Christopher A. Jimenez, E. White, Gregory Brown, J. Ritschel, B. Lucas, Michael J. Seibel
{"title":"Using Pre-Milestone B Data to Predict Schedule Duration for Defense Acquisition Programs","authors":"Christopher A. Jimenez, E. White, Gregory Brown, J. Ritschel, B. Lucas, Michael J. Seibel","doi":"10.1080/1941658X.2016.1201024","DOIUrl":null,"url":null,"abstract":"Accurately predicting a realistic schedule for a defense acquisition program is a difficult challenge considering the inherent risk and uncertainties present in the early stages of a program. Through the application of multiple regression modeling, we provide the program manager with a statistical model that predicts schedule duration from official program initiation, which occurs at Milestone B, to the initial operational capability of the program’s deliverable system. Our model explains 42.9% of the variation in schedule duration across historical data from a sample of 56 defense programs from all military services. Statistically significant predictor variables include whether a program is a new effort or modification to an existing program, the year of Milestone B start as it relates to changes in defense acquisition reform policy, and the amount of raw funding (adjusted for inflation) prior to Milestone B for a program. Our final and strongest predictor variable, percentage of the total RDT&E (Research Development Test and Evaluation) funding profile allocated at Milestone B, indicates that increased percentage of RDT&E funding for pre-Milestone B technology risk reduction may shorten a program’s schedule duration to initial operational capability.","PeriodicalId":390877,"journal":{"name":"Journal of Cost Analysis and Parametrics","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cost Analysis and Parametrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/1941658X.2016.1201024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
Accurately predicting a realistic schedule for a defense acquisition program is a difficult challenge considering the inherent risk and uncertainties present in the early stages of a program. Through the application of multiple regression modeling, we provide the program manager with a statistical model that predicts schedule duration from official program initiation, which occurs at Milestone B, to the initial operational capability of the program’s deliverable system. Our model explains 42.9% of the variation in schedule duration across historical data from a sample of 56 defense programs from all military services. Statistically significant predictor variables include whether a program is a new effort or modification to an existing program, the year of Milestone B start as it relates to changes in defense acquisition reform policy, and the amount of raw funding (adjusted for inflation) prior to Milestone B for a program. Our final and strongest predictor variable, percentage of the total RDT&E (Research Development Test and Evaluation) funding profile allocated at Milestone B, indicates that increased percentage of RDT&E funding for pre-Milestone B technology risk reduction may shorten a program’s schedule duration to initial operational capability.