HR Analytics Help Reduce Turnover
While there are exceptions to every rule, I have found most people do not leave a job solely for better pay — especially if the increase is minimal. So if money is not the sole motivator for most people to jump ship then why do they leave? If you have not asked this question then it is likely time to ask. As the old adage goes, “you cannot countermeasure that which you do not know.”
HR analytics is finally now becoming a topic of interest; unfortunately in most organizations it is woefully weak and only minimally useful. Analytics related to the human side of every organization should be on par with the data gathering effort related to the analysis of quality, cost, productivity, etc.
When I have looked at attrition data (rarely with any analysis included), it is extremely difficult to understand why employees are leaving. The data too often simply describes how someone left (quit, walked-off-the-job, no-show, etc.) and not why he or she left.
If the data does include the why (another job, pay, treatment, etc.), it virtually never includes a “why-why” analysis to derive the actual root cause. If an organization does not have meaningful data backed up by in-depth analysis, how can any effective countermeasure to improve retention be implemented? Again, “you cannot countermeasure that which you do not know.”
If we cannot countermeasure quality, safety, or cost issues without data and analysis, how can we expect to countermeasure turnover without the necessary data and analysis? Organizational leadership and HR will say they know why employees are leaving, but I have yet to find one who can specifically link the actual number of exits to an identifiable root cause. Without specifics it is far too easy to make excuses, deflect criticism or pass the blame — all of which retards the development of effective countermeasures. This in turn allows the vicious cycle of employee turnover to worsen.
Equally troublesome is not clearly knowing why employees stay. What makes some stay while others leave? If an organization does not collect retention data and performs detailed analysis of the data it is very difficult to replicate the actions, programs, culture, etc., that are the reasons employees stay. Yet there is danger in this data analysis if not performed with a high degree of reliability. A company should not be making wholesale changes to policies and programs based on data that is less than credible.
One final point is that like any discipline within an organization (finance, quality, safety, etc.) data related to the human side of the organization must be converted into meaningful information. Finance data may make sense to an accountant but not to someone else. Likewise HR related data must be converted to information that is “user-friendly” in order for the organization to grasp a clear understanding of the actual situation. The data must be meaningful to the people who are expected to act on it.
Tim A. Garrett is a consultant, author, speaker and founder of Diversified Performance Solutions, LLC. DPS was founded on the principles of business ethics, personal integrity and value creation. We welcome the opportunity to work with quality organizations of any size or line of business that want to create positive change to enhance competitiveness and employees’ work environment. Tim can be reached at email@example.com. For more information, visit timagarrett.com