A curated dataset of the most current U.S. employee turnover statistics for 2024–2025, including voluntary and total turnover rates, monthly quit rates, sector-level comparisons, job-level differences, reasons for leaving, preventability, and cost impacts. Compiled by HIGH5 from sources including Mercer, the U.S. Bureau of Labor Statistics (JOLTS), Gallup, Work Institute, and others.

The Job Openings and Labor Turnover Survey program provides national estimates of rates and levels for job openings, hires, and total separations. Total separations are further broken out into quits, layoffs and discharges, and other separations.

In 2024, the average staff turnover rate of hospitals in the U.S. stood at **** percent. The percentage of employees leaving hospitals has decreased since the peak of ** percent in 2021. A closer look at turnover reveals that most was among less tenured staff, with the highest rates among certified nursing assistants.

Maintain the state employee turnover rate at or below the annual regional average of surrounding states every year through 2019.

A time series of staff turnover rates, broken down by provider type. Staff turnover rates are the number of staff who left employment during the period expressed as a percentage of the total number of staff employed at the start of the period.

In 2023, employee attrition rates decreased in the Americas and EMEA regions, however increased in the ACAP region. The Americas showed a decrease of 1.2 percent, with the ACAP region demonstrating a 3.3 percent increase. Relatively, however, these percentages were some of the best recorded between 2015 and 2023.

Job Openings and Labor Turnover Survey data from the U.S. Bureau of Labor Statistics

The employee attrition rate of professional services organizations worldwide ********* overall between 2013 and 2023, despite some fluctuations. During the 2023 survey, respondents reported an average employee attrition rate of **** percent.

Brazil Formal Employment: Turnover Rate: Metropolitan: São Paulo data was reported at 4.390 % in Apr 2019. This records an increase from the previous number of 4.150 % for Mar 2019. Brazil Formal Employment: Turnover Rate: Metropolitan: São Paulo data is updated monthly, averaging 3.630 % from Feb 2003 (Median) to Apr 2019, with 195 observations. The data reached an all-time high of 4.410 % in Mar 2016 and a record low of 2.010 % in Dec 2003. Brazil Formal Employment: Turnover Rate: Metropolitan: São Paulo data remains active status in CEIC and is reported by Ministry of Labor and Social Security. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBB093: Formal Employment: Turnover Rate: by Region and State.

Graph and download economic data for Quits: Total Nonfarm (JTSQUR) from Dec 2000 to Aug 2025 about quits, nonfarm, and USA.

In 2024, the average turnover rate for registered nurses that worked in hospitals across the United States stood at **** percent. This was lower than the turnover rate of **** percent in 2022. According to this survey, the percentage of registered nurses (RN) that left hospitals in 2023 ranged from roughly ** percent to nearly ** percent, depending on the discipline. The highest RN turnover was found among Telemetry nurses. On the other hand, RN turnover was the lowest in Pediatrics.

Brazil Formal Employment: Turnover Rate: Manufacturing: North data was reported at 3.430 % in Apr 2019. This records an increase from the previous number of 3.400 % for Mar 2019. Brazil Formal Employment: Turnover Rate: Manufacturing: North data is updated monthly, averaging 3.530 % from Feb 2003 (Median) to Apr 2019, with 195 observations. The data reached an all-time high of 4.380 % in Mar 2005 and a record low of 1.470 % in Dec 2015. Brazil Formal Employment: Turnover Rate: Manufacturing: North data remains active status in CEIC and is reported by Ministry of Labor and Social Security. The data is categorized under Brazil Premium Database’s Labour Market – Table BR.GBB096: Formal Employment: Turnover Rate: by Region and State: Manufacturing.

The Synthetic Employee Attrition Dataset is a simulated dataset designed for the analysis and prediction of employee attrition. It contains detailed information about various aspects of an employee's profile, including demographics, job-related features, and personal circumstances.

The dataset comprises 74,498 samples, split into training and testing sets to facilitate model development and evaluation. Each record includes a unique Employee ID and features that influence employee attrition. The goal is to understand the factors contributing to attrition and develop predictive models to identify at-risk employees.

This dataset is ideal for HR analytics, machine learning model development, and demonstrating advanced data analysis techniques. It provides a comprehensive and realistic view of the factors affecting employee retention, making it a valuable resource for researchers and practitioners in the field of human resources and organizational development.

FEATURES:

Employee ID: A unique identifier assigned to each employee. Age: The age of the employee, ranging from 18 to 60 years. Gender: The gender of the employee Years at Company: The number of years the employee has been working at the company. Monthly Income: The monthly salary of the employee, in dollars. Job Role: The department or role the employee works in, encoded into categories such as Finance, Healthcare, Technology, Education, and Media. Work-Life Balance: The employee's perceived balance between work and personal life, (Poor, Below Average, Good, Excellent) Job Satisfaction: The employee's satisfaction with their job: (Very Low, Low, Medium, High) Performance Rating: The employee's performance rating: (Low, Below Average, Average, High) Number of Promotions: The total number of promotions the employee has received. Distance from Home: The distance between the employee's home and workplace, in miles. Education Level: The highest education level attained by the employee: (High School, Associate Degree, Bachelor’s Degree, Master’s Degree, PhD) Marital Status: The marital status of the employee: (Divorced, Married, Single) Job Level: The job level of the employee: (Entry, Mid, Senior) Company Size: The size of the company the employee works for: (Small,Medium,Large) Company Tenure: The total number of years the employee has been working in the industry. Remote Work: Whether the employee works remotely: (Yes or No) Leadership Opportunities: Whether the employee has leadership opportunities: (Yes or No) Innovation Opportunities: Whether the employee has opportunities for innovation: (Yes or No) Company Reputation: The employee's perception of the company's reputation: (Very Poor, Poor,Good, Excellent) Employee Recognition: The level of recognition the employee receives:(Very Low, Low, Medium, High)

Attrition: Whether the employee has left the company, encoded as 0 (stayed) and 1 (Left).

A data-driven review of employee retention and turnover in 2024–2025 with benchmarks, industry comparisons, drivers of quits, and actionable retention levers.

Bureau of Labor Statistics - Job Openings and Labor Turnover Survey (JOLTS) 2000-2025From the BLS:Job Openings and Labor Turnover Survey Overview PageThe Job Openings and Labor Turnover Survey (JOLTS) is a monthly survey that has been developed to address the need for data on job openings, hires, and separations.PurposeThese data serve as demand-side indicators of labor shortages at the national level. Prior to JOLTS, there was no economic indicator of the unmet demand for labor with which to assess the presence or extent of labor shortages in the United States. The availability of unfilled jobs—the job openings rate—is an important measure of the tightness of job markets, parallel to existing measures of unemployment.ScopeData from a sample of approximately 21,000 U.S. business establishments are collected by the Bureau of Labor Statistics through JOLTS Data Collection Centers in Atlanta and Kansas City. The JOLTS survey covers all nonagricultural industries in the public and private sectors for the 50 States and the District of Columbia.Data ElementsJOLTS collects data on Total Employment, Job Openings, Hires, Quits, Layoffs & Discharges, and Other Separations. For more information on the JOLTS data elements, see the JOLTS data definitions page.Reference PeriodsTotal Employment - the pay period that includes the 12th of the month.Job Openings - the last business day of the month.Hires and Separations - the entire calendar month.

Turnover data by fiscal year for the City of Tempe compared to the seven market cities, which include Chandler, Gilbert, Glendale, Mesa, Phoenix, Peoria, and Scottsdale. There are two totals, one with and one without retirees.Please note that the Valley Benchmark Cities’ annual average is unavailable for FY 2020/2021 due to a gap in data collection during that year. Please note that corrections were made to the data, including historic data, due to additional review and research on the data on 10/2/2024.This page provides data for the Employee Turnover performance measure.The performance measure dashboard is available at 5.07 Employee Turnover.Data DictionaryAdditional InformationSource: Department ReportsContact: Lawrence La VictoireContact E-Mail: lawrence_lavictoire@tempe.govData Source Type: ExcelPreparation Method: Extracted from PeopleSoft, and requested data from other cities is entered manually into a spreadsheet, and calculations are conducted to determine the percent of turnover per fiscal yearPublish Frequency: AnnuallyPublish Method: Manual

Voluntary employee turnover in business service centers in Poland in 2024 was nearly *** percent. The highest turnover was recorded in 2022.

Graph and download economic data for Layoffs and Discharges: Total Private (JTS1000LDL) from Dec 2000 to Aug 2025 about discharges, layoffs, private, and USA.

Job Quits Rate in the United States decreased to 1.90 percent in August from 2 percent in July of 2025. This dataset includes a chart with historical data for the United States Job Quits Rate.

Graph and download economic data for Quits: Accommodation and Food Services (JTS7200QUR) from Dec 2000 to Aug 2025 about quits, accommodation, food, services, and USA.