Using the law firm diversity data tool
31 January 2022
The diversity tool is an interactive and easy way to view diversity information about firms by population and diversity category. You can also filter this by number of partners, number of branches, region and work type.
The data only covers people working in law firms in England and Wales, it does not cover solicitors working in-house or in other employed roles.
Some of the figures in the tool may add up to 99% or 101%. This is because we have rounded all our percentages to the nearest 1% which may not add up to 100% exactly.
Searching by population
You can search by the following five populations:
- Partners
- Solicitors
- All lawyers
- Other staff
- All
Definitions for these populations are available by clicking on the "Good to know" tab underneath the population drop down box.
Using firm filters
You can only use one filter at a time, the filters available are:
- By firm size using the number of partners within each firm
- By the number of branches a firm has
- By each English region and for Wales - firms with branches in more than one area are recorded under the region where the firm's head office is located
- By work type - a firm will be classed in a particular category if they have told us they do 50% or more of that work type
The definition for each work type is as follows:
Corporate/financial/IP
debt collection, financial advice or bankruptcy/insolvency.
Litigation/ADR
all types of litigation, including personal injury, civil liberties and human rights, and all types of arbitration.
Private client
work for private individuals covering children, consumer, matrimonial, immigration, mental health, social welfare, wills and probate.
Property
conveyancing, planning and landlord/tenant.
Other
includes any type of work that does not reasonably fit into the other categories.
Criminal
Mixed Work Type
Our approach to analysis
We have changed our approach to reporting data for 2021 by including the ‘prefer not to say’ data in our analysis. This means that the overall numbers reported last year across all categories will be slightly lower and cannot be compared with the data published in previous years. When we started collecting this data some years ago, we applied recognised modelling techniques to the raw data to predict the outcomes for those who preferred not to say or did not provide a valid response at all.
As part of our commitment to presenting transparent and meaningful information in this important area, and in line with what is now usual practice for many organisations, we have decided that it would be more appropriate to use the raw data and include the ‘prefer not to say’ information, which itself is an important indicator. In this analysis we have drawn any comparison with earlier years based on the raw data for those years.