Hey guys - I’m calculating attrition for my compan...
# general-qna-forum
r
Hey guys - I’m calculating attrition for my company at the moment. I know that we basically have to divide number of people in the team by number of people who resigned in a particular time period. I also know that people who are let go or laid off don’t have to be factored into this number. However I’m struggling to understand how to calculate attrition without including people who were let go in the opening number to ensure they’re also not accounted for the closing number. If any of you have dealt with something similar, possible to help here? Thank you!
a
I don't think you need to omit involuntary attrition. In fact it's another data point for you to calculate voluntary vs involuntary attrition. If you follow what you're saying you'll have to completely neglect the laid off folks as employees at all. You won't count them in any data which will not lead to true results, I feel. Also you need to divide the attrition count by the average of total count at the beginning and at the end of the considered time period. Feel free to correct me if I am wrong.
k
I wonder what Keka uses / can we check? @Megha
m
Yes, I will check this on Keka and revert back
On Keka - The Overall attrition rate is calculated by total number of employees divided by the people who resigned / were terminated / combination of both. There are other demographic insights like exit reason, exit type, compensation, performance , age and gender. @Kartik Mandaville ^
r
Thanks for the help, guys! 🙂
Another follow up question if you could help - my annual overall attrition %age will be an average of all of my monthly attrition %ages for the year, right?
a
Hey Richa, yes agree with what others have replied, but I highly suggest you build or integrate a software to have all this automated. Also a number doesn't say anything by itself. For ex, 30% attrition. Why? Who? When?
You need to have these answers if you want to increase your performance and engagement and of course have low turnovers. I work in data analytics so the problem is not in the numbers, but in the reasons behind them. If you want me to explain further feel free to DM me
r
Thanks much 🙂