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https://dair.nps.edu/handle/123456789/4202
Title: | Budget Forecasting for U.S. Marine Corps Corrective Maintenance Costs |
Authors: | Eddine Dahel |
Keywords: | Budget Forecasting U.S. Marine Corps Maintenance Costs |
Issue Date: | 30-Mar-2020 |
Publisher: | Acquisition Research Program |
Citation: | Published--Unlimited Distribution |
Series/Report no.: | Budget Forecasting;SYM-AM-20-053 |
Abstract: | This project presents some methodologies to forecast corrective maintenance costs of the 1st Marine Division. Nearly half of the 1st Marine Division’s budget, approximately $25 million, is used for maintenance. The current budgeting process has a number of weaknesses, which include insufficient detail to defend against funding cuts and overreliance on historical execution and expert opinion, and is therefore ill-equipped to adapt to changing requirements or communicate impacts on readiness. By combining and analyzing data from a variety of independent sources, including financial, maintenance, and transportation data, two classes of models were developed to assist maintenance budget planners develop accurate forecasts of corrective maintenance costs. The first class, consisting of causal models, is used to identify cost drivers impacting corrective maintenance costs of two vehicles among the 20 most expensive vehicles used by the Division. The second class, consisting of time series techniques, is used to forecast corrective maintenance costs of the Division’s Type A items (or items consuming 80% of the maintenance budget). The analysis indicates that the models can provide a more quantitative and accurate methodologies for 1st Marine Division planners to build, justify, and defend its corrective maintenance budget. |
Description: | Acquisition Management / Defense Acquisition Community Contributor |
URI: | https://dair.nps.edu/handle/123456789/4202 |
Appears in Collections: | Annual Acquisition Research Symposium Proceedings & Presentations |
Files in This Item:
File | Description | Size | Format | |
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SYM-AM-20-053.pdf | 793.1 kB | Adobe PDF | View/Open |
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