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The initial EAC becomes the baseline for which the rest of the program’s development cycle is compared. However, the initial EAC may be subject to the greatest degree of inaccuracy due to unknown future cost risks. To help mitigate these risks, the DoD and NASA published the JA CSRUH . Within the JA CSRUH , a myriad of estimations and techniques are conveyed to help develop realistic EACs. Also, within the JA CSRUH lies the ToLR, which serves as the last course of action regarding what the cost growth might be for a program’s WBS element if essentially none of the other JA CSRUH’s methodologies can be adopted (DoD, 2014).
Our analysis of budgeted cost growth is not directly comparable to the ToLR. However, by utilizing the same metrics and distributions as the ToLR, confidence increases in the methods and practical application for the acquisition community.
We adopt the metrics and distributions considered in the ToLR to ascertain what patterns would emerge by analyzing budgeted cost growth with respect to the final EAC to the initial EAC of a WBS element. For our dataset, we utilized Project Ginger II from the Air Force Life Cycle Management Center’s Financial Management Directorate to obtain EAC data reported on the DD 1921s for aircraft development programs only. Therefore, our analysis of budgeted cost growth is not directly comparable to the ToLR. However, by utilizing the same metrics and distributions as the ToLR, confidence increases in the methods and practical application for the acquisition community. Overall, our analysis suggests either the lognormal or the Weibull distributions are reasonable distributions to assume when modeling the distribution of EAC cost growths for the WBS elements of Cost, Fee, Data, PME, SE, SEPM, ST&E, and Training. If one wished for more granularity for Data, then we would further suggest adopting a beta distribution to model EAC cost growth. In contrast, if one wished to strictly use just one distribution to model, then we suggest the lognormal distribution. Such a recommendation is in line with other sources (DoD, 2014; Garvey et al., 2016). The mean, CV, and 85th percentile values, as shown in Table 6, do suggest a skewed right pattern of EAC cost growth. In other words, a DoD ACAT I
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Defense ARJ , Spring 2025, Vol. 32 No. 1
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