Applied Managerial Decision-Making
WidgeCorp Discussion Board IV
December 12, 2012

Our company is considering delving into the product line of cold beverages. Forecasting future monthly sales of cold beverages has been approached to insure and demonstrate good stewardship of the company’s resources. Determining whether to go into the cold beverage sales business requires tools such as a regression model in which use of historical information might benefit the organization particularly since this model’s benefit of allowing its users to capitalize on the benefit of choosing previously collected research data taking advantages of time saved from this element of the research, accuracy and the speed of organizing data obtained in previous research studies (Bowerman, O’Connell, Murphree, & Orris, 2010) Using the regression model, the information will be gathered and organized categorically into cold beverages that are considered healthy, cold beverages that are most popular, sodas, fruit juices, etc. to determine how the organization could capitalize in the market by gaining greater market shares by strategically introducing a new cold beverage product. In this case my line of questioning would be what popular drinks are being marketed successfully currently? Is the health-concious drinks and foods at the top of the food chain currently? Is there a more convenient consumption of cold beverages we can capitalize on such as a no-sugar-added fruit juice in a carton that is individual in size? How will the product be marketed? What regions are the cold beverages selling best? What surveys indicate who is buying the drinks by gender, age, time of year, etc. These are all questions that would be important to my report to identify a relationship between variables, probably single linear analysis would provide this information best with dependent and independent variables to be considered. The variables in my mind then become gender, will the drink be more appealing to women than men; portability, will the personalized approach to individual grab-and-go drinks be more appealing to consumers in that market? Research could easily show a company where most cold beverages are sold from regionally designed research for collecting this data. This variable would be region. The generational/age input or “baby boomer” effect could be part of the input or variables (Can Soft Drink Taxes Reduce Population Weight?). Placing the correct variables into the regression model should give me a fairly accurate answer with regard to my question of whether the organization should delve into the business of selling cold beverages.
References
Can Soft Drink Taxes Reduce Population Weight? (n.d.). National Center for Biotechnology Information. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2908024/Stockburger, D. W. (n.d.). Regression
Bowerman, B. L., O’Connell, R. T., Murphree, E. S. & Orris, J. B. (2010). Essentials of Business Statistics (3rd Ed.). New York: McGraw-Hill Irwin.