The cost of replacing an employee can be anywhere from 50% to 250% of their salary, depending on their role. There is also the cultural impact to consider, including lower levels of productivity and an overall drop in team morale as the result of someone leaving.
Low employee engagement leads to staff turnover. When you know why your employees leave and you’re able to measure how engagement changes over time, it’s possible to spot the warning signs that someone is about to leave. According to our data, it’s possible to predict when someone is going to leave up to 9 months in advance. This gives you time to address the underlying issues and take a proactive approach to reducing attrition costs.
Introducing Real-Time Attrition Prediction
Peakon’s Attrition Prediction model is trained on hundreds of thousands of employee data points that include both behavioural and demographic data. Our analysis has highlighted four key factors that indicate a high risk of departure.
Based on the response to the eNPS question: “How likely are you to recommend [your organisation] as a place to work?” Employees who provide a 0-6 score to the eNPS question are 3 times more likely to resign than those who score the question 9-10.
Response to the eNPS loyalty question: “If you were offered the same job at another organisation, how likely is it you would stay at [this organisation]?” The average loyalty score of employees that remain with a business is 20% higher than the average score of departing employees.
The survey response rate of employees that resign from a business is 15% lower than that of employees who remain.
Employees in the 3-12 month tenure bracket are most likely to leave an organisation. Low responsiveness, engagement and loyalty scores during this time is a significant indicator of attrition.
“Resigning employees are significantly less engaged, express less loyalty and participate less frequently in employee engagement surveys. Employee tenure can also indicate how likely it is that a person will leave. If employees are disengaged early on in their time at your organisation, they are a significant attrition concern”Jakob Nielsen, Senior Data Scientist
The Six Levels of Real-Time Attrition Risk
Our Attrition Prediction model estimates the attrition risk for each of your employee populations in real-time. Risk is recalculated every time an employee submits feedback. The aggregated, segment-level view keeps the accuracy of your predictions high while preserving individual employee anonymity.
This overview of attrition risk in each employee segment helps managers and senior leaders in your organisation to identify the areas of greatest concern, and prioritise the actions that need to be taken to reduce regrettable employee turnover.
Reducing Attrition Costs with Peakon
Creating an environment that supports employee development is a much smarter investment than replacing people that leave. Those that stay with your organisation over the long-term have stronger internal networks, more in-depth market expertise, and an intimate understanding of how your organisation works – also known as institutional knowledge.
It’s equally important to consider that the cost of replacing talent will almost always be bigger than retaining them through training and development. The most obvious is the cost of replacing departing employees, which can be as much as 250% of their salary.
There’s also the cost that comes with abandoned pipeline, damaged customer relationships and additional workload for those left behind. Even when a replacement is found, it can take weeks, if not months, before they reach the same level of performance as their predecessor.
Peakon allows you to reduce attrition costs in two ways:
- Understand and immediately address the concerns of employee groups that have a high risk of attrition. Our research clearly shows that you have 9 months to address these issues before an employee decides to leave.
- Take a proactive approach to recruitment. Some level of regrettable churn is unavoidable, but Peakon can inform your budget planning for new hires accordingly – without having to wait for someone to quit.
To learn more about how Attrition Prediction works, watch the webinar below, where Michael, our Director of Employee Experience, and Jakob, Senior Data Scientist, take a look at the reasons why people quit, and how low employee engagement contributes to staff turnover.