some cases, where training costs and recruiting costs are higher, this number can be much more. Employee turnover, also called employee churn, is therefore a serious issue. Retaining your best employees can sometimes be hard, especially if the exact reason for leaving is not known or stored somewhere. Is it because the employee is unhappy about his salary, or is it because he is a job hopper and it’s time to hop to the next job? This article will zoom in how you can retain your employees with HR analytics.
The earlier the HR department knows about this, the earlier it can act. If the employee is one of the rockstars in the firm and is relatively underpaid compared to his peers, a bump in salary could make sure that he will stay longer. If the HR department knows on time that he is a job hopper, and based on his history the time has come to search for something else, the company could offer him a job in another department and thus making sure that the talent stays within the firm. But how should the HR department know the reasons for turnover for each employee?
It all starts with collecting the historical data on employees that previously left the firm. The more data the better, as this can give an insight in previously unknown drivers of turnover. Data that could be collected are staffing data, engagement data (collected through surveys), salary data, productivity data and performance data. When the historical data is collected, this is then consolidated and cleaned to make sure that it is ready for analysis.
Getting The Insights
Several mathematical techniques can be used to give an insight in the drivers of employee turnover. Logistic regression or decision trees are often used for this purpose as they provide easy-to-understand results. A decision tree for instance divides your employees, dependent on their characteristics, into buckets. Each bucket has a probability of turnover, which means that the employees in that bucket will have approximately the same chance of leaving the firm based on their characteristics. More advanced techniques, like a Random Forest Model, can also be used for this purpose. The main disadvantage of these models is that they can turn quite fast into a black-box and it can not always be explained why a certain result is shown.
Predicting The Future
After you have chosen a mathematical technique to get an insight in the drivers for turnover within your organization, is it time to see what that means for your current workforce. If a decision tree is chosen for example, a machine learning algorithm can predict which employees have a higher chance of leaving the firm. Besides this, the algorithm can also indicate what the main driver is for this high percentage. The HR department can now act on time and for instance talk with the employee to persuade him or her in staying longer at the firm. As the HR department knows what the reason is that the employee wants to leave, HR can come up with solutions that fit the employee and will benefit employee satisfaction tremendously. With the use of HR Analytics, the company stays ahead of high employee turnover and therefore saves a lot of business costs.
With the Emplysight platform you can analyze the main drivers for turnover within your company and predict your future workforce with the build-in machine learning algorithms. Emplysight is experienced in analyzing turnover and can help you in collecting and consolidating the data. We also help with translating the mathematical outcomes into business perspectives.
Emplysight was founded to give you better insight in your employees. The company aims to use both simple analytics as more advanced predictive analytics, such as machine learning and Artificial Intelligence, to help organizations get a better understanding of their employees. Emplysight helps all HR departments, wherever they are in their analytical journey.