Civil Service Statistics data browser (2021)

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

Status Year Region_ITL1 Parent_department Region_london Region_ITL2 Headcount FTE Mean_salary Median_salary
In post 2021 East Midlands (England) Attorney General’s Departments Outside London Derbyshire and Nottinghamshire 275 255 37450 30370
In post 2021 East Midlands (England) Attorney General’s Departments Outside London Leicestershire, Rutland and Northamptonshire 155 140 39390 38470
In post 2021 East Midlands (England) Attorney General’s Departments Outside London Lincolnshire 10 10 41360 41280
In post 2021 East Midlands (England) Cabinet Office Outside London Derbyshire and Nottinghamshire 25 25 48990 39510
In post 2021 East Midlands (England) Cabinet Office Outside London Lincolnshire [c] [c] [c] [c]
In post 2021 East Midlands (England) Department for Business, Energy and Industrial Strategy Outside London Derbyshire and Nottinghamshire 185 175 31230 30950
In post 2021 East Midlands (England) Department for Business, Energy and Industrial Strategy Outside London Lincolnshire 30 30 38180 37080
In post 2021 East Midlands (England) Department for Education Outside London Derbyshire and Nottinghamshire 290 275 41750 37100
In post 2021 East Midlands (England) Department for Environment, Food and Rural Affairs Outside London Derbyshire and Nottinghamshire 160 155 32770 29190
In post 2021 East Midlands (England) Department for Environment, Food and Rural Affairs Outside London Leicestershire, Rutland and Northamptonshire 25 25 31260 26520
In post 2021 East Midlands (England) Department for Environment, Food and Rural Affairs Outside London Lincolnshire 45 40 34810 31330
In post 2021 East Midlands (England) Department for International Trade Outside London Derbyshire and Nottinghamshire 10 10 [c] [c]
In post 2021 East Midlands (England) Department for Transport Outside London Derbyshire and Nottinghamshire 435 415 35050 31380
In post 2021 East Midlands (England) Department for Transport Outside London Leicestershire, Rutland and Northamptonshire 165 160 31390 27250
In post 2021 East Midlands (England) Department for Transport Outside London Lincolnshire 45 45 29310 26780
In post 2021 East Midlands (England) Department for Work and Pensions Outside London Derbyshire and Nottinghamshire 2690 2395 28460 27570
In post 2021 East Midlands (England) Department for Work and Pensions Outside London Leicestershire, Rutland and Northamptonshire 1645 1460 25540 27570
In post 2021 East Midlands (England) Department for Work and Pensions Outside London Lincolnshire 555 485 26440 27570
In post 2021 East Midlands (England) Department of Health and Social Care Outside London Derbyshire and Nottinghamshire 165 155 43750 36330
In post 2021 East Midlands (England) Department of Health and Social Care Outside London Leicestershire, Rutland and Northamptonshire 20 20 48340 42530
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 2023-02-17, with GIT 71a76ea.

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.
Five 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, Defence Electronics and Components Agency, 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.
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).