# Project #90822 - Demand Forecasts (Excel)

Turn in a single MS Excel file containing your individual work.

 Sales Yr 1 Yr 2 Yr 3 Yr 4 Yr 5 Jan 2000 2706 3214 3537 3800 Feb 5000 6323 8105 9184 9978 Mar 7000 9494 10361 12666 13238 Apr 11000 15216 16860 18789 21028 May 14500 18000 21298 25576 30828 Jun 19000 25264 29086 30954 37167 Jul 26000 36449 38057 47982 50933 Aug 15000 18503 23695 28530 28663 Sep 10000 13053 15037 17091 21534 Oct 5000 6478 7711 8635 9654 Nov 4500 5665 6874 8531 8876 Dec 3000 4003 4660 4974 5731

Hint: you'll probably want to make these demand numbers a single column!

Directions:

Using the table of sales figures listed above, construct the following:

1) All possible moving average forecasts, plus forecasts for year 6 using "periodicity(p) + 1" as the number of periods to include.

2) All possible four-month weighted moving average forecasts, plus forecasts for year 6, with the weights of 20%, 20%, 30%, and 30% (most recent month last).

3) All possible simple exponential smoothing forecasts, plus a forecast for year 6. Use solver to find and use the optimal alpha.

4) The "Static" deseasonalizing method forecast for all possible periods, plus year 6.

5) Use Winter's method of trend and seasonality corrected exponential smoothing to forecast all possible periods, plus year 6. Use solver to find the optimal alpha, beta, and gamma.

6) Construct the historical MAD, MAPE, and MSE for each of the forecasting methods. Which method works best?

To be clear, I want you to create a file that has similar features to the "Tahoe Salt" example analysis in Excel.

 Subject Business Due By (Pacific Time) 11/07/2015 12:00 am
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