Forecasting: Out-tel, Inc - Case Study Example

2. Seasonally adjusted data forecasting particularly focuses on variation due to a particular day, week, moth or year in a timeline series. On the other hand, trend forecasting does not incorporate these types of fluctuations. 3. Seasonally adjusted data forecasting produces a graph in which parabolic shapes due to seasonal fluctuations are displayed whereas the graph of trend forecasting shows the linear pattern which is not the realistic way of forecasting. f) On the basis of Mean Absolute Deviation measure to decide which forecasting method is providing the better results, it can be inferred that Exponential Smoothing method is generating better results as its MAD value is 18.

16 which is less than 5.17 from MAD value of Moving Average method which is calculated as 23.33. The lesser the value of MAD, the greater will be the accuracy of the forecasting technique. Based on above calculation, it will be totally top management’s authority to decide on the production volume of the two products. Since this analysis is based on application of different forecasting methods on two different products, therefore exact relative and comparable results cannot be