As a subcontractor to CardnoTEC, Inc., RDN completed multiple aspects of the US Coast Guard’s Nationwide Housing Study to include Housing Market Survey and Analyses (HMSAs), the creation of the online Requirements Assessment and Forecasting Tool (RAFT), and the design, implementation, and analysis of a nationwide customer satisfaction survey of 14,000+ active duty US Coast Guard (USCG) personnel.
A Housing Market Survey and Analysis (HMSA) or Remote HMSA (RHMSA) is a site-specific study which assesses the capacity of the private sector to provide military and/or other designated personnel with housing meeting specific criteria for acceptability. It was used as the Coast Guard’s primary tool for determining the number of government-provided housing units needed at a particular location. RDN assisted USCG leadership in adapting methodology originally developed by the Office of the Secretary of Defense. This model, as well as the assumptions, criteria, and general approach it incorporates, has involved from more than two decades of inter-service efforts to improve the reliability of forecasts of housing requirements for US uniformed personnel.
The defining feature of RDN’s HMSAs were on-site data collection, which included kick-off meetings with local and/or area housing office and installation leadership personnel, metrics to establish the geographical limits of the market area, surveys of community housing adequacy, and extensive interviews with planners and housing professionals. RDN performed HMSAs at seven locations to include San Francisco, CA; Juneau, AK; Sitka, AK; San Juan, PR; Aguadilla, PR; the Upper Keys, FL; and Astoria, OR. RHMSAs were conducted for 18 locations in the continental United States as well as Alaska.
Additionally, RDN developed an online tool to help USCG leadership identify market areas not covered by the HMSA and RHMSA analyses where USCG personnel may be having difficulties finding housing or where the USCG may have excess owned housing. The Requirements Assessment and Forecasting Tool (RAFT) was built on structural models that estimated the percentage of USCG renters not likely to find suitable-quality, affordable housing at locations where an HMSA or RHMSA had not been accomplished or was outdated due to significant chances in the demographics or force structure of USCG personnel, economic conditions, or additional considerations. RAFT accomplished many functions, the primary of which were: (1) display of preliminary forecasts of the need for government-provided housing in select user-defined geographical areas; (2) modeling changes in housing requirements due to changes in homeownership rates and/or personnel levels i.e. performance of “what if” drills; (3) provision of a summary overview of preliminary RAFT forecasts and/or HMSA results at each USCG location, by city, including recommendations for further action, and (4) catalog and display of reports/summary results of the most current HMSA for all applicable USCG locations.
RDN’s nationwide survey of all active duty personnel in the USCG survey comprised two principal objectives: (1) gathering of necessary demographic information to be used in studies of housing requirements and (2) allowing USCG leadership to hear directly from “customers”, unit commanders, and officers in charge to identify areas of concern regarding the need for housing; the condition and function of existing housing; and where the mission may have been impacted in an adverse housing situation. We designed and implemented an online questionnaire which gathered information on marital status, dual military households, accompaniment status, family size, local homeownership, housing type and size in the private sector, location of private sector residence and commute, and the monthly cost of rent, utilities, renter’s insurance, mortgage, taxes, and homeowner’s insurance. Additionally, the survey provided various metrics for quantifying customer satisfaction with their residence and housing community. Our comprehensive report provided detailed analysis and results by pay grade, district, installation, number of dependents, and a variety of other factors.