4 Ways to Predict and Prevent Employee Attrition
Top of mind for employers, employee retention is seemingly a never-ending challenge. From the loss of knowledge and experience to the high cost of turnover, employee attrition impacts an organization on many levels, justifying its priority on your to-do list.
And now that we’re facing the Great Resignation? Employers are witnessing historical turnover rates as we emerge from the pandemic.
Today, however, talent professionals have a tool in their belt, helping you predict employee retention, attrition, and turnover—artificial intelligence (AI). By leveraging AI, talent professionals can predict turnover through data and analytics, allowing you to retain top talent proactively.
Read on to learn about four ways to predict and prevent employee attrition with AI.
1. Gauge True Reasons for Turnover
With more than half of employees planning to look for new jobs this year, it’s critical to identify the true reasons for turnover. With the onset and staying power of COVID, many employees are leaving their jobs for more flexibility, higher pay, or better benefits. However, employees are also leaving for reasons related to the pandemic, such as diminishing company culture or burnout, reports SHRM.
In the past, employers often used surveys to gauge employees’ happiness and engagement. The problem with this? Employees aren’t always honest on those surveys, creating a disconnect in turnover perceptions.
According to data and analytics leader TWDI, using compromised and subjective information, such as results from traditional surveys, causes organizations to make poor recruitment decisions. Instead, companies can improve their “retention strategies by relying on data analytics that removes human emotion.”
When gathering employee data, such as promotions, past reviews, sick time used, commute times, and compensation, through data analytics, you can find trends that you didn’t realize existed. For example, does lack of promotion correlate with higher employee attrition? Does the use of sick days correlate with turnover as well?
Let the data “speak for itself.” By doing this, you can make better recruitment decisions while also discovering what deserves further analysis.
2. Assess Workplace Accountability
AI can also analyze workplace accountability among your employees – and leaders – determining if they feel that they’re adding to the company’s mission and values. According to Forbes, “[w]ithout a sense of purpose, felt accountability plummets and turnover escalates.”
With AI, companies can more accurately measure employees’ accountability. For example, by leveraging AI, companies can measure how often employees ask strategic questions about the company’s mission and long-term goals (instead of questions on day-to-day operations).
Too often, employees just go through the motions at work without any sense of purpose. With AI, you can detect these trends, allowing you to correct course.
3. Understand Employee Engagement
Predictive data analytics can also help you benchmark and predict employee engagement. For example, through AI, you can objectively measure employee’s attendance and interaction at company-wide or department-level events and meetings.
Additionally, you can measure various factors contributing to employee engagement, such as attitudes towards and use of benefit plans, flexible schedules, or wellbeing. Instead of relying on assumptions, you can make evidence-based decisions, proactively reducing turnover.
And don’t forget to measure how employees feel when it comes to working at your company. Do employees feel as if they are listened to when they offer ideas? Do they feel that your company demonstrates empathy, especially post-pandemic? Do they feel that they’re recognized for their efforts and wins? Use data analytics to drill down on these perceptions, allowing you to gain (and use) the insights revealed.
4. Use AI-Driven Data
Compromised and subjective information can lead to poor decision-making. Let’s flip that.
Using objective AI-driven data analytics helps you make better recruitment decisions moving forward. By incorporating data analytics into your internal processes, you can better predict employee attrition. For example, you can use these predictions strategically to coach your teams, provide training and growth opportunities, explore flexible schedules, and offer additional benefits to employees.
Additionally, you can use science-based analytics to hire employees more aligned with your company’s goals and vision through pre-hire assessments. By objectively measuring predictors of personality and soft skills before employees work for you, you can better head off employee attrition.
With better data comes better retention. Now more than ever is the time to focus on preventive measures to reduce employee attrition. See how Cangrade can support the retention and strengthening of your talent. Find out more.