Henry Clements Car rental
Henry Clements Car Rental Agency Case Study
Embry-Riddle Aeronautical University
Henry Clements Car Rental Agency Case Study The purpose of this case study is to determine, utilizing quantitative methods, the recommendations that should be made to Henry Clements in regards to forecasting to help improve his business’ performance.
Table 1
3 Month Data
Week
1
2
3
4
5
6
7
8
9
10
11
12
Demand
126
200
243
167
132
211
243
1667
131
208
251
171
Table 2
Standard Cost
Product
Material
Labor
Overhead
Selling Price
W0075C
$33.00
$9.90
$23.10
$100.00
W0033C
$25.00
$7.50
$17.50
$80.00
W0005X
$35.00
$10.50
$24.50
$130.00
W0007X
$75.00
$11.25
$63.75
$175.00
From this data, as well as the data given on manufacturing methods and hours per method, a solution could be found utilizing the linear programming method of analysis. To analyze the data, the actual profit on each material was first calculated. This was done by taking the selling price and subtracting each cost associated with the given material. The results are $34.00 for the 75C, $30.00 for the 33C, $60.00 for the 5X, and $25.00 for the 7X. The next step was to determine how many constraints would be part of the analysis. There was determined to be 10 constraints in the analysis, 4 for the April orders, 4 for the manufacturing methods and 2 for the minimum orders promised by Vivian. With this data, the amount of each product to be produced to maximize profit for April could be determined. The results can be seen in Table 3.
Table 3
April Production
Product
Units
Backorder
Profit
Total Profit
W0075C
1100
300
$34.00
$37,400
W0033C
250
0
$30.00
$7,500
W0005X
0
1510
$60.00
$0.00
W0007X
600
516
$25.00
$15,000
Total Profit
$59,900
The data shows which product should be produced and which should not and also highlights the backorder amount of each product. In terms of bringing in temporary workers to help
Embry-Riddle Aeronautical University
Henry Clements Car Rental Agency Case Study The purpose of this case study is to determine, utilizing quantitative methods, the recommendations that should be made to Henry Clements in regards to forecasting to help improve his business’ performance.
Table 1
3 Month Data
Week
1
2
3
4
5
6
7
8
9
10
11
12
Demand
126
200
243
167
132
211
243
1667
131
208
251
171
Table 2
Standard Cost
Product
Material
Labor
Overhead
Selling Price
W0075C
$33.00
$9.90
$23.10
$100.00
W0033C
$25.00
$7.50
$17.50
$80.00
W0005X
$35.00
$10.50
$24.50
$130.00
W0007X
$75.00
$11.25
$63.75
$175.00
From this data, as well as the data given on manufacturing methods and hours per method, a solution could be found utilizing the linear programming method of analysis. To analyze the data, the actual profit on each material was first calculated. This was done by taking the selling price and subtracting each cost associated with the given material. The results are $34.00 for the 75C, $30.00 for the 33C, $60.00 for the 5X, and $25.00 for the 7X. The next step was to determine how many constraints would be part of the analysis. There was determined to be 10 constraints in the analysis, 4 for the April orders, 4 for the manufacturing methods and 2 for the minimum orders promised by Vivian. With this data, the amount of each product to be produced to maximize profit for April could be determined. The results can be seen in Table 3.
Table 3
April Production
Product
Units
Backorder
Profit
Total Profit
W0075C
1100
300
$34.00
$37,400
W0033C
250
0
$30.00
$7,500
W0005X
0
1510
$60.00
$0.00
W0007X
600
516
$25.00
$15,000
Total Profit
$59,900
The data shows which product should be produced and which should not and also highlights the backorder amount of each product. In terms of bringing in temporary workers to help