Dollar Cost Banding: A New Algorithm for Computing Inventory Levels for Army Supply Support Activities
Abstract
When Army equipment fails, the speed with which maintenance technicians can restore it to mission-ready condition depends on the availability of needed spare parts. When parts are available at the maintainer's supporting supply support activity (SSA), maintainers receive their orders quickly; in contrast, parts that are unavailable at the supporting SSA might not arrive for a week or more. But despite the advantages of having parts available from the maintainer's supporting SSA, Army inventory managers determining what to stock in their deployable SSAs cannot simply base their decisions on the desire to achieve a high level of customer service by stocking as many items as possible. Instead, they must balance performance goals against the realities of limited funding and storage capacity constraints. To manage this tradeoff, the Army uses an algorithm that tracks customer demands and computes which items to stock and how many of each. However, the Army was not satisfied with the existing algorithm used to compute inventory levels for SSAs. Metrics developed under Velocity Management (VM) suggested that performance could be improved, and this was supported by evidence that Army maintainers too often found that critical parts were not on the Authorized Stockage List (ASL) of the supporting SSA, leading to long customer wait times, extended repair times, and reduced equipment availability. Part unavailability could also increase maintenance workload if maintenance technicians chose to work around a problem by removing needed parts from other pieces of inoperable equipment. When no workaround was possible, repairs could not be completed until all needed parts had arrived, thus reducing equipment readiness. The Army's Deputy Chief of Staff, G-4 (Logistics) asked RAND Arroyo Center to develop a new algorithm for calculating inventory levels in SSAs. As part of this process, Arroyo developed a new stockage determination algorithm known as dollar cost banding (DCB).
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2004
- Accession Number
- ADA440452
Entities
People
- Arthur Lackey
- Daniel A. Relles
- Darlene J. Blake
- Kenneth J. Girardini
- Kristin Leuschner
- Mark Totten
Organizations
- RAND Corporation