Carrying Cost of Goods Definition

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Carrying Costs (Inventory) Definition

The cost incurred by a company to hold and store its inventory for a certain period of time is called the carrying cost. In marketing, it is also known as the holding cost or carrying cost of inventory. It is often expressed as a percentage of the inventory value and helps in understanding how long the inventory could be put on hold before suffering a loss.

Typically, the carrying cost includes taxes, the cost of keeping the products in the warehouse, salary and wages of the employees, depreciation, insurance, the cost of insuring and replacing items and others.

A Little More on What is Carrying Costs for Inventory

Generally, the manufacturing companies store a certain amount of inventory in stock for fulfilling the seller’s orders. The carrying cost of inventory includes four components:

(i)            Capital cost

(ii)           Cost of the storage space

(iii)          Service cost

(iv)          Risk cost

Capital cost: It is a cost expanded by a company for carrying inventory. It is the major portion of the total costs of carrying inventory. It is expressed as a percentage of the total inventory. This percentage can be an exact figure calculated by the company or a subjective figure based on the experience and industry norms.

Cost of the storage space: Costs are involved in operating and maintaining the storage space. It includes the rent or mortgage of the warehouse, costs of the power supply and other requirements, wages of the employees, handling the cost of moving the products in and out of the warehouse. While the rent or mortgage cost is fixed the other parts vary from time to time.

Service cost: The inventory service cost includes local tax and insurance premiums. The amount of the insurance premium is determined by the nature and volume of the product. Local authorities may ask for taxes for maintaining the inventory. It depends on the rate of the tax charged by the respective authority.

Risk cost: Storing the products in the warehouse involve a certain amount of risk. The product can become obsolete with the advent of new technology. The products that come with an expiry date may expire in the warehouse if stored for a long time. The expired products need to be scrapped and the company faces a loss. The products can also get damaged due to several reasons. Theft and pilferage are also included in such risk factors. All these should be included in the inventory risk cost.

The carrying costs can be calculated as –

(C + T + I + W + (S – R1) + (O – R2))/ Average annual inventory costs

Here the C is the Capital cost, T is the taxes, I stands for the insurance premiums, W is the cost of the warehouse, S is the costs of scraping, O is the obsolescence costs and R is the recovery cost.

It is important for a business to calculate its carrying costs for estimating the profit that can be made from the current inventory. It also helps them to determine whether to increase or decrease production in order to maintain the desired level of profit. The carrying cost constitutes for a major percentage of inventory value and is an essential cost factor.

References for Carried Interest

Academic Research for Carried Interest

  • Distribution strategies that minimize transportation and inventory costs, Burns, L. D., Hall, R. W., Blumenfeld, D. E., & Daganzo, C. F. (1985). Operations Research, 33(3), 469-490. This paper aims to solve the distribution problems by developing an analytic method that minimizes the cost of distributing by truck. Direct shipping and peddling, these two distribution strategies are analyzed and compared and formulas for transportation and inventory costs are derived. The formulas simplify the calculation and provide accuracy. The formulas help in quickly computing the cost trade-off with a hand calculator. It facilitates the sensitivity analysis indicating the effect of parameter value changes on the costs and operating strategies.
  • Optimum production lot size model for a system with deteriorating inventory, MISRA, R. B. (1975). The International Journal of Production Research, 13(5), 495-505. The paper attempts to develop a production lot size model for an inventory system dealing with deteriorating items. It suggests a numerical method where the deterioration rate is varying as the paper finds it impossible to obtain a simple expression for the production lot size in such cases. The approximate expression for the production lot size is derived for the cases of a constant rate of deterioration. The impact of deterioration is explained through a numerical expression.
  • A note on optimal inventory management under inflation, Misra, R. B. (1979). Naval Research Logistics Quarterly, 26(1), 161-165. A discounted-cost model for inventory management is proposed in the paper. The proposed model is similar to the classical economic order quantity model, but the inflation rates and parameters of the inventory system are included. The effects are illustrated through a numerical problem.
  • Survey of literature on continuously deteriorating inventory models, Raafat, F. (1991). Journal of the Operational Research society, 42(1), 27-37. It is a complete survey of published literature on continuously deteriorating inventory models. It focusses on the papers where the effect of deterioration is considered as a function of the on-hand level of inventory. The paper makes some suggestions for future research and presents a classification scheme.
  • Stock replenishment and shipment scheduling for vendor-managed inventory systems, Çetinkaya, S., & Lee, C. Y. (2000). Management Science, 46(2), 217-232. An analytical model to coordinate inventory and transportation decisions in Vendor-managed Inventory system is proposed in this paper. The paper considers a case where the vendor receives random orders from a group of retailers located in the same geographical area. The paper argues, as the vendor has the autonomy of holding the orders until an agreed dispatch time with an expectation to receive more order from that region, the shipment-release policy partially affects the inventory requirements. The optimum replenishment quantity and dispatch frequency are calculated simultaneously and a renewal theoretic model for the case of Poisson demands is developed.
  • EOQ models with general demand and holding cost functions, Goh, M. (1994). European Journal of Operational Research, 73(1), 50-54. The paper considers the single item inventory system in the retail sector where the demand rate depends on the existing inventory level. It keeps the traditional parameter of the replenishment cost as constant but allows variation in the carrying cost per unit. Two possibilities of variation are considered in this case: a non-linear function of the duration of the time it is held in the inventory and a non-linear function of the volume of on-hand inventory. Optimal policies and decision rules are found in the paper.
  • Economic order quantities with inflation, Buzacott, J. A. (1975). Journal of the Operational Research Society, 26(3), 553-558. The paper establishes that with inflation, the pricing policy affects the choice of the inventory carrying charge used in the EOQ formula. It argues the inventory charge should remain low and independent of the inflation rate if the prices change independently of replenishment order timing. However, the carrying charge is high and dependent on the inflation rate and the mark-up, if the company uses constant percentage mark-up and “double ticketing” is not allowed.
  • EOQ under inspection costs, Schwaller, R. L. (1988). Production and Inventory Management Journal, 29(3), 22. This article analyses the limitation of the classical EOQ model and discusses the EOQ under the inspection cost.
  • Financial implications of lot-size inventory models, Beranek, W. (1967). Management Science, 13(8), B-401. This paper argues the financial environment must be taken into consideration while developing a model to determine the optimal inventory and optimal means of financing the inventory. It provides examples to illustrate the procedure of developing such models under different financial circumstances. The results of such procedures are compared to the results derived from the application of the standard lot-size model to indicate the savings in inventory cost. This is especially true for the companies dealing with several different products or with single product involving a large commitment of resources.
  • Dynamic version of the economic lot size model, Wagner, H. M., & Whitin, T. M. (1958). Management science, 5(1), 89-96. The paper provides a forward algorithm as a dynamic version of the economic lot size model. It allows the possibility of demands for a single item, inventory holding charges, and setup costs to vary over N period. The paper attempts to derive a minimum total cost inventory management scheme that satisfies known demand in every period. The necessity of acquiring data for the full N periods is eliminated in this model that disjoints planning horizons.
  • Inventory models involving lead time as a decision variable, Ben-Daya, M. A., & Raouf, A. (1994).Journal of the Operational Research Society, 45(5), 579-582. This paper discusses the inventory models considering lead time as one of the decision variables. The paper argues, while addressing the issues of the inventory, most of the literature assumes that the lead time is prescribed, either deterministic or probabilistic. However, the lead time can be reduced at an added cost under certain circumstances.

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