100+ datasets found
  1. E

    Payroll Statistics By Employee Retention, Automation And Facts (2025)

    • electroiq.com
    Updated Jul 2, 2025
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    Electro IQ (2025). Payroll Statistics By Employee Retention, Automation And Facts (2025) [Dataset]. https://electroiq.com/stats/payroll-statistics/
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    Dataset updated
    Jul 2, 2025
    Dataset authored and provided by
    Electro IQ
    License

    https://electroiq.com/privacy-policyhttps://electroiq.com/privacy-policy

    Time period covered
    2022 - 2032
    Area covered
    Global
    Description

    Introduction

    Payroll Statistics: Payroll management is an important facet affecting business operations, employee satisfaction, compliance, and financial planning. In the year 2024, several trends began appearing, reshaping the way organisations look at payroll.

    In 2024, payroll emerged as a critical business function, with nearly 70 percent of companies reporting issues in their payroll data, and over 82 million American workers experiencing paycheck errors at some point. About 65 percent of employees relied on each paycheck to cover basic expenses, and 95.15 percent were paid via direct deposit. In the private sector, 43 percent of establishments adopted a biweekly pay cycle, making it the most common rhythm, followed by 27 percent on weekly pay, 19.8 percent semi‑monthly, and 10.3 percent monthly. Payroll inaccuracies carried a tangible cost: a 1.2 percent error rate across a payroll of 100 employees earning $900 weekly could cost $56,647 annually.

    Small businesses typically devoted more than six hours each month to payroll tasks, with one-third reporting that payroll consumed over 35 percent of HR effort. Cloud and automation adoption reached approximately 74 percent, yet 85 percent of organizations still encountered challenges with their payroll technologies.  Additionally, around 53 percent of companies were penalized for non‑compliance within five years.

    This article shall talk about some up-to-date Payroll statistics and latest insights so as to offer a full overview of the current scenario of payroll.

  2. O

    State of Oklahoma Payroll - Fiscal Year 2025

    • data.ok.gov
    csv
    Updated Jun 16, 2025
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    Office of Management and Enterprise Services (2025). State of Oklahoma Payroll - Fiscal Year 2025 [Dataset]. https://data.ok.gov/dataset/state-of-oklahoma-payroll-fiscal-year-2025
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    csv(20108539), csv(26975133), csv(15856328), csv(20547800), csv(20157848), csv(20046874), csv(18895075), csv(20227944), csv(26565289), csv(17340104), csv(17665514)Available download formats
    Dataset updated
    Jun 16, 2025
    Dataset authored and provided by
    Office of Management and Enterprise Services
    Area covered
    Oklahoma
    Description

    The payroll data represents the amount paid to an employee during the reported time period. In addition to regular pay, these amounts may include other pay types such as overtime, longevity, shift differential or terminal pay. This amount does not include any state share costs associated with the payroll i.e. FICA, state share retirement, etc. This amount may vary from an employee’s ‘salary’ due to pay adjustments or pay period timing. The payroll information will be updated monthly after the end of the month. For example, July information will be added in August after the 15th of the month.

  3. d

    2025 State Employee Pay

    • catalog.data.gov
    • data.mo.gov
    Updated Jul 5, 2025
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    data.mo.gov (2025). 2025 State Employee Pay [Dataset]. https://catalog.data.gov/dataset/2025-state-employee-pay
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    Dataset updated
    Jul 5, 2025
    Dataset provided by
    data.mo.gov
    Description

    Pay Information for calendar year 2025 for the employees of the State of Missouri by their Agency of employment, Position Title or Employee name.

  4. Global gender pay gap 2015-2025

    • statista.com
    • ai-chatbox.pro
    Updated Jul 23, 2025
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    Statista (2025). Global gender pay gap 2015-2025 [Dataset]. https://www.statista.com/statistics/1212140/global-gender-pay-gap/
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    Dataset updated
    Jul 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    The difference between the earnings of women and men shrank slightly over the past years. Considering the controlled gender pay gap, which measures the median salary for men and women with the same job and qualifications, women earned one U.S. cent less. By comparison, the uncontrolled gender pay gap measures the median salary for all men and all women across all sectors and industries and regardless of location and qualification. In 2025, the uncontrolled gender pay gap in the world stood at 0.83, meaning that women earned 0.83 dollars for every dollar earned by men.

  5. F

    Employed full time: Median usual weekly real earnings: Wage and salary...

    • fred.stlouisfed.org
    json
    Updated Jul 22, 2025
    + more versions
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    (2025). Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over [Dataset]. https://fred.stlouisfed.org/series/LES1252881600Q
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 22, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employed full time: Median usual weekly real earnings: Wage and salary workers: 16 years and over (LES1252881600Q) from Q1 1979 to Q2 2025 about full-time, salaries, workers, earnings, 16 years +, wages, median, real, employment, and USA.

  6. U.S. wage and salary workers: weekly earnings by gender and ethnicity Q1...

    • statista.com
    Updated Jul 14, 2025
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    Statista (2025). U.S. wage and salary workers: weekly earnings by gender and ethnicity Q1 2025 [Dataset]. https://www.statista.com/statistics/185409/median-weekly-earnings-of-full-time-wage-and-salary-workers-by-gender-and-ethnicity/
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    Dataset updated
    Jul 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    This statistic shows the median weekly earnings of full-time wage and salary workers in the United States by gender and ethnicity in the first quarter of 2025. The usual weekly earnings of a male Asian American wage worker was 1,822 U.S. dollars.

  7. United States Monthly Earnings

    • ceicdata.com
    Updated Mar 21, 2025
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    CEICdata.com (2025). United States Monthly Earnings [Dataset]. https://www.ceicdata.com/en/indicator/united-states/monthly-earnings
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    Dataset updated
    Mar 21, 2025
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2024 - Feb 1, 2025
    Area covered
    United States
    Description

    Key information about United States Monthly Earnings

    • United States Monthly Earnings stood at 4,901 USD in Feb 2025, compared with the previous figure of 4,887 USD in Jan 2025
    • US Monthly Earnings data is updated monthly, available from Mar 2006 to Feb 2025, with an average number of 3,469 USD
    • The data reached the an all-time high of 4,901 USD in Feb 2025 and a record low of 2,743 USD in Mar 2006

    CEIC calculates Monthly Earnings from Average Weekly Earnings multiplied by 4. U.S. Bureau of Labor Statistics provides Average Weekly Earnings in USD. Monthly Earnings include Private Non Agricultural sector only.


    Further information about United States Monthly Earnings

    • In the latest reports, US Population reached 341 million people in Dec 2024
    • Unemployment Rate of US increased to 4 % in Feb 2025
    • The country's Labour Force Participation Rate remained the same rate at 62 % in Feb 2025

  8. Employee Satisfaction Statistics (2024–2025) in the US and Globally

    • high5test.com
    html
    Updated Jul 24, 2025
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    HIGH5 Test (2025). Employee Satisfaction Statistics (2024–2025) in the US and Globally [Dataset]. https://high5test.com/employee-satisfaction-statistics/
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    htmlAvailable download formats
    Dataset updated
    Jul 24, 2025
    Dataset provided by
    Authors
    HIGH5 Test
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2024 - Dec 31, 2025
    Area covered
    United States
    Description

    A comprehensive dataset of employee and job satisfaction statistics for 2024 and 2025, covering the United States and global comparisons. Data includes breakdowns by age, race, income, job type, and key drivers such as pay satisfaction, burnout, hybrid work, recognition, and sense of purpose.

  9. T

    United States Wages and Salaries Growth

    • tradingeconomics.com
    • pl.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jun 14, 2025
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    TRADING ECONOMICS (2025). United States Wages and Salaries Growth [Dataset]. https://tradingeconomics.com/united-states/wage-growth
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Jun 14, 2025
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 31, 1960 - Jun 30, 2025
    Area covered
    United States
    Description

    Wages in the United States increased 4.78 percent in June of 2025 over the same month in the previous year. This dataset provides the latest reported value for - United States Wages and Salaries Growth - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

  10. F

    Employment Level - Nonagriculture, Private Households Wage and Salary...

    • fred.stlouisfed.org
    json
    Updated Aug 1, 2025
    + more versions
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    (2025). Employment Level - Nonagriculture, Private Households Wage and Salary Workers [Dataset]. https://fred.stlouisfed.org/series/LNU02032190
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Aug 1, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Employment Level - Nonagriculture, Private Households Wage and Salary Workers (LNU02032190) from Jan 2000 to Jul 2025 about nonagriculture, salaries, workers, 16 years +, wages, household survey, private, employment, and USA.

  11. d

    Employee Payroll Data (FMPS Payroll Costing)

    • catalog.data.gov
    • data.cityofchicago.org
    Updated Jul 12, 2025
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    data.cityofchicago.org (2025). Employee Payroll Data (FMPS Payroll Costing) [Dataset]. https://catalog.data.gov/dataset/employee-payroll-data-fmps-payroll-costing
    Explore at:
    Dataset updated
    Jul 12, 2025
    Dataset provided by
    data.cityofchicago.org
    Description

    Note, 7/10/2025: Please see this article for information on a change to the EMPLOYEE DATASET ID column and this article for information on a data correction. Welcome to the official source for Employee Payroll Costing data for the City of Chicago. This dataset offers a clean, comprehensive view of the City's payroll information by employee. About the Dataset: This has been extracted from the City of Chicago's Financial Management and Purchasing System (FMPS). FMPS is the system used to process all financial transactions made by the City of Chicago, ensuring accuracy and transparency in fiscal operations. This dataset includes useful details like employee name, pay element, pay period, fund, appropriation, department, and job title. Data Disclaimer: The following data disclaimer governs your use of the dataset extracted from the Payroll Costing module of the City of Chicago's Financial Management and Purchasing System (FMPS) or (FMPS Payroll Costing). Point-in-Time Extract: The dataset provided herein, represents a point-in-time extract from the FMPS Payroll Costing module and may not reflect real-time or up-to-date data. Financial Statement Disclaimer – Timeframe and Limitations: This dataset is provided without audit. It is essential to note that this dataset is not a component of the City's Annual Comprehensive Financial Report (ACFR). As such, it remains preliminary and is subject to the end-of-year reconciliation process inherent to the City's annual financial procedures outlined in the ACFR. Note on Pay Elements: All pay elements available in the FMPS Payroll Costing module have been included in this dataset. Previously published datasets, such as "Employee Overtime and Supplemental Earnings," contained only a subset of these pay elements. Payroll Period: The dataset's timeframe is organized into 24 payroll periods. It is important to understand that these periods may or may not directly correspond to specific earnings periods. Aggregating Data: The CIty of Chicago often has employees with the same name (including middle initials). It is vital to use the unique employee identifier code (EMPLOYEE DATASET ID) when aggregating at the employee level to avoid duplication. Data Subject to Change: This dataset is subject to updates and modifications due to the course of business, including activities such as canceling, adjusting, and reissuing checks. Data Disclosure Exemptions: Information disclosed in this dataset is subject to FOIA Exemption Act, 5 ILCS 140/7 (Link:https://www.ilga.gov/legislation/ilcs/documents/000501400K7.htm)

  12. Average monthly pay of employees in the UK in 2025, by percentile

    • statista.com
    Updated May 14, 2025
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    Statista (2025). Average monthly pay of employees in the UK in 2025, by percentile [Dataset]. https://www.statista.com/statistics/1224844/monthly-pay-of-employees-uk/
    Explore at:
    Dataset updated
    May 14, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 2025
    Area covered
    United Kingdom
    Description

    In March 2025, the top one percent of earners in the United Kingdom received an average pay of over 16,000 British pounds per month, compared with the bottom ten percent of earners who earned around 800 pounds a month.

  13. T

    United States - Time To Prepare And Pay Taxes (hours)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 13, 2017
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    TRADING ECONOMICS (2017). United States - Time To Prepare And Pay Taxes (hours) [Dataset]. https://tradingeconomics.com/united-states/time-to-prepare-and-pay-taxes-hours-wb-data.html
    Explore at:
    json, excel, xml, csvAvailable download formats
    Dataset updated
    Jun 13, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    Time to prepare and pay taxes (hours) in United States was reported at 175 hours in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Time to prepare and pay taxes (hours) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

  14. 2025 Green Card Report for Bachelor Degree In Statistics With A...

    • myvisajobs.com
    Updated Jan 16, 2025
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    MyVisaJobs (2025). 2025 Green Card Report for Bachelor Degree In Statistics With A Concentration In Mathematics [Dataset]. https://www.myvisajobs.com/reports/green-card/major/bachelor-degree-in-statistics-with-a-concentration-in-mathematics
    Explore at:
    Dataset updated
    Jan 16, 2025
    Dataset provided by
    MyVisaJobs.com
    Authors
    MyVisaJobs
    License

    https://www.myvisajobs.com/terms-of-service/https://www.myvisajobs.com/terms-of-service/

    Variables measured
    Major, Salary, Petitions Filed
    Description

    A dataset that explores Green Card sponsorship trends, salary data, and employer insights for bachelor degree in statistics with a concentration in mathematics in the U.S.

  15. T

    United States - Unemployment Rate - Financial Activities Industry, Private...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Mar 12, 2018
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    TRADING ECONOMICS (2018). United States - Unemployment Rate - Financial Activities Industry, Private Wage and Salary Workers [Dataset]. https://tradingeconomics.com/united-states/unemployment-rate-financial-activities-industry-private-wage-and-salary-workers-fed-data.html
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Mar 12, 2018
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    United States
    Description

    United States - Unemployment Rate - Financial Activities Industry, Private Wage and Salary Workers was 2.30% in June of 2025, according to the United States Federal Reserve. Historically, United States - Unemployment Rate - Financial Activities Industry, Private Wage and Salary Workers reached a record high of 7.70 in March of 2010 and a record low of 1.30 in September of 2022. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Unemployment Rate - Financial Activities Industry, Private Wage and Salary Workers - last updated from the United States Federal Reserve on August of 2025.

  16. F

    Average Weekly Earnings of All Employees, Total Private

    • fred.stlouisfed.org
    json
    Updated Jul 3, 2025
    + more versions
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    (2025). Average Weekly Earnings of All Employees, Total Private [Dataset]. https://fred.stlouisfed.org/series/CES0500000011
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Jul 3, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Average Weekly Earnings of All Employees, Total Private (CES0500000011) from Mar 2006 to Jun 2025 about earnings, establishment survey, private, employment, and USA.

  17. China Disposable Income per Capita: ytd: Wage and Salary

    • ceicdata.com
    Updated Feb 15, 2025
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    CEICdata.com (2025). China Disposable Income per Capita: ytd: Wage and Salary [Dataset]. https://www.ceicdata.com/en/china/income-per-capita/disposable-income-per-capita-ytd-wage-and-salary
    Explore at:
    Dataset updated
    Feb 15, 2025
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2022 - Dec 1, 2024
    Area covered
    China
    Variables measured
    Household Income and Expenditure Survey
    Description

    China Disposable Income per Capita: Year to Date: Wage and Salary data was reported at 6,975.788 RMB in Mar 2025. This records a decrease from the previous number of 23,327.000 RMB for Dec 2024. China Disposable Income per Capita: Year to Date: Wage and Salary data is updated quarterly, averaging 10,104.000 RMB from Mar 2013 (Median) to Mar 2025, with 49 observations. The data reached an all-time high of 23,327.000 RMB in Dec 2024 and a record low of 2,849.430 RMB in Mar 2013. China Disposable Income per Capita: Year to Date: Wage and Salary data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Household Survey – Table CN.HD: Income per Capita.

  18. T

    World - Time To Prepare And Pay Taxes (hours)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 2, 2017
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    TRADING ECONOMICS (2017). World - Time To Prepare And Pay Taxes (hours) [Dataset]. https://tradingeconomics.com/world/time-to-prepare-and-pay-taxes-hours-wb-data.html
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    Jun 2, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    World, World
    Description

    Time to prepare and pay taxes (hours) in World was reported at 233 hours in 2019, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Time to prepare and pay taxes (hours) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

  19. O

    2025 Fort Collins City Employee Base Pay

    • opendata.fcgov.com
    application/rdfxml +5
    Updated Feb 21, 2025
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    Human Resources (2025). 2025 Fort Collins City Employee Base Pay [Dataset]. https://opendata.fcgov.com/High-Performing-Government/2025-Fort-Collins-City-Employee-Base-Pay/3ahc-jpuf
    Explore at:
    csv, application/rssxml, tsv, xml, application/rdfxml, jsonAvailable download formats
    Dataset updated
    Feb 21, 2025
    Dataset authored and provided by
    Human Resources
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Area covered
    Fort Collins
    Description

    City employee base salary as of 2025-01-14.

    The 2025 data provides base salaries for every position's compensation. The data represents a snapshot of base salaries for all employees as of 2025-01-14 for the City of Fort Collins in an hourly rate or annual salary format for 2025 rather than a forecasted amount of actual salary payments for 2025. Personnel spending data can be found on openbook.fcgov.com

  20. T

    North America - Wage And Salary Workers; Male (% Of Males Employed)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Feb 6, 2020
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    TRADING ECONOMICS (2020). North America - Wage And Salary Workers; Male (% Of Males Employed) [Dataset]. https://tradingeconomics.com/north-america/wage-and-salary-workers-male-percent-of-males-employed-wb-data.html
    Explore at:
    csv, json, xml, excelAvailable download formats
    Dataset updated
    Feb 6, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    North America
    Description

    Wage and salaried workers, male (% of male employment) (modeled ILO estimate) in North America was reported at 91.57 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. North America - Wage and salary workers; male (% of males employed) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

Share
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Electro IQ (2025). Payroll Statistics By Employee Retention, Automation And Facts (2025) [Dataset]. https://electroiq.com/stats/payroll-statistics/

Payroll Statistics By Employee Retention, Automation And Facts (2025)

Explore at:
Dataset updated
Jul 2, 2025
Dataset authored and provided by
Electro IQ
License

https://electroiq.com/privacy-policyhttps://electroiq.com/privacy-policy

Time period covered
2022 - 2032
Area covered
Global
Description

Introduction

Payroll Statistics: Payroll management is an important facet affecting business operations, employee satisfaction, compliance, and financial planning. In the year 2024, several trends began appearing, reshaping the way organisations look at payroll.

In 2024, payroll emerged as a critical business function, with nearly 70 percent of companies reporting issues in their payroll data, and over 82 million American workers experiencing paycheck errors at some point. About 65 percent of employees relied on each paycheck to cover basic expenses, and 95.15 percent were paid via direct deposit. In the private sector, 43 percent of establishments adopted a biweekly pay cycle, making it the most common rhythm, followed by 27 percent on weekly pay, 19.8 percent semi‑monthly, and 10.3 percent monthly. Payroll inaccuracies carried a tangible cost: a 1.2 percent error rate across a payroll of 100 employees earning $900 weekly could cost $56,647 annually.

Small businesses typically devoted more than six hours each month to payroll tasks, with one-third reporting that payroll consumed over 35 percent of HR effort. Cloud and automation adoption reached approximately 74 percent, yet 85 percent of organizations still encountered challenges with their payroll technologies.  Additionally, around 53 percent of companies were penalized for non‑compliance within five years.

This article shall talk about some up-to-date Payroll statistics and latest insights so as to offer a full overview of the current scenario of payroll.

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