Kickstart your machine learning journey in demand forecasting with EyeOn Proof of Concept
Machine learning is all about using machines to improve your demand forecasting capabilities. So how do you set up the machine to do this successfully?
See caseInventory reduction by multi echelon optimization
A leading flavor and fragrance producer with complex inter-company good flows and a high level of dependencies asked EyeOn to further optimize inventory settings in their supply chain.
See caseWarehouse footprint optimization
One of the leading providers of paper-based packaging struggled with seasonality creating an unbalanced situation between supply and demand. To absorb the swings they rented external warehousing which caused a high total cost of warehousing.
See caseTactical and strategic industrial footprint optimization
Global animal nutrition producer needed fact-based decision making based on scenario analysis. EyeOn offered a structured approach to build a decision support model. Watch the demo video!
See caseMarket driver-based forecasting at Rockwool
The challenge in long-term forecasting is to find the relevant drivers that predict market changes and development. We developed a model that supports Rockwool to understand the market with fact-based forecasting.
Supporting Aspen with planning activities
EyeOn supported Aspen with multiple planning activities during a large scale SAP implementation: support with master data design and collection, cut-over, go-live and hypercare activities.
See caseRedesigning statistical forecast
EyeOn supported a multinational semiconductor manufacturer to redesign their statistical forecast based on an efficient process to quickly evaluate various scenarios in order to improve their lead times.
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