Autostock Inventory Forecast Management

Autostock Functions &

Why you need them

Automated selection of best fit forecast from one of nine different statistical forecast methods. Advanced users have control over forecast parameters.
Auto selection of the optimum forecast method makes the initial forecast set up simple. You can also review items individually in the forecast manager (from the planning workbench) to review and change the forecast method.
​Un-forecastable items are reported for manual forecasting or simple stock level management.
​​Not everything can be forecast by statistics. Autostock identifies irregularly selling items that need the forecast to be set manually. Set them a buy to order strategy or, if you need to stock them, apply a short range average forecast (so that you track demand as it changes over time) and focus on the important items that sell.
​Manual forecast overrides by item and period may be keyed directly in the planning workbench.
​Just had a conversation with the sales manager? Key in his sales estimates for next month on the fly and recalculate what you need to buy.
​Pure manual forecasting using sales driven forecasts developed in Excel may be uploaded directly into Autostock.
Entering a new market or product range is always a challenge. If there is no history to go on, or your business is more marketing driven, then get the forecast from the sales and marketing teams and upload it into Autostock and save all that data entry.
Correct sales history to remove anomalies leading to forecasting errors.
Sometimes the forecast is wrong due to abnormal sales (or lack of sales) that skew the data. You can easily fix this by correcting the data to get a better forecast.
Apply history from superseded items to forecast the replacement items.
​In the fashion business and need to forecast the new model? Use the supersessions function to use the history from the old item to plan for the new item.
Rapidly apply preferred statistical forecast methods to items with difficult or highly variable history patterns.
​Want to keep it simple and just use an average forecast method? Just pick your preferred forecast method and apply it to a range of items using the Confirm Forecast function. Useful if your history is lacking or lumpy.