ERS Staffing Models

Fannie Mae’s Healthy Housing Rewards - Enhanced Resident Services (ERS) program provides financing incentives for properties where an owner has committed to providing a robust system of resident services coordination either through its own CORES-certified resident services infrastructure or through a CORES-certified third party. As part of the ERS proposal, applicants are asked to provide information about the property, the surrounding community (neighborhood amenities and data), resident demographics (if available), a proposed property-level resident services staffing model (and any virtual supports that may be part of this), a description of how resident services and property management will interact and collaborate, a description of any co-located programs or existing partnership that may be leveraged, and a proposed budget.  


For the staffing model -- CORES has identified a target of a minimum of 1 FTE:150 households for ERS financed properties. This ratio was developed in recognition of existing industry resident services staffing standards (i.e. HUD guidance (p.16) calls for a minimum ratio of 1 FTE:50-100 residents in their Multifamily Housing Program (assisting seniors and persons with disabilities) and Corporation for Supportive Housing has identified a minimum staffing ratio of 1 FTE:10-25 Residents in Permanent Supportive Housing models. The ERS target ratio of 1 FTE to 150 households recognizes that ERS financed properties serve a range of populations with varying levels of need, but still ensures a robust level of service coordination support for residents. 


The evaluation of ERS staffing plans takes into account (1) # of hours of property level staff and # of hours of virtual support, (2) # hours/level of support to the property from regional/corporate offices , (3) whether or not there are co-located programs/partners and/or existing partners that operate onsite regularly (such as an partner operating an afterschool program, dining program, or a health clinic), and (4) identification of populations that may require higher levels of engagement (based on community level data and/or property level data provided).