Department

EconomicsCourse Code

ECON 438Professor

erics jhonsonStudy Guide

FinalThis

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SAYED M. IRFAN | M.Engg. (Industrial Engineering) / Certified Supply Chain Design Analyst, MIT

NEEDLESS MAKEUP INVENTORY PROBLEM

November 13, 2016

Question:

Needless Markup (NM), a famous "high end" department store, must decide on the quantity of a

high-priced woman's handbag to procure in Spain for the coming Christmas season. The unit cost of

the handbag to the store is $28.50 and the handbag will sell for $150.00. Any handbags not sold by

the end of the season are purchased by a liquidator for $10.00 each. In addition, the store

accountants estimate that there is a cost of $0.40 for each dollar tied up in inventory, as this dollar

invested elsewhere could have yielded a gross profit. Assume that this cost is attached to unsold

bags only.

Answer the following questions:

1. Due to the long distance and limited capacity, NM must place the order 6 months in advance. A

detailed analysis of past data shows that if forecasting 6 month in advance, the number of bags

sold can be described by a normal distribution, with mean 150 and standard deviation 60. What is

the optimal number of bags to purchase?

2. What is the expected cost of mismatch under the optimal purchase quantity? What is the optimal

expected profit?

3. Another supplier in the US, offers the same product but at a higher price of $35 due to its higher

production cost. For this supplier, NM only needs to place the order 3 months in advance which

results in a much better forecast. Past data shows if ordering 3 months in advance, the number

of bags sold can be described by a normal distribution, with mean 150 and standard deviation 20.

Which supplier should NM choose?

Let us first establish the required data attributes for implementing the procedure. The relevant

terms, therefore, are:

• Selling price, p = $150

• Cost, c = $28.50

• Cost of holding and disposal, h = $0.40

• Salvage value, s = $10

Now, the underage and overage costs and the critical ratio can be computed as:

• Cu = (p – c) = 150− 28.50 = 121.5

• Co = (c + h – s) = 28.5 + 0.40 – 10 = 18.9

• Critical Ratio = 121.5 / (121.5 + 18.9) = 0.865

At the optimal order quantity, the probabilities of marginal expected costs and benefits (profits) of

ordering the Qth unit are equal. The critical ratio, in effect, implies that probability. Therefore, we

need to find the point in our demand distribution that corresponds to the cumulative probability

equal to the critical ratio. Using the NORMSINV function to get the number of standard deviations,

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