Full Description

Predicting cash flow is an important element in Gwinnett County's $1.5 Billion Water and Wastewater CapitalImprovements Program (CIP). Being able to accurately forecast cash flow reduces numerous problems inprioritizing, 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 manyhundreds of projects within its CIP. With such an enormous workload and strain on available capital, DWR soughtto achieve better predictability of project cash flow. Because of the quantity and complexity of projects included inthe CIP, a Primavera P3 master scheduling program was used and cash flow projections were developed on aproject-by-project basis. In each project, a cash flow distribution similar to a Gauss-Laplace normal probabilitydistribution was initially used. Through trial and error, the probability distribution was often modified toaccommodate front-loading or back-loading depending on project type. The resulting information was then used toconsider various financial options to make funds available to complete the projects. Although these cash flowforecasts seemed to at least get us into the ballpark, these predictions were often overly optimistic, fraught withtechnical concerns such as a "bow-wave" effect, and relied heavily on individuals' reasoning and experience. Theresults were often inaccurate forecasts which led to under-expenditure of bond funds and a growing desire for amore accurate model. By analyzing historical cash flow patterns and broadly accommodating the variables, DWRdeveloped 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 thepredictive models used. Includes figures.

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Edition: Vol. - No. Published: 11/01/2008 Number of Pages: 8File Size: 1 file , 1.1 MB