© Copyright 2003 by the Wyoming Department of Employment, Research & Planning


Your Firm's Employee Turnover: How to Calculate it and How it Compares

by: Tony Glover, Research Analyst and Douglas W. Leonard, Research Analyst

"Using micro-level Wage Records in concert with other administrative data allows us to determine turnover rates at levels of detail not attainable with survey methods."

What is turnover? A popular Internet search engine returned 567,000 hits for the key words “Employment Turnover.” The majority of the first 100 hits dealt with suggestions for retaining employees with the objective of lowering costs associated with recruitment and training of new employees. Therefore, turnover is a measure of the loss of employees that creates job openings which may need to be filled. Turnover traditionally has a negative connotation but that is not always the case. We demonstrate, through an employer level example, that turnover can be an adaptive behavior that allows employers to survive in Wyoming.

The primary intent of this article is to offer employers the tools to determine their own turnover rates and compare them to rates of firms within their industries. A secondary goal is to re-introduce our readers to the first of a set of data tools Research & Planning (R&P) has developed and presented over the past few years. We demonstrate that using micro-level Wage Records in concert with other administrative data allows us to determine turnover rates at levels of detail (e.g., employer, county, region, occupation) not attainable with survey methods.

Calculating Turnover

The foundation of R&P turnover calculations is the Wage Records database. Wage Records are collected quarterly by the Unemployment Insurance (UI) Tax section and include a list of all Social Security Numbers (SSN) and associated total wages paid by UI covered employers to their employees. Wage Records is a useful tool in determining the distribution of employees by industry in any given quarter. R&P adds another dimension to Wage Records data by combining archived (back to 1992) and current quarterly data. The use of Wage Records as a time series allows us to study the dynamic relationship between an employee and an employer. In aggregating micro (SSN with Employer) level data, we can analyze worker behavior at the employer, industry, or county level and compare it to similar groups.

Table 1 is a modified excerpt of the first two quarters of 2003 (2003Q1 and 2003Q2) for two employers from R&P’s Wage Records data. Our first modification was removing employer UI account numbers and replacing them with the characteristic of being either a Low Turnover Employer or a High Turnover Employer. Additionally, the employee’s SSNs have been replaced with names selected at random from the top 50 most popular names for men and women. Lastly, we have added a column that defines the employee’s work status with the employer in 2003Q1 relative to 2003Q2.

As shown in Table 1, the Low and High Turnover Employers had 15 and 14 employees, respectively, working in 2003Q1. Working means the individual had wages during the quarter. By 2003Q2 one employee (Bryce) was no longer employed by the Low Turnover Employer and seven employees were no longer with the High Turnover Employer. Those employed during 2003Q1 but no longer with the employer during 2003Q2 are defined as Exits (X in the Work Status column) during 2003Q1. The employees remaining with the employer, for the time being, are defined as Continuous (C) employees. The turnover rate (exit rate) of the Low Turnover Employer is equal to the number of Exits (1) divided by the total number of employees (15) in 2003Q1 or 6.7 percent. Likewise, the turnover rate for the High Turnover Employer is equal to 7 divided by 14 or 50.0 percent.

Comparing Employers, Industries, and Totals

The Low and High Turnover Employers are at different ends of the spectrum with respect to how they used labor during 2003Q1. There are, however, a few things to consider when deciding if the interactions of these employers with their employees are necessarily good or bad. Table 2 shows that both employers belong to the Accommodations industry, which has a total turnover rate of 21.5 percent. R&P selected an employer in the Accommodations industry with low turnover, a hotel in a populated city by Wyoming standards, and high turnover, a mountain lodge that caters to seasonal cross-country skiers and snowmobilers. It is unlikely that the seasonal nature of the mountain lodge’s revenue would allow it to maintain its employees year round.

The turnover rate of the Accommodations industry in 2003Q1 is the result of summing the total number of employees working in the industry in 2003Q1 who were not working for the same employers in 2003Q2 (1 [Low Turnover Employer] + 7 [High Turnover Employer] + 2,237 [Balance of Employers] = 2,245 Exits). Divide the total Exits by the total number of employees working in the industry in 2003Q1 (15 [Low Turnover Employer] + 14 [High Turnover Employer] + 10,432 [Balance of Employers] = 10,461 Total Employees). This calculation (2,245 Exits divided by 10,461 Total Employees) produces a turnover rate of 21.5 percent for the Accommodations industry in 2003Q1. The same procedure is used to calculate the turnover rates for all of the industries and the total.

Table 2 shows that turnover varies by industry with some industries at the low end (Government and Utilities) and others at the upper extremes (Leisure & Hospitality and Construction). Further, it reveals that turnover is seasonal in nature with peaks occurring in the third quarter. This is the result of employers shedding excess employees following the summer months. The Figure shows the seasonal fluctuations more clearly. While these fluctuations are a result of increased turnover, it is important that Wyoming’s economy take advantage of business opportunities related to the seasonal climate. However, in terms of maximizing training program outcomes and locating stable employment so entry-level workers can gain job experience, it makes sense to place clients of training programs with industries/employers that are likely to retain them year round.


R&P uses the bottom up approach to turnover calculation. In the preceding examples, we have demonstrated how turnover is calculated at the employer level and offer the methodology to employers in Wyoming. We have also shown that using Wage Records, we begin at the employee-with-employer level data and aggregate up to calculate industry and total labor market turnover. This bottom up procedure, when combined with other administrative data, allows us to apply the described method to numerous labor force issues. Lastly, turnover (exit rates) only reflects one component of labor market dynamics. Additional literature, available on R&P’s website, discusses other data tools available.


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