How do you compute turnover?

We have a high turnover rate in some areas due to having high school and college students working part-time. Many are hired just for the summer, but their coming and going makes their department and total turnover look terrible.

It was suggested to me that part-time people count as 1/2 a person for turnover stats. Anyone else do something like that?

Right now, I just divide # of terminations by # of staff on a given day, or average # midpoint in the year.

I need to come up with three years of stats for a major report.

Comments

  • 4 Comments sorted by Votes Date Added
  • If you have summer students as a matter of course, you might consider not counting that as turnover at all. The real turnover are those emloyees who are employed all the year.
  • We don't count temps. We hire college students to work during the summer and many of them are back for a few weeks at Christmas or for spring break. I add them to my FTE's as 100 FTE's +3 temps, but we don't consider them when figuring turnover.
  • I agree with Gillian and HRBanker. We do not consider temps or casuals or part timers in such calculations. They totally distort what you're trying to portray. If you do count them, you cannot have a true picture of your turnover. The thing that destroys our turnover credibility the most is the fact that we don't run with a consistent number of positions. Sure, over time, we can average total position count as compared to those leaving; but, all of the ups and downs in employment level authorized over time will slowly but surely give you resulting figures that are basically meaningless, as averages often are. As has been said, the man who has his head in an oven and his feet in ice water, is on average, comfortable. I find the same sorts of problems with 'trend graphs' which engineers love to use. They generally (at least the ones the engineers pass around) show a downward trend in things like scrap and upward trend lines in things like production efficiency (or they wouldn't bring them to the meeting). These neat little upward slanting lines look great to officers. However, upon investigation you see that the nice little upward trend line is nothing more than an average of (e.g.) 5 dismally low months and 5 satisfactory months. Again, on average, the trend seems nice. But who bothers to explain the 5 dismally low months, which are problematic? Rather, the assumption is reached that the trend line must be telling us all is well because it shows that neat little upward tilt over the year. Hogwash! All the people around the table need to have a clear understanding of what your figures mean and what they do not mean before they go off the edge with their variety of interpretations. You may have averaged only one car wreck in the past two years; however the one you just had totalled your car and broke your spine. How does it feel to be average? Good luck with your turnover stats.
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