The correlation of cost and schedule variance in satellite programs: level of effort versus discrete cost accounts

Andy Lewin, Ekundayo Shittu (), Thomas Mazzuchi and Rene Dorp
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Andy Lewin: The George Washington University
Ekundayo Shittu: The George Washington University
Thomas Mazzuchi: The George Washington University
Rene Dorp: The George Washington University

Environment Systems and Decisions, 2021, vol. 41, issue 2, 248-266

Abstract: Abstract This research analyzes cost account-level detail from ten similar satellite programs to assess the relationship between cost and schedule variances. A model is defined to break activity into two types: level of effort (LOE), in which cost is directly proportional to the cost account’s duration and discrete, where the cost is independent of the schedule. Primary data collected by the authors from the ten satellite programs are split into these two categories and analyzed separately. Marginal distributions for schedule and cost for each of the two databases are built using the generalized two-sided power distribution (GTSP). Correlations between cost and schedule variance are calculated for the LOE and discrete cost accounts. Finally, joint distributions are created for each database using generalized diagonal band copulas. The results show that the GTSP effectively modeled the marginal distributions and the generalized diagonal band copula with a slope generating function successfully representing the observed joint distribution. The analysis, resulting from the correlation values, show that the cost and schedule variance for discrete cost accounts are not correlated. However, the LOE cost accounts show a correlation well below the projected perfect correlation. The models were validated by removing one program’s data from the database, regenerating the models, and assessing the accuracy of the model against the program excluded from the model. The model derived from nine programs successfully modeled the results from the tenth program. These results provide both a modeling method and guidance for modeling parameters for joint cost and schedule risk analysis.

Keywords: Cost; Schedule; Risk analysis; Cost–schedule risk analysis (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10669-021-09799-y

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