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.
Forecasting
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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