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Generate Key Insights from Employee Offboarding

Author

Jasmine Gordon

More by Jasmine
Author

Jasmine Gordon

More by Jasmine

With an average monthly quit rate of about 2 percent, according to the Bureau of Labor Statistics, employee offboarding is top-of-mind for many HR leaders. A tightening talent market has raised voluntary turnover, leaving HR scrambling. As you manage outgoing talent, it's important to consider the key insights from offboarding employees and how they can benefit your organization.

Exit interviews are a common part of the HR toolkit. However, the most valuable insights can lie in the analysis of trends and patterns of employees leaving voluntarily. The Harvard Business Review writes that, in one financial organization's case, the exit interviews of four employees "all told the same story." This case study isn't unique, and missed opportunities for engagement and retention may only be clear in hindsight.

Offboarding Data: Which Insights Matter?

At a very high level, HR executives understand that a steady stream of employees' leaving can speak to company-wide issues. Most HR execs are familiar with the credo that employees don't leave companies, they leave managers. Forbes reports that poor management can speak louder than compensation or benefits, particularly when it comes to voluntary turnover.

Research by University of Illinois Business Professors Ravi S. Gajendran and Deepak Somaya highlights that, for any sized organization, particularly companies in "high velocity" labor markets, exit interviews can play a crucial role in alumni relations. In an interview with Claims Journal, Gajendran stated that "when people are leaving, you shouldn't just stop with an exit interview and a pat on the back. You should be thinking of them as a contact you can tap in the future."

Exit interviews or other modes of data collection should, therefore, focus on the most vital ingredients for employee engagement, in order to uncover trends on an organizational, department or team level. This can include any or all of the following:

  • Quality of relationship with direct manager
  • Trust in senior management
  • Satisfaction with organizational culture
  • Opportunities for advancement
  • Quality of total compensation

In addition, it can be valuable to gain insight into employee satisfaction with the following aspects of your compensation and benefits structure:

  • Fiscal compensation
  • Health and wellness benefits
  • Learning and Development
  • Work-life balance
  • Collaboration tools

Collecting Offboarding Insights

Manual collection of data, through phone or in-person interviews, can reveal deep insights, but it can also significantly increase the volume of work for HR departments or direct managers. Data may require manual entry or manipulation in order to be ready for analysis and dashboards. In addition, certain methods of manual collection may allow offboarding employees to decline participation. This could skew data results toward the most or least satisfied participants, resulting in data that's not truly representative of existing employees.

While online or app-based surveys are less common among modern organizations for conducting exit interviews, an automated methodology can help to make sure that data is consistently collected and aggregated. Provided engagement is high with surveying, HR can derive valuable insights and sort them easily to help inform strategic decision-making.

Although many organizations are gathering insights manually, because of the inconsistent collection processes, they are left with little actionable data to act on these insights. On the other hand, automated collection can ensure data consistency and actionability, but it can also be perceived as impersonal. While there is not likely to be a universal solution for organizations, the right answer may be a balance of manual and automated collection. By combining in-person interviews with online surveying, organizations can ensure former talent receive an in-person experience while maximizing the quality and consistency of data.