How the inventory management solution works

How the UiPath Inventory Management solution generates demand forecasts and inventory recommendations using machine learning models and historical data.

The UiPath solution for inventory management supports inventory decisions by analyzing historical data, evaluating business objectives, and generating an intelligent demand forecast alongside target stock recommendations. Machine learning models predict future demand based on all available historical and external data, then using this as a baseline, generate safety stock and target stock levels. These consider factors such as lead time, demand volatility, and more. This forms the output recommendation.

How this fits into inventory planning workflows

Following the ingestion of required data, this solution will generate an intelligent demand forecast and stock levels at the SKU-location level. If optional modules have been purchased, optimal recommendations will also be generated. Integrations to systems of record and action can also form part of this solution, for easier actioning of these recommendations. For more information, reach out to your team contact.

Required inputs

The inventory management solution relies on supply chain data that reflects how inventory behaves across products, locations, and time.

For details on the data requirements for the Inventory Management solution, refer to Inventory Management.

Outputs and recommendations

Intelligent demand forecasts and optimal inventory levels, which can be viewed within the application front end provided or in systems of action or record with the use of integrations.