Measuring the Impact of Business Rules on Inventory Balancing

Abstract

Naval Supply Systems Command recently employed the Navy Enterprise Resource Planning Single Supply Solution to improve efficiency through the sharing of data across the organization. For the first time, replenishment decisions were made using shared enterprise data. Since all items from all sites are in one central database, Weapon Systems Support has total visibility of assets across all available supply sources. Inventory balancing is a promising functionality for enhancing the performance of inventory systems. With a balancing policy in place, stock can be moved from a location that has excess inventory to another location experiencing a shortage. The purpose of this movement of materiel is to reduce inventory costs and increase the percentage of demand satisfied by on-hand stock. This paper compares the relative effectiveness of different balancing business rules. A simulation model comprising a two-echelon supply network with three warehouse locations is used to evaluate the various business rules for several items with varying unit prices and demand frequencies. Although no single balancing policy is optimal in all situations, simple modifications to the proposed business rules will increase the benefits of balancing while minimizing any negative effects.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2013
Accession Number
ADA589703

Entities

People

  • Andrew Oswald

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Basic Programming Language
  • Business Administration
  • Databases
  • Department Of Defense
  • Governments
  • Information Science
  • Inventory Control
  • Lead Time
  • Logistics
  • Mathematical Models
  • Operations Research
  • Procurement
  • Supply Chain
  • Supply Chain Management
  • United States
  • United States Government
  • United States Naval Academy

Readers

  • Logistics and Supply Chain Management.
  • Parallel and Distributed Computing.