Big data helps HR prioritize employee needs to drive retention strategies.

Well-designed, proactive employee retention strategies are a crucial element for business success. Although the impact of decreased productivity and the costs of low morale of overworked employees aren't a line item on profit and loss statements, HR leaders know the negative impact the "costs" associated with voluntary turnover can have on organizational results. In the past, employers seeking to manage issues with employee churn were forced to use limited, subjective information to predict voluntary turnover. Now, thanks to big data, HR leaders have access to powerful insights they can use to benchmark turnover and build retention models.

Voluntary Turnover Is Part of Business

Gone are the days when employees stayed with organizations for an entire career. In fact, the ADP Research Institute® (ADP RI) report, "Revelations from Workforce Turnover. A Closer Look Through Predictive Analytics" indicates that "60 to 80% of turnover in each industry is voluntary." Knowing that turnover is a fact of business, the first step in reducing these high percentages of churn is to identify the common factors that cause employees to leave.

Factors and Attributes That Cause Employees to Leave

According to ADP RI, there are a variety of factors that impact the likelihood that an employee will leave. Using a sample subset of 1900 firms representing about 7 million employees, ADP RI was able to identify a set of about 40 attributes relevant to voluntary turnover that cause employees to leave. These attributes are grouped into four categories:

  • Job characteristics
  • Organizational dynamics
  • Compensation elements
  • Employee demographics

"The factors are dynamic in nature so their relative weighting changes from client to client and employee to employee," reports ADP RI. "The factors work in combination with one another and consist of a mix of individual employee data points, internal and industry benchmarks and ratios."

It's no surprise that the factors of pay and promotion are consistent drivers of voluntary turnover across industries. However, other factors such as commuting distance, overtime pay and job experience also influence the likelihood that an employee may voluntarily leave an organization.

In some situations, turnover may benefit an organization with the potential to recruit and hire exceptional new talent. However, when there are high rates of voluntary turnover, it's generally a sign that issues exist and there are only more problems to come.

Take Time to Predict Turnover

Rather than reacting to turnover after it's occurred, employers can proactively manage turnover by taking time to use big data to examine and uncover the factors that make employees leave. Armed with information, HR leaders can then create employee retention strategies to encourage people to stay with the organization, for example:

  • If benefits are a factor that contribute to voluntary turnover, update offerings to meet employee needs
  • If commute times are an issue for workers, consider the options of flexible schedules or remote work
  • If dissatisfaction with overtime pay forces employees to leave, determine a new approach

In addition to analyzing the data, efforts by HR to conduct "stay interviews" with employees who are most likely to leave can be time well spent. Digging into what makes those employees stay, and finding out what it would take to make them leave, provides HR with valuable insight to create employee retention strategies.

Predictive data combined with proactive follow-up allows HR leaders to focus their efforts on employees who are candidates for voluntary turnover. Understanding the factors that force people to voluntarily leave is the foundation for creating employee retention strategies that have the potential to make employees stay.

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Tags: big data Employee Engagement Retention