I'm taking a course on Supply Chain Mmgt. Currently, we're discussing "forecast errors" such as the
- Squared Error (MSE)
- MAD (Mean Absolute Deviation)
- MAPE (Mean Absolute Percentage Error)
- Tracking Signal (TS)
I'm completely worked out an elaborate Excel solution. The actual Excel spreadsheet is not important for addressing this question though.
However, I'm trying to get a better understanding (the textbook is not very clear in my opinion) as to how the 5 forecast errors relate to each other.
I've posted a snapshot (JPG file) of the Excel forecast errors at the following site:
http://img108.imageshack.us/img108/143/ ... orsxi9.jpg
1. Just looking at the forecast errors, which underlying forecast method (moving average, simple exp. smoothing, Holt's, Winter's) seems to be the most efficient one?
2. Is there really one method that is better than all others? Or, based on the errors, does each method have some advantages and disadvantages?
Thanks so much in advance!