Civil Service Statistics data browser (Beta)

Back to Civil Service Statistics

Data preview: All civil servants / Function_of_post / Sex / Ethnicity

Status Year Function_of_post Sex Ethnicity Headcount FTE Mean_salary Median_salary
In post 2021 Analysis Female Asian 210 200 43230 38630
In post 2021 Analysis Female Black 100 100 38410 36120
In post 2021 Analysis Female Chinese 30 30 [c] [c]
In post 2021 Analysis Female Mixed 90 80 42220 37020
In post 2021 Analysis Female Other ethnicity [c] [c] [c] [c]
In post 2021 Analysis Female Undeclared 60 60 44850 42220
In post 2021 Analysis Female Unknown 380 360 40660 36980
In post 2021 Analysis Female White 2370 2200 42260 37320
In post 2021 Analysis Male Asian 220 220 42530 39730
In post 2021 Analysis Male Black 80 80 41080 39870
In post 2021 Analysis Male Chinese 30 30 [c] [c]
In post 2021 Analysis Male Mixed 110 100 42560 38160
In post 2021 Analysis Male Other ethnicity [c] [c] [c] [c]
In post 2021 Analysis Male Undeclared 180 180 44990 41790
In post 2021 Analysis Male Unknown 570 560 41030 36570
In post 2021 Analysis Male White 2710 2660 45000 39850
In post 2021 Analysis Unknown Black [c] [c] [c] [c]
In post 2021 Analysis Unknown Mixed [c] [c] [c] [c]
In post 2021 Analysis Unknown Unknown [c] [c] [c] [c]
In post 2021 Analysis Unknown White [c] [c] [c] [c]
In post 2021 Commercial Female Asian 140 130 39670 34550
In post 2021 Commercial Female Black 120 120 38600 36060
In post 2021 Commercial Female Chinese [c] [c] [c] [c]
In post 2021 Commercial Female Mixed 60 60 38630 34670
In post 2021 Commercial Female Other ethnicity [c] [c] [c] [c]
In post 2021 Commercial Female Undeclared 120 110 36780 34090
In post 2021 Commercial Female Unknown 770 750 56350 53320
In post 2021 Commercial Female White 2290 2170 39550 35570
In post 2021 Commercial Male Asian 140 130 42930 37920
In post 2021 Commercial Male Black 60 60 43940 40580
In post 2021 Commercial Male Chinese [c] [c] [c] [c]
In post 2021 Commercial Male Mixed 40 40 [c] [c]
In post 2021 Commercial Male Other ethnicity [c] [c] [c] [c]
In post 2021 Commercial Male Undeclared 160 160 43310 40580
In post 2021 Commercial Male Unknown 840 830 61620 56340
In post 2021 Commercial Male White 2200 2170 45430 40580
In post 2021 Communications Female Asian 210 210 35740 31810
In post 2021 Communications Female Black 140 130 33700 31810
In post 2021 Communications Female Chinese [c] [c] [c] [c]
In post 2021 Communications Female Mixed 100 100 37080 33730
In post 2021 Communications Female Other ethnicity [c] [c] [c] [c]
In post 2021 Communications Female Undeclared 90 80 35730 31810
In post 2021 Communications Female Unknown 1070 1030 33840 28500
In post 2021 Communications Female White 2650 2470 36250 31810
In post 2021 Communications Male Asian 290 290 30500 26210
In post 2021 Communications Male Black 70 70 31410 25560
In post 2021 Communications Male Chinese [c] [c] [c] [c]
In post 2021 Communications Male Mixed 60 60 35410 31810
In post 2021 Communications Male Other ethnicity [c] [c] [c] [c]
In post 2021 Communications Male Undeclared 130 130 33590 31810
In post 2021 Communications Male Unknown 1100 1090 32290 25560
In post 2021 Communications Male White 2240 2200 35200 31810
In post 2021 Counter Fraud Female Asian 290 270 31500 29570
In post 2021 Counter Fraud Female Black 160 160 31400 29570
In post 2021 Counter Fraud Female Chinese [c] [c] [c] [c]
In post 2021 Counter Fraud Female Mixed 60 50 30820 27830
In post 2021 Counter Fraud Female Other ethnicity [c] [c] [c] [c]
In post 2021 Counter Fraud Female Undeclared 200 180 33730 31810
In post 2021 Counter Fraud Female Unknown 730 680 30840 29570
In post 2021 Counter Fraud Female White 3050 2760 32830 31810
In post 2021 Counter Fraud Male Asian 320 320 33160 31810
In post 2021 Counter Fraud Male Black 90 90 31710 29570
In post 2021 Counter Fraud Male Chinese [c] [c] [c] [c]
In post 2021 Counter Fraud Male Mixed 80 70 36840 34250
In post 2021 Counter Fraud Male Other ethnicity [c] [c] [c] [c]
In post 2021 Counter Fraud Male Undeclared 380 360 37520 32520
In post 2021 Counter Fraud Male Unknown 960 930 33130 31810
In post 2021 Counter Fraud Male White 3250 3130 35660 31810
In post 2021 Debt Female Asian 220 180 23710 24360
In post 2021 Debt Female Black 100 90 25420 24120
In post 2021 Debt Female Chinese [c] [c] [c] [c]
In post 2021 Debt Female Mixed [c] [c] [c] [c]
In post 2021 Debt Female Other ethnicity [c] [c] [c] [c]
In post 2021 Debt Female Undeclared 80 60 24390 24120
In post 2021 Debt Female Unknown 810 730 21600 20140
In post 2021 Debt Female White 1400 1180 24040 21440
In post 2021 Debt Male Asian 140 120 24100 21400
In post 2021 Debt Male Black 60 50 25310 25600
In post 2021 Debt Male Chinese [c] [c] [c] [c]
In post 2021 Debt Male Mixed [c] [c] [c] [c]
In post 2021 Debt Male Other ethnicity [c] [c] [c] [c]
In post 2021 Debt Male Undeclared 70 70 25100 21440
In post 2021 Debt Male Unknown 740 720 21370 20140
In post 2021 Debt Male White 1000 960 24300 21440
In post 2021 Digital, Data & Technology Female Asian 320 310 41290 36390
In post 2021 Digital, Data & Technology Female Black 160 150 38250 35960
In post 2021 Digital, Data & Technology Female Chinese [c] [c] [c] [c]
In post 2021 Digital, Data & Technology Female Mixed 100 100 42300 40480
In post 2021 Digital, Data & Technology Female Other ethnicity 30 30 [c] [c]
In post 2021 Digital, Data & Technology Female Undeclared 150 150 41060 38540
In post 2021 Digital, Data & Technology Female Unknown 790 760 40470 36780
In post 2021 Digital, Data & Technology Female White 3420 3220 40170 37540
In post 2021 Digital, Data & Technology Male Asian 480 480 41190 37640
In post 2021 Digital, Data & Technology Male Black 220 220 39930 36030
In post 2021 Digital, Data & Technology Male Chinese 30 30 [c] [c]
In post 2021 Digital, Data & Technology Male Mixed 130 130 44470 40040
In post 2021 Digital, Data & Technology Male Other ethnicity 60 60 45840 40230
In post 2021 Digital, Data & Technology Male Undeclared 500 490 42090 39670
In post 2021 Digital, Data & Technology Male Unknown 1700 1680 40390 37060
In post 2021 Digital, Data & Technology Male White 5480 5380 42950 39100
Note: Data has been truncated to 100 rows, please download the data to view the remaining rows

Download the data

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 30 civil servants for FTE or Headcount, and less than 50 civil servants for median and mean salary (shown as [c]). Additionally, zero responses have been suppressed for GPDR protected characteristics. Figures are rounded to the nearest 10, or £10 as appropriate.

Data source: All figures are aggregated from the Cabinet Office Annual Civil Service Employment Survey collection.

Version: Generated on 2022-07-26, with GIT 03ee02c.

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.
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. The Defence Electronics and Components Agency does not record the date in which their employees first enter the Civil Service and so entrants data is not available. 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 March 31st).
Function_of_post Functions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
Home Office, Welsh Government and Royal Fleet Auxiliary did not report any functions information for their employees.
Of the 20 bodies under the Scottish Government, 16 did not report any functions information for their employees.
Sex Self reported sex.
“Unknown” accounts for employees who were recorded with an unknown sex.
Ethnicity Self reported ethnicity. For consistency with Civil Service Statistics, ‘Chinese’ is shown separately in the 2021 figures, but counted within ‘Asian’ for 2022.
“Undeclared” accounts for employees who have actively declared that they do not want to disclose their ethnicity and “Unknown” accounts for employees who have not made an active declaration about their ethnicity.
Headcount Total number of civil servants (rounded to nearest 10).
FTE Total full-time equivalent employment numbers (rounded to nearest 10).
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.
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.