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The major advantage of having more suppliers is the fact that it brings about competition between these suppliers.

Suppliers
Should a firm attempt to have fewer or more suppliers? What are the advantages and disadvantages of each approach? Your initial post should be 200-250 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 2017). 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, 104, 145-155.
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 (2013; 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 200-250 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 2001-2011

Year
Mergers
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

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    37,649.56


MSE = 37,649.56 / 7 = 5,378.51
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 = 192.3

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                         366       36          3,721
2006    7                           83                         581       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
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
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
52.6
61
61-52.6=8.4
(8.4)2=70.56
2006
55.6
83
83-55.6=27.4
(27.4)2=750.76
2007
63
123
123-63=60
(60)2=3,600
2008
75.2
97
97-75.2=21.8
(21.8)2=475.24
2009
85.6
186
186-85.6=100.4
(100.4)2=10,080.16
2010
110
225
225-110=115
(115)2=13,225
2011
142.8
240
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
Coded Value for Year (X)
Mergers (Y)
XY
X2
Y2
2000
1
46
46
1
2,116
2001
2
46
92
4
2,116
2002
3
62
186
9
3,844
2003
4
45
180
16
2,025
2004
5
64
320
25
4,096
2005
6
61
366
36
3,721
2006
7
83
581
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
Total
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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