- Strategic Transport Apprenticeship Taskforce releases third annual report on delivery of road and rail apprenticeships
- report shows diversity has increased, with the proportion of black, asian and minority ethnic (BAME) apprentices shooting up 56% over the last 2 years.
A report published today (11 July 2019) shows that strong progress is being made by an industry-led taskforce in boosting the proportion of under-represented groups in transport apprenticeships.
The Strategic Transport Apprenticeship Taskforce’s (STAT) 3 year progress report marks the latest in a series of annual reports setting out progress against ambitions from the government’s 2016 Transport infrastructure skills strategy, as well as information on the diversity of those undertaking apprenticeships.
And statistics in today’s report show that BAME representation now stands at over a fifth of apprentice intake, representing a 56% proportional increase over the last 2 years in the share of BAME apprentices in the sector.
The figure provides a positive result for STAT, who have exceeded their commitment to improve BAME representation in apprenticeships.
And the picture for women’s representation also shows positive improvement, with women now making up 15.4% of technical and engineering apprenticeship starts, up from 10% 2 years ago, representing a 54% proportional increase. The figures again show real progress towards the STAT’s target of 20%. Female representation in all apprentice roles has increased to 23.6%, up from 20% 2 years ago.
Minister Nusrat Ghani said:
Drawing from the widest pool of talent is vital for any industry, particularly where there are skills shortages. 41,000 people are needed in roads by 2025, and rail needs 50,000 extra people by 2033 to deliver planned investment.
That’s why it’s fantastic to see how apprenticeships can be used to attract and train a more diverse workforce. STAT’s work is vital in getting under-represented groups into transport apprenticeships and meeting skills needs. They are providing great opportunities for all, regardless of background.