Improving Sales Forecast Accuracy with Mathematical Regression

MKTG 470 Case Study 1-1 Caitlin Meusel Andros Intercom Revision a Sales Force Approach Points that helped the decision-making process - Underestimated sales by 21% and 16% in the past two years - David helped create forecasts for a couple of other companies so he should be well versed in this - They have not tried a mathematical forecasting method before - In the past only top management was concerned with forecasting - Many sales reps prefer the intuition models and customer input Questions. Assume that in 2017, Andros will spend $1.1 million on advertising, sell its products for an average of $3,300, and that there will be 36.0 thousand housing starts. Run a multiple regression analysis. What is the 2017 sales forecast using this approach? Show the regression equation. Constant = -398558.33 Coefficient1 (Advertising) = 368.75 Coefficient2 (HousingStarts) = 11089.84 Coefficient3 (Price) = 1602.08 Sales = -398558.33 + 368.75 * 1.1 + 11089.84 * 36.0 + 1602.08 * 3300 Sales = $7,772,694.33 The 2017 sales forecast using this multiple regression approach is $7,772,694.33. Describe the advantages and disadvantages associated with both the old and the new approach to sales forecasting. Discuss the accuracy of both approaches. The advantage of the old approach to sales forecasting is that sales reps like this method. They can use their own intuition and customers' input for what they believe they will buy in the next year. Using this method does not involve complicated math, which the sales reps do not want to spend extra time doing, and the company's higher-ups have always liked it. One major disadvantage to this method is that it has been very inaccurate in the past two years. This has caused them to miss out on many sales opportunities. This method is very inaccurate as it is completely based on guesses and intuition from previous years. It is completely based on guesses and intuition from previous years. The newly proposed method is much more accurate as it uses mathematical multiple regression analysis that calculates a very specific number used in previous years. This tool should be very accurate. Sales representatives do not wish to have to learn the new math and do not wish to spend time learning how to use this tool. Based on your analysis, which approach do you recommend? Explain. Based on the analysis, I would use the new sales forecasting method, because, in previous years, the forecast has been off costing them some sales they could have otherwise had. It won't hurt to test out this method to see if it is more accurate as they have lost a lot of money in the previous years. Testing this out could lead them to make more money in the future.
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