Analysis of the Ship Ops Model's Accuracy in Predicting U.S. Naval Ship Operating Cost

Abstract

The purpose of this MBA Project was to investigate and provide a comprehensive analysis of the accuracy of the Ship Ops model used by the U.S. Navy to budget for ship-operating costs. This project was conducted with the sponsorship and assistance of the OPNAV N82 office, also known as Office of Budget (FMB). The goal of this project was to improve FMB's ability to predict ship-operating costs through the use of an improved Ship Ops model. This project provides an in depth introduction to the Ship Ops model currently in use and an analysis of the model's performance in predicting accurate operating costs. The project also provides suggestions for improvements to the model and tools that can be used to predict costs on an individual ship level that is not possible with the current model. This project observed only limited improvements in predicting Repair Parts and OPTAR cost through the use of regressions based on operational data such as days underway. Significant improvement was observed when the current moving average methodology for predicting Repair Parts cost was replaced with a regression-based prediction based on a sequential independent variable, Fiscal Year.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2003
Accession Number
ADA417410

Entities

People

  • An Drew M. Matthews
  • Andrew M. Hascall
  • Mihaly Gyarmati
  • William K. Gantt

Organizations

  • Naval Postgraduate School

Tags

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Business Administration
  • Cost Estimates
  • Data Analysis
  • Databases
  • Growth Factors
  • Information Science
  • Monte Carlo Method
  • Naval Operations
  • Naval Vessels
  • Navy
  • Regression Analysis
  • Spreadsheet Software
  • United States
  • Uss Arleigh Burke
  • Uss Nimitz
  • Uss Ticonderoga

Readers

  • Computational Modeling and Simulation
  • Enterprise Information Systems Architecture and Joint Command Capability Interoperability Support.
  • Logistics and Supply Chain Management.