As you know turnover is a very important part of any business, and our Attrition Analytics provide you the tools to view and explore turnover within your organization. We encourage you to gain a deeper understanding of the attrition trends to help reduce the risk of future regrettable leavers. The following article explores some of the commonly asked questions we get about attrition.
This article covers:
- My attrition analytics rates are completely different to my expectations, why is this?
Why are there different calculation methods and which one should I be using?
There are a number of different calculation methods used globally. We looked at the Top 3 methods and provided them. These methods are:
- Full Employee Monthly Count (Recommended)
- Monthly Average Employee Count
- Period Start Date Employee Count
We recommend using the Full Employee Monthly Count method is it is the recommended method by the Society for HR management in USA as a standard measurement which removes time bias. This method is used widely across USA and Europe.
This method is based on the full employee count for any given month. Employee count is determined by count of employees at the start of the month plus the count of all new employees that started in the same month. This is the most accurate and consistent method over time. Fast growing business will have an artificially inflated attrition rate without using this method.
This method is considered best practice, however we respect that historically you may have used a different method. The most important thing is to be consistent with your calculation method.
My attrition analytics rates are completely different to my expectations, why is this?
Different calculation method selected than usual
As we mentioned above, consistency is key when it comes to calculating your attrition. This is because different calculation methods can show drastically different results due to time bias etc. You can check which calculation method you are using by opening Page Settings and looking at the Rate Calculation Method.
Historical data not provided in implementation
If only current staff are uploaded during your tenant implementation this will significantly impact attrition calculations as you will start off having a 0% attrition rate, any attrition after this will appear more severe in calculations. We recommend having at least 12 months to 2 years of historical data to provide more accuracy in reporting.
Why does this rate look so high?!
We commonly get this question when looking at the Annualised Attrition Rate - this is what attrition would be if it stayed at the current rate over the course of a year, providing you with a bigger picture outlook. If that turnover continued the same way that it has this month for 12 months, this is the impact. What this does is allow you to identify helps identify particular time frames or periods that affect turnover as well as any hidden factors behind the build-up to it.
For example, a particularly high turnover month could follow after when bonuses are paid, projects end and people are looking for the next new thing. This is the most typical industry turnover time.
Identifying when and why you may be losing staff allows you to put strategies in place to increase retention. Analytics are exploratory, we want you to see trends and give you the ability to drill down into this information and find the root cause.
What insights can I gather from this analytics page?
Identify Attrition Trends
Using Attrition Analytics allows you to take emotion out of attrition by looking directly at the data. You can identify if there are key times of peak attrition and key events that happen beforehand to contribute to this. To take this one step further you can cross reference your data with other analytics pages. Pages you may wish to investigate are Sentiment, Performance, Goals, Happiness, eNPS results, Wellbeing, Training Investment, Remuneration Changes and Span of Control. This allows you to gain a better understanding of the attributes that affect turnover (e.g. lacking training, no goals, manager reach etc.) and use the decision tree to plan actions to prevent future unwanted attrition. Our role is to provide the information so the right person can put the answers together.
Turnover Type and Exit Motivators
We also recommend looking at reasons for leaving (voluntary vs involuntary turnover) as this is important high level data, make sure to watch for trends here. Exit motivators are pulled from Exit Surveys for both managers and their employees. If there are gaps in what the employee and the manager believe is the reason for them leaving the business, this is something you should pay attention to. “Where there’s a gap, there's an opportunity to investigate”, look into the qualitative aspects of that content in exit surveys, to gain further context.