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License information was derived automatically
Private businesses in the United States hired 37 thousand workers in May of 2025 compared to 60 thousand in April of 2025. This dataset provides the latest reported value for - United States ADP Employment Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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Graph and download economic data for Total Nonfarm Private Payroll Employment (ADPMNUSNERSA) from Jan 2010 to May 2025 about payrolls, nonfarm, private, employment, and USA.
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Graph and download economic data for Total Nonfarm Private Payroll Employment (DISCONTINUED) (NPPTTL) from Apr 2002 to May 2022 about payrolls, headline figure, nonfarm, private, employment, and USA.
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Graph and download economic data for Nonfarm Private Payroll Employment for Construction (ADPMINDCONNERSA) from Jan 2010 to May 2025 about payrolls, nonfarm, construction, private, employment, and USA.
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License information was derived automatically
Non Farm Payrolls in the United States increased by 139 thousand in May of 2025. This dataset provides the latest reported value for - United States Non Farm Payrolls - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.
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License information was derived automatically
Analysis of ‘Baltimore City Employee Salaries’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/09dd5c6e-6cc5-4322-adf7-8c0a6616dbc7 on 12 February 2022.
--- Dataset description provided by original source is as follows ---
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 2021, the data are combined from the ADP
system and the Workday enterprise resource planning system which now
includes payroll.
Change Log
2021-10-29:
- Added FY2021 data
- Metadata added
- Columns renamed to a standard format
- Youth workers not employed by City removed
- Agency names reformatted with Workday conventions
Data Dictionary
field_name | description | data_type | range_of_possible_values | example_values |
firstName | The first name of the employee. | Text | N/A | |
middleInitial | The middle initial of the employee. | Text | N/A | |
lastName | The last name of the employee. | Text | N/A | |
jobClass | The job classification of the employee. Job classifications are a standardized system of job responsibilities and pay and are frequently not the same as an employee's functional title. Participants in Youthworks who were not employed by the City are not included in this dataset. | Category | There are 1,898 unique job classficiations in this dataset. | "911 OPERATOR" ; "LABORER" ; "CDL DRIVER I" ; "OPERATIONS MANAGER III" |
agencyID | A unique identifier for the agency or department the employee works for. There is a one-to-one relationship between the agencyID and agencyName fields. | Text | There are 73 unique agencyID values corresponding to 73 unique agencyName values. | "A01" ; "A54"; "R01" |
agencyName | The name of the agency or department the employee works for. There is a one-to-one relationship between the agencyID and agencyName fields. The agencyID is typically a letter followed by two numbers though there are a few exceptions. | Text | There are 73 unique agencyID values corresponding to 73 unique agencyName values. | "Police Department" ; "Public Works - Solid Waste (weekly)" ; "Convention Center" |
hireDate | The date the employee was hired. | Date | 6/23/1951 through 6/30/2021 | 4/3/1979 |
annualSalary | The employee's base annual salary for the fiscal year. | Number | 0 through 276375 | |
grossPay | The total sum of compensation the employee received during the fiscal year. To be included in this dataset the employee must have earned more than $0.00 in the fiscal year. | Number | 1.71 through 373111.20 | |
fiscalYear | The fiscal year during which the employee worked for the city. Fiscal years for the City begin July 1 and end June 30 each year. Employees must have earned more than $0.00 during the fiscal year to be included for that year. | Category | FY2011 through FY2021 | "FY2021" |
--- Original source retains full ownership of the source dataset ---
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The global job screening services market, valued at $138.9 million in 2025, is projected to experience steady growth, driven by increasing concerns about workplace safety and regulatory compliance. The market's Compound Annual Growth Rate (CAGR) of 2.1% from 2019-2033 indicates a consistent, albeit moderate, expansion. Key drivers include the rising adoption of cloud-based solutions offering scalability and cost-effectiveness for businesses of all sizes, a growing emphasis on background checks to mitigate risks associated with employee misconduct, and the increasing demand for comprehensive screening processes that incorporate skills assessments and personality tests. The market is segmented by deployment (cloud-based and on-premise) and user type (large enterprises and SMEs), with cloud-based solutions witnessing faster adoption due to their flexibility and accessibility. Geographic expansion, particularly in developing economies with burgeoning workforces, presents significant opportunities for market players. However, factors such as stringent data privacy regulations and the potential for bias in automated screening processes pose challenges to market growth. The competitive landscape comprises both established players like ADP, Paychex, and HireRight, and emerging companies focusing on specialized screening solutions. This competitive environment necessitates continuous innovation and adaptation to evolving technological advancements and regulatory requirements. The forecast period of 2025-2033 will see a continued but measured expansion, largely influenced by economic conditions and technological advancements in applicant tracking and background verification. The on-premise segment, though more established, may face gradual decline as cloud-based solutions offer superior scalability and cost optimization. Large enterprises are expected to remain the primary consumers of comprehensive screening services, while SMEs will show increased adoption due to easier access and affordability of cloud-based solutions. Regional growth will vary; North America and Europe are likely to maintain dominance, while Asia-Pacific and other developing regions are expected to demonstrate significant growth potential based on increasing workforce size and evolving employment practices. Competitive strategies will focus on service diversification, enhanced data analytics capabilities, and proactive compliance with ever-changing regulations.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Analysis of ‘Baltimore City Employee Salaries’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/e35392a8-b2b3-4748-b696-1637b8e774a0 on 12 February 2022.
--- Dataset description provided by original source is as follows ---
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 2021, the data are combined from the ADP
system and the Workday enterprise resource planning system which now
includes payroll.
Change Log
2021-10-29:
- Added FY2021 data
- Metadata added
- Columns renamed to a standard format
- Youth workers not employed by City removed
- Agency names reformatted with Workday conventions
Data Dictionary
field_name | description | data_type | range_of_possible_values | example_values |
firstName | The first name of the employee. | Text | N/A | |
middleInitial | The middle initial of the employee. | Text | N/A | |
lastName | The last name of the employee. | Text | N/A | |
jobClass | The job classification of the employee. Job classifications are a standardized system of job responsibilities and pay and are frequently not the same as an employee's functional title. Participants in Youthworks who were not employed by the City are not included in this dataset. | Category | There are 1,898 unique job classficiations in this dataset. | "911 OPERATOR" ; "LABORER" ; "CDL DRIVER I" ; "OPERATIONS MANAGER III" |
agencyID | A unique identifier for the agency or department the employee works for. There is a one-to-one relationship between the agencyID and agencyName fields. | Text | There are 73 unique agencyID values corresponding to 73 unique agencyName values. | "A01" ; "A54"; "R01" |
agencyName | The name of the agency or department the employee works for. There is a one-to-one relationship between the agencyID and agencyName fields. The agencyID is typically a letter followed by two numbers though there are a few exceptions. | Text | There are 73 unique agencyID values corresponding to 73 unique agencyName values. | "Police Department" ; "Public Works - Solid Waste (weekly)" ; "Convention Center" |
hireDate | The date the employee was hired. | Date | 6/23/1951 through 6/30/2021 | 4/3/1979 |
annualSalary | The employee's base annual salary for the fiscal year. | Number | 0 through 276375 | |
grossPay | The total sum of compensation the employee received during the fiscal year. To be included in this dataset the employee must have earned more than $0.00 in the fiscal year. | Number | 1.71 through 373111.20 | |
fiscalYear | The fiscal year during which the employee worked for the city. Fiscal years for the City begin July 1 and end June 30 each year. Employees must have earned more than $0.00 during the fiscal year to be included for that year. | Category | FY2011 through FY2021 | "FY2021" |
--- Original source retains full ownership of the source dataset ---
https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy
The Labor Management Software market is booming, projected to reach $23.985 billion by 2033 with a 6% CAGR. This comprehensive analysis explores market drivers, trends, restraints, key players (ADP, Honeywell, Infor, IBM, etc.), and regional insights. Discover the future of workforce optimization with our in-depth report. The market, currently valued at an estimated $XX million in 2025 (assuming a logical value based on common market sizes for similar software sectors and the provided CAGR), is projected to maintain a Compound Annual Growth Rate (CAGR) of 6% from 2025 to 2033. This growth is fueled by several key factors. The rising adoption of cloud-based solutions offers scalability and cost-effectiveness, attracting businesses of all sizes. Furthermore, the integration of advanced technologies like AI and machine learning into LMS platforms is enabling more precise workforce planning, predictive analytics for scheduling optimization, and automated time and attendance tracking, leading to significant efficiency gains. The increasing complexity of labor regulations across different geographies also necessitates robust LMS solutions for compliance management. Key players like ADP, Honeywell, Infor, IBM, and others are employing diverse competitive strategies, including mergers and acquisitions, product innovation, and strategic partnerships, to gain market share and meet evolving customer demands. The focus is shifting towards delivering highly personalized user experiences and seamless integrations with existing HR and payroll systems to maximize user adoption and enhance return on investment for businesses.The segmentation of the LMS market reveals significant opportunities within various types of software (e.g., time and attendance, workforce management, scheduling) and applications (e.g., manufacturing, healthcare, retail). While North America currently holds a substantial market share due to early adoption and technological advancements, regions like Asia-Pacific are exhibiting rapid growth potential driven by economic expansion and increasing digitalization. However, challenges remain, including the high initial investment costs for implementing LMS, resistance to change from employees accustomed to traditional methods, and data security concerns. Overcoming these challenges through robust training programs, user-friendly interfaces, and robust data security measures will be crucial for sustained market expansion in the coming years. The overall trajectory suggests a bright future for the LMS market, promising increased efficiency, cost savings, and enhanced employee satisfaction for businesses across various sectors globally. Key drivers for this market are: Increasing adoption of automation and AI in workforce management. . Potential restraints include: Data security and privacy concerns with cloud-based solutions. . Notable trends are: The LMS market is experiencing robust growth driven by several key trends. The increasing adoption of cloud-based solutions is a prominent factor, offering scalability, accessibility, and reduced IT infrastructure costs. Businesses are increasingly recognizing the strategic value of data-driven insights from their workforce, leading to demand for advanced analytics capabilities within LMS platforms. The need to optimize workforce costs, improve employee engagement and retention, and ensure regulatory compliance are further pushing LMS adoption. The integration of mobile technologies, enabling real-time tracking and communication, enhances productivity and simplifies task management. Furthermore, the rising adoption of AI and machine learning is transforming LMS, enabling predictive scheduling, automated time-off requests, and improved workforce forecasting. This shift towards intelligent automation streamlines processes, minimizes errors, and improves overall efficiency. Finally, the rise of the gig economy and the increasing need to manage diverse workforce models are driving demand for flexible and adaptable LMS solutions that can accommodate a variety of employee types and schedules. This includes managing the complexities of contractor payroll, tracking freelance worker hours, and ensuring compliance across diverse employment models..
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The global job screening services market is experiencing robust growth, driven by increasing demand for efficient and reliable candidate vetting processes across diverse industries. The market, estimated at $20 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033, reaching an estimated market value of approximately $35 billion by 2033. This expansion is fueled by several key factors. The rise of remote work and the gig economy necessitates stringent background checks and verification of credentials. Furthermore, heightened regulatory scrutiny regarding compliance and data privacy is prompting organizations to adopt advanced screening solutions. Technological advancements, such as AI-powered tools for candidate screening and automated reference checks, are improving efficiency and accuracy, thereby contributing to market growth. The market is segmented by application (large enterprises and SMEs) and type (cloud-based and on-premise solutions), with cloud-based services gaining significant traction due to their scalability and cost-effectiveness. North America currently holds a dominant market share, followed by Europe and Asia Pacific, although growth in emerging economies is expected to accelerate in the coming years. The competitive landscape is characterized by a mix of established players and emerging technology providers. Key players such as ADP, HireRight, and Sterling are leveraging their extensive experience and robust networks to maintain their market position. However, smaller, more agile companies are innovating with AI and data analytics, creating a dynamic and competitive environment. While the market faces restraints such as the potential for bias in automated screening tools and the complexities of global compliance regulations, the overall outlook remains positive, driven by the ongoing need for effective and secure candidate assessment processes. Future growth will depend on the ability of service providers to adapt to evolving technological advancements, regulatory changes, and the changing needs of employers in a rapidly evolving global talent market.
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Graph and download economic data for Nonfarm Private Manufacturing Payroll Employment (DISCONTINUED) (NPPMNF) from Apr 2002 to May 2022 about payrolls, nonfarm, private, manufacturing, employment, and USA.
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The global Job Screening Services market is experiencing robust growth, projected to reach a market size of $160.7 million in 2025. While the precise Compound Annual Growth Rate (CAGR) isn't provided, considering the increasing demand for efficient and secure hiring practices across various industries, a conservative estimate of a 7-10% CAGR for the forecast period (2025-2033) is reasonable. This growth is driven by several factors. The rising adoption of cloud-based solutions offers scalability, cost-effectiveness, and enhanced data security, attracting both large enterprises and SMEs. Furthermore, increasing regulatory compliance requirements regarding background checks and candidate verification are propelling market expansion. The evolving nature of work, with remote work becoming increasingly prevalent, also necessitates robust screening processes to mitigate risks. Market segmentation reveals a strong preference for cloud-based solutions over on-premise systems, reflecting the broader technological shift in business operations. Large enterprises currently dominate market share due to their greater resources and higher hiring volumes, however, SMEs are showing accelerated adoption as technology becomes more accessible and affordable. Geographic growth is expected to be diverse, with North America and Europe initially holding significant market shares due to established regulatory frameworks and higher adoption rates, but Asia-Pacific is poised for significant growth fueled by rapid economic development and increasing technological penetration. The competitive landscape is characterized by a mix of established players like ADP, Paychex, and HireRight, and emerging companies specializing in niche segments. The market will continue to evolve with technological advancements, particularly in areas like AI-powered candidate screening and predictive analytics. Potential restraints include data privacy concerns, the need for continuous compliance updates, and the potential for bias in automated screening processes. Addressing these challenges effectively will be critical for sustained market growth and maintaining user trust. Companies are increasingly investing in improving the user experience and integrating advanced technologies to enhance accuracy and efficiency while minimizing the potential for bias in candidate screening, thereby shaping the future of the industry.
The aim is to look at how different kinds of work are combined within households and how social and labour market policies in different countries affect this. With debates about flexibility taking place in many European countries, the project considers what effects different policies regarding flexible employment might have for the daily lives of people and families. An important aspect of this is the gendered division of work both inside and outside of the home and the combinations of paid and unpaid work. The project is based upon a sample survey of people in each country who are asked about their own experiences of different kinds of employment along with those of other members of their households. The questionnaire considers paid as well as unpaid work and the strategies through which households approach these different kinds of work. Flexibility is construed as flexibility of time, place and conditions of work. The questionnaire is designed to cover the way in which the activities of different household members combine, including both paid and unpaid work, work in the formal and in the black or grey economy (a very important field in some countries). It is also designed to look at attitudes to flexibility as well as behaviour. For this reason, we have been concerned to look at all forms of work, including domestic work, child care, work in the informal economy, self provisioning and additional casual and occasional jobs in addition to various kinds of regular employment. Each of these issues has very different connotations in the different parts of Europe. The first part of the questionnaire relates to the individual responses and in order to try to understand the combination of different types of economic activity, we have asked in some detail about various sources of income. There are then some more detailed questions about the main economic activity, including the kinds of hours worked, places worked and working conditions. There are some questions designed to elucidate not just under what conditions a person is working, but also the reasons for that particular set of conditions and whether it is chosen or forced upon them. Finally, respondents are asked about how happy they are with these arrangements and if they would want to change them. Similar, although less detailed questions, are asked about the second, third and fourth economic activity of the respondent. The assumption is that the flexible work would more likely found in the second, third or fourth activity and that this might be combined with a more stable first activity. The second part of the questionnaire uses a series of grids to ask about other members of the household. Here the information collected is less detailed, because it is collected from only one person in the household. The composition of the household forms the topic of one grid. The different kinds of work undertaken by different household members are the subject of the second grid. The third grid looks at a variety of different domestic tasks and asks respondents which household member, or who outside of the household carries out these tasks. The next grid considers voluntary and unpaid work for others outside of the household by different family members, with the intention to get some measure of social capital in different countries. It is assumed that whereas formal social capital in the sense of contribution to voluntary organisations may be low in CECs, informal help for others might nevertheless be well developed. The next grid attempts to look at how key household decisions are made and who has the most important decision making role in this respect. Is it the key wage earner? Or is it the most senior person on the household? In this part of the questionnaire we should be able to explore the extent to which different contributions to the household may result in different balances of power within the household. The third section of the questionnaire is devoted to work values. It considers the extent to which people are happy about their various economic activities and the extent to which these might impinge upon or help family life. Finally, we try to look at sources of discord and tension in the area of work and household with particular respect to flexibility. This part of the questionnaire should enable us to better understand the extent to which flexibility may be a help or a hindrance to the organisation of family life and the extent to which it may lead to conflict. The next section of the questionnaire considers the potential for flexibility, by asking under what conditions people would move house, move jobs or retrain. Another table considers job changes since 1989 and this would be particularly relevant in CEC countries. This would give some indication of how flexible the respondent was until now. The final questions in the questionnaire measure the economic resources of the household, including not only income but also other resources such as consumer goods, land and domestic animals owned, access to telecommunications and so on. Document status: 4 - Full Study description and XML DDI Codebook Data description with full questions text. Access to original study description on ADP https://old.adp.fdv.uni-lj.si/opisi/hwf01-en.xml
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Job satisfaction and attitude of DP users to EDP-facilities.
Topics: Replication of the study archived under ZA Study No. 0903: frequency and media of interaction with computers; participation in the introduction of EDP facilities at work; consideration of user interests in implementation; duration of occupation with EDP equipment; questions on company organization and position in hierarchy; scope of action.
Scales: job satisfaction (SAZ short form after Fisher and Lueck); attitude to automated data processing (ADP scale); individual scope of action (HSR scale).
Demography: age (classified); sex; union membership; income (classified); school education; participation in the survey 1974.
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The global labor recruitment outsourcing services market is experiencing robust growth, driven by increasing demand for specialized skills, a growing gig economy, and the need for cost-effective talent acquisition strategies across diverse industries. The market's expansion is fueled by a rising preference among businesses for outsourcing non-core functions, allowing them to focus on their core competencies. Technological advancements, such as AI-powered recruitment platforms and applicant tracking systems (ATS), are further streamlining recruitment processes, increasing efficiency, and reducing time-to-hire. While the market faced some headwinds during the initial phases of the pandemic, it has rebounded strongly, demonstrating its resilience and importance in a dynamic business environment. This growth trajectory is expected to continue, propelled by the ongoing digital transformation within the HR sector and the persistent need for organizations to access a global talent pool. The competitive landscape is characterized by a mix of established global players like Adecco, ManpowerGroup, and Randstad, along with specialized firms catering to niche sectors. These companies are continually innovating to provide comprehensive solutions that encompass everything from candidate sourcing and screening to onboarding and compliance management. Market segmentation reveals a strong demand across various industries, with particularly high growth observed in sectors experiencing rapid technological advancements and skills shortages, such as technology, healthcare, and finance. Strategic mergers and acquisitions are also likely to reshape the market landscape in the coming years, leading to further consolidation among market leaders. Furthermore, the increasing adoption of flexible workforce models, including contract and freelance positions, is significantly impacting the growth of this market.
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Private businesses in the United States hired 37 thousand workers in May of 2025 compared to 60 thousand in April of 2025. This dataset provides the latest reported value for - United States ADP Employment Change - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.