Quit Rates by Workplace Size, 2023 to 2026

The Bureau of Labor Statistics measures quits every month by the size of the establishment in its Job Openings and Labor Turnover Survey (JOLTS). An establishment is a single workplace, not a company: a small workplace can belong to a large company, and one company can have several workplaces. BLS assigns each establishment to a size class under its own survey methodology, which may not match a workplace’s headcount in a given month. BLS describes the survey’s coverage this way: “The JOLTS program covers all private nonfarm establishments, as well as civilian federal, state, and local government entities in the 50 states and the District of Columbia.” This article uses the private nonfarm size-class series (BLS “total private”) only.

Quit rates rise, then fall, with workplace size

Average monthly quits per 100 employees, private nonfarm establishments, all six published BLS size classes, seasonally adjusted (source: U.S. Bureau of Labor Statistics, JOLTS, Table 7 series JTS100000000000001QUR through JTS100000000000006QUR, flat files downloaded October 3, 2026, data through August 2026):

BLS publishes 10 to 49 and 50 to 249 as two separate classes, and no combined rate for them is calculated here. August 2026 is preliminary, and BLS revises seasonally adjusted figures each year, so later releases can differ. The middle-class high and the 5,000-or-more low held month by month, not only on average. In each of the 36 months from September 2023 through August 2026, the highest published quit rate estimate among the six classes was at 10 to 49 or 50 to 249 employees, and the lowest was at 5,000 or more. The same was true in each of the 36 months from January 2017 through December 2019. The smallest class did not have the lowest rate. In the recent window, establishments with 1 to 9 employees (1.81) and with 1,000 to 4,999 (1.83) were close. At the precision of the published monthly rates, the 1-to-9 class was higher in 16 months, lower in 15, and tied in 5. In the earlier window, it was higher in 28 months, lower in 1, and tied in 7.

BLS publishes median standard errors for JOLTS by industry and region, not by establishment size class, so this article makes no claim of statistical significance. It reports averages and how consistently the pattern held from month to month.

How this framing came about. The study’s plan, fixed before any size-class figure was computed, set one comparison: the 1-to-9 class against a pooled group of the two largest classes. Outside reviewers pointed out that this comparison hides the shape shown above. After the results were seen, a dated amendment moved the six published classes to the front. The registered comparison is unchanged and is reported in full in the next section.

The registered comparison: 1 to 9 against a pooled 1,000-or-more group

The study set one comparison in advance: the monthly quit rate at establishments with 1 to 9 employees minus the rate at establishments with 1,000 or more. Over the 36 months, the difference averaged 0.32 quits per 100 employees per month. The 1-to-9 group had the higher rate in 86.1% of the 36 monthly comparisons, and the monthly difference ranged from negative 0.21 to positive 1.01. The 36-month average is the primary figure. The month-by-month sign count and range describe how the monthly difference varied around it.

The registered comparison group pools the two largest published classes. Over the 36 months it averaged 1.49 quits per 100 employees per month. The pooled 1,000-or-more figure is not a BLS seasonally adjusted series. Each published series is seasonally adjusted on its own, so adjusted figures need not add up exactly, and this pooled rate, built from already adjusted levels, is not the rate BLS would publish for one combined class. Each month this study reconstructs employment for each of the two classes as the seasonally adjusted total separations level divided by the seasonally adjusted total separations rate, times 100. It then divides the sum of the two classes’ seasonally adjusted quits levels by the sum of that employment, times 100. Because the published levels and rates are both rounded, this reconstructed employment can differ from the denominator BLS used, and it is not a separately published BLS series. The pooled group combines two published classes with very different quit rates, 1.83 and 0.86, so its result depends heavily on the 5,000-or-more class. As in the rest of this article, no claim of statistical significance is made.

Layoffs, hires and separations

The registered design compared four groups on all four measures. The 250 to 999 class was left out of that design before any size-class estimate was computed, and it appears only in the six-class quits table above.

Seasonally adjusted rates per 100 employees per month, private nonfarm establishments, averaged over each window (source: U.S. Bureau of Labor Statistics, JOLTS, seasonally adjusted total private by establishment size class, Table 7 series JTS100000000000001QUR, JTS100000000000002QUR, JTS100000000000003QUR, JTS100000000000005QUR, JTS100000000000006QUR, with the matching quits, LD, HI and TS level (L) series and LD, HI and TS rate (R) series, flat files downloaded October 3, 2026, data through August 2026. Inputs are the published classes. The 1,000 or more column is not a BLS series and is not in Table 7. It is this study’s pool of the seasonally adjusted 1,000 to 4,999 and 5,000 or more levels and rates):

The 1 to 9, 10 to 49, and 50 to 249 columns are averages of published BLS seasonally adjusted rates. The 1,000 or more column, including the earlier window and the change row, is not a BLS series. It is this study’s pooled calculation from the published 1,000 to 4,999 and 5,000 or more classes (see Method). Table values are rounded to two decimals. Unrounded values are in the study’s reproducibility files. Changes are the later window minus the earlier window, calculated from unrounded window averages and then rounded to two decimals, so they can differ by 0.01 from subtracting the rounded values shown. Total separations also include other separations, such as retirements, transfers and deaths, which is consistent with quits plus layoffs and discharges being less than total separations for every size group in each window.

Quit levels relative to total separations levels

Quits are one category of separation from an establishment’s payroll. Here, the quit-to-separations ratio is the sum of seasonally adjusted quits levels divided by the sum of seasonally adjusted total separations levels over September 2023 to August 2026, so it is not the ratio of the averaged rates in the table. Because seasonally adjusted series are not strictly additive, this ratio is approximate. On that basis, the ratio was 56.0% at establishments with 1 to 9 employees, 64.9% at 10 to 49, 64.5% at 50 to 249, and 54.4% at 1,000 or more.

JOLTS counts events, not people. It does not record worker demographics, the reason for a quit, or the kind of job involved. Size classes differ in industry and occupation mix. Differences by size reflect both. Nothing here isolates an effect of size.

What the numbers mean for an owner

This section and everything after it, up to Method, are interpretation and guidance from operating practice. They are not findings of this study.

In every month of both periods studied, the highest published quit rate among the six classes was in either the 10 to 49 or the 50 to 249 employee class, and the lowest was at 5,000 or more. The data does not explain why, and size classes differ in industry and occupation mix, so the pattern is not proof that size itself drives quits. For an owner, the more useful reading is practical. A workplace in either middle class that sees about two and a half quits per 100 employees a month is close to the national average for its class over September 2023 to August 2026. JOLTS does not show the spread of rates within a class, so closeness to the average is a benchmark, not a verdict.

That changes the question an owner should ask. A rising headcount often brings layers of supervision, more varied roles, and less direct contact with the owner, and the middle classes are where those changes tend to arrive. Whether they cause the higher quit rates is outside this data. Whether a specific workplace is above or below its own class average is something an owner can measure.

How to handle it: measure first, then fix the causes that are visible

The steps below are an operating recommendation. This study did not test them, and BLS does not endorse them.

1. Measure quits consistently with the BLS definition. Count voluntary quits during the month, excluding retirements and transfers to other locations. Divide by employment for the pay period that includes the 12th of the month, then multiply by 100. Track it every month for at least a year. A single month moves in large steps in a small workplace and says little on its own.

2. Compare against the closest class. Use the published establishment size class that best matches the workplace, not the company as a whole and not the largest classes. BLS assigns classes under its own survey methodology, so treat the match as approximate. For private nonfarm establishments with 10 to 49 employees, the seasonally adjusted average from September 2023 to August 2026 was 2.52 quits per 100 employees per month. A workplace well above its class average over a full year has something specific to find.

3. Ask the people who leave, and the people who stay. A short, consistent exit conversation, written down the same way each time, turns individual departures into a record. A brief conversation with people who stay, asking what would make them leave, often surfaces the same issues earlier and at lower cost.

4. Fix the systems the conversations point to. Common findings are unclear expectations in the first weeks, uneven scheduling, and supervisors promoted without guidance on how to manage. Each has a procedural answer: a written onboarding sequence, a published scheduling rule, and a short management standard for new supervisors.

What this data does not tell you

• It does not show why quit rates differ by size class, or that any practice lowers them.
• It counts quits, not people. JOLTS records no demographics and no reason for leaving.
• Figures are national averages across industries for private nonfarm establishments. An establishment is a single workplace, not a company.
• August 2026 data are preliminary, and BLS revises seasonally adjusted figures each year.

As operating guidance rather than a finding: know the workplace’s own rate, compare it to its class, and build the routines that help people stay once they are hired. The national figures are a benchmark for that work. They do not show which practices reduce quits.

Method

Already published by the agency: BLS publishes monthly JOLTS levels and rates by establishment size class in Table 7 of each release (“Job openings, hires, and separations levels and rates by establishment size class, seasonally adjusted”). New here: 36-month averages for all six published size classes in a current and a pre-pandemic window, a month-by-month count of where quits were highest and lowest, the registered pooled comparison, and quit-to-separations ratios.

Source. U.S. Bureau of Labor Statistics, Job Openings and Labor Turnover Survey, flat files (series for total private, seasonally adjusted, by establishment size class), downloaded October 3, 2026. Data run through August 2026, which BLS marks preliminary. BLS notes: “Establishment size class data are produced for the total private sector only.”

Measures. Rates are the number of events during the month as a percent of employment, which BLS states as per 100 employees. The 1,000-or-more group combines the 1,000 to 4,999 and 5,000-or-more classes. For each class and month, implied employment is the total separations level divided by the total separations rate, times 100. The pooled rate for each measure is the sum of the two classes’ levels divided by the sum of their implied employment, times 100. It is not an average of their rates. Because published levels and rates are rounded, the pooled figures cannot be reproduced exactly from rounded table values. Window figures are simple means of the monthly rates. The quit-to-separations ratio is total quits divided by total separations over the window, both in levels. No multiplicity adjustment was made. BLS revises seasonally adjusted data each year, so later downloads can differ slightly.

Protocol. The analysis plan, including the single primary comparison and the windows, was fixed in a dated protocol before any size-class estimate was computed. The six-class framing of this article was adopted after the results were seen, by a dated amendment (Amendment 8) that keeps the registered comparison and reports it in full. All amendments are listed in the protocol: https://kamyarshah.com/public-data-protocol/

Check. The July and August 2026 monthly rates for quits, layoffs and discharges, and hires in the downloaded files matched BLS Table 7 of the September 29, 2026 release for each of the six published size classes. The pooled 1,000-or-more figures are this study’s calculation and do not appear in Table 7.

The agencies did not review or endorse this analysis. Kamyar Shah sells fractional COO and CMO services.

Questions about this analysis can be sent through https://kamyarshah.com/contact/.

Kamyar Shah Fractional COO, Fractional CMO & Business Consultant

Fractional COO, Fractional CMO, and Executive Coach, Kamyar Shah, founder of World Consulting Group with over 25 years of experience helping organizations achieve operational excellence and sustainable growth. He has led 650+ consulting engagements producing more than $300M+ in measurable results. Kamyar contributes regularly to KamyarShah.com and Coruzant.

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