Using the data from Problem 3.1 (page 128) on your book develop three forecasts for 2015 January. 

Using the data from Problem 3.1 (page 128) on your book develop three forecasts for 2015 January.

1) A 12-month moving average

2) Exponential smoothing with alpha that corresponds to a 12 month moving average block (see formula 3.26). Initialize by averaging the first 11 months.

3) Winter’s method using Centered MA12 (then you need MA2 because the center of 12 is 6.5). Get alphaHW, betaHW from formulas 3.34 and 3.35, respectively and gammaHW is 0.15.

Calculate MAD for each method.


MGT 509

















Forecasting is

like driving your car only by looking at the rear view mirror.

rarely accurate.

however necessary for resource allocation planning.

an art as much as a science.








Forecasting process

Historical Data

Mathematical Model

Forecast of Demand

Human input

Forecast Errors

Actual demand observed









Time Series

Five components

Additive models

Demand = Level +Trend + Seasonal + Cyclic + Irregular

Multiplicative models

Demand = (Trend)(Seasonal)(Cyclic)(Irregular)


1) Select underlying demand pattern

2) Select the values of parameters inherent in the model

3) Use the model to forecast demand








Short-term forecasts








Winter’s Method








Accuracy measures








Monitoring Bias








Taking corrective action








Inserting Judgement








Integrating judgement

Combined forecasts

For short term forecasts judgmental forecasts can be better than statistical forecasts IF done by domain experts

Even without domain experience combining judgmental and statistical forecasts help

Use equal weights

Revised statistical forecasts

Results are mixed

Judgement should be an input rather than revision

If revision is a must, it must be done by domain experts in a structured way

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