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Operations Research, Systems Engineering and Industrial Engineering Commons™
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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Agile Software Development: Creating A Cost Of Delay Framework For Air Force Software Factories, J. Goljan, Jonathan D. Ritschel, Scott Drylie, Edward D. White
Agile Software Development: Creating A Cost Of Delay Framework For Air Force Software Factories, J. Goljan, Jonathan D. Ritschel, Scott Drylie, Edward D. White
Faculty Publications
The Air Force software development environment is experiencing a paradigm shift. The 2019 Defense Innovation Board concluded that speed and cycle time must become the most important software metrics if the US military is to maintain its advantage over adversaries.1 This article proposes utilizing a cost-of-delay (CoD) framework to prioritize projects toward optimizing readiness. Cost-of-delay is defined as the economic impact resulting from a delaying product delivery or, said another way, opportunity cost. In principle, CoD assesses the negative impacts resulting from changes to the priority of a project.
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine
Faculty Publications
Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. These diminishing learning rates cause traditional learning curves to underestimate required resources, potentially resulting in cost overruns. A diminishing learning rate model, namely Boone’s learning curve, was recently developed to model this phenomenon. This research confirms that Boone’s learning curve systematically reduced error in modeling observed learning curves using production data from 169 Department of Defense end-items. However, high amounts of variability in …