Civil Service Statistics data browser (2022)

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

Status Year Sex Region_ITL1 Region_ITL2 Responsibility_level_grouped Headcount FTE Mean_salary Median_salary
In post 2022 Female East Midlands (England) Derbyshire and Nottinghamshire AA/AO 2160 1885 21990 21260
In post 2022 Female East Midlands (England) Derbyshire and Nottinghamshire EO 2200 1960 27020 27130
In post 2022 Female East Midlands (England) Derbyshire and Nottinghamshire G6/G7 685 650 57230 55210
In post 2022 Female East Midlands (England) Derbyshire and Nottinghamshire SCS level 40 40 91310 87400
In post 2022 Female East Midlands (England) Derbyshire and Nottinghamshire SEO/HEO 2110 1975 36110 33840
In post 2022 Female East Midlands (England) Derbyshire and Nottinghamshire Unknown 585 515 28980 28200
In post 2022 Female East Midlands (England) Leicestershire, Rutland and Northamptonshire AA/AO 1635 1400 21830 21260
In post 2022 Female East Midlands (England) Leicestershire, Rutland and Northamptonshire EO 1000 890 27340 27570
In post 2022 Female East Midlands (England) Leicestershire, Rutland and Northamptonshire G6/G7 130 120 56630 54420
In post 2022 Female East Midlands (England) Leicestershire, Rutland and Northamptonshire SCS level 5 5 [c] [c]
In post 2022 Female East Midlands (England) Leicestershire, Rutland and Northamptonshire SEO/HEO 485 455 36510 34290
In post 2022 Female East Midlands (England) Leicestershire, Rutland and Northamptonshire Unknown 450 410 29350 28200
In post 2022 Female East Midlands (England) Lincolnshire AA/AO 695 630 21680 21260
In post 2022 Female East Midlands (England) Lincolnshire EO 400 365 27340 27570
In post 2022 Female East Midlands (England) Lincolnshire G6/G7 50 50 58560 54350
In post 2022 Female East Midlands (England) Lincolnshire SCS level [c] [c] [c] [c]
In post 2022 Female East Midlands (England) Lincolnshire SEO/HEO 265 250 36070 34170
In post 2022 Female East Midlands (England) Lincolnshire Unknown 160 150 29850 28200
In post 2022 Female East of England Bedfordshire and Hertfordshire AA/AO 655 590 23980 23230
In post 2022 Female East of England Bedfordshire and Hertfordshire EO 945 860 28850 29290
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 2023-02-14, 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.
Organisation specific notes on status: In late June 2021 around 7,000 employees from Community Rehabilitation Companies were transferred in from the private sector to HM Prison and Probation Service, counting as entrants. HM Land Registry do not record where their departing employees transfer to and so are unable to identify those that transfer to another Civil Service department.
Year Year of data collection (as at 31 March).
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.
Sex Self reported sex.
“Unknown” accounts for employees who were recorded with an unknown sex.
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).