Running Head: CASE STUDY
Expansion Strategy and Establishing a Re-Order Point
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CASE STUDY
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Case 1: Bell Computer Company
The Bell Computer Company has only two options of carrying out the expansion. The
two options are the large scale and the medium scale. With the use of the options of expansion,
the medium scale expansion, and the large-scale expansion, the demands can either be high,
medium or low depending on the probability of 0.3, 0.5 and 0.2 respectively (Keeney, & Raiffa,
1993).
In the option of medium scale expansion, the profits may exist as follows in case of high,
medium and low demand, $200,000, $150,000 and $50,000 respectively. For the option of largescale expansion, the profits may appear as follows in case of high, medium and low, $300,000,
$100,000 and $0 respectively.
The current management is facing a tricky dilemma of whether to use the large-scale
expansion or medium scale expansion. The large-scale expansion has a high potential of
generating a higher amount of profits in case of experiencing a high demand. The large-scale
expansion will thus generate a lower profit than the medium scale expansion when in the case of
low and medium demand. During the low demand, the large-scale expansion will give out an
output result in nil profit. In this case, it’s clear that the large-scale expansion gets under a high
risk of the low scale expansion. The anticipated action value is thus the expected value in the
case. Generally, various possible outcomes come as a result of an action. In this case to every
action, we thus need to determine the main probability of occurrence for every outcome got from
the action (Keeney, & Raiffa, 1993).
CASE STUDY
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The value expected is thus calculated by using finding the product of every possible
outcome with their probability of occurrence and adding the all the values respectively so as to
come up with the best result. The expected value of large-scale expansion and medium scale
expansion will provide great help to the management when making a choice of the appropriate
option of expansion depending on the option that will result in the generation of a high amount
of profit (Keeney, & Raiffa, 1993).
The value expected for the two alternatives are expansion option of medium scale: $145
large scale expansion: $140 of the medium scale expansion. In this case, the medium scale
expansion alternative gives a higher expected value than the project of large scale expansion.
The expansion option of the medium scale is thus more preferred for the objectives of
maximizing the profit expected. By realizing that the value expected is not enough in taking an
informed decision it thus becomes an important role in recognizing how the profits may deviate
from the value expected (Iggulden, & Fields, 2001).
In this case and for this purpose is used since it’s more important in determining the how
far random values set has gone as they get spread to form the mean value. A variance is an
important tool for measuring the far the set of random values are spread from the mean value.
Therefore the higher the variance the far the random values are spread from the mean and
therefore the in the low variance is thus more desirable. As a VP I thus conclude by
recommending that it’s appropriate to use the medium scale expansion option because it gives a
high expected profit under a lower risk (Iggulden, & Fields, 2001).
CASE STUDY
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Case 2: Kyle Bits and Bytes
Kyle Bits and Bytes is a computing products retailer. The HP laser printer is Kyle’s
product that is the most popular. This product has an average weekly demand of 200 units with a
lead time of one week. The demand, in this case, is thus not constant but Kyle has made an
observation that the standard deviation is 30. Kyle needs to know the best time of placing an
order that involves a reordering of points and a level of inventory that shows that there is stock
out. In the case of Kyle failing to fulfill the order of stocking out is thus exposed unto the risk of
losing the sale and other additional sales (Iggulden, & Fields, 2001).
Kyle has thus set a maximum probability that’s more acceptable in stocking up in any
week to a rate of 6%. With such a target Kyle thus wants to understand what the re-order point
should be and the number of HP laser printers to bring in the stock. A special place in the stock
is left for placing the recorder products by Kyle Bits and Bytes in their business. The reorder
point is thus driven by the products demand in the market and therefore in this case products,
demand is variable and thus having a normal type of distribution. When a demand is variable it’s
always assumed to have, the demand has a normal form of distribution in the market and thus the
supply meets the appropriate quantity in the market (Iggulden, & Fields, 2001).
Average demand for the lead time is thus the sum of the daily average demand for an
appropriate number of days in the lead time period in the distribution. This can thus be calculated
by simply multiply the average demand in daily basis lead the lead time. The distribution
variance is therefore done by simply finding the sum of the daily variance with the actual number
of days in the lead time (Zhang, Wen, Guan, Kilper, Luo, & Wu, 2013).
CASE STUDY
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According to Taylor and Russell information, the reorder point is thus referenced by R=
dL + z × σ × √L. in this case the d is the daily average demand, L is the lead time, σ is thus the
standard deviation for the daily demand and z is the appropriate number of standard deviation
that’s corresponding to the service level probability (Zhang, Wen, Guan, Kilper, Luo, & Wu,
2013).
Now based in this case, Kyle Bits and Bytes has, d= 200/7 units, L= 7days and σ =30/7
and the maximum probability that’s accepted of stock out is only 6%. This, therefore, means that
the service level is 0.94 and in addition, the z-table is thus used in determining the appropriate
corresponding value of z and therefore, in this case, it is assumed to be 1.56. By following that
formula it will be very easy and possible to for Kelly to place a reorder of the products when the
inventory gets to the level of 218 units (Zhang, Wen, Guan, Kilper, Luo, & Wu, 2013).
CASE STUDY
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Reference
Iggulden, J., & Fields, K. (2001). U.S. Patent No. 6,256,378. Washington, DC: U.S. Patent and
Trademark Office.
Keeney, R. L., & Raiffa, H. (1993). Decisions with multiple objectives: preferences and value
trade-offs. Cambridge university press.
Simon, H. A. (1979). Rational decision making in business organizations. The American
economic review, 493-513.
Zhang, W., Wen, Y., Guan, K., Kilper, D., Luo, H., & Wu, D. O. (2013). Energy-optimal mobile
cloud computing under stochastic wireless channel. IEEE Transactions on Wireless
Communications, 12(9), 4569-4581.
Low
Demand Medium
High
Medium-Scale
Large-Scale
Expansion Profits
Expansion Profits
Annual
Annual
Profit
Profit
($1000s)
($1000s)
P(x)
P(x)
50
20%
0
20%
150
50%
100
50%
200
30%
300
30%
Expected Profit ($1000s)
Risk Analysis for Medium-Scale Expansion
Annual Profit
(x)
Probability
P(x)
(x - µ)2 (x - µ)2 * P(x)
Demand $1000s
(x - µ)
Low
50
20%
Medium
150
50%
High
200
30%
σ2 =
σ=
Risk Analysis for Large-Scale Expansion
Annual Profit
(x)
Probability
P(x)
(x - µ)2 (x - µ)2 * P(x)
Demand $1000s
(x - µ)
Low
0
20%
Medium
100
50%
High
300
30%
σ2 =
σ=
Case Study – Week 3 Individual Assignment
QNT/561 Version 9
Case Study – Bell Computer Company
The Bell Computer Company is considering a plant expansion enabling the company to begin production
of a new computer product. You have obtained your MBA from the University of Phoenix and, as a vicepresident, you must determine whether to make the expansion a medium- or large- scale project. The
demand for the new product involves an uncertainty, which for planning purposes may be low demand,
medium demand, or high demand. The probability estimates for the demands are 0.20, 0.50, and 0.30,
respectively.
Case Study – Kyle Bits and Bytes
Kyle Bits and Bytes, a retailer of computing products sells a variety of computer-related products. One of
Kyle’s most popular products is an HP laser printer. The average weekly demand is 200 units. Lead time
(lead time is defined as the amount of time between when the order is placed and when it is delivered) for
a new order from the manufacturer to arrive is one week.
If the demand for printers were constant, the retailer would re-order when there were exactly 200 printers
in inventory. However, Kyle learned demand is a random variable in his Operations Management class.
An analysis of previous weeks reveals the weekly demand standard deviation is 30. Kyle knows if a
customer wants to buy an HP laser printer but he has none available, he will lose that sale, plus possibly
additional sales. He wants the probability of running short (stock-out) in any week to be no more than 6%.
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