Research for Inventory

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May 1, 2007
This paper examines labor use trends for the Navy, with the objective of identifying support functions that are potential candidates for labor adjustments. The authors calculate total labor for Navy IGCA inventory based functions each year from FY 2002 through FY 2005 as the sum of military, civil service, and contractor work-years. The latter are estimated from annual contracting dollars and cost per contractor for the federal supply classification (FSC) codes that are associated with each of the IGCA functions. They sought output measures for the functions, but found that useable output measures could not be found for about half of the functions. They develop and use a system for ranking the potential of functions as candidates for labor adjustments and recommend 14 candidate functions for further detailed examination. They also provide a conceptual model of how these functional output measures might be used as inputs to a Leonteif input-output business interaction model which could link shore function outputs to warfighter requirements and capabilities.
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August 1, 2006
This information memorandum describes the forecasting model for the Marine Corps’ aviator inventory. The model is written in Excel Visual Basic for Applications (VBA) and is contained within two workbooks. The paper details how a user can gather the data necessary for the model, as well as how to run the model. The appendices provide greater detail about the workings of the model’s programs, as well as the actual code used.
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February 1, 2005

The Marine Corps's manpower costs—about $9.4 billion—represent 60 percent of its annual budget. Before this study, there was no institutionalized and documented methodology for forecasting losses and no systematic attempt to improve existing techniques. Personnel charged with developing plans to meet Marine Corps endstrength requirements relied on information gleaned during overlap with their predecessors and sometimes developed their own methods, which were susceptible to errors. The study's authors revamped the process to make it more systematic and recommended ways to accurately forecast endstrength losses and gains.

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