Methodology

Read about our methodology for collecting workforce data and how we calculate and create workforce estimates. Skills for Care has confidence in the quality of these estimates; the methodologies used have been peer reviewed by universities and an independent statistician.

We estimate the size, structure and characteristics of the adult social care workforce in England. Good quality information about the adult social care workforce is vital to help improve the planning and quality of social care services, which will improve outcomes for people who use these services, both now and in the future.

We use data collected in the Adult Social Care Workforce Data Set (ASC-WDS) to create workforce models that allow for estimates of the whole adult social care workforce to be produced.

Our methodology permits the analysis to be representative of all adult social care workers, even if the ASC-WDS has uneven levels of data coverage. All data is validated at source and has been through rigorous data quality checks before analysis.


Read our methodology in full

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Read about our methodology for estimating the size and characteristics of the adult social care workforce in England, including information about the data quality of our adult social care estimates.

Appendix A – Data collected through the ASC-WDS service - MS Excel spreadsheet

Details we collect

The ASC-WDS collects information about the adult social care sector and workforce. It's structured into two parts;

The workplace

  • employment type or sector, e.g. local authority, private or voluntary/charity
  • main and other care services provided, e.g. residential care with or without nursing, or domiciliary care (35 service types in total)
  • geographical location
  • CQC registration information
  • care and support needs supported e.g. dementia care, learning disabilities
    (23 options)
  • new starters, staff leavers and vacancy information.

The workforce

  • main job role of workers (32 job role options)
  • contract type, e.g. permanent, temporary or agency
  • demographics e.g. gender, age, disability status, ethnicity and nationality
  • employment information e.g. zero-hours contracts, contracted or average hours, sickness rates
  • experience in sector and role, and source of recruitment
  • qualification and training information, Care Certificate status and apprenticeship training
  • pay rate / reasons for leaving.

Coverage

There is information recorded in the ASC-WDS for approximately half of the adult social care workforce. This coverage varies by care service, job role and geographical area.   

For local authorities (adult social services departments), an annual data return submitted to the ASC-WDS is mandatory. Between 2012 and 2021, all 151 local authorities in England met the criteria of a full data return each year for people working in their adult social services departments. In 2022, all local authorities apart from Salford submitted a return. In 2023, Cumbria divided into two new local authority areas: Cumberland, and Westmoreland and Furness, however neither of the new areas provided a complete data return. In 2024, all local authorities submitted a complete data return, meaning we have data from every local authority with an adult social services department in England.  

When local authorities do not provide a complete data submission, we use proxy information and estimations in place of the missing data.   

  • For variables that are similar year on year, e.g. average age, gender and ethnicity, we use the previous year’s data as a proxy (where possible).   

  • For variables that are likely to change e.g. starters, leavers, sickness and pay using a proxy is not possible. Instead, we use estimates to try and reduce the impact on national and regional totals.   

CQC-regulated services make up a large proportion of care services in the ASC-WDS, as many establishments must be regulated by law. Our coverage of CQC-regulated establishments varies month by month but is typically around 50%. A sample of this size provides a solid basis for creating reliable and precise analysis about the adult social care workforce at both a national and local level.  


Methodology

We use data collected by the ASC-WDS to create workforce models that, in turn, allow for estimates of the whole adult social care workforce to be produced.

To do this, we make estimates of workforce characteristics (e.g. demographics, pay rates, employment statuses) for each geographical area, service type, employer type and job role combination that we report by. These estimates are then ‘weighted’ according to coverage/completeness of the sector in each of the above areas. For example, an area with 50% coverage would use more weighted data in the final analysis than an area with 90% coverage. Using this methodology allows for the analysis to be representative of all adult social care workers even if the ASC-WDS has uneven levels of data coverage.

Skills for Care is confident in the quality of these estimates and the methodologies used have been peer reviewed by universities and an independent statistician.

For a more detailed overview of how we create our workforce estimates, please download the ‘Methodology for estimating the size and characteristics of the adult social care workforce in England, 2024’ report at the top of this webpage.  


Integrity and data quality

Every effort is made to ensure that information derived from the ASC-WDS is reliable.

  • In March 2025, the ASC-WDS contained information on just over half of all CQC-regulated social care establishments (54.4%).
  • All data in the ASC-WDS has been updated or confirmed to be up to date within the last two years and most employers have updated their data in the past 12 months.
  • All data is validated at source and has been through rigorous data quality checks during the analysis.

Suppression and rounding for ASC-WDS publications

The following rounding rules have been applied to the ASC-WDS weighted workforce estimates.

  • We suppress information if there are less than 10 filled posts within any group. In some cases, for example when showing pay rates, suppression is used if there are less than 25 filled posts in a group.
  • Rounding and suppression rules are applied after any calculations (sums, averages, percentages etc.). This sometimes means numbers in tables may appear not to add up. 


    Round to the nearest      
Raw filled posts value from  | to  |  All sectors or independent sector   | Local authority  | Direct payment recipients   
 0  0.000 0 0 0  
 10  14,999 10 10 10  
 15  24,999 25 25 25  
 25  499.999 25 25 50  
 500  999,999 50 50 50  
 1,000  9,999.999 100 100 100  
 10,000  24,999.999 500 100 250  
 25,000  249,999.999 1,000 100 1,000  
 250,000  - 5,000 100 5,000  

 

 

Rationale for rounding and suppressing data

  • Rounding and suppression reduces the risk of identifying individuals from published figures. Even when the data contains no personally identifiable information.
  • Rounding of all figures to the nearest (see table above) prevents multiple tables being used to identify small numbers.
  • Percentages are suppressed for small groups to prevent percentages from giving away the real un-rounded figures in a table.
  • Percentages are displayed to zero decimal places unless there is a good statistical reason for using more precision.
  • Suppression reduced the risk of decisions being based on small sample sizes.

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