Good Home Network Meeting May: Staffing Recruitment and Retention

The Good Home Network had its first meeting this May, focusing on recruitment and retention challenges in delivering home improvement services. The meeting summary has been published on the Centre For Ageing Better website, outlining key resource challenges facing local authorities, including staffing structures and accessing funding. The Good Home Network suggest solutions to these challenges and provides further resources to achieve change.

In September 2022, Skills for Care – the leading source of workforce intelligence for England’s adult social care – published data showing vacancy rates for OT posts in the adults’ services departments at 11.3% (up from 8.9% the previous year). This data highlights a particular issue with recruiting occupational therapists, although it is difficult to recruit staff across various roles with experience delivering the Disabled Facilities Grant.

Local authorities commission external expertise at a high cost to continue delivering services. With the increased cost of living, they must also compete against the private sector to attract recruits based on pay and incentives. Some staffing structures within wider Home Improvement Agencies lead to fragmented teams and affect their ability to deliver services effectively. As the proportion of in-house agencies grows, a multi-disciplinary, integrated and customer-centred approach is required to bring these teams together.

Increased costs, and growing demand for home improvement services, mean some local authorities have to allocate their Disabled Facilities Grant budget by prioritisation methods and waiting lists. Whereas; local authorities in other areas have not been able to use their Disabled Facilities Grant allocation within the budget year.

To read the brief, including solutions and resources, visit https://ageing-better.org.uk/sites/default/files/2023-05/Good_Home_network_briefing.pdf

To read the full report, visit https://ageing-better.org.uk/sites/default/files/2023-05/Learning-output-GHN.pdf