Data Quality Problems in Army Logistics

Classification, Examples, and Solutions

by Lionel A. Galway, Christopher Hanks

Download

Download eBook for Free

FormatFile SizeNotes
PDF file 0.3 MB

Use Adobe Acrobat Reader version 10 or higher for the best experience.

Purchase

Purchase Print Copy

 FormatList Price Price
Add to Cart Paperback89 pages $15.00 $12.00 20% Web Discount

Many new Army initiatives such as Velocity Management and Force XXI are based on the assumption that information will be a key asset for U.S. armed forces of the future. Many Army logistics data, however, are widely perceived to be of poor quality. In this report, the authors review the current literature on data quality, develop a three-way scheme for classifying data quality problems, and apply the classification to the analysis of an important logistics data element, the End Item Code (EIC). The authors argue that the EIC has quality problems of all three types, and review the evidence and efforts of the Army to address each. The most fundamental problem is due to the deep gap between the retail organizations that create EIC data and the wholesale organizations that use it. The authors propose several strategies to bridge the gap in order to improve the quality of the EIC data. An appendix applies the data classification scheme to a number of other important logistics data elements exhibiting data-quality problems and reaches similar conclusions about their causes.

Research conducted by

This report is part of the RAND Corporation Monograph report series. The monograph/report was a product of the RAND Corporation from 1993 to 2003. RAND monograph/reports presented major research findings that addressed the challenges facing the public and private sectors. They included executive summaries, technical documentation, and synthesis pieces.

This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.

The RAND Corporation is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.