operations management:Forecasting

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wreelwe

Business Finance

Description

Purpose of Assignment

The purpose of this assignment is for students to learn how to apply Operations Forecasting.

Assignment Steps

Resources: Use Microsoft® Excel® to do the forecast.

The instructor will provide information and data for this assignment.

Assignment:

1. Write a brief APA paper to analyze and comment on the forecasting system being used by Fork and Hoe. Suggest changes or improvements that you believe are justified. Include a response to question 6 after you have completed the year 5 forecast.

2. Determine if the 4 years of demand data indicate an ANNUAL trend.

3. Determine if the 4 years of demand data indicates MONTHLY seasonality. If so, illustrate how you make the adjustments to your year 5 forecast.

4. Develop an ANNUAL forecast for bow rakes for year 5. Develop a MONTHLY forecast for each month of year 5. Justify your forecast by showing your work.

5. Include an Excel spread sheet with the paper to illustrate the details of your forecasting method.

6. Determine if your year 5 forecast will correct the problems that plague Fork and Hoe..

Format your assignment consistent with APA guidelines.

Click the Assignment Files tab to submit your assignment.

Unformatted Attachment Preview

month Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec 1 55220 57350 15445 27776 21408 17118 18028 19883 15796 53665 83269 72991 2 39875 64128 47653 43050 39359 10317 45194 46530 22105 41350 46024 41856 Years 3 32180 38600 25020 51300 31790 32100 59832 30740 47800 73890 60202 55200 4 62377 66501 31404 36504 16888 18909 35500 51250 34443 68088 68175 61100 Case –Fork and Hoe The Fork and Hoe Company is a leading producer of garden tools ranging from wheelbarrows, mortar pans, and hand trucks to shovels, rakes, and trowels. The tools are sold in four different product lines ranging from the top-of-the-line Hercules products, which are rugged tools for the toughest jobs, to the Garden Helper products, which are economy tools for the occasional user. The market for garden tools is extremely competitive because of the simple design of the products and the large number of competing producers. In addition, more people are using power tools, such as lawn edgers, hedge trimmers, and thatchers, reducing demand for their manual counterparts. These factors compel the company to maintain low prices while retaining high quality and dependable delivery. Garden tools represent a mature industry. Unless new manual products can be developed or there is a sudden resurgence in home gardening, the prospects for large increases in sales are not bright. Keeping ahead of the competition is a constant battle. No one knows this better than Alan Roberts, president of the Fork and Hoe Company. The types of tools sold today are, by and large, the same ones sold 30 years ago. The only way to generate new sales and retain old customers is to provide superior customer service and produce a product with high customer value. This approach puts pressure on the manufacturing system, which has been having difficulties lately. Recently, Roberts has been receiving calls from long-time customers, such as Sears and Tru-Value Hardware Stores, complaining about late shipments. These customers advertise promotions for garden tools and require on-time delivery. Roberts knows that losing customers like Sears and Tru-Value would be disastrous. He decides to ask consultant, Sharon Place, to look into the matter and to report to him in one week. Roberts suggests that she focus on the bow rake as a case in point because it is a high-volume product and has been a major source of customer complaints of late. Planning Bow Rake Production A bow rake consists of a head with 14 teeth spaced one inch apart, a hardwood handle, a bow that attaches the head to the handle, and a metal ferrule that reinforces the area where the bow inserts into the handle. The bow is a metal strip that is welded to the ends of the rake head and bent in the middle to form a flat tab for insertion into the handle. The rake is about 64 inches long. The consultant, Sharon Place, decides to find out how the Fork and Hoe company plans rake production. She goes straight to the production manager, Phil Stanton, who gives her the following account: Planning is informal around here. To begin, marketing determines the forecast for bow rakes by month for next year. Then they pass it along to me. Quite frankly, I think the forecasts are usually inflated – must be their big egos over there. I have to be careful because we enter into long-term purchasing agreements for steel, and having it just sitting around is expensive. So, I usually reduce the forecast by 10 percent or so. I use the modified forecast to generate a monthly final assembly schedule, which determines what I need to have from the forging and woodworking areas. The system works well if the forecasts are good. But when marketing comes to me and says they are behind on customer orders, as they often do near the end of the year, it wreaks havoc with the schedules. Forging gets hit the hardest. For example, the presses that stamp the rake heads from blanks of steel can handle only 7000 heads per day, and the bow rolling machine can only do 5000 per day. Both operations are also required for many other products. The marketing department provides crucial forecast information to the production department, so Sharon Place decides to see the marketing manager, Ron Adams. He explains how he arrives at the bow rake forecasts. Things do not change much from year to year. Sure, sometimes we put on a sales promotion of some kind, but we try to give production enough warning before the demand kicks in – usually a month or so. I meet with several managers from the various sales regions to go over shipping data from last year and discuss anticipated promotions, changes in the economy, and shortages we experienced last year. Based on these meetings, I generate a monthly forecast for the next year. Even though we take a lot of time getting the forecast, it never seems to avoid customer problems. The Problem The consultant, Sharon Place, ponders the comments from Phil Stanton in production and from Ron Adams in marketing. She understands Stanton’s concerns about costs and keeping inventory low. She understands Adam’s concerns about having enough rakes on hand to make timely shipments. Both are also somewhat concerned about capacity. Yet, she decides to check actual customer demand for the bow rake over the past four years before making her final report to Alan Roberts, president of The Fork and Hoe. Four-Year Demand History for the Bow Rake Forecast for year 5 Demand (in units) Month Year 1 Year 2 Year 3 Year 4 1 55220 39875 32180 62377 2 57350 64128 38600 66501 3 15445 47653 25020 31404 4 27776 43050 51300 36504 5 21408 39359 31790 16888 6 17118 10317 32100 18909 7 18028 45194 59832 35500 8 19883 46350 30740 51250 9 15796 22105 47800 34443 10 53665 41350 73890 68088 11 83269 46024 60202 68175 12 72991 41856 55200 61100 Year 5 Assignment: 1. Write a brief APA paper to analyze and comment on the forecasting system being used by Fork and Hoe. Suggest changes or improvements that you believe are justified. Include a response to question 6 after you have completed the year 5 forecast. 2. Determine if the 4 years of demand data indicate an ANNUAL trend. 3. Determine if the 4 years of demand data indicates MONTHLY seasonality. If so, illustrate how you make the adjustments to your year 5 forecast. 4. Develop an ANNUAL forecast for bow rakes for year 5. Develop a MONTHLY forecast for each month of year 5. Justify your forecast by showing your work. 5. Include an Excel spread sheet with the paper to illustrate the details of your forecasting method. 6. Determine if your year 5 forecast will correct the problems that plague Fork and Hoe.. Four-Year Demand History for the Bow Rake Forecast for year 5 Demand (in units) Month Year I Year 2 Year 3 Year 4 1 55220 39875 321 80 62377 2 57350 64128 38600 66501 J 15445 47653 25020 31404 aA 27776 43050 5 1300 36544 5 21448 39359 31790 16888 6 171 18 t03t7 32100 18909 7 18028 45194 59832 35500 8 19883 46350 30740 s1250 9 t5796 22rc5 47800 34443 10 53665 41350 73890 11 83269 46024 60202 68175 12 72991 41 856 55200 61 100 Year 5 Assignment: l. Write a brief APA paper to analyze and comment on the forecasting system being used by Fork and Hoe. Suggest changes or improvements that you believe are justified. Include a response to question 6 after you have completed the year 5 forecast. 2. Determine if the 4 years of demand data indicate an ANNUAL trend. 3. Determine if the 4 years of demand data indicates MONTHLY seasonality. make the adjustments to your year 5 forecast. If so, illustrate how you 4. Develop an ANNUAL forecast for bow rakes for year 5. Develop a MONTHLY forecast for each month of year 5. Justifu your forecast by showing your work. 5. Include an Excel spread sheet with the paper to illustrate the details of your forecasting method. rruE.. I'rrrr\ d.rru Llrdr plague and Hoe. year 5 J forecast [UrgUASt will Wlil UUTI(iUL correct the Llrtr problems 6. Determine il. your yUUt yEi.t EtEIIIilIItr if PruurrrlrrJ that PI46tIE Fork ?q qsi -L'Ji o#5*,. ,zyhib it I b3 , -. t t''c "":bT h tt\ o'l SeVchw h'-t\d'l-
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Explanation & Answer

Kindly see attached files with the requested forecast and the analysis of the case studyI've included both a word and a pdf version in case you have any problem when trying to read the equations used

Running head: THE FORK AND HOE COMPANY CASE STUDY

The Fork and Hoe Company Case Study
(Name)
(Course)
(Date)

1

THE FORK AND HOE COMPANY CASE STUDY
The Fork and Hoe Company Case Study
Background information
The Fork and Hoe Company is a company selling manual gardening tools. The manager
of the company tries to optimize the company’s sales and overcome the current trend according
to which most of the customers are moving towards automatic gardening machines. In order not
to loose more clients, it is of utmost importance that the company is sure of avoiding stock outs
as much as possible. This is especially critical considering the high competition existing in the
gardening industry.
For this purpose, the company has evaluated the past monthly demands in the last four
years. In order to minimize inventory costs while avoiding stock outs, the company plans the
production of gardening tools according to the forecasted demand for the next year taking into
account the data of the past four years.
Do the demand of the four years indicate an annual trend?
Even while the provided dataset does not directly provide information about an annual
trend in the demand for the bow rake, this can be estimated by calculating the annual demand
over the past four years adding up the monthly demand for the different months as indicated in
table 1. The average monthly demand, on the other hand, has been estimated by dividing the
annual demand by 12.

2

THE FORK AND HOE COMPANY CASE STUDY

3

Table 1. Calculation of the annual demand and yearly average monthly demand
Month
January
February
March
April
May
June
July
August
September
October
November
December
ANNUAL
Average monthly
demand

Year 1
55220
57350
15445
27776
21408
17118
18028
19883
15796
53665
83269
72991
457949
38162

Year 2
39875
64128
47653
43050
39359
10317
45194
46530
22105
41350
46024
41856
487441
40620

Year 3
32180
38600
25020
51300
31790
32100
59832
30740
47800
73890
60202
55200
538654
44888

Year 4
62377
66501
31404
36504
16888
18909
35500
51250
34443
68088
68175
61100
551139
45928

As can be observed from the computed annual demand, it presents an increasing trend
over the four-year period considered. According to the graph presented in figure 1, it seems that
the annual demand increased by approximately 33,000 annually.

Figure 1. Annual demand trend

THE FORK AND HOE COMPANY CASE STUDY
Is there a monthly seasonality in the demand for bow rakes?
Figure 2 represents the monthly demand of bow rakes for the different years. As can be
observed from the graph, the demand during the months October – February seems to be higher
than that during the months March – September. This trend is observed for all the four years
during which the company has recorded the monthly demand of bow rakes.

Figure 2. Seasonal variation in the demand of bow rakes
Taking this into account, an average annual seasonality factor has been calculated by:


Estimating the seasonality factor by dividing the monthly demand by the average
monthly demand for each of the twelve months in the four years



Evaluating the average of the seasonality factors for each month taking into account the
values computed for each year
As an example, the following equation shows the estimation of the average seasonality

factor for the month of January:
𝑆𝐽𝑎𝑛,𝑦𝑒𝑎𝑟 1 =

55220
= 1.447
38162

4

THE FORK AND HOE COMPANY CASE STUDY

𝑆𝐽𝐴𝑁𝑈𝐴𝑅𝑌 =

𝑆𝐽𝑎𝑛,𝑦𝑒𝑎𝑟 2 =

39875
= 0.982
40620

𝑆𝐽𝑎𝑛,𝑦𝑒𝑎𝑟 3 =

32180
= 0.717
44888

𝑆𝐽𝑎𝑛,𝑦𝑒𝑎𝑟 4 =

62377
= 1.358
45928

5

1.447 + 0.982 + 0.717 + 1.358
= 1.126
4

Table 2 summarizes the results calculated for the seasonality factors for years 1-4 and the
resulting average seasonality factor for each month.
Table 2. Seasonality factors
Month
January
February
March
April
May
June
July
August
September
October
November
December

Year 1
1.447
1.503
0.405
0.728
0.561
0.449
0.472
0.521
0.414
1.406
2.182
1.913

Year 2
0.982
1.579
1.173
1.060
0.969
0.254
1.113
1.145
0.544
1.018
1.133
1.030

Year 3
0.717
0.860
0.557
1.143
0.708
0.715
1.333
0.685
1.065
1.646
1.341
1.230

Year 4
1.358
1.448
0.684
0.795
0.368
0.412
0.773
1.116
0.750
1.482
1.484
1.330

AVERAGE
1.126
1.347
0.705
0.931
0.651
0.457
0.923
0.867
0.693
1.388
1.535
1.376

The computed average seasonality factors confirm the previous observation according to
which demand for bow rakes is higher in the period from October to February and lower from
March to September.
Forecasts of the monthly and annual demand for next year
Figure 1 showed that the demand for bow rakes increased following a nearly linear
model. This result has been used in the forecast of the annual demand for this year. Hence,

THE FORK AND HOE COMPANY CASE STUDY

6

substituting in the regression equation Year = 5, the forecasted annual demand would be of
Demand = 33078 * 5 + 426100 = 591,490 bow rakes.
Taking this value into account, the monthly average demand for next year would be of
591,490/12 = 49,291 bow rakes. This value can then be used in the estimation of the monthly
demand for each of the months by considering the computed average seasonality factors
summarized in table 2. As an example, the monthly forecasted demand for January would be:
𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡𝑒𝑑 𝑑𝑒𝑚𝑎𝑛𝑑𝐽𝑎𝑛𝑢𝑎𝑟𝑦,𝑌𝑒𝑎𝑟 5 = 𝑆𝐽𝐴𝑁𝑈𝐴𝑅𝑌 ∗ 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑚𝑜𝑛𝑡ℎ𝑙𝑦 𝑑𝑒𝑚𝑎𝑛𝑑𝑌𝑒𝑎𝑟 5
𝐹𝑜𝑟𝑒𝑐𝑎𝑠𝑡𝑒𝑑 𝑑𝑒𝑚𝑎𝑛𝑑𝐽𝑎𝑛𝑢𝑎𝑟𝑦,𝑌𝑒𝑎𝑟 5 = 1.126 ∗ 49,291 = 55,497
The computed forecasted demands for the different months is summarized in table 3.
Month

Year 1

Year 2

Year 3

Year 4

January
February
March
April
May
June
July
August
September
October
November
December
Annual

55220
57350
15445
27776
214...


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