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6️⃣ Turnover
Jessie Walsh avatar
Written by Jessie Walsh
Updated over a week ago

🚇 On this page:

Index of metrics contained in the Turnover chapter.

Related pages:

Overview

When a departing employee rides off into the sunset, HR is left wondering about many things. Why did they have to leave? Was it something we did? Could things have turned out differently? Who’s next? The metrics in the Turnover chapter will point to the answers.


Access the Turnover Chapter

You can access the Stories page through the link in the global navigation bar at the top of every page. You can also use the search box to find a specific metric or story chapter.

The top of the Stories page will display all the available Chapters so you can click the one you want to see.


Turnover metrics

Retention

Number of leavers

A metric within the Turnover story chapter.

Definition

Number of contract terminations provides an overview of employees exiting the organization. It shows all leavers regardless if they resigned or their contract was terminated by the company.

Insight to

It provides an insight into the attrition of organizational headcount and the workload on offboarding employees. Understanding these numbers in time context, per department, location etc. is essential to uncover outliers and spikes.

How we calculate this

Number of leavers is a simple count of employees leaving the company for a given period.

Source data

Extracted from HRIS:

  • Employees employment end date

🚑 Problem with source data? See Data Health 101 for remedies.

Available filters

  • Age

  • Department

  • Division

  • Employment type

  • Race/Ethnicity

  • Gender

  • Generation

  • Location

  • Manager

  • Role

  • Team

  • Tenure

  • Turnover type

Turnover Rate

A metric within the Turnover story chapter.

Definition

This metric shows the absolute number of contract terminations (resignations and terminations) and the annualized turnover rate over time. The Turnover Rate is the percentage of employees who left the company in the observed period of time.

Insight to

Attrition overview of your headcount indicating talent loss trends. It also shows the workload of HR on offboarding employees. Understanding these numbers in the context of time and demographics is essential to uncover outliers and spikes in turnover.

How we calculate this

Counts employees leaving the company (voluntary and involuntary) for a given period. The Turnover Rate is calculated by dividing the number of employees that left the company by the total number of employees in a given period. The Unknown label shows only if you didn't enter an exit type in a dedicated filed in your HRIS.

Source data

Extracted from HRIS.

🚑 Problem with source data? See Data Health 101 for remedies.

Available filters

  • Age

  • Department

  • Division

  • Employment type

  • Race/Ethnicity

  • Gender

  • Generation

  • Location

  • Manager

  • Role

  • Team

  • Tenure

  • Turnover type

Annualized Turnover Rate

A metric within the Turnover story chapter.

Definition

This metric shows the absolute number of contract terminations (resignations and terminations) and the annualized turnover rate over time based on your setup within the view. The Turnover Rate is the percentage of employees who left the company in the observed period of time. Unknown type can appear due to data health problems within your HRIS.

Insight to

Attrition overview of your headcount indicating talent loss trends. It also shows the workload of HR on offboarding employees. Understanding these numbers in the context of time and demographics is essential to uncover outliers and spikes in turnover.

How we calculate this

Count employees leaving the company (voluntary, involuntary and internal movement) for a given period.

The Turnover Rate is calculated by dividing the number of employees that left the company in a given period by the average number of employees for the same period. The average number of employees is calculated by summing the headcounts at the start and the end of the selected time period and dividing by 2.

Finally, the Turnover Rate is multiplied by 365 (days in a year), and divided by the number of days selected for which the Turnover Rate is calculated.

The Unknown label shows only if you didn't enter an exit type in a dedicated field in your HRIS.

Source data

Extracted from HRIS.

🚑 Problem with source data? See Data Health 101 for remedies.

Available filters

  • Age

  • Department

  • Division

  • Employment type

  • Race/Ethnicity

  • Gender

  • Generation

  • Location

  • Manager

  • Role

  • Team

  • Tenure

  • Turnover type

New Hire Turnover

A metric within the Turnover story chapter.

Definition

The First-year Attrition Rate indicates the number of employees who have left before working a full 12 months in a given period.

Insight to

Number of new employees leaving within their first year divided by total departures during the chosen timeframe.

How we calculate this

Number of employees leaving in their first 12 months/total number of leavers

Source data

Extracted from HRIS.

🚑 Problem with source data? See Data Health 101 for remedies.

Available filters

  • Age

  • Department

  • Division

  • Employment type

  • Race/Ethnicity

  • Gender

  • Generation

  • Location

  • Manager

  • Role

  • Team

  • Tenure

  • Turnover type

Turnover Probability Analysis

A metric within the Turnover story chapter.

Definition

The probability of leaving indicates the expected probability that an employee will leave the company at the specific year of tenure.

Insight to

When analyzed for all employees, it provides an insight into a general turnover with regards to tenure. When analyzed per different filters, it provides an insight into groups that are at high immediate risk of leaving the company. Examining a specific group will give further insights into the turnover probability of employees from that group with respect to their tenure.

How we calculate this

The probability an employee will leave the company after a T period of time is the product of number of employees left at time Ti / number of employees not left until Ti for all previous Ti period of times.

Source data

Extracted from HRIS:

🚑 Problem with source data? See Data Health 101 for remedies.

Available filters

  • Age

  • Department

  • Division

  • Employment type

  • Race/Ethnicity

  • Gender

  • Generation

  • Location

  • Manager

  • Role

  • Team

Experience loss

A metric within the Turnover story chapter.

Definition

Experience Loss represents the total amount of organizational tenure lost in a given period as a result of voluntary turnover.

Insight to

Experience Loss indicates one of the costs related to turnover. The quality of experience is quite important so you should explore break down by performance rating and other employee segments.

How we calculate this

Experience Loss for a given period is calculated by adding up tenures of employees leaving the company in that period, expressed in years.

Source data

Extracted from HRIS:

  • Employees employment start date

  • Employees employment end date

🚑 Problem with source data? See Data Health 101 for remedies.

Available filters

  • Age

  • Department

  • Division

  • Employment type

  • Race/Ethnicity

  • Gender

  • Generation

  • Location

  • Manager

  • Role

  • Team

  • Tenure

  • Turnover type

Avoidable turnover

A metric within the Turnover story chapter.

Insight to

Compare this to the exit consideration metric to understand how proactive your organization is when an employee considers leaving.

Definition

Avoidable Turnover indicates the percentage of employees that communicated their considerations to change a job with superiors or HR Team. This metric is often observed alongside Exit Consideration to understand how proactively does the organization react once the employee starts considering leaving.

How we calculate this

Avoidable Turnover is calculated as a ratio of number of employees leaving who communicated their exit consideration, and total number of employees voluntarily leaving the company in a given period.

Source data

Extracted from:

  • HRIS.

🚑 Problem with source data? See Data Health 101 for remedies.

Available filters

  • Age

  • Department

  • Division

  • Employment type

  • Race/Ethnicity

  • Gender

  • Generation

  • Location

  • Manager

  • Role

  • Team

  • Tenure

  • Turnover type

Regrettable Exits

A metric within the Turnover story chapter.

Definition

Regrettable Exits are the ones when an employee's departure from a company has a negative impact on the team. It is measured by the direct manager's willingness to rehire employees and the assessment of competency loss that needs to be replaced in the team.

Insight to

Regrettable Exits represent leaves that are unwanted by the organization and probably mean a good performer was lost. To create a strategy of retention and prevent such leaves in the future HR can observe reasons for leaving provided through the exit process.

How we calculate this

Regrettable Exits is calculated as a ratio of number of employees leaving the company, who are also eligible for rehiring as indicated by their direct managers, and total number of employees leaving the company in a given period.

Source data

Extracted from HRIS.

🚑 Problem with source data? See Data Health 101 for remedies.

Available filters

  • Age

  • Department

  • Division

  • Employment type

  • Race/Ethnicity

  • Gender

  • Generation

  • Location

  • Manager

  • Role

  • Team

  • Tenure

  • Turnover type


Source of metrics

Metrics for the Turnover chapter are extracted from your HRIS.

The metrics will only show up if you connected the required external data sources to your People Analytics account. If the data required to construct a specific metric is missing, a placeholder is displayed instead:

☝️ Example of a placeholder pointing out a missing metric

If you need help, follow the instructions to connect external data sources to your P account.

🚑 To get accurate and reliable metrics and filters, make sure your source data is in good shape. See more in the Data Health 101 guide.


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