Private businesses in the United States hired 54 thousand workers in August of 2025 compared to 106 thousand in July 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.

Graph and download economic data for Total Nonfarm Private Payroll Employment (ADPMNUSNERSA) from Jan 2010 to Aug 2025 about payrolls, nonfarm, private, employment, and USA.

View monthly updates and historical trends for ADP Employment Change. from United States. Source: ADP. Track economic data with YCharts analytics.

This dataset provides values for ADP EMPLOYMENT CHANGE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides values for ADP EMPLOYMENT CHANGE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides values for ADP EMPLOYMENT CHANGE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

ADP Market Outlook

The global Automated Data Processing (ADP) market size is projected to grow from USD 5.5 billion in 2023 to an estimated USD 9.7 billion by 2032, reflecting a Compound Annual Growth Rate (CAGR) of approximately 6.5%. This growth is being driven by increasing demands for automated data processing solutions across various sectors, spurred by enterprises seeking enhanced operational efficiency and data accuracy. The market is also witnessing substantial support from advancements in artificial intelligence and machine learning technologies, which are integral to the evolution and adoption of ADP solutions.

The primary growth factor for the ADP market is the escalating volume of data generated by enterprises across the globe. Digital transformation initiatives have resulted in the exponential growth of data, necessitating sophisticated data processing capabilities. Automated data processing solutions offer unparalleled speed, accuracy, and efficiency in handling large datasets, making them indispensable to modern businesses. Moreover, the integration of AI and machine learning technologies within ADP systems enables predictive analytics and real-time decision-making, providing a significant competitive edge to organizations leveraging such systems.

Additionally, the increasing complexity of business operations and the need for compliance with regulatory standards are driving the demand for advanced data processing solutions. Industries such as BFSI, healthcare, and manufacturing are particularly sensitive to data accuracy and compliance. ADP solutions help these industries streamline their data management processes, ensuring that all data is accurate, up-to-date, and compliant with industry regulations. The ability to automate repetitive and mundane tasks also allows human resources to focus on more strategic activities, further enhancing organizational productivity and efficiency.

The rise in cloud computing adoption is another pivotal factor contributing to the growth of the ADP market. Cloud-based ADP solutions offer scalability, flexibility, and cost-efficiency, making them attractive to enterprises of all sizes. Small and medium enterprises (SMEs), in particular, are increasingly adopting cloud-based ADP solutions to leverage advanced data processing capabilities without the need for significant capital investment in infrastructure. This trend is expected to continue as cloud technologies evolve and become more accessible.

When considering regional outlook, North America is expected to remain the dominant market for ADP solutions, owing to the region’s advanced technological infrastructure and early adoption of innovative technologies. Asia Pacific is anticipated to register the highest growth rate during the forecast period, driven by rapid industrialization, digital transformation initiatives, and increased IT spending in emerging economies such as China and India. Europe also presents significant growth opportunities, particularly in sectors such as BFSI and healthcare, where data processing and compliance are critical.

Component Analysis

In the ADP market, the component segment is primarily divided into software and services. Software solutions dominate this segment due to their ability to automate complex data processing tasks, thereby reducing human error and enhancing accuracy. ADP software encompasses various applications, including data mining, reporting, and predictive analytics tools. These applications are being continuously upgraded with AI and machine learning capabilities, making them more efficient and intelligent in handling large volumes of data. The software segment's growth is further fueled by the increasing demand for real-time data processing and the need for advanced analytics across various industries.

Services, on the other hand, play a crucial role in the implementation and maintenance of ADP solutions. This sub-segment includes consulting, integration, and support services that ensure the successful deployment and ongoing performance of ADP systems. As businesses continue to adopt more sophisticated data processing solutions, the demand for professional services to assist with customization, integration with existing systems, and training for end-users is also on the rise. These services are essential for maximizing the return on investment for ADP solutions and ensuring that they deliver the desired outcomes.

A notable trend within the services segment is the increasing focus on managed services. Many enterprises are opting for managed ADP services to outsource the man

This dataset provides values for ADP EMPLOYMENT CHANGE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides values for ADP EMPLOYMENT CHANGE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Non Farm Payrolls in the United States increased by 22 thousand in August 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.

Scheme wise Progress Report of Approved District ADP 2017-18 @ 50% Release (District Hangu)

This dataset provides values for ADP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This project is part of a larger plan to transfer commonly requested TJJD data onto the Texas Open Data Portal. This will allow for greater efficiency in sharing publicly available information and answering Public Information Requests (PIRs). Average Daily Population (ADP) data provides the daily population of specific TJJD locations of the following types: Institutions, Halfway Houses, Contract Services, Orientation and Assessment, Parole, Other Parole (Out of State Parole) and Interstate Compact. There are two levels of measurement of ADP on this data set. The first, titled MTD ADP (Month to Date), provides a month to month population count; it does NOT take into account the previous month's population count. Each month's population count is specific to that month. The second, titled YTD ADP (Year to Date), provides a rolling average of ADP; it includes the previous month's population and averages it out with that month's population count.
Lastly, both Calendar Years (CY) and Fiscal Years (FY) are provided on this data set. TJJD’s fiscal year starts in September and ends in August of the following year.

Thailand ADP: Calendar Year data was reported at 63,795.866 NA in May 2018. This records an increase from the previous number of 47,506.920 NA for Apr 2018. Thailand ADP: Calendar Year data is updated monthly, averaging 14,098.024 NA from Oct 2017 (Median) to May 2018, with 8 observations. The data reached an all-time high of 63,795.866 NA in May 2018 and a record low of 0.000 NA in Dec 2017. Thailand ADP: Calendar Year data remains active status in CEIC and is reported by State Enterprise Policy Office. The data is categorized under Global Database’s Thailand – Table TH.F031: Investment and Disbursement Budget Plan.

The principal pacemaker of the circadian clock of the cyanobacterium S. elongatus is a protein phosphorylation cycle consisting of three proteins, KaiA, KaiB and KaiC. KaiC forms a homohexamer, with each monomer consisting of two domains, CI and CII. Both domains can bind and hydrolyze ATP, but only the CII domain can be phosphorylated, at two residues, in a well-defined sequence. While this system has been studied extensively, how the clock is driven thermodynamically has remained elusive. Inspired by recent experimental observations and building on ideas from previous mathematical models, we present a new, thermodynamically consistent, statistical-mechanical model of the clock. At its heart are two main ideas: i) ATP hydrolysis in the CI domain provides the thermodynamic driving force for the clock, switching KaiC between an active conformational state in which its phosphorylation level tends to rise and an inactive one in which it tends to fall; ii) phosphorylation of the CII domain provides the timer for the hydrolysis in the CI domain. The model also naturally explains how KaiA, by acting as a nucleotide exchange factor, can stimulate phosphorylation of KaiC, and how the differential affinity of KaiA for the different KaiC phosphoforms generates the characteristic temporal order of KaiC phosphorylation. As the phosphorylation level in the CII domain rises, the release of ADP from CI slows down, making the inactive conformational state of KaiC more stable. In the inactive state, KaiC binds KaiB, which not only stabilizes this state further, but also leads to the sequestration of KaiA, and hence to KaiC dephosphorylation. Using a dedicated kinetic Monte Carlo algorithm, which makes it possible to efficiently simulate this system consisting of more than a billion reactions, we show that the model can describe a wealth of experimental data.

Thailand ADP: National Science Museum data was reported at 1,202.915 NA in May 2018. This records an increase from the previous number of 1,053.448 NA for Apr 2018. Thailand ADP: National Science Museum data is updated monthly, averaging 160.056 NA from Oct 2017 (Median) to May 2018, with 8 observations. The data reached an all-time high of 1,202.915 NA in May 2018 and a record low of 30.870 NA in Oct 2017. Thailand ADP: National Science Museum data remains active status in CEIC and is reported by State Enterprise Policy Office. The data is categorized under Global Database’s Thailand – Table TH.F031: Investment and Disbursement Budget Plan.

Exports of ADP Equipment and Office Machines in the United States increased to 1933 USD Million in February from 1761 USD Million in January of 2024. This dataset includes a chart with historical data for the United States Exports of Adp Equipment And Office Machines.

Thailand ADP: Total data was reported at 133,946.737 NA in May 2018. This records an increase from the previous number of 104,065.211 NA for Apr 2018. Thailand ADP: Total data is updated monthly, averaging 54,463.497 NA from Oct 2017 (Median) to May 2018, with 8 observations. The data reached an all-time high of 133,946.737 NA in May 2018 and a record low of 7,899.427 NA in Oct 2017. Thailand ADP: Total data remains active status in CEIC and is reported by State Enterprise Policy Office. The data is categorized under Global Database’s Thailand – Table TH.F031: Investment and Disbursement Budget Plan.

ADP: State Railway of Thailand data was reported at 26,339.900 NA in May 2018. This records an increase from the previous number of 20,314.231 NA for Apr 2018. ADP: State Railway of Thailand data is updated monthly, averaging 18,804.546 NA from Oct 2017 (Median) to May 2018, with 8 observations. The data reached an all-time high of 26,339.900 NA in May 2018 and a record low of 2,405.350 NA in Oct 2017. ADP: State Railway of Thailand data remains active status in CEIC and is reported by State Enterprise Policy Office. The data is categorized under Global Database’s Thailand – Table TH.F031: Investment and Disbursement Budget Plan.

ADP: Thailand Post Company Limited data was reported at 944.042 NA in May 2018. This records an increase from the previous number of 732.335 NA for Apr 2018. ADP: Thailand Post Company Limited data is updated monthly, averaging 293.621 NA from Oct 2017 (Median) to May 2018, with 8 observations. The data reached an all-time high of 944.042 NA in May 2018 and a record low of 0.000 NA in Dec 2017. ADP: Thailand Post Company Limited data remains active status in CEIC and is reported by State Enterprise Policy Office. The data is categorized under Global Database’s Thailand – Table TH.F031: Investment and Disbursement Budget Plan.