Most public utilities routinely develop, or update, their Capital Improvement Plans (CIP) to project facility needs, identify discrete projects, estimate costs, and prioritize capital expenditures to keep up with the changing facility needs based on changes in land-use, demographics, environmental mandates, or any number of other factors affecting a utility. The CIP is the critical outcome of the longer term project planning process.
The CIP process typically involves identifying projects and prioritizing them by ranking according to a scale. However, many prioritization processes do not consider a project’s life cycle costs or other quantitative and qualitative factors which are so pivotal to the long term cost efficiencies of the planned projects and have continuing impacts on the customer service levels. Failure to identify these factors can affect the utilities and their communities due to higher than necessary operation and maintenance costs, sub-optimal reliability, diminished or other long term financial and operational issues.
The objective of this study was to develop an innovative asset management approach to prioritize CIP’s based on life cycle costs, criticality of identified projects, probability of project failure, costs associated with project failure, and the socio-economic needs of the affected community. The study involved developing a comprehensive but easy to use spreadsheet model to prioritize projects based on the above factors.
The model is designed to help utility managers and even the policy makers to efficiently analyze project prioritization elements and make effective capital investment decisions for their communities. The model is flexibly designed to perform sensitivity and scenario analyses by varying the critical factors that affect investment decisions. Thus the model can also serve as a dynamic companion to an existing CIP for ready refreshing of the project priority listing.
Sensitivity analysis was carried out to identify the sensitivity of the prioritization to life cycle costs, project criticality, failure costs and socio-economic needs. The model was also run under different scenario conditions to compare the changes in project prioritization. The scenarios included evaluating the project prioritization ranking during times of high life cycle costs, high socio-economic needs, and high project criticality and during times of high risk to project failures.
This innovative asset management technique to prioritize capital improvement projects is easily adopted by developing a simple spreadsheet model. The technique also provides the flexibility to incorporate additional decision variables into the model that may be considered important by the decision makers. The modeling technique provides the ease and flexibility to assist utility managers and policy makers to make effective capital investment decisions.