A Job-shop manufacturer that specializes in replacement parts has no forecasting system in place and manufactures products based on last month's sales. 24 months of data are available as given in the following Table.

Month______________ Sales

Jan-05........................430

Feb............................420

Mar...........................436

Apr............................452

May...........................477

Jun............................420

Jul.............................398

Aug...........................501

Sep............................514

Oct............................532

Nov............................512

Dec............................410

Jan-06........................442

Feb............................449

Mar............................458

Apr............................472

May...........................463

Jun............................431

Jul.............................400

Aug...........................487

Sep............................503

Oct............................503

Nov...........................548

Dec............................432

Plot the data using Excel. What kind of pattern do you observe?

Use a naive model to generate monthly sales forecasts (e.g. the February 2005 forecast is given by the January 2005 value, and so forth). Compute the MAPE and MSE. (Use Excel.)

Use simple exponential smoothing with smoothing constants 0.1 and 0.6. What are the MAPE and MSE values? (Use Minitab).

Calculate the autocorrelations for the residuals of the methods used in part c. What do you observe?

Use Winter's method with smoothing constants α = β = γ = 0.5. Calculate the autocorrelations for the residuals. Compare the MSE and MAPE of this method with the previous ones.

What are your comments regarding the best method to use in forecasting the above data set? Explain.