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Should a firm attempt to have fewer or more suppliers? What are the advantages and disadvantages of each approach? Your initial post should be

2

00-2

5

0 words.

Guided Response:

 

Respond to at least two of your classmates’ posts in a substantive manner. Some ways could include examples, current events, and/or possible outcomes.

Respond to

Lemeshia Spears

post

The major advantage of having more suppliers is the fact that it brings about competition between these suppliers. Competition among the suppliers is beneficial to the company seeking supplies because chances are higher of getting better deals, which includes lower prices as the suppliers try to outdo each other (Bohner & Minner 20

1

7

). However, having more suppliers has its disadvantages. One of them is the fact that a company with multiple suppliers will buy smaller volumes from different suppliers as compared to buying a considerable supply volume from one supplier. This takes away the economies of scale the company would enjoy if it bought a huge supply volume from one or a few suppliers.

        The major advantage of having a single or few suppliers is based on economies of scale. When a company is partnering with one or few suppliers, it gets huge volumes of supplies from these suppliers; therefore, the company can benefit in discounts, tailored service delivery, and the orders from that company are taken seriously by the supplier, on the other hand, has one or few suppliers could be disadvantageous. In case the production chain of the supplier who is being depended on is broken, the company in question could face difficulties trying to find another supplier in a fixed period of time.

Reference

Bohner, C., & Minner, S. (2017). Supplier selection under failure risk, quantity and business volume discounts. Computers & Industrial Engineering,

10

4

, 1

45

-155.

Respond to

Peggy Harvey

post

      Whether it is better for a company to have fewer or more suppliers depends specifically on the individual company and what works best for them. Some benefit from having fewer suppliers and some benefit from having more suppliers. According to our text  Operations mangement (201

3

; sec 5.4) when company’s use many suppliers it allows them to take advantage of the completion among those suppliers depending on which one performs and provides the best. The text also references having only a few suppliers or even one supplier , and how these partnerships encourage closer relationships among the two.

      As we know there are always disadvantages to consider when making business choices and interactions. When considering using several suppliers company’s would have to be concerned with not being able to fulfill the requirements needed by so many suppliers. For instance each supplier may have require that they provide a specific amount of services for the company per month. Depending on how business flow is, the company may have difficulties meeting such demands. However the likely disadvantage to using a fewer number of suppliers is the limits that are placed on the company in reference to their available options in the event that their suppliers cannot meet the company demand. Company’s would better benefit for having back up options for suppliers to ensure that they can always meet the demand of their consumers.

              

                                                                 

References

:

Vonderembse, M. A., & White, G. P. (2013). 

Operations management

 [Electronic version]. Retrieved from https://content.ashford.edu/

Forecasting Methods

Read Problem

6

in Chapter 6 of your textbook. Calculate and answer parts a through d. Include all calculations and spreadsheets in your post.

Explain why the moving average method was used instead of another forecasting method.

What might be another forecasting method that could prove to be just as useful?

Your initial post should be 200-

25

0 words.

Guided Response: Respond to at least two of your classmates’ posts to identify some of their recommended forecasting methods. Give additional advice and alternative solutions that might be used as well.

Respond to

Peter Sawyer

post

Below shows the number of mergers by year that took place in the Savings and Loan industry from

2001

20

11

 

Year

Mergers

46

Year

Mergers

2000

46

2006

8

3

2001

2007

12

3

2002

62

2008

9

7

2003

45

2009

186

2004

64

2010

225

2005

61

2011

240

 

The calculation below shows a 5-year moving average that will forecast the number of mergers in 2012

 

Ƒ2012 = (123+

97

+186+225+240)/5 = 174.2

 

The calculation below determines the forecast for 2005 – 2011.

 

Ƒ2005 = (64+45+62+46+46)/5 =

52.6

Ƒ2006 = (61+64+45+62+46)/5 =

55.6

Ƒ2007 = (83+61+64+45+62)/5 =

63

Ƒ2008 = (123+83+61+64+45)/5 =

75.2

Ƒ2009 = (97+123+83+61+64)/5 =

85.6

Ƒ2010 = (186+97+123+83+61)/5 =

110

Ƒ2011 = (225+186+97+123+83)/5 =

142.8

 

Year     Actual     Forecasted     Error     Squared          

2005     61           52.6                8.4        70.56

2006    83           55.6                27.4      750.76

2007    123          63                   60         3,600

2008    97            75.2                21.8      475.24

2009    186          85.6               

100

.4    10,080.

16

2010    225          110                 115       13,225

2011    240          142.8              97.2      9,447.84

Total

                                         

430.2

   

37,6

49

.56

 
 

MSE = 37,649.56 / 7 = 5,3

78

.51

MAD = 430.2 / 7 = 61.46

 

The below calculation shows a 5-year weighted average that forecasts the number of mergers for 2012

 

Ƒ2012 = (.30)240+ (.25)225+ (.20)186+ (.15)97+ (.10)123

= 72+56.25+37.2+14.55+12.3 = 1

92

.3

 

Below regression analysis was used to forecast the number of mergers in 2012

 

Year     Coded Value   Mergers           

XY

         

X2

         

Y2

for Year            

2000    1                           46                         46          1           

2,116

2001    2                           46                         92          4            8,464

2002    3                           62                         186       9           

3,844

2003    4                           45                        

180

       16         

2,025

2004    5                           64                        

320

       25         

4,096

2005    6                           61                        

36

6

       36         

3,721

2006    7                           83                        

5

81

       49         

6,889

2007    8                           123                     

984

       64         

15,129

2008    9                           97                        

873

       81         

9,409

2009    10                         186                     

1,860

   100      

34,596

2010    11                         225                     

2,475

  

121

      

50,625

2011    12                         240                     

2,880

  

144

      

57,600

SUM     78                        

1,278

                 

10,843

             

650

       198,514

 
 

Ƅ = 12(10,843) – 78(1,278) / 12(650) – 782

= 130,116 – 99,684 / 7,800 – 6,084

= 30,432 / 1,716

= 17.73

a = 1,278/12 – 17.73(78)/12

= 106.5 – 115.25

= -8.75

r = 12(10,843) – 78(1,278) / √{12(650)-782}{12(198,514)-1,2782}

= 130,116-99,684/√{7,800-6,084}{2,382,168-1,633,248}

= 130,116-99,684/√(1,716)(748,920)

= 30,432/√1,285,146,720

= 30,432/35,848.94

= 0.85

              

The moving average method was used due to the ease of calculating data from a number of sources. It can take specific timelines and have a more even and precise prediction on numbers.

References

Vonderembse, M. A., & White, G. P. (2013). Operations management [Electronic version]. Retrieved from https://content.ashford.edu/

Respond

Maria Harosullivan

post

Explain why the moving average method was used instead of another forecasting method.

The number of merger data has large peaks and valleys.  The use of moving average method is used to smooth out the most recent period to project the next time period, Vonderembse, M. A., & White, G. P. (2013). 

What might be another forecasting method that could prove to be just as useful?

According to Vonderembse there are of forecast methods for a firm to choose.  A forecast is a prediction of the future, Vonderembse, M. A., & White, G. P. (2013). Regression analysis is another method to forecast both time-service and cross-sectional data.

The figures below indicate the number of mergers that took place in the savings and loan industry over a 12-year period.

Year

Mergers

2000

46

2006

83

2001

46

2007

123

2002

62

2008

97

2003

45

2009

186

2004

64

2010

225

2005

61

2011

240

Year Mergers

2012. Calculate a 5-year moving average to forecast the number of mergers for 2012.

Moving Average forecasting formula

Ƒ2012 = (123+97+186+225+240)/5 = 174.2

 

2011. Use the moving average technique to determine the forecast for 2005 to 2011. Calculate measurement error using MSE and MAD.

Ƒ2005 = (46+46+62+45+64)/5 = 52.6

Ƒ 2006 = (46+62+45+64+61)/5 = 55.6

Ƒ 2007 = (62+45+64+61+83)/5 = 63.0

Ƒ 2008 = (45+64+61+83+123)/5 = 75.2

Ƒ 2009 = (64+61+83+123+97)/5 = 85.6

Ƒ 2010 = (61+83+123+97+186)/5 = 110.0

Ƒ 2011 = (83+123+97+186+225)/5 = 142.8

Year                           Moving Average       Actual           Error                          Squared Error

2005

61

2006

83

2007

123

2008

97

2009

186

2010

225

2011

240

 

 

52.6

61-52.6=8.4

(8.4)2=70.56

55.6

83-55.6=27.4

(27.4)2=750.76

63

123-63=60

(60)2=3,600

75.2

97-75.2=21.8

(21.8)2=475.24

85.6

186-85.6=100.4

(100.4)2=10,080.16

110

225-110=115

(115)2=13,225

142.8

240-142.8=97.2

(97.2)2=9,447.84

Total 430.2 37,649.56

 

MSE = 37,649.56/7 = 5,378.51

MAD = 430.2/7 = 61.46

2012. Calculate a 5year weighted moving average to forecast the number of mergers for 2012. Use weights of 0.10, 0.15, 0.20, 0.25, and 0.30,with the most recent year weighted being the largest.

0.10(123)+0.15(97)+0.20(186)+0.25(225)+0.30(240) = 192.3

 

2012. Use regression analysis to forecast the number of mergers in 2012.

 

Year

2000

46

46

1

2001

46

2,116

2002

62

186

2003

4

45

2004

64

2005

61

2006

83

2007

123

64

2008

9

97

2009

186

2010

225

2011

240

Total

Coded Value for Year (X)

Mergers (Y)

XY X2 Y2
1 2,116
2 92 4
3 9 3,844
180 16 2,025
5 320 25 4,096
6 366 36 3,721
7 581 49 6,889
8 984 15,129
873 81 9,409
10 1,860 100 34,596
11 2,475 121 50,625
12 2,880 144 57,600
78 1,278 10,843 650

192,166

 

b = 12 (10,843) – 78 (1,278) / 12 (650) – 782

b= 130,116 – 99,684 / 7,800 – 6.084

b= 30,432/1,716

b= 17.73

 

a= 1,278   – 17.73(78)

       12            12

a= 106.5 – 115.25

a=-8.75

 

Ye= -8.75 + 17.73 (13)

Ye= 221.74

Thus, the projection of mergers is 221.7

 
Reference

Vonderembse, M. A., & White, G. P. (2013). 
Operations management
 [Electronic version]. Retrieved from https://content.ashford.edu/

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