Civil Service Statistics data browser (2023)

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

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

Status Year Region_london Region_ITL1 Profession_of_post Headcount FTE Mean_salary Median_salary
In post 2023 London London Commercial 1710 1680 58580 56000
In post 2023 London London Communications 1995 1955 49110 44970
In post 2023 London London Corporate Finance 70 70 57190 50240
In post 2023 London London Counter Fraud 1975 1865 37160 32540
In post 2023 London London Digital, Data and Technology 5300 5210 51590 48070
In post 2023 London London Economics 1610 1580 51660 54330
In post 2023 London London Finance 2635 2565 51150 46000
In post 2023 London London Human Resources 2950 2860 48670 43650
In post 2023 London London Inspector of Education and Training 105 105 69160 72470
In post 2023 London London Intelligence Analysis 1240 1190 40770 37850
In post 2023 London London Internal Audit 200 190 53690 52230
In post 2023 London London International Trade 1390 1375 50430 46630
In post 2023 London London Knowledge and Information Management 830 800 41990 38640
In post 2023 London London Legal 4640 4375 58100 57020
In post 2023 London London Medicine 340 300 74340 67380
In post 2023 London London Operational Delivery 34510 32560 35780 32520
In post 2023 London London Operational Research 395 385 50780 46600
In post 2023 London London Other 2350 2270 44730 36180
In post 2023 London London Planning 100 100 50200 44470
In post 2023 London London Planning Inspectors 30 25 61320 60050
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 2023-07-26, 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).
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.
Profession_of_post Professions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
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).