Civil Service Statistics data browser (2023)

Data preview: All civil servants / Region_ITL1 / Region_ITL2 / Region_london / Responsibility_level_ungrouped

Status Year Region_ITL1 Region_ITL2 Region_london Responsibility_level_ungrouped Headcount FTE Mean_salary Median_salary
In post 2023 East Midlands (England) Derbyshire and Nottinghamshire Outside London AA 400 365 22210 23230
In post 2023 East Midlands (England) Derbyshire and Nottinghamshire Outside London AO 3780 3445 24570 22520
In post 2023 East Midlands (England) Derbyshire and Nottinghamshire Outside London EO 3665 3390 28260 28120
In post 2023 East Midlands (England) Derbyshire and Nottinghamshire Outside London G6 340 325 70900 69940
In post 2023 East Midlands (England) Derbyshire and Nottinghamshire Outside London G7 1110 1065 56520 56870
In post 2023 East Midlands (England) Derbyshire and Nottinghamshire Outside London HEO 2535 2420 34480 34700
In post 2023 East Midlands (England) Derbyshire and Nottinghamshire Outside London SCS level 80 75 91400 87330
In post 2023 East Midlands (England) Derbyshire and Nottinghamshire Outside London SEO 1550 1485 42850 42140
In post 2023 East Midlands (England) Derbyshire and Nottinghamshire Outside London Unknown 900 825 29740 29050
In post 2023 East Midlands (England) Leicestershire, Rutland and Northamptonshire Outside London AA 320 295 21630 21250
In post 2023 East Midlands (England) Leicestershire, Rutland and Northamptonshire Outside London AO 2285 2035 24480 21780
In post 2023 East Midlands (England) Leicestershire, Rutland and Northamptonshire Outside London EO 1715 1580 28490 28120
In post 2023 East Midlands (England) Leicestershire, Rutland and Northamptonshire Outside London G6 55 55 73720 72070
In post 2023 East Midlands (England) Leicestershire, Rutland and Northamptonshire Outside London G7 210 200 55400 53410
In post 2023 East Midlands (England) Leicestershire, Rutland and Northamptonshire Outside London HEO 610 580 35010 34170
In post 2023 East Midlands (England) Leicestershire, Rutland and Northamptonshire Outside London SCS level 15 15 83480 78490
In post 2023 East Midlands (England) Leicestershire, Rutland and Northamptonshire Outside London SEO 340 325 44160 41670
In post 2023 East Midlands (England) Leicestershire, Rutland and Northamptonshire Outside London Unknown 650 610 30130 29050
In post 2023 East Midlands (England) Lincolnshire Outside London AA 300 285 21840 21380
In post 2023 East Midlands (England) Lincolnshire Outside London AO 990 920 25540 22330
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 2023-07-28, 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).
Responsibility_level_ungrouped 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_ungrouped shows the mapped grades at a higher level of detail, however not all Government Departments / bodies have distinct grades that map exactly to these levels so figures should be considered as approximations and treated with caution.
Region_london Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard.
Region_london groups the ITL classifications into "London", "Outside London": all UK regions excluding London, "Overseas", and "Unknown".
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).