Civil Service Statistics data browser (2023)

Data preview: All civil servants / Region_ITL1 / Responsibility_level_grouped / Region_ITL2 / Parent_department

Status Year Region_ITL1 Responsibility_level_grouped Region_ITL2 Parent_department Headcount FTE Mean_salary Median_salary
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Attorney General’s Departments 80 75 22360 22870
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Department for Business, Energy and Industrial Strategy 25 25 21400 21230
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Department for Environment, Food and Rural Affairs 50 45 22150 22150
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Department for Transport 55 55 24310 22500
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Department for Work and Pensions 650 555 21680 21690
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Department of Health and Social Care 5 5 [c] [c]
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire HM Land Registry 110 105 23240 23390
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire HM Revenue and Customs 1095 1000 22620 22520
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Home Office [c] [c] [c] [c]
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Ministry of Defence 200 190 24790 22220
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Ministry of Justice 1875 1740 26520 25340
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire National Crime Agency [c] [c] [c] [c]
In post 2023 East Midlands (England) AA/AO Derbyshire and Nottinghamshire Office for Standards in Education, Children’s Services and Skills 25 25 22450 22490
In post 2023 East Midlands (England) AA/AO Leicestershire, Rutland and Northamptonshire Attorney General’s Departments 50 50 22110 22870
In post 2023 East Midlands (England) AA/AO Leicestershire, Rutland and Northamptonshire Department for Transport 35 30 25180 27490
In post 2023 East Midlands (England) AA/AO Leicestershire, Rutland and Northamptonshire Department for Work and Pensions 600 505 21670 21690
In post 2023 East Midlands (England) AA/AO Leicestershire, Rutland and Northamptonshire HM Land Registry 80 75 23390 23390
In post 2023 East Midlands (England) AA/AO Leicestershire, Rutland and Northamptonshire HM Revenue and Customs [c] [c] [c] [c]
In post 2023 East Midlands (England) AA/AO Leicestershire, Rutland and Northamptonshire Home Office 35 35 22400 22400
In post 2023 East Midlands (England) AA/AO Leicestershire, Rutland and Northamptonshire Ministry of Defence 130 125 22860 21580
Note: Data has been truncated to 20 rows, please download the data to view the remaining rows

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About: The Civil Service Statistics data browser is a pilot project by Cabinet Office to provide access to more detailed data on the Civil Service workforce from the Annual Civil Service Employment Survey. We welcome feedback or comments on this project, which can be addressed to civilservicestatistics@cabinetoffice.gov.uk

Notes: Summary figures are suppressed when information relates to less than 5 civil servants for FTE or Headcount, and less than 10 civil servants for median and mean salary (shown as [c]). Zero responses and salaries for less than 30 civil servants have been suppressed for GPDR special category data. FTE figures are not shown for entrants or leavers due to data quality concerns for these groups. Figures are rounded to the nearest 5, or £10 as appropriate.

Data source: All figures are aggregated from the Cabinet Office Annual Civil Service Employment Survey collection.

Version: Generated on 2023-07-26, with GIT d545f65.

Data column Description
Status Employment status of the civil servants.
In post - includes staff that were in post on the reference date (31 March).
New entrant CS - includes new entrants to the Civil Service over the year (1 April to 31 March).
Leaver CS - includes leavers from the Civil Service over the year (1 April to 31 March). This includes employees who have an Unknown leaving cause.
Leaver Dept. - includes leavers from the department over the year (1 April to 31 March), who did not leave the Civil Service.
Four organisations do not report when their employees first entered the Civil Service and so entrants data for these organisations is not available . These are as follows: Foreign Commonwealth and Development Office (excl. agencies), Foreign Commonwealth and Development Office Services, Scottish Forestry and Forest and Land Scotland. A further three organisations also could not provide entrants data in 2021. These are as follows: Department for International Development, Foreign and Commonwealth Office (excl. agencies) and Royal Fleet Auxiliary.
Year Year of data collection (as at 31 March).
Parent_department Government Department, total figures for both Ministerial and Non-Ministerial Departments include all of their Executive Agencies.
Responsibility_level_grouped With the exception of the centrally managed Senior Civil Service, government departments have delegated pay and grading. For statistical purposes departments are asked to map their grades to a common framework by responsibility level.
This table shows staff in their substantive responsibility level unless on temporary promotion in which case staff are recorded at the higher responsibility level.
Responsibility_level_grouped combines the mapped grades into five broad responsibility levels. This is the headline measure for responsibility level for the Civil Service and is consistent with the published National Statistics.
Region_ITL1 Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard.
Following the UK’s withdrawal from the EU, a new UK-managed international statistical geography - International Territorial Levels (ITL) - was introduced from 1st January 2021, replacing the former NUTS classification. They align with international standards, enabling comparability both over time and internationally. To ensure continued alignment, the ITLs mirror the NUTS system. They also follow a similar review timetable - every three years.
ITL 1 divides into Wales, Scotland, Northern Ireland, and the 9 statistical regions of England.
Region_ITL2 Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard.
Following the UK’s withdrawal from the EU, a new UK-managed international statistical geography - International Territorial Levels (ITL) - was introduced from 1st January 2021, replacing the former NUTS classification. They align with international standards, enabling comparability both over time and internationally. To ensure continued alignment, the ITLs mirror the NUTS system. They also follow a similar review timetable - every three years.
ITL 2 divides into Northern Ireland, counties in England (most grouped), groups of districts in Greater London, groups of unitary authorities in Wales, groups of council areas in Scotland.
Headcount Total number of civil servants (rounded to nearest 5).
FTE Total full-time equivalent (FTE) employment numbers (rounded to nearest 5).
FTE figures are not shown for entrants or leavers due to data quality concerns for these groups.
Mean_salary Average salary (mean, rounded to nearest £10). For part-time employees, salaries represent the full-time equivalent earnings, while for full-time employees they are the actual annual gross salaries.
These figures should be interpreted with caution when the total number of employees in a group is small, as they will tend to show more variability than larger groups (i.e. may be much higher or lower than can be explained by the data shown).
Median_salary Median salary (rounded to nearest £10). For part-time employees, salaries represent the full-time equivalent earnings, while for full-time employees they are the actual annual gross salaries.
These figures should be interpreted with caution when the total number of employees in a group is small, as they will tend to show more variability than larger groups (i.e. may be much higher or lower than can be explained by the data shown).