AWWA ACE68600

Predicting cash flow is an important element in Gwinnett County's $1.5 Billion Water and Wastewater Capital Improvements Program (CIP). Being able to accurately forecast cash flow reduces numerous problems in prioritizing, scheduling, funding, and completing essential projects. Gwinnett's Department of Water Resources (DWR), in order to meet the infrastructure demands of a rapidly growing Metro-Atlanta community, has many hundreds of projects within its CIP. With such an enormous workload and strain on available capital, DWR sought to achieve better predictability of project cash flow. Because of the quantity and complexity of projects included in the CIP, a Primavera P3 master scheduling program was used and cash flow projections were developed on a project-by-project basis. In each project, a cash flow distribution similar to a Gauss-Laplace normal probability distribution was initially used. Through trial and error, the probability distribution was often modified to accommodate front-loading or back-loading depending on project type. The resulting information was then used to consider various financial options to make funds available to complete the projects. Although these cash flow forecasts seemed to at least get us into the ballpark, these predictions were often overly optimistic, fraught with technical concerns such as a "bow-wave" effect, and relied heavily on individuals' reasoning and experience. The results were often inaccurate forecasts which led to under-expenditure of bond funds and a growing desire for a more accurate model. By analyzing historical cash flow patterns and broadly accommodating the variables, DWR developed normalized cash flow curves for various project types. These curves yield better predictive models, thereby improving the forecasting capability of DWR. This paper discusses the analyses and presents the predictive models used. Includes figures.