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"New items with analogues;"
The system calculates their sales forecast based on sales data for similar products. When building a forecast, the system takes into account the coefficient of influence of each of the analogues, which is specified when adding a new position. (details of adding analogs are described in the section New).
"New items which analogs are not specified or which have no sales history or analogs at all;"
In this case system automatically automatically finds the SKUs, which are in the assortment matrix, have less than 4 weeks of sales history and there are no analogs of them. Then algorithm forecasts them as an average position for the group, taking into account the price of the new position (if it is present if not, the forecast is calculated using the average value of the group). For this it takes sales of Group/Store level and divides them by the number of positions on the stock, and then recounts the group's forecast, taking into account the price of the new position, and then applies it to a new position.
"New positions for which analogues are not specified, but there is a history of sales over the regions;"
For forecasting this positions system uses "Expansion of distribution" algorithm. This option is used to predict a new position in the store more accurately, If new position has already been used in other region's stores assortment, then this option can be used.
Expansion of the distribution is used if the number of weeks of historical sales for a new position in the store is less than a previously set number of weeks (the number of weeks is set using the forecast configuration file), but there are sales in the region for a new position. In this case, the system does not consider this position as completely new, but as an extension of the store's assortment.
For positions that fall under the expansion of distribution, the system calculates the new position forecast as a forecast for the position from the region and applies it to the store level using the following proportion: Sales/Forecast value on SKU/Region level is multiplied by Sales/Forecast on Group/Store and divided by Sales/Forecast from Group/Region level.
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When testing each model, MySales builds the forecast for the past 52 weeks, and calculates Mean Absolute Percentage Error (MAPE) for the forecast on each model. Then based on your model settings, MySales adds the penalty for each model and chooses the model with minimum error including Penalty. The penalty is a percentage that you can use to reduce sensetivity sensitivity for a particular model.
You can see Penalty percentage for each model on SETTINGS page. To see the tested models and the selected models, use Models button on MY SALES page.
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Using past undefined weeks to evaluate the forecast
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There are multiple options, but the more generic solution is to take the forecasted quantity for the delivery period (from the nearest delivery day to the next delivery day), add Mean Absolute Deviation (MAD) or Mean Absolute Percentage Error (MAPE) as a safety stock. Your target stock quantity is ready, then just substract subtract the current stock and your quantity to order is ready. If the forecast accuracy is high, using MAPE is preferred when you need to increase the safety stock for the forecasted peaks. Using MAD is preferred when the forecast accuracy is less, or sales are low, or the sales expected to be more smooth without high peaks.
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