# “Sales Forecasting, Managing in the Global Economy, and Outsourcing Offshore” Please respond to the following: •From the scenario for Katrina’s Candies, assuming the absence of quantitative data, determine the qualitative forecasting techniques that could be used within this scenario. Now, assume you have acquired time series data that would enable you to make forecasts. Ascertain the quantitative forecasting technique that will provide you with the most accurate forecast. •When deciding whether or not to outsource offshore, list the key factors the manager should consider, aside from maximizing profits. Which of these key factors do you believe are the most influential? ——————————————————————————– Optional: (You may substitute one of the above discussion prompts). •Consider the sales pattern shown in the data set below: Sales Year Time Index 121 2004 0 130 2005 1 145 2006 2 160 2007 3 155 2008 4 179 2009 5 215 2010 6 208 2011 7 235 2012 8 262 2013 9 ? 2014 10 ? 2015 11 Using the regression feature of Excel, compute the equation of a trend line to forecast sales in 2014 and 2015. Note, you can use ‘Year’ as the explanatory variable or the ‘Time Index’ as the explanatory variable, but not both in the same equation. In your opinion, is this a good equation for forecasting future sales? Why or why not?

“Sales Forecasting, Managing in the Global Economy, and Outsourcing Offshore” Please respond to the following:

•From the scenario for Katrina’s Candies, assuming the absence of quantitative data, determine the qualitative forecasting techniques that could be used within this scenario. Now, assume you have acquired time series data that would enable you to make forecasts. Ascertain the quantitative forecasting technique that will provide you with the most accurate forecast. •When deciding whether or not to outsource offshore, list the key factors the manager should consider, aside from maximizing profits. Which of these key factors do you believe are the most influential?

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Optional: (You may substitute one of the above discussion prompts).

•Consider the sales pattern shown in the data set below:

Sales Year Time Index 121 2004 0 130 2005 1 145 2006 2 160 2007 3 155 2008 4 179 2009 5 215 2010 6 208 2011 7 235 2012 8 262 2013 9 ? 2014 10 ? 2015 11

Using the regression feature of Excel, compute the equation of a trend line to forecast sales in 2014 and 2015. Note, you can use ‘Year’ as the explanatory variable or the ‘Time Index’ as the explanatory variable, but not both in the same equation. In your opinion, is this a good equation for forecasting future sales? Why or why not?