1. Consider using simple moving average model. Experiment with models using five weeks' and three weeks' past data. The past data in each region is given in the tab "Moving Average Analysis," that also includes the 13 week data (table above) along with the past 5 weeks'. Evaluate the forecasts that would have been made over the past 13 weeks (week 1 to week 13) using the "mean absolute deviation" and "tracking signal " as criteria.
2. Next, consider using a simple exponential smoothing model. In your analysis, test two alpha values 0.2 and 0.4. Use the same criteria for evaluating the model as in part 1. Assume that the initial previous forecast for the model using an alpha value of 0.2 is the past three-week average. For the model using an alpha value of 0.4, assume that the previous forecast is the past five-week average.
Altavox is considering a new option for distributing the model VC 202 where, instead of using five vendors, only a single vendor would be used. Evaluate this option by analyzing how accurate the forecast would be based on the DEMAND AGGREGATED ACROSS ALL REGIONS. Use the model that you think is best from your analysis of questions 1 and 2. Use a new criterian that is calculated by taking the MAD and dividing by the average demand. This criterian is called the mean absolute percent error (MAPE) and gauges the error of a forecast as a percent of the average demand.
. What are the advantages and disadvantages of aggregating demand from a forecasting view? Are there other things that should be considered when going from multiple distributors to a single distributor.