How Can I Predict Employee Attrition for the Next 3 Months Using My Data?

Hi, I have a report that includes the termination date and hiring date of employees. I need to forecast attrition for the next 3 months. Are there any suggestions? I have attached sample data and hope someone here can help. Thank you!

Dear Zina A,

Thank you for raising a proper HR query. Most of the queries on this forum concern notice periods, PF/ESI, etc., which are not considered true HR queries.

I have reviewed the Excel sheet you provided and noted the following observations:

a) You have included the date of exit (not termination) and the date of joining for 135 employees. However, this data is consolidated for the entire organization without a breakdown by department, hindering department-wise analysis.

b) To facilitate analysis, I have converted the Excel sheet into a Google Sheet. You can view it by clicking [here](https://docs.google.com/spreadsheets/d/1ldiJG5W9Y3lVhmvm6pjRQuHi1LGuVQAt3-V_1faSd1g/edit?usp=sharing).

The following insights are derived from the Google Sheet:

c) The highest employee attrition rate (19%) occurs within the _____ year slab.

d) Attrition rates for the three duration slabs - ____ years, ____ years, and ____ years - stand at 50%.

Corrective actions for (c) and (d): Commence conducting stay interviews as employees reach _____ years of tenure. Develop career plans to demonstrate growth opportunities within the company.

e) Employee attrition within the _________ slab is 12%, potentially due to employees' inability to align with the work environment or tasks.

Corrective action for (e): Enhance recruitment practices.

f) ____% of employee attritions belong to the >10 years slab, possibly because employees remain until retirement. If long-serving employees do not contribute value, consider hiring replacements at a lower salary to mitigate their departure.

I trust you find the analysis satisfactory.

Forecasting Explanation

Your query pertains to forecasting attrition, yet the provided data is insufficient for any forecast. Given an average employee tenure of 1,618 days and a Standard Deviation (SD) of 1,468 days, forecasting based on these figures is challenging.

Senior members are encouraged to review the Google sheet and offer their insights.

Thank you,
Dinesh Divekar

Dear all,

I have now added one more sheet titled "Month-wise Analysis" to determine whether there is a seasonality factor in the data. The following are the findings:

a) Maximum attrition happens in the months of _______, _______, _______, _______, and May. These five months constitute ___% of employee attrition.

b) From December to May, attrition drops in February. Why this happens merits investigation.

c) From ____ to _____, these five months are slack. Just ____% of exits occurred during these months.

d) Although I have not added a separate sheet, I have studied the recruitment pattern. There are no slack months in recruitment. In February, June, and October, fewer employees joined compared to other months.

e) Slight flaw: Although the data is for 136 employees, when I did a month-wise breakdown, the analysis accounts for only 134 employees. The reason for this discrepancy of 2 employees is not understood.

Thanks,

Dinesh Divekar

My query is that I want to create awareness about early attrition, i.e., (0-3) months, among the managers via email. Can someone help me with the content of the email on staffing yield?

Regards, MG

Dear Zina, Earlier, I provided an exhaustive reply on "Attrition Analysis." You may click the following link to refer to it:

https://www.citehr.com/519562-have-w...ml#post2211229

Please create the data based on the points given in my above reply.

Secondly, anyone with the link can download the Google Sheet. Several members and my other friends have downloaded the Google Sheet that I created. Therefore, downloading the sheet should not be a problem for you.

For further discussion, feel free to call me at [Phone Number Removed For Privacy-Reasons].

Thanks,

Dinesh Divekar