Optimal control of warehousing means avoiding both delivery bottlenecks and excessively large stocks. The sales forecast models currently in use only provide selective forecasts, so they cannot predict the probability of the forecasted sales deviating from the actual sales. Dispatchers have to decide for themselves to what extent they trust the forecast when planning. As a result, many companies hold unnecessarily high safety stocks.
Optimizing warehousing with AI processes
The artificial intelligence approach could improve this situation. Together with the project partners, FIS GmbH is developing and testing an AI process that can be used to determine the optimal stock level. Aspects such as quantity-dependent purchasing conditions, logistical lot sizes, storage costs and more are also included.
As part of the OBER project, the new forecast tool will therefore be available from the project partner Iron fisherman implemented in parallel to the previously used methods. Over the project duration of a total of 32 months, the AI forecast, conventionally generated forecast and actual market development can be compared again and again. The AI then “learns” from the results how to make the predictions more precise. The aim is to develop software that is easy to use, especially for SMEs. The connection to SAP implemented by FIS not only serves to integrate all SAP data, but also ensures that the new process can be easily integrated into existing SAP systems.
The FIS Informationssysteme und Consulting GmbH forms the roof of the FIS group with over 800 employees. The focus of FIS is on SAP projects and the development of efficient solutions that advance digitalization in companies. Together with the subsidiary Medienwerft, FIS covers the entire SAP area for customer experience (CX). (sg)
Also read: Intelligent supply chain management for online retail
