Questions about staffing costs occur frequently, especially during budget season or when planning special projects such as new libraries or expanding hours. The ability to respond quickly and confidently to these complex questions is an essential function of the administrative team. The complexities of staffing studies can make it one of the more intensive activities a library undertakes. Furthermore, these complexities often lead stakeholders to ask for more information about how figures are derived.

In 2017, the library began using linear regression to estimate staffing levels using the best data available. Reviewing 16 different data points, a modified stepwise regression was conducted across the data. The regression identified a standard equation to determine full-time equivalent staffing. The resulting regression is already being used to estimate staffing needs at new facilities and renovations. City partners are being provided with funding estimates which can be quantified.

Use of linear regression does not replace professional knowledge of populations, age of facilities or populations served. Rather, it allows a cross check of data to ensure staffing levels are aligned to the unique characteristics of the community served and to other county branches. Stakeholders have confidence that staffing estimates provided by the library are accurate and based on reliable data. The result is easily generated staffing models that accurately account for service needs.