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)
This dataset is a listing of all active City of Chicago employees, complete with full names, departments, positions, employment status (part-time or full-time), frequency of hourly employee –where applicable—and annual salaries or hourly rate. Please note that "active" has a specific meaning for Human Resources purposes and will sometimes exclude employees on certain types of temporary leave. For hourly employees, the City is providing the hourly rate and frequency of hourly employees (40, 35, 20 and 10) to allow dataset users to estimate annual wages for hourly employees. Please note that annual wages will vary by employee, depending on number of hours worked and seasonal status. For information on the positions and related salaries detailed in the annual budgets, see https://www.cityofchicago.org/city/en/depts/obm.html
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)
This transformed view of Employee Demographics - Public dataset counts the number of and percentage of city employees by race as self-reported by employee based on EEOC classification. This information is used by "City Employee vs. Community Demographics dataset" at https://citydata.mesaaz.gov/Economic-Development/Chart-Data-for-City-Employee-vs-Community-Demograp/bt2n-zimw
ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
License information was derived automatically
A. SUMMARY The San Francisco Controller's Office maintains a database of the salary and benefits paid to City employees since fiscal year 2013.
B. HOW THE DATASET IS CREATED This data is summarized and presented on the Employee Compensation report hosted at http://openbook.sfgov.org, and is also available in this dataset in CSV format.
C. UPDATE PROCESS New data is added on a bi-annual basis when available for each fiscal and calendar year.
D. HOW TO USE THIS DATASET Before using please first review the following two resources:
This dataset comprises the ten generic queries related to employment monitoring software with the highest volume of internet searches since March 2020. The terms are ordered largest to smallest. The percentage difference values are based on that period’s search volume compared to the average monthly searches in 2019.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This data is subject to change at any time due to personnel actions that are consistent with the City's approved Pay Plan. Employee compensation is limited to the following pay: regular wages, over time, productivity enhancement, shift differential, standby, incentive pay, allowances, and leave payouts. The data is a snapshot as of December 31st of the reported year.
Job descriptions, pay ranges, and benefits information is available at: https://www.phoenix.gov/hr/job-descriptions
Total compensation information is available at: https://www.phoenix.gov/hr/current-jobs/total-compensation-information
Employee terms by unit is available at: https://www.phoenix.gov/hr/employee-terms-by-unit
Explore demographic data on the Massachusetts executive branch workforce. Track our progress toward our goals to reflect the diversity of the people we serve, and to stand out as an employer of choice.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
A comprehensive dataset featuring the latest employee motivation statistics, including factors influencing workplace motivation, engagement levels, productivity metrics, and psychological insights from various sources.
Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
License information was derived automatically
Employee jobs by industry and sex, UK, published quarterly, not seasonally adjusted.
The Office of Personnel Management requires government agencies, at a minimum, to query employees on job satisfaction, organizational assessment and organizational culture. VHA maintains response data for all census surveys such as the Voice of VA as well as the VA Entrance and Exit surveys.
This dataset was created by Pinky Verma
Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
License information was derived automatically
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This is a synthetic dataset that contains information about 300 employees, each represented by three features: date_of_birth, date_of_joining, and gender. The date_of_birth and date_of_joining columns are provided in dd-mm-yyyy format, indicating the employee's age and tenure with the company respectively. The gender column includes values such as male, female, and other . The target variable, promoted, indicates whether an employee received a promotion (yes) or not (no). The dataset is logically structured such that employees who are older, have spent more time in the company, and identify as female have a higher likelihood of being promoted.
Starting with 2023 data, this series of annual datasets has been replaced with the Employee Payroll Data (FMPS Payroll Costing) dataset.
Employee overtime and supplemental earnings by month and year-to-date.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Private Employee: ARP: Part-Time Workers data was reported at 22.000 % in 2018. This records an increase from the previous number of 21.000 % for 2017. Private Employee: ARP: Part-Time Workers data is updated yearly, averaging 20.500 % from Mar 1999 (Median) to 2018, with 18 observations. The data reached an all-time high of 23.000 % in 2008 and a record low of 18.000 % in 2003. Private Employee: ARP: Part-Time Workers data remains active status in CEIC and is reported by Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.G077: Employee Benefits Survey: Private Industry.
This dataset includes Baltimore City employee salaries and gross pay from fiscal year 2011 through last fiscal year and includes employees who were employed on June 30 of the last fiscal year. For fiscal years 2020 and prior, data are extracted from the ADP payroll system. For fiscal year 2023, the data are combined from the ADP system and the Workday enterprise resource planning system which now includes payroll.Change Log- Added FY2023 data- Metadata added- Columns renamed to a standard format- Youth workers not employed by City removed- Agency names reformatted with Workday conventions-7/25/24: Added FY2024 data. To leave feedback or ask a question about this dataset, please fill out the following form: Baltimore City Employee Salaries feedback form.
In fiscal year 2023, the number of employees working for the Japanese retail company Ryohin Keikaku exceeded 10 thousand people for the first time in the last decade.Ryohin Keikaku Co. Ltd. is the retailer and wholesaler behind the Japanese brand Mujirushi Ryohin (Muji), which offers a wide variety of household items and consumer goods.
https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy
In 2023, the global market size for Employee Pulse Survey Tools was valued at approximately USD 1.2 billion, with a forecasted growth to USD 3.5 billion by 2032, driven by a robust CAGR of 12.3%. This impressive growth can be attributed to a combination of factors including rising awareness about employee engagement, the increasing emphasis on real-time feedback mechanisms, and the continuous advancements in data analytics and AI technologies.
The primary driver of growth in the Employee Pulse Survey Tool market is the increasing recognition of the critical role that employee engagement and satisfaction play in organizational success. Companies are increasingly focusing on maintaining a healthy workplace environment to enhance productivity and reduce turnover rates. Employee pulse surveys provide a continuous and real-time feedback loop, enabling organizations to understand and address employee concerns proactively. This real-time feedback mechanism is proving invaluable in refining management strategies, improving work culture, and ultimately driving business outcomes.
Another significant growth factor is the advancement in data analytics and AI technologies. Modern employee pulse survey tools are leveraging advanced analytics and machine learning algorithms to deliver deeper insights into employee sentiment and engagement levels. These tools can analyze large volumes of feedback data efficiently, identifying trends and patterns that might not be immediately obvious. This capability allows organizations to make informed decisions based on data-driven insights, which in turn enhances the effectiveness of their employee engagement strategies.
The increasing integration of pulse survey tools with other HR and management systems is also contributing to market growth. By seamlessly integrating with existing HR systems, these tools can provide a more comprehensive view of employee data, facilitating better decision-making. This integration also helps in streamlining processes, reducing administrative burdens, and providing a unified platform for employee engagement and feedback management. As a result, organizations are more inclined to adopt these tools, further driving market growth.
As organizations strive to enhance employee engagement and satisfaction, the role of an Employee Feedback Platform becomes increasingly crucial. These platforms provide a structured and efficient way for employees to share their thoughts and concerns, fostering an environment of open communication. By utilizing an Employee Feedback Platform, companies can gather valuable insights into employee sentiment, allowing them to address issues proactively and improve workplace culture. This proactive approach not only helps in retaining talent but also boosts overall productivity and morale. The integration of feedback platforms with pulse survey tools further enhances their effectiveness, providing a comprehensive solution for managing employee engagement and feedback.
From a regional perspective, North America is expected to hold the largest market share, followed by Europe and the Asia Pacific. The high adoption rate of advanced HR technologies and the presence of a significant number of large enterprises in North America are key factors contributing to its leading position. Meanwhile, the Asia Pacific region is anticipated to witness the highest growth rate, driven by the increasing awareness about employee engagement and the rising number of SMEs adopting pulse survey tools.
The Employee Pulse Survey Tool market can be segmented by component into software and services. The software component, which includes platforms and applications, is often the primary focus as it represents the actual tools that organizations use to conduct surveys and analyze data. These software solutions are designed to be user-friendly, customizable, and scalable, catering to the diverse needs of different organizations. With continuous advancements in software capabilities, such as enhanced data analytics, AI-driven insights, and seamless integration with other HR systems, the demand for robust and feature-rich software solutions is on the rise.
On the other hand, the services component is equally critical as it encompasses various support and consulting services that enhance the implementation and utilization of pulse survey tools. These services include technical support, training,
According a report from Casaleggio Associati, the energy sector had the highest average revenue per employee in the United States in 2018. That year, the energy industry had an average revenue of 1.79 million U.S. dollars per employee.
As of March 2024, employers of civilian, industry, and state and local government workers in the United States all averaged around 33 percent of their employee costs on benefits. The highest among them were those employing state and local government workers, who spent an average of 38.1 percent of their employee costs on benefits.
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)