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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