Civil Service Statistics data browser (2021)

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

Status Year Region_ITL1 Region_ITL2 Profession_of_post Region_london Headcount FTE Mean_salary Median_salary
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Commercial Outside London 75 70 43680 42490
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Communications Outside London 85 80 36960 36590
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Counter Fraud Outside London 20 15 35050 36060
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Digital, Data and Technology Outside London 180 175 38690 35860
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Finance Outside London 155 145 37290 33330
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Human Resources Outside London 315 295 39150 33840
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Inspector of Education and Training Outside London 70 65 64380 64500
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Intelligence Analysis Outside London 30 30 32510 28170
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Internal Audit Outside London 25 20 41610 41820
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire International Trade Outside London 15 15 35480 31810
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Knowledge and Information Management Outside London 60 55 37120 36340
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Legal Outside London 365 340 40410 35000
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Medicine Outside London 20 20 81340 90060
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Operational Delivery Outside London 5525 5110 27720 25560
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Operational Research Outside London 5 5 [c] [c]
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Other Outside London 195 190 31940 22080
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Planning Outside London [c] [c] [c] [c]
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Policy Outside London 235 220 41180 36960
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Project Delivery Outside London 195 185 43070 39130
In post 2021 East Midlands (England) Derbyshire and Nottinghamshire Property Outside London 305 290 38660 36970
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 2023-02-16, 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).
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.
Profession_of_post Professions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
The Department for Work and Pensions provided aggregated professions data for 2021, which are available in the Civil Service Statistics publication. However, figures in this browser are derived from individual level data and so are not available for this department in 2021.
Of the 20 bodies under the Scottish Government, 16 did not report any professions information for their employees.
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).