A utility program considers four key variables when assessing the cost-effectiveness of an energy efficiency measure: energy savings, peak demand savings, measure costs and effective useful life (EUL). Of these four variables, programs typically place the least emphasis on setting and updating measure costs. For this analysis, we explore measure costs by mining program participant data across multiple regions over a four year period. Our analysis focuses on a select group of top retrofit measures in commercial programs, where the incremental cost is equal to the full measure cost. We examine how costs change year-to-year and across different geographic regions. Our analysis found that: 1.Regional differences can have a very significant impact on average measure cost ranging from 7% to 51%, with an average of 22%. 2.Temporal differences can also have a significant impact ranging from 1% to 24%, with an average of 9%. 3.Variables such as project size and changing market conditions can have significant impacts on costs over time. These observations support our best practice recommendations to base measure cost estimates on the region where the program is located and to update those cost estimates at least every two to three years.
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