2015Unpublished venueRequires access

Inventory Reduction Without Regret: Balancing Storage and Rebuy Costs

Marygail K. Brauner, John F. Raffensperger, Edward W. Chan

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Abstract

Abstract : With the drawdown after ten years of war, policymakers are keen to find savings. Unfortunately, some managers view the Army s currently high (relative to current demand) parts inventory as an inherent source of waste, which has led to a push within the Army to dispose of inventory. This push is unlikely to save money. The primary metric now used to assess the cost of inventory is its total dollar value, calculated as purchase price times the quantity on hand. Setting a goal to reduce the dollar value of parts inventory can lead to disposing too much of it, ultimately resulting in higher long-run costs through eventual purchases or repairs that would have been unnecessary if parts had been retained. To avoid these extra costs, we recommend that the Army assess the cost of inventory based instead on the long-run cost of inventory (LRCoI) already purchased. LRCoI accounts for storage costs, repair costs, and the risk of rebuy. We have developed LRCoI formulas that the Army could implement in its existing information systems. By using this metric, the Army would optimize inventory retention by reducing the risk of future rebuy and reducing storage costs, and it would better align retention with Army policy that calls for justification based on economics.1

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Abstract : With the drawdown after ten years of war, policymakers are keen to find savings. Unfortunately, some managers view the Army s currently high (relative to current demand) parts inventory as an inherent source of waste, which has led to a push within the Army to dispose of inventory. This push is unlikely to save money. The primary metric now used to assess the cost of inventory is its total dollar value, calculated as purchase price times the quantity on hand. Setting a goal to reduce the dollar value of parts inventory can lead to disposing too much of it, ultimately resulting in higher long-run costs through eventual purchases or repairs that would have been unnecessary if parts had been retained. To avoid these extra costs, we recommend that the Army assess the cost of inventory based instead on the long-run cost of inventory (LRCoI) already purchased. LRCoI accounts for storage costs, repair costs, and the risk of rebuy. We have developed LRCoI formulas that the Army could implement in its existing information systems. By using this metric, the Army would optimize inventory retention by reducing the risk of future rebuy and reducing storage costs, and it would better align retention with Army policy that calls for justification based on economics.1

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Available abstract

Abstract : With the drawdown after ten years of war, policymakers are keen to find savings. Unfortunately, some managers view the Army s currently high (relative to current demand) parts inventory as an inherent source of waste, which has led to a push within the Army to dispose of inventory. This push is unlikely to save money. The primary metric now used to assess the cost of inventory is its total dollar value, calculated as purchase price times the quantity on hand. Setting a goal to reduce the dollar value of parts inventory can lead to disposing too much of it, ultimately resulting in higher long-run costs through eventual purchases or repairs that would have been unnecessary if parts had been retained. To avoid these extra costs, we recommend that the Army assess the cost of inventory based instead on the long-run cost of inventory (LRCoI) already purchased. LRCoI accounts for storage costs, repair costs, and the risk of rebuy. We have developed LRCoI formulas that the Army could implement in its existing information systems. By using this metric, the Army would optimize inventory retention by reducing the risk of future rebuy and reducing storage costs, and it would better align retention with Army policy that calls for justification based on economics.1

Key concepts: Dispose pattern, Liberian dollar, Operations management, Inventory theory, Regret, Present value, Economic order quantity, Operations research

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