Yankee Fork and Hoe Company

Topics: Normal distribution, Forecasting, Standard deviation Pages: 2 (572 words) Published: April 9, 2008
Yankee Fork and Hoe Company
Yankee Fork and Hoe Company is a leading producer of garden tools. The situation is that long time customers are experiencing frequent late shipments because of manufacturing issues which cannot fulfill customer demand. Phil Stanton, is in charge of inventory and is concerned about high costs and keeping the inventory low. However, Ron Adams, the marketing manager, is concerned about having enough rakes on hand for timely shipments. There is an agency problem amongst Yankee Fork and Hoe Company. They both have bias views on how the forecasts should be run. They are behind on customer demands because of Phil’s forecast philosophy. Diagnostic Analysis

The bow machines for Yankee Fork and Hoe Company can only produce 5,000 bows a day. This equates to 150,000 per month. Phil is decreasing demand forecasts by 10% to generate a monthly final-assembly schedule. Phil is decreasing his demand forecast by 15,000 units in fear of being overstocked. However, the marketing department is requesting to Phil that they produce more units. Due to the constant decreasing actions made by Phil, the company has become backlogged to fulfill the customers’ needs. These results prove that the demand exceeds 150,000 units from which the company can only produce in a month. The machines are working at full capacity and are being overworked because of the sloppy and poor forecasts of Phil Stanton. Solution Options

A possible solution for Yankee Fork and Hoe Company would be the simple mean or average. This is the average for the set of data. This would not be recommended because it does not recognize the fluctuation of demand due to the constant changes that the data implies. Another possible solution is the forecast trend solution. This method computes the forecast when data displays a clear trend over time. But the error resulting in this method is too high to accept in priority. Another option is the seasonal index method....
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