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<p>In the management of the U.S. Naval inventory, data quality is of critical importance.  Errors in major inventory databases contribute to increased operational costs, reduced revenue, and loss of confidence in the reliability of the supply system.  Maintaining error-free databases is not a realistic objective.  Data-quality efforts must be prioritized to ensure that limited resources are allocated to achieve the maximum benefit.   This thesis proposes a methodology to assist the Naval Inventory Control Point in the prioritization of its data-quality efforts.  By linking data errors to Naval inventory performance metrics, statistical testing is used to identify errors that have the greatest adverse impact on inventory operations.  By focusing remediation efforts on errors identified in this manner, the Navy can best use its limited resources devoted to improvement of data quality.     Two inventory performance metrics are considered:  Supply Material Availability (SMA), an established metric in Naval inventory management; and Backorder Persistence Metric (BPM), which is developed in the thesis.  Backorder persistence measures the duration of time that the ratio of backorders to quarterly demand exceeds a threshold value.  Both metrics can be used together to target remediation on reducing shortage costs and improving inventory system performance.
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<br>Subjects: Data Quality; Statistics; Wilcoxon Rank Sum Test; Inventory; Inventory Performance Metrics; Backorders; F404 Engine System</div>
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Burson, Patrick A. R.</div>
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