New Balance Case Study Solution
Introduction
According to the forecasts, New Balance will be seeing growth for the next three years. Currently, the facility is too small for the desired production and the company needs to expand. The best location for expansion is Texas.
Exponential Smoothing Forecast
In exponential smoothing forecast, more weight is given to recent data. This type of forecasting is ideal for data with no seasonality. Seasonality, or regular changes in the data, is not seen for New Balance. The forecast includes a damped trend, because there is always a limit to growth. The level and trend weight used in the forecast are .5 and .1, respectively. The trend modifier is .9, because this allows for a smaller mean squared error than other values.
Despite the …show more content…
New Balance’s most pressing concern is their inability to meet production demands. Therefore, production is given the most weight (5). Job market and growth potential are both given weights of 4. The job market includes being able to find skilled workers to work at the new location. Since it is hard to quantify quality, I added this factor to the job market category. New Balance uses their workers to maintain quality, and will continue to do so. The forecast predicts that New Balance will increase in sales (see Exhibit A). The new location should allow for this growth to occur. Growth potential also includes regional sales and consideration is given to regions where sales stand to grow. Cost is given a weight of 3. The cost category includes lease, equipment, wage rates, material costs and manufacturing overhead. The company does consider cost when expanding, but it is not as important as production, growth potential and job market. Finally, government assistance is given a weight of 3. Government assistance usually results in lower financial considerations; therefore, I am giving both factors the same …show more content…
It combines both factors to create an overall value index for each location. The intangibles are given a score between 1-10 (1 being ideal, 10 being a disaster). Each factor is given a weight (1-least important, 5-most important). The first dimensional analysis was done between Lawrence, Massachusetts and Texas (Exhibit B). The second comparison was between Texas and Ireland (Exhibit C). Since Texas is the better location, a comparison between Lawrence and Ireland was not done. In this analysis, higher numbers are better. Since companies want lower costs, the weight for cost became a
According to the forecasts, New Balance will be seeing growth for the next three years. Currently, the facility is too small for the desired production and the company needs to expand. The best location for expansion is Texas.
Exponential Smoothing Forecast
In exponential smoothing forecast, more weight is given to recent data. This type of forecasting is ideal for data with no seasonality. Seasonality, or regular changes in the data, is not seen for New Balance. The forecast includes a damped trend, because there is always a limit to growth. The level and trend weight used in the forecast are .5 and .1, respectively. The trend modifier is .9, because this allows for a smaller mean squared error than other values.
Despite the …show more content…
New Balance’s most pressing concern is their inability to meet production demands. Therefore, production is given the most weight (5). Job market and growth potential are both given weights of 4. The job market includes being able to find skilled workers to work at the new location. Since it is hard to quantify quality, I added this factor to the job market category. New Balance uses their workers to maintain quality, and will continue to do so. The forecast predicts that New Balance will increase in sales (see Exhibit A). The new location should allow for this growth to occur. Growth potential also includes regional sales and consideration is given to regions where sales stand to grow. Cost is given a weight of 3. The cost category includes lease, equipment, wage rates, material costs and manufacturing overhead. The company does consider cost when expanding, but it is not as important as production, growth potential and job market. Finally, government assistance is given a weight of 3. Government assistance usually results in lower financial considerations; therefore, I am giving both factors the same …show more content…
It combines both factors to create an overall value index for each location. The intangibles are given a score between 1-10 (1 being ideal, 10 being a disaster). Each factor is given a weight (1-least important, 5-most important). The first dimensional analysis was done between Lawrence, Massachusetts and Texas (Exhibit B). The second comparison was between Texas and Ireland (Exhibit C). Since Texas is the better location, a comparison between Lawrence and Ireland was not done. In this analysis, higher numbers are better. Since companies want lower costs, the weight for cost became a