Introduction
This module covers several key functionalities for forecasting and data management in Microsoft Dynamics 365 Supply Chain Management:
Export forecasts - After creating, analyzing, and editing a forecast, you can export it back into Supply Chain Management. Additionally, you can download time series values as a CSV file directly from the application.
Manage data export profiles - You can view, run, and create data export profiles to transfer data to specific instances in Supply Chain Management. Additionally, you can configure settings, such as connection URLs, map data columns, and define export rules.
Rolling forecasts - Implementing rolling forecasts allows for continuous updates and extensions of forecast horizons by using the latest data, ensuring alignment with evolving business needs.
Forecast profiles - You can work with existing forecast profiles to predict demand over future periods, customize new profiles, and manage forecast models by using algorithms, such as AutoRegressive Integrated Moving Average (auto-ARIMA), error, trend, and seasonality (ETS), Prophet, or the best fit model.
Microsoft Azure Machine Learning integration - You can use your own Azure Machine Learning algorithms for demand forecasting by setting up connections and configuring forecast profiles in Supply Chain Management.