Case 1_Final Report

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CASE 1 : Yankee Fork and Hoe Company

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Question 1 : Comment on the forecasting system being used in Yankee. Suggest changes or improvements that you believe are justified.

According to the case, there are several weakness of current forecasting system that are needed some adjustment, we would like to comment on the main problems and the way of improvement below.

 Using only Qualitative analysis, instead of Quantitative analysis.

According to the marketing manager, Ron Adams explained on how he arrives at the forecast figures by meeting with managers from various sale regions to go over shipping data from last year. There was no mathematical technique explained in his calculation for the forecast. It seems that Adams has been using the Qualitative method rather than Quantitative method.

In qualitative method, Adams could gain advantages of quick forecast and experiences from each manager. However there are some disadvantages such as group-think and since he’s meeting with sale managers, the forecast tend to be overly inflated which related to Phil Stanton, production manager said that the forecasts are usually inflated and he usually reduce the forecast by 10 percent.

Our suggestion is that a quantitative method should implement here. This method is suitable for the existing products that have stable demand and historical data are provided. According to demand from last four years, it tends to fall in seasonal pattern and there was not much changed in each year. Adams could use seasonality technique with the linear trend equation technique to calculate the future demand of year five. This method could provide more accuracy forecast regarding the different demand in each month.

 Using Actual Shipment figure, instead of Actual Demand figure

The forecasting technique by used by the Marketing Department is based on actual shipment rather than on actual demand. Even though the Marketing Department tries to adjust for shortages in actual shipment data by meeting with various sales regions to go through the anticipated promotions and environmental and economical changes that brought about the shortages they has experienced last year, it is still reflecting past experience not for the future demand.

The Marketing Department should focus on the past demand in order to project the future demand instead. The forecasting based on actual demand will help the Production Department schedule the production line more effectively. Also, the forecasting based on actual demand, instead of actual shipment will provide the Marketing Department more clear picture about the market situation. They can project more realistic volume and create more sales and revenue for the company when they anticipate the upward trend of demand. On the other hands, they can help preventing losses when anticipated downward trend of demand or unexpected changes in the market as well.

 Lacking of communication between Production and Marketing department

Due to the fact that the market for garden tools is extremely competitive, so the cooperation between production and marketing department is very crucial for the company like Yankee Fork and Hoe. Concerning for low-cost production and on-time delivery are the objective for each department, in order that the accurate forecasting system is the essential tool for both departments to attain their objective. However, in the case, it seems like both departments do not have accurate forecasting system and different perception for the system. To maintain low-cost production, the long-term purchasing agreement is needed in order to keep the price low for the raw material from suppliers, but having it just there is the price to pay for the company. Although, the marketing department give the warning for the anticipated demand ahead, the preparation time is still not enough.

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CASE 1 : Yankee Fork and Hoe Company

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In order to cope with the problem, Yankee Fork and Hoe should improve the lines of communication between marketing and production department regarding the preparation of forecasts. For example, previously, forecasting system preparation is based on only sales and marketing department when they conduct the meeting, the production department should take part in the meeting to provide relevant information about raw material on hand and production schedule, plus making comment on what could be or could not be done for the anticipated demand. Moreover, the meeting should conduct at the end of each month because monthly forecast for the whole next year period is not enough; both departments should adjust the anticipated demand monthly to avoid unexpected changes in the economy and shortage of the raw material.

 The Marketing division may not be optimistic. The problem of delayed delivery may come

from the Production itself (Low productivity).

It is viewed that the delay delivery problem was not caused by the too-optimistic monthly forecast from Marketing Department but the low productivity of Production Department. Currently, the final-assembly schedule relied on “adjusted forecast” that we could obviously see that the current production is not sufficient to serve our customer order.

The production capacity seemed not to be a problem as rake head and bow could be produced 7,000 and 5,000 units per day respectively, compared to the highest sales record in the last 4 year (month 11 year 1) at 83,269 units.It seemed that the inappropriate inventory management was the major factor causing the unproductive production.

In order to be able to deliver all customer order without any obstruction, the following ways were suggested:

- To track and gather the real demand of Top 5 – Top 10 customer who were influential to total company sales and set the minimum stock to at least be able to serve such customers since the current excess demand might be occurred from one of this group.

- To negotiate and revise the raw material order with existing suppliers. The annual committed volume method is recommended given that company could solve the fluctuated demand problem and might get the higher discount from the high volume order. Also, finding prospect suppliers could mitigate the supplier concentration risk.

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CASE 1 : Yankee Fork and Hoe Company

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Question 2 : Develop your own forecast for bow rakes for each month of the next year (year 5). Justify your forecast and the method you used.

After we improve the communication between Production and Marketing department, we would use the quantitative analysis which would make the forecasting more reliable. First, we would use the actual demand to analyze instead of actual shipment and try to find whether there is any pattern of past demand.

Based on the bow rake’s demand in the table 1, we can use the demand to plot the graphs. We have found that the annual bow rake’s demand have a linear trend and the bow rake’s demand of each year have an effect of seasonal pattern as shown below in figure 1 and 2 respectively.

Demand Year on Year Growth

Month Year 1 Year 2 Year 3 Year 4 Year 2 Year 3 Year 4 1 55,220 39,875 32,180 62,377 -28% -19% 94% 2 57,350 64,128 38,600 66,501 12% -40% 72% 3 15,445 47,653 25,020 31,404 209% -47% 26% 4 27,776 43,050 51,300 36,504 55% 19% -29% 5 21,408 39,359 31,790 16,888 84% -19% -47% 6 17,118 10,317 32,100 18,909 -40% 211% -41% 7 18,028 45,194 59,832 35,500 151% 32% -41% 8 19,883 46,530 30,740 51,250 134% -34% 67% 9 15,796 22,105 47,800 34,443 40% 116% -28% 10 53,665 41,350 73,890 68,088 -23% 79% -8% 11 83,269 46,024 60,202 68,175 -45% 31% 13% 12 72,991 41,856 55,200 61,100 -43% 32% 11% Total 457,949 487,441 538,654 551,139 Average 38,162 40,620 44,888 45,928 42% 30% 7% Growth 29,492 51,213 12,485 6% 11% 2%

Table 1 : Bow Rake’s Demand Analysis

Figure 1 : Annual Bow Rake’s Demand 0 100,000 200,000 300,000 400,000 500,000 600,000

Year 1 Year 2 Year 3 Year 4

A n n u al D e m an d ( Pi e ce )

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CASE 1 : Yankee Fork and Hoe Company

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Figure 2 : The Bow Rake’s Demand of Year 1 – 4

Since the annual trend have linear pattern, we can use Linear Trend Equation Technique to forecast Year 5 volume as following.

From Linear Trend Equation;

We can get the number of Year 5 forecasting by formulating the linear equation. We can calculate and by using the below formulas;

Year (t) t2 Demand (Ft) t·Ft 1 1 457,949 457,949 2 4 487,441 974,882 3 9 538,654 1,615,962 4 16 551,139 2,204,556  10 30 2,035,183 5,253,349 2 100

Table 2 : The Linear Trend Equation Calculation 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000 1 2 3 4 5 6 7 8 9 10 11 12 D e m an d (Pi e ce ) Month

The Bow Rake's Demand of Year 1 - 4

Year 1 Year 2 Year 3 Year 4

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CASE 1 : Yankee Fork and Hoe Company

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We can use the figures in the table 2 or the Linear Trend Equation Calculation Table to substitute in the equation to find the value of and ;

We would get or . Thus, we can find the annual forecast volume of Year 5 by substituting 5 into the equation.

After we have got the annual demand of Year 5, we would allocate the volume into monthly projection by using technique for seasonality to calculate. Since we have observed that the monthly demand has regularly seasonal pattern, we would formulate the seasonal index and calculate the monthly forecast for Year 5 as table 3.

Demand Avearage Year 1-4 [(F1+F2+F3+F4)/4] Average Monthly [All Demands/48] Seasonal Index [Average Year 1-4/ Average Monthly] Year 5 Forecast [F5/12xSeasonal Index]

Month Year 1 Year 2 Year 3 Year 4

1 55,220 39,875 32,180 62,377 47,413 42,400 1.1182 55,026 2 57,350 64,128 38,600 66,501 56,645 42,400 1.3360 65,740 3 15,445 47,653 25,020 31,404 29,881 42,400 0.7047 34,678 4 27,776 43,050 51,300 36,504 39,658 42,400 0.9353 46,025 5 21,408 39,359 31,790 16,888 27,361 42,400 0.6453 31,755 6 17,118 10,317 32,100 18,909 19,611 42,400 0.4625 22,760 7 18,028 45,194 59,832 35,500 39,639 42,400 0.9349 46,003 8 19,883 46,530 30,740 51,250 37,101 42,400 0.8750 43,058 9 15,796 22,105 47,800 34,443 30,036 42,400 0.7084 34,859 10 53,665 41,350 73,890 68,088 59,248 42,400 1.3974 68,761 11 83,269 46,024 60,202 68,175 64,418 42,400 1.5193 74,761 12 72,991 41,856 55,200 61,100 57,787 42,400 1.3629 67,065 Total 590,491

Table 3 : Monthly Forecast for Year 5

In sum, we can use the technique that is suitable for the demand to project Year 5 demand. However, after we come up with these numbers, we should bring them into discussion between Production and Marketing department again to make sure that both of them will use the same figure and implement our suggestion from the question 1 in order to improve the quality of forecasting. Moreover, we should include the number of orders that we have not shipped to customer yet so as to cover all late delivery shipments, current demand and future demand.

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