Sport Obermeyer Case

Topics: Supply and demand, Economics, Price Pages: 6 (1324 words) Published: February 18, 2015
Sport Obermeyer case (Venugopal Vinjamuri and Kailash Kothari) In order to determine the quantity of each product that should be purchased at the outset so as to fill half of the total forecasted volume (10,000 units), we need to calculate the purchase price per product (something that isn’t provided in the case) and also the salvage price per product. Let’s start with the cost information of the Rococo Parka. The cost to produce one piece in Hong Kong is $60.08 while the cost in China is $51.92. On the lines of Wally’s plan, let’s assume that half the orders will be fulfilled from Hong Kong and the rest from China. This places the average cost at $56. The total retail price of 112.5$ should equal the sum of cost ($56), profit ($27 as mentioned in the case) and operating expenses (expenses to run the company besides the cost of sourced products). This gives us a figure of $29.5 as the average operating cost, which is about 26% of wholesale price. We’ll apply this percentage across the board to arrive at purchase price per product (Exhibit 1). We’ll also arrive at the salvage price as product cost + operating costs – loss ($9 as mentioned in the case). The mean and std. deviation figures have been provided and it this point, arriving at production quantity per product is a trivial exercise (see results in Exhibit 2), using the template provided in class. Note that increments of 100 have been used.

If this were single sourced to Hong Kong (Question 2), the cost figures as the relate to Hong Kong would be used ($60.08 for the Rokoko Parka). Please see Exhibit 3. Also, since the minimum order quantity is 600, this would be used as the starting point during quantity calculations (Exhibit 4). The approach basically compares the marginal benefit associated with each product in an iterative manner, always incrementing quantities of the products with the highest marginal benefit (note that our excel template compares three products at a time rather than all ten, so multiple products may be incremented for quantity with each iteration). The idea is that, the marginal benefit of a specific product reduces as more of that product is ordered. Thus after every iteration, a new product may have the highest marginal benefit. The marginal benefit represents how attractive or unattractive a certain product is, given its price, salvage value in case of overstock, forecasted demand and demand volatility as compared to the other products. This is clearly a less desirable scenario than the previous one where no minimum quantities were required.

If the entire order were instead fulfilled using the Chinese manufacturing capacity, the calculation is greatly simplified. Since a minimum of 1200 pieces of each product must be ordered at a time, we would simply order that minimum resulting in a total of 12,000 units. This illustrates, how ordering from China can be very constrained under relatively low order volumes. Responding to volatile market demand can be difficult with the Chinese supply chain model. Of course, there would be a cost benefit due to economies of scale (only if those can be reliably predicted), but higher minimum order quantities along with quota restrictions make it hard to fine tune sourcing decisions during times of uncertainty. While quantifying the measure of risk we followed the following methodology: The first row gives the number of orders to be placed. As the case suggests, the 2*S.D is the number which is being considered by Wally while looking at the variability in the demand. So we calculated the high demand which is the addition of mean demand and 2*S.D and so the understock is calculated by subtracting number of orders with high demand. Low demand is calculated by subtracting the mean demand with (2*S.D) and then subtracting the number of orders with the low demand gives us the overstock. The case gives us the cost of overstock and understock which are 9$ and 27$ respectively, so we just calculated the total...
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