Case Study
“AI Control Tower” – Intelligent demand forecast for transport orders as a solution for supply chain
Problem
- The clients have strict SLAs with their clients defining the quantity and quality of fulfillment
- There is only limited visibility into the future order volume in dimensions quality (which SKU) and quantity
- The Warehouse Managers have the challenge to plan and allocate the respective number of resources and stock levels to fulfill the SLA while operating cost and resource effective
Approach
- Develop prototype of AI Control Tower to forecast the demand for transport orders – understand and prioritize the the most relevant internal and external data points
- The generated database allows to optimize product placement in the warehouse, reduce the probability of over- and understaffing, lower picking and overall workings expenses
Results
- Increase of productivity
- Easier resource planning & monitoring
- Better SLA & peak management due to forecasting capability
- Optimization of stock levels and values•Identification of quick wins and potential of new ASCS offering
Business Value
Productivity, Resource Planning & Monitoring, SLA & peak management
Industry
Case
Client
Supply Chain Provider
Global provider of supply chain management and logistics services that offers customized solutions to a diverse range of industries. The portfolio of services includes inbound and outbound logistics, order fulfillment, inventory management, and various customer-specific value-added services.
The company operates in over 20 countries and serves a diverse range of industries including healthcare, consumer goods, high-tech, and entertainment.
