What if you could translate the amount of monthly or annual turnover in your organization into an equation with various inputs and trajectories? Sadly, quantifying the whole sum of tangible and intangible causes of turnover is practically impossible. However the good news is that a good regression analysis of employee turnover as the dependent variable could prove extremely useful. A regression equation for employee turnover could show for example that a gain-sharing program causes a X% increase in employee retention. Or on the other end, increases in employee paid insurance premium portions or decreased benefits might cause a Y% increase in turnover.
The examples I am considering are below. Feel free to chime in on any other ideas. I hope to begin compiling data later this week.
Dependent Variable: Employee Turnover (Annual or Monthly Time Series)
Potential Independent Variables:
- Local unemployment conditions
- Company specific or regional wages
- Insurance premium changes or increases?
- Dow Jones Industrial Average
- Industrial organization and competition
- Employee satisfaction data
- Training and development budget