Occupations in demand
Calendar year 2024

Description

This page describes the underlying data files for the ‘Occupations in demand’ official statistics in development release. This data is released under the terms of the Open Government License (opens in a new tab) (http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/).

The publication methodology (https://www.gov.uk/government/publications/occupations-in-demand-in-2024) explains the definitions used and how estimates have been produced. It also provides information on the data sources, their coverage and quality.

Coverage

The data used in this release mostly relate to the UK labour market and are aggregated together to create a UK demand index. The exception to this are indicators using data from the annual survey of hours and earnings, which does not contain data from Northern Ireland and is therefore Great Britain only.

The earliest data used in this release contains data to April 2022, the latest contains data to March 2024.

Information on how occupations or industries have been grouped together can be found in the additional supporting files of this release.

Full details of the coverage for each source are provided in the publication methodology (https://www.gov.uk/government/publications/occupations-in-demand-in-2024).

File formats and conventions

The underlying data files are provided in comma separated value (csv) format.

Rounding and decimal places vary across the different files, based on conventions for the relevant sources and what is appropriate for the analysis that has been undertaken.

Symbols used in the underlying data are as follows:

- ‘z’ when an observation is not applicable
- ‘x’ when data is unavailable for other reasons
- ‘c’ confidential data removed due to suppression

Data files

Scaled and weighted occupation demand

Filename: scaled_weighted_oid_output.csv
Geographic levels: National
Time period: 2024
Content summary: This file contains demand indicators used in determining occupations in demand after weighting and scaling together with the overall demand index.

Variable names and descriptions for this file are provided below:

Variable name                           |  Variable description
--------------------------------------  |  ----------------------------------------------------------------------------------------------
annual_change_in_contract_temp_workers  |  Annual change in contract or temporary workers
annual_change_in_hourly_wage            |  Annual change in hourly wage
annual_change_in_hours_worked           |  Annual change in hours worked
cluster                                 |  Occupation group - Filter by occupation cluster groups
construction                            |  Occupation is in construction - Filter by construction occupations
count                                   |  Number of occupations
demand_index                            |  Demand index
demand_level                            |  Demand type - Filter by type of demand
demand_level_percent                    |  Proportion of workers in demand
employees                               |  Number of workers
hourly_wage                             |  Average hourly wage
imputed_indicators                      |  Number of indicators imputed from 3-digit SOC
missing_indicators                      |  Number of indicators with missing data
online_job_ad_density                   |  Online job advert density
percent                                 |  Proportion of workers
shortage_occupation_list                |  Occupation is in the shortage occupation list - Filter by shortage occupation list occupations
skill_level                             |  ONS skill level - Filter by skill level
skills_shortage_vacancy_density         |  Skills shortage vacancy density
SOC_description                         |  SOC20 Description - Filter by occupation description
SOC20                                   |  SOC20 - Filter by occupation
STEM                                    |  Occupation is in STEM - Filter by STEM occupations
visa_application_density                |  Visa application density
wage_premium                            |  Wage premium

Footnotes:

1. Some occupations from ONS’ job advert statistics were excluded from this analysis since the relative occupational distribution compared with annual population survey occupational data were judged in some cases to be relatively atypical. ONS plan to continue improving their statistics, including with an enhanced SOC allocation process, which may trigger revisions of the occupations excluded in future.
2. Only occupations which did not have any missing demand indicator data and were not otherwise excluded from the analysis were included in the clustering analysis, 268 out of 412 occupations.
3. Only four occupations were grouped into group 1. These occupations were grouped together because visa application density was their main demand indicator and this indicator was much higher than seen in all other occupations, indicating these occupations may react strongly to changes to visa rules.
4. Employment volumes sourced from: Annual population survey Apr 2023 - Mar 2024 (https://www.nomisweb.co.uk/datasets/aps218/reports/employment-by-status-and-occupation?compare=K02000001)
5. Median wages sourced from: Earnings and hours worked, occupation by four-digit SOC: ASHE Table 14 - Office for National Statistics (ons.gov.uk) (https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/occupation4digitsoc2010ashetable14)
6. The demand index covers a range of scores between -1.22 and 1.49.
7. Elected officers and representatives and senior officers in fire, ambulance, prison and related services are in critical demand due to a high wage premium and annual change in hours worked indicator respectively. However, data for these occupations is unavailable for three out of seven indicators and data is imputed from 3-digit SOC20 data for the remaining four. This also applies to three occupations in elevated demand: collector salespersons and credit agents, market and street traders and assistants, and visual merchandisers and related occupations. Care should be taken when considering the demand for these occupations.
8. Proportions may not sum to 100% due to rounding.


Unscaled unweighted occupation demand

Filename: unscaled_unweighted_oid_output.csv
Geographic levels: National
Time period: 2024
Content summary: This file contains demand indicators used in determining occupations in demand before weighting and scaling.

Variable names and descriptions for this file are provided below:

Variable name                           |  Variable description
--------------------------------------  |  ----------------------------------------------------------------------------------------------
annual_change_in_contract_temp_workers  |  Annual change in contract or temporary workers
annual_change_in_hourly_wage            |  Annual change in hourly wage
annual_change_in_hours_worked           |  Annual change in hours worked
cluster                                 |  Occupation group - Filter by occupation cluster groups
construction                            |  Occupation is in construction - Filter by construction occupations
count                                   |  Number of occupations
demand_level                            |  Demand type - Filter by type of demand
demand_level_percent                    |  Proportion of workers in demand
employees                               |  Number of workers
hourly_wage                             |  Average hourly wage
imputed_indicators                      |  Number of indicators imputed from 3-digit SOC
missing_indicators                      |  Number of indicators with missing data
online_job_ad_density                   |  Online job advert density
percent                                 |  Proportion of workers
shortage_occupation_list                |  Occupation is in the shortage occupation list - Filter by shortage occupation list occupations
skill_level                             |  ONS skill level - Filter by skill level
skills_shortage_vacancy_density         |  Skills shortage vacancy density
SOC_description                         |  SOC20 Description - Filter by occupation description
SOC20                                   |  SOC20 - Filter by occupation
STEM                                    |  Occupation is in STEM - Filter by STEM occupations
visa_application_density                |  Visa application density
wage_premium                            |  Wage premium

Footnotes:

1. Some occupations from ONS’ job advert statistics were excluded from this analysis since the relative occupational distribution compared with annual population survey occupational data were judged in some cases to be relatively atypical. ONS plan to continue improving their statistics, including with an enhanced SOC allocation process, which may trigger revisions of the occupations excluded in future.
2. Only occupations which did not have any missing demand indicator data and were not otherwise excluded from the analysis were included in the clustering analysis, 268 out of 412 occupations.
3. Only four occupations were grouped into group 1. These occupations were grouped together because visa application density was their main demand indicator and this indicator was much higher than seen in all other occupations, indicating these occupations may react strongly to changes to visa rules.
4. Median wages sourced from: Earnings and hours worked, occupation by four-digit SOC: ASHE Table 14 - Office for National Statistics (ons.gov.uk) (https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/occupation4digitsoc2010ashetable14)
5. Proportions may not sum to 100% due to rounding.


Industry demand

Filename: sic_oid_output.csv
Geographic levels: National
Time period: 2024
Content summary: This file contains industry level demand indicators used in determining industries in demand after weighting and scaling.

Variable names and descriptions for this file are provided below:

Variable name                           |  Variable description
--------------------------------------  |  ----------------------------------------------------------------------------------------------
annual_change_in_contract_temp_workers  |  Annual change in contract or temporary workers
annual_change_in_hourly_wage            |  Annual change in hourly wage
annual_change_in_hours_worked           |  Annual change in hours worked
cluster                                 |  Occupation group - Filter by occupation cluster groups
construction                            |  Occupation is in construction - Filter by construction occupations
count                                   |  Number of occupations
demand_index                            |  Demand index
demand_level                            |  Demand type - Filter by type of demand
demand_level_percent                    |  Proportion of workers in demand
hourly_wage                             |  Average hourly wage
imputed_indicators                      |  Number of indicators imputed from 3-digit SOC
industry_employees                      |  Industry workers
missing_indicators                      |  Number of indicators with missing data
occupation_employees                    |  Occupation workers
online_job_ad_density                   |  Online job advert density
percent                                 |  Proportion of workers
shortage_occupation_list                |  Occupation is in the shortage occupation list - Filter by shortage occupation list occupations
SIC_name                                |  Industry name - Filter by industry
skill_level                             |  ONS skill level - Filter by skill level
skills_shortage_vacancy_density         |  Skills shortage vacancy density
SOC_description                         |  SOC20 Description - Filter by occupation description
SOC20                                   |  SOC20 - Filter by occupation
STEM                                    |  Occupation is in STEM - Filter by STEM occupations
visa_application_density                |  Visa application density
wage_premium                            |  Wage premium

Footnotes:

1. Some occupations from ONS’ job advert statistics were excluded from this analysis since the relative occupational distribution compared with annual population survey occupational data were judged in some cases to be relatively atypical. ONS plan to continue improving their statistics, including with an enhanced SOC allocation process, which may trigger revisions of the occupations excluded in future.
2. Only occupations which did not have any missing demand indicator data and were not otherwise excluded from the analysis were included in the clustering analysis, 268 out of 412 occupations.
3. Only four occupations were grouped into group 1. These occupations were grouped together because visa application density was their main demand indicator and this indicator was much higher than seen in all other occupations, indicating these occupations may react strongly to changes to visa rules.
4. Employment volumes sourced from: Annual population survey Apr 2023 - Mar 2024 (https://www.nomisweb.co.uk/datasets/aps218/reports/employment-by-status-and-occupation?compare=K02000001)
5. Median wages sourced from: Earnings and hours worked, occupation by four-digit SOC: ASHE Table 14 - Office for National Statistics (ons.gov.uk) (https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/datasets/occupation4digitsoc2010ashetable14)
6. The demand index covers a range of scores between -1.22 and 1.49.
7. Proportions may not sum to 100% due to rounding.
