- Out-of-stock situations and excess inventory exist at all levels of the supply chain and need to be reduced
- Whip effects are to be identified in the historical sales data and countermeasures implemented
- Increasing product diversity should be managed without the need for manual intervention
- Breaking down the data silos of the various stages and establishing an overarching data lake for centralised control of the entire supply chain
- Implement automated sales forecasts for all stages of the supply chain with machine learning algorithms based on historical sales data.
- Forecasting the unknown demand by modelling the demand data from the historical sales data
- A universal, automated forecasting environment that can be flexibly deployed at all stages of the supply chain
- Reduction of the whip effect through shorter response times and reliable forecasts at all levels
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