How BI and Predictive Analytics Can Improve Employee Retention

Each generation that enters the workforce seems to leave jobs faster than the last, significantly affecting employee retention rates. While individuals nearing retirement age are more likely to work for the same company for decades, those in mid-level positions or even just starting their careers are always searching for the next best thing. This can lead to financial stress for businesses as with each employee that needs to be replaced, both time and money are spent training someone new. Not to mention the stress this puts on other employees who have to pick up the slack if a position remains unfilled for a while. 

To reduce turnover, companies are using predictive analytics and BI tools to better understand why their employees are leaving in order to prevent it. Here’s how you can do the same.

Understanding The Importance Of Employee Retention Rates

When hiring new employees, you invest in them in numerous ways. First, there is the cost of posting jobs ads or paying a recruiter to find you the appropriate candidates. Then there is the tedious process of going through applications, resumes, and interviews which can take weeks or months. Those in charge of finding the new hire aren’t performing all of their usual day-to-day tasks and either need to work overtime or burden other employees with their responsibilities.

Once a new employee is hired, the investments continue. Other employees will need to take extensive time out of their days to hold training sessions and answer their questions. Again, this is time spent that they’re not performing the tasks required of their position.

 When you add all of this to the expense of business cards, new accounts on CRM tools and other necessary software, and the time lost while this position was unfilled, you can see that having high turnover rates are costing your business more than just an employee’s salary. In fact, a report released by the Center for American Progress found that replacing an employee costs you between 16% and 21% of that position’s salary. If you’re replacing several employees a year, the price your paying for low employee retention rates can quickly become more than you can afford.

High Turnover Rates Lead To A Dangerous Cycle

Studies have shown that most employees don’t understand why their employees leave. This was clearly demonstrated in an survey which found that 89% of employers believed turnover was a direct result of an employee’s desire to earn more money. However, the same survey found that only 12% of employees actually left for this reason, which is a huge difference. One that is eating your businesses profits.

So, why are employees leaving your company? They were unhappy, but why? Only predictive analytics and BI tools can determine for sure why. However, until you discover what those reasons are, you will be stuck in an unhealthy cycle too many businesses are familiar with these days. 

When your company has low retention rates and a position is left unfilled, your other employees are left to pick up the slack. When this happens too often or for extended lengths of time, it adds stress to your workers and will give them a reason to leave. Not only does this lower your retention rates even further but it creates a turnover cycle that can lead to a toxic work environment. Breaking the cycle and improving employee retention rates can be done with simple predictive analytics tools.

How To Use Predictive Analytics Tools To Reduce Turnover

In order to understand why your company is experiencing low retention rates, it’s not going to help just asking employees if they’re happy. Not only are they likely going to lie, but it doesn’t give you the information you need to reduce turnover. You may be surprised to learn that you probably already have most of the data you need to see what is making your employees leave, you just have to know how to use it to your benefit.

Using information on each employee such as their history of pay raises and promotions, sick days used, past performance reviews, company benefits, time spent at work, and even estimated commute times, predictive analytics and BI tools can find telling patterns. For example, you may learn that employees with longer commute times are more likely to leave in under two years or employees who use more sick days are planning to quit. Not only will this help you to better understand why your retention rates are low but you may be able to predict when an employee plans to depart and be able to prevent it.

Make Changes Based On Your Findings

It’s one thing to know why your employees leave but another thing to actively work to prevent this. Based on the examples in the paragraph above, a company who experiences high turnover rates from their employees who have a long commute may want to consider allowing some employees to work from home or only hire candidates who live in the area. If a policy change can improve retention rates, then it’s definitely worth dealing with any disadvantages to save on costs associated with new hires.

If something can be measured, then it can be fixed and that’s exactly what BI tools can do for your company. Improve office culture and save money at the same time with predictive analytics and watch as your business flourishes when employees are on your side.

About the Author

Chris Mayer is an account manager for, a Stone Door Group Company. Stone Door Group specializes in DevOps based digital transformation of the enterprise. To learn more about how we can help embed your analytics, drop us a line -