Transport/Logistics

In the transport and logistics industry in particular, up-to-date planning of operational business is of fundamental importance. However, the associated data is usually stored in various operational systems, so-called isolated solutions. The first step in efficient management is therefore to merge these different data pools.

Subsequently, due to the individuality of the transport routes, there are various starting points for establishing data-supported decision-making.

Use cases from our projects:

• Driver-based planning: For example, focusing on key factors such as allocation, volume, freight rate, CRC, S&D, CPD, SSY and overhead including HR, investment and CL scheme. Allows you to effectively link capacity, volume, revenue and cost planning and offers the possibility to test scenarios through simulations.
• Advanced analytics: Our forecasting framework enables, for example, improved empty container management of surplus and demand areas. This creates more accurate forecasts of the required capacities worldwide.
• Process automation: Everyday tasks such as processing depot invoices for empty containers can be made more efficient through automation.  
• GenAI platform: Use of AI to enable faster access to scattered, relevant company data.
• Data governance: Holistic concepts from user to platform with a focus on the data mesh or hub-and-spoke approach, security and clear role definitions ensure the efficient use of data.
• Cloud cost optimization: Finop's can save up to 20% in the cloud environment by, among other things, optimizing the use of cloud services and defining clear responsibilities and budget allocations.

Whether for company-wide financial or capacity planning, analyzing the container situation, case management or transshipment processes: With our experience from countless projects in the transport & logistics sector, we help you to create exactly the transparency you need to manage your company.

Our customers include: