Automatic Forecast System Checklist

Looking for automating sales forecasts for retail chain? Use these questions as part of your vendor research

1. Does the system allow for building promo forecasts and simulating various scenarios? Is it taking into account the interplay between product, price, seasonality and promo factors?

2. Does the system take into account the effects of seasonality and weather for each combination of store and SKU individually?

3. Does the system take into account the impact of price changes on the forecast?
   Context: Particularly important for fresh goods so that write-offs do not increase after price increases.

4. Can the system account for cannibalization in the forecast?
   Context: Let’s draw an example from eggs where the appearance of a new top position in the group leads to a significant drop in sales of other positions.

5. Is the system providing daily forecast recalculation, taking into account the latest daily sales, price change, seasonality and weather data? Is it made separately for promo sales and regular sales?

6. Is the forecast calculated according to a top-down or bottom-up approach?
   Context: Top-down approach means global forecast decomposed to store level. Bottom-up is a separate model for each combination of store and SKU. Bottom-up approach performs better in capturing store specifics. Weather, location in the city, local purchasing power, among other factors.

7. Is the promo forecast module allowing for taking into account factors such as marketing activities? How customizable is it?

8. Does the system provide insights on why given predictors were chosen in a particular model?

9. Is the system building a separate ML model for each combination of store and SKU? Does it support daily or even more frequent recalculations?

10. How many competing models is the system building before choosing the best one?

11. Is the system allowing for building custom reports?

12. Is promo forecast automatically calculated into overall forecast?

13. Is it possible to exclude periods of demand anomalies for the sake of future forecasts? Can this be done in bulk or automatically?
    Context: Covid quarantine, war in Ukraine led to increased purchases of certain categories.

14. Is the system allowing for using competitor’s prices as one of the predictors?

15. Is the system allowing for customizing for how long into the future and to the past should the forecast be done?

16. In the case of a sale (price cut, e.g. due to the upcoming expiry date), is the system able to categorize the record as a sale, so that the increased sales volume does not result in a disproportionate increase in the forecasted sales for subsequent periods?

17. Is the system allowing for using competitor prices as a factor in a sales forecast?