Demand chain management

The subject of demand chain management is complex and dynamic supplier and customer networks, with the customer side playing a special role. (see Wieland / Wallenburg, 2011)

Demand chain management (DCM) is the management of relationships between suppliers and customers around the demand of the customers through the supply chain (Engl. Supply chain ) minimizes the effect and at the lowest possible cost. The term demand chain management means the same thing as supply chain management , but with an emphasis on the demand side. Demand chain management software aims to close the gap between customer relationship management and supply chain management.

During the logistical processes company are organized (the supply chain) to the (presumed to exist) demand to fulfill customers' best, provides a study by the University of Wageningen ( Netherlands ) DCM as an extension of the supply chain through the explicit inclusion of market perspective.

A large topic within demand chain management is that of the communication model. The retailer often protects his end customers and only wants to look after them directly. This is where the so-called conflict of objectives arises between the manufacturer and the retailer ( sales promotion ).

Different implementations of DCM

A demand chain management approach combines business intelligence software and forecasting models, which take public holidays, sporting events, vacations and other factors into account to calculate future customer demand. The supply chain is controlled based on these results.

Another approach is called real-time DCM. With this approach, all inventory changes (sales, deliveries, etc.) are processed in real time. Based on this data you can calculate current sales trends and react quickly in order to have products available at all times. Systems of this type can, for example, warn that the organic milk will be sold out in 4 hours. The supply chain is continuously supplied with the latest data. If the corresponding delivery times are taken into account, delivery bottlenecks can be avoided by taking real inventory data and current sales trends into account.

Individual evidence

1. ↑ cf. Andreas Wieland, Carl Marcus Wallenburg (2011): Supply chain management in stormy times . Berlin.
2. ↑ Collaborative Planning, Forecasting and Replenishment (CPFR). (No longer available online.) In: johngalt.com. Archived from the original on July 15, 2016 ; accessed on July 15, 2016 . Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice.  
3. ↑ Wageningen University dissertation no. 4036 ( Memento from August 3, 2007 in the web archive archive.today )