Employee turnover continues to be THE dominant metric in HR Analytics.

Unfortunately, the terms “employee turnover rate” and “employee retention rate” are often used interchangeably.

As we will see in this post, employee retention and employee turnover rates are closely related but they are not quite the same thing.

## How Do I Calculate Employee Retention and What Does It Mean?

To *retain* is to keep. Accordingly, employee retention answers the question “What percentage of our employees working here on *Date 1* were still working here on *Date 2*?”

The basic formula for employee retention is the following:

(# of employees who stayed at the company for the whole time period)/(# employees at start of the time period) X 100

Note: We multiply the decimal value by 100 to convert to a percentage.

- Example 1: If 87 people were working at my company as of June 1st and 80 of those same people were still working at my company as of June 30th, my retention rate for the month of June would be the following: 80/87 * 100 = 92%
- Example 2: If 104 people were working at my company as of January 1st and 80 of those same people were still working at my company as of June 30th, my retention rate for Jan-Jun would be the following: 80/104 * 100= 77%

Observe that by this definition, employee retention completely ignores new hires. In Example 1, we started out on June 1st with 87 people. Whether we hired no one or 27 new people during that month makes no difference. We are only asking “What percentage of people have been with us through the whole period?”. We’ll treat the issue of new hires below

### Calculating Retention Rate in Excel

Calculating this in Excel turns out to be straightforward. In this screenshot, we have the number of people starting the month in one column and the number of those same people in the next column. To get retention rate for each individual month, we just divide the “stayers” column by the “starters” column. Note that the numbers for “Employees at Start of Month” change because new people are hired. However, we are NOT including those people in our retention rate calculation unless they were actually in their job at the beginning of the month. For example, if I hire someone who joins the company mid-January, they will not be included in our retention calculations for January because they were not in their job at the time of hire. They will, however, be part of the February calculations.

The data here are organized by months but you could also organize it by quarter or year to get the quarterly or annual retention. Remember though that retention rate measures the proportion of ‘stayers’ among the people you started with.

### Calculating Retention Rate in R

The same calculation with a bit of R code this time. For those just picking up R knowledge, we are just creating a dataframe with two columns just named “start” and “end” and assigning some simulated data. Then we divide the one column by the other and round the result.

```
temp <- data.frame(start = c(80,86,84,84,83,87,89,84,96,98,102,97),
end = c(78,83,84,82,83,86,84,82,93,98,97,97))
print(round(temp$end/temp$start, 2))
```

`## [1] 0.98 0.97 1.00 0.98 1.00 0.99 0.94 0.98 0.97 1.00 0.95 1.00`

## But What About New Hires? Don’t They Count?

There is some debate and inconsistency in the HR field, but the consensus based on my experience and research is that the basic formula detailed above is the commonly accepted definition: new hires do not count towards the retention for the month they are hired. For example, someone hired in June would not count toward the retention measure until the following month.

In contrast, new hires are typically included when measuring turnover within that same time period (see below).

It’s worth noting that our core definition is also consistent with the use of “retention rate” in other contexts as well. For instance, retention rate in college enrollment refers the number of students first year undergraduate students who continue at the school the following year.

Similarly, customer retention typically means the ratio of the number of customers retained through some time period to the number at the beginning of the period.

Ultimately, what matters is communication and shared understanding. The formula here is the most common in HR practice as well as common usage across domains. That’s a good starting point when it comes to reporting but be aware that organizational history often trumps standard definitions.

## Employee Retention v. Employee Turnover: Not the Same

The basic formula for employee turnover is a little different:

(# of people leaving during a time period)/ (average of the # of people at the beginning and end of the period) X 100

In words, this formula answers the question “What percentage of our people left during a given time period?”

If you are not familiar with employee turnover calculations, you also might find this 2 minute tutorial video helpful:

You can also learn more about turnover measures **here**, **here**, and **here**.

There are two important but subtle differences between employee turnover and retention here:

- Retention is about the people
*staying*while turnover is about people*leaving*. These are of course closely related: if employees aren’t generally leaving (low turnover) then they must be staying around (high retention) BUT… - Whereas employee retention ignores new hires, employee turnover folds new hires into its measure.

In particular, turnover divides the number of people leaving by the AVERAGE of those at the start and at the end. The number of people at the end will include any new hires that occurred during that time period. Retention measures don’t care about new hires. They just want to know what proportion of the people you started with stuck around for the whole time period.

### Example of Retention Rate v. Turnover Rate:

Let’s suppose 87 people were working at my company as of June 1st and 80 of those same people were still working at my company as of June 30th. In addition, let’s suppose we also hired an additional 20 people in June and that none of these new hires left.

As before, my retention rate for the month of June would be the following: 80/87 * 100 = 92%. In words, 80 of the 87 people I started with at the beginning of June are still around, a retention rate of 92%.

My turnover rate, however, takes the new hires into account. We started the month with 87 people but ended with 100 people (87 starters – 7 leavers + 20 new hires). If we average the 87 at the start of the month with the 100 we had at the end of the month, we get an average of 93.5 employees during the month. To calculate turnover then, we divide these 7 leavers by the average number of employees throughout the month.

7 (leavers)/ average(87 at start and 100 at end) X 100 = 7.5%.

## Summary and Advice:

In many ways, I actually prefer measuring retention instead of turnover because the interpretation is not muddied by the contribution of new hires. In particular, it won’t shift up or down according to any random shifts in the timing and scale of hiring.

In principle, one could lose a bunch of people in a month but then partially offset this with some new hires. The addition of these new hires will then soften the measured turnover impact of those leaving. Your retention numbers, on the other hand, will not be impacted.

Still, turnover is king (even if it is sometimes confused with retention). Considered as a whole, I recommend the following:

- Determine if there are clear, consistent formulas used in your company. If there are and they are consistent with our specifications you are in good shape.
- If there is no consistency or distinction, arrive at consensus formulas for both turnover and retention. Then emphasize the difference and do so consistently. If it turns out that the retention measure in your company is slightly different, that’s fine. What’s critical is that everyone is on the same page and that you calculate consistently across reports.
- Be explicit about your formula in HR reporting. Actually put it on the page, say, as a footnote. Decision-makers simply need to know what they are looking at when formulating decisions. Formulas communicate cleanly. Take advantage of that to avoid confusion.
- Report both retention and turnover.

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**Comments or Questions?**

Add your comments OR just send me an email: john@hranalytics101.com

I would be happy to answer them!

Hello, First off thank you for your tutorials. They are extremey helpful.

I do have a question though, I understand that you are not supposed to account for new hires for retention ratio, however I noticed in your example that the beginning headcount varies of each month. What is adding to the headcount? And how do I explain that to my leaders?

Looking Forward to hearing from you soon.

Thank you,

-Mohamed

Hi Mohamed:

Thank you for your question. I have changed some of the text to explain that more explicitly. The key addition is the following: “To get retention rate for each individual month, we just divide the “stayers” column by the “starters” column. Note that the numbers for “Employees at Start of Month” change because new people are hired. However, we are NOT including those people in our retention rate calculation unless they were actually in their job at the beginning of the month. For example, if I hire someone who joins the company mid-January, they will not be included in our retention calculations for January because they were not in their job at the time of hire. They will, however, be part of the February calculations”

Let me know if you have any additional questions. -john

Hello John,

Thank you for the explanation! I greatly appreciate it.

Sincerely,

-Mohamed

Hi, very useful article! So, considering your answer could we clarify that if an employee leaves at the last day of the month do we include this employee in the “stayers” or not..? what is the most appropriate?

Thank you very much,

Nik

Hi Nik:

Thanks for the question. Typically, one would say that a person who leaves on the last day of the month should be counted as a “leaver” rather than a “stayer” because they left the company within the time period under consideration. It is also critical that you use the same rule in all cases so your numbers mean the same thing over time. Using this as a rule will make sense to your colleagues and leaders and is consistent with the field.

Let me know if you have any additional questions.

Cheers,

-john