More updates to the Netstock app: Advanced Forecasting feature
This month we officially released the Advanced Forecasting Module, designed to complement and extend Netstock’s existing forecasting functionality. At release, we’ve included two core features: multi-item forecast adjustment and group seasonal forecasting.
In this update
Multi-item forecast adjustment
Look forward – warehouse orders
Multi-item forecast adjustment allows you to filter on a list of items and easily amend their forecasts in one convenient view:
Group seasonal forecasting can improve the app’s forecasts by applying the seasonality found on a group of items to individual items that don’t clearly exhibit their own seasonality. The example below shows an item with only a few months of sales history, but the app was still able to apply a seasonal forecast because the item belongs to a seasonal group:
You can read more about the module here: https://www.netstock.tv/netstock/advanced-forecasting
Look forward for warehouse orders
By popular request, we’ve added the look forward feature as an option when raising warehouse orders (i.e. transfers) in the app. While we were at it, we took the opportunity to add extra fields to make the page layout consistent with supplier ordering.
The look forward feature gives you the option to accumulate recommended orders from a number of days into the future before creating the order. It’s good practice to use look forward days if you know you won’t be placing another order for a period of time. It can also be very useful if you want to target a certain order value, volume or weight.
If you don’t see the “Look fwd days” field in your app, you may not have the feature enabled. Reach out to your customer success team and ask for the “Projected Orders” feature.
Faster batch run times
We invested some time this month optimizing the refresh process and making efficiency changes to several of the app’s calculations. If you’ve noticed faster refresh times during August, this is probably why. Whether you experience the benefit largely depends on a number of factors including your data size, optional modules and the complexity of your supply chain structure.