By the time an employer knows that an employee is leaving, it’s often too late to change their mind. Tools like artificial intelligence technology can inform retention strategies and help employers predict who is most likely to leave, as well as what incentives might encourage them to stay.
For example, workers who switched jobs received an average 15 percent increase in pay at their new position, an option their previous employers did not offer absent a promotion, says Brian Kropp, group vice president at research and advisory company Gartner. Fewer opportunities for promotion also make it more appealing for workers to switch jobs.
Why renegotiation and exit interviews aren’t enough
Often, the first notice a company has that an employee will leave comes in the form of the employee’s resignation. It’s possible to offer to renegotiate the employee’s compensation or duties at this point, and many companies do. Yet an employee who has resigned has already decided to leave the company — and may already have another job waiting for them.
Most retention strategies rely on two tools: exit interviews and annual employee surveys. Exit interviews seek to learn why an individual employee is leaving, while surveys seek to take the temperature of the existing team and predict potential disruptions that may result in resignation, write researchers Brooks Holtom and David Allen.
“The problem is that these data don’t give managers a real-time picture of who might be considering leaving,” they write.
Understanding employee behavioral intentions is particularly important when it comes to predicting attrition. A study by Robert P. Steel and Nestor K. Ovalle in the Journal of Applied Psychology, for instance, found that “intentions were more predictive of attrition than overall job satisfaction, satisfaction with work itself, or organizational commitment.”
When an employee leaves, the costs can be steep for employers. One Gallup poll estimates that “the replacement cost of an employee can be 150 percent of his or her annual salary or more,” according to Brandon Rigoni, Ph.D., and Bailey Nelson at Gallup.
How AI identifies risks and opportunities for employees
“By using big data, firms can track indicators of turnover propensity and identify employees who may be at an elevated risk of leaving the organization,” say Holtom and Allen. Organizations that develop their own means of measuring turnover propensity gain a further advantage, because their ability to predict turnover is tailored to their specific organization and industry.
Artificial intelligence can also use data on skills, including the skills successful employees have and the skills employees will need in order to advance their careers. By focusing on skills-related data, AI retention tools can help company leadership have frank conversations about the skills an employee needs to keep growing, says Ginni Rometty, CEO of IBM.
Rethinking reviews, feedback, and performance
Traditional retention strategies that only use employee performance reviews to measure engagement are clearly broken. In a global survey by Mercer, only two percent of human resources leadership said their current method of performance management “delivers exceptional value.”
Seventy percent of responding companies saw a need for performance management to be integrated more closely with other talent decisions. These decisions may include hiring and renegotiating the terms for top employees who seek to leave the company.
With so much on the line, companies are responding quickly. In a McKinsey survey, two-thirds of companies said they had “made at least one major change to their performance-management systems” in the 18 months before the survey, according to Bryan Hancock, Elizabeth Hioe and Bill Schaninger at McKinsey.
Instead of relying on a once-a-year review to communicate with employees and make predictions, managers are turning to methods that allow them to receive and understand feedback as it happens. One of the changes many companies have embraced is the use of big data to understand employees’ skill sets, determine what helps employees succeed, and better grasp what keeps employees motivated and engaged.
Managing employee uncertainty
Many employees give notice with the firm intention of leaving their current employer. Some even have a new job waiting for them. Others, however, waffle over whether or not to leave even as they announce their intention to do so.
When an employee’s resolve is firm, “usually there’s little more to do than thank the person for their service and prepare your strategy for backfilling the position and distributing the individual’s work,” says Paul Falcone, CHRO at the Motion Picture & Television Fund. Employees whose resolve wavers, however, offer an opportunity for employers to convince them to stay, especially if their work has been exemplary.
But what will solve the employee’s quandary? While an exit interview can help, it may not reveal the true source of the employee’s discontent. This is particularly likely to be the case when the employee is not aware of the root of the issue or has no confidence that their supervisor can address that root issue.
Here, AI tools can help both employer and employee better understand what’s happening and how to fix it. For example, AI can identify patterns in events, including complaints or concerns raised by staff members. It can also point a bored or disengaged employee toward more fulfilling work by analyzing skill sets and past successes.
Using AI to inform retention strategies
Artificial intelligence can be adapted to solve problems in a number of different areas, including many topics that concern human resources and corporate leadership. Focusing AI on the problem of retaining restless top talent can be achieved in several different ways, depending on the needs of the company and its workers.
Encouraging employee growth
CNBC contributor and coauthor of “The Real-Life MBA” Suzy Welch recommends that restless employees ask themselves one question: “When was the last time I did something at work for the first time?”
This measurement allows workers to see whether they’ve been growing in their current role or not. Employers can also use this question to see which employees have stagnated and get their growth moving once again.
Bolstering engagement, purpose and accountability
Closely related to stagnation in skill development is an employee’s sense of purpose and accountability when it comes to meeting their own or their company’s work objectives.
AI tools can help companies better understand the factors that surround engagement and purpose, says Falon Fatemi, CEO and founder of Node. These factors can be considered when determining which employees are least engaged and thus most likely to seek employment elsewhere.
Factors like engagement and purpose can be difficult to quantify, even if they appear obvious in conversation or observation of a particular employee. “AI can solve this by aggregating large volumes of employee feedback and converting them into action points,” writes Chiradeep BasuMallick at HR Technologist.
Meeting employees’ concrete needs
Some employees choose to look for a new job not because they lack a sense of fulfillment or growth, but for specific reasons such as a schedule that is incompatible with other life goals. Artificial intelligence can also help employers understand these factors and how they drive employee’s job-search behavior.
For example, AI can be used to analyze and rebuild workers’ schedules in a way that ensures essential tasks are completed while also maintaining a more satisfying work-life balance, says Jayson Saba, senior director of product marketing at workforce management and HCM cloud solutions provider Kronos.
AI offers a way to help company leadership predict which employees are most likely to seek work elsewhere. It can highlight the reasons employees become restless, and it can help leadership intervene before an employee acts on the idea that another company and another job are the answer to their discontent.
By using AI to understand and address the reasons employees leave, companies can improve retention strategies and gain better insights into why their top talent stays — and which job candidates are more likely to stay as well.
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