Forecasting in supply chain management
With the help of sales forecasts and demand forecasting, the entire supply chain is to be optimised for a beverage company.
Significant reduction of the whip effect, which increases as the level in the supply chain rises.
Reduction of out-of-stock situations despite simultaneous reduction of stocks
Central calculation of order proposals enables transition to vendor-managed inventory: "Delivery is already waiting at the door when the order is actually only supposed to be placed".
- 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
Are you interested in your own use cases?
An automotive company would like to visualise various market-specific data in order to create a Competitive analysis for the US market.
There will be a interactive and Flexible application, including of different maps with two different views implemented.
Relevant markets are identifies, analyses and visualises. The dealer or the respective sales department have the possibility to compare the direct competition with their own product and to visualise the relevant data.