Greetings Dr. Jain,
I am currently trying to develop the best way to calculate our forecasting accuracy. We end up with a significant number of SKU’s that have some shipments, yet did not have a forecast, and vice versa. In addition, We have a small number of SKU’s accounting for the majority of our volume. I am interested in the SMAPE formula and have two questions:
1. Seems there are a few versions of this formula, which is the best one?
2. Is this formula used often, if not, what is the best or most commonly used formula? (I tried to download the report on this, but this side seems to have some technical issues.)
Thanking you in advance,
The SMAPE for measuring forecasting error is found only on the Internet. You won’t find any discussion on this metric in any forecasting book, nor in any forecasting conferences. In fact, I don’t know any company that uses it. My main concern with the formula that I see on the Internet is in dividing error by the average of actual and forecast to arrive at the percentage error. To me, the objective of the forecast error is to see how forecast deviated from the actual, and not from the average of actual and forecast. This can be only accomplished by dividing the error by just actual.
Based on the IBF survey data, most of the companies use MAPE (Mean Absolute Percent Error), though I feel WMAPE (Weighted Mean Absolute Percent Error) is even better. There are a number of companies that use it. You can find their formulas in any forecasting textbook.
Having a large percentage of sales coming from a handful of SKUs is quite common. Pareto laws applies to most companies.
I hope this helps.
Dr. Chaman Jain
St. John’s University