© 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.
Conclusion
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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