Civil Service Statistics data browser (2022)

Data preview: All civil servants / Sex / Profession_of_post / Region_london

Explore further: Parent_department, Organisation, Responsibility_level_grouped, Responsibility_level_ungrouped, Region_ITL1, Region_ITL2, Region_ITL3, Function_of_post, Ethnicity, Disability, Sexual_orientation, Age

Status Year Sex Profession_of_post Region_london Headcount FTE Mean_salary Median_salary
In post 2022 Female Commercial London 580 565 44670 41500
In post 2022 Female Commercial Outside London 2805 2645 37240 35070
In post 2022 Female Commercial Overseas 10 10 [c] [c]
In post 2022 Female Commercial Unknown [c] [c] [c] [c]
In post 2022 Female Communications London 1330 1280 46190 42710
In post 2022 Female Communications Outside London 1150 1075 37770 36240
In post 2022 Female Communications Overseas 5 5 [c] [c]
In post 2022 Female Communications Unknown 5 5 [c] [c]
In post 2022 Female Corporate Finance London 20 20 [c] [c]
In post 2022 Female Corporate Finance Outside London 60 55 41110 38260
In post 2022 Female Counter Fraud London 705 620 31860 31060
In post 2022 Female Counter Fraud Outside London 3195 2785 27580 27570
In post 2022 Female Counter Fraud Unknown 5 5 [c] [c]
In post 2022 Female Digital, Data and Technology London 1535 1495 47970 43880
In post 2022 Female Digital, Data and Technology Outside London 5450 5170 38960 36000
In post 2022 Female Digital, Data and Technology Overseas [c] [c] [c] [c]
In post 2022 Female Digital, Data and Technology Unknown 10 10 [c] [c]
In post 2022 Female Economics London 605 580 48550 51500
In post 2022 Female Economics Outside London 155 150 39640 36720
In post 2022 Female Economics Overseas 10 10 [c] [c]
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).
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”.
Profession_of_post Professions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
Cabinet Office (excl agencies) reported profession information for only 60 out of a total 9,930 employees.
Of the 20 bodies under the Scottish Government, 16 did not report any professions information for their employees.
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).