Abstract: Certain embodiments of the disclosure concern a computer-implemented method. For a distributable product, the method can store a representation of a production process involving a plurality of prerequisites and input quality parameters, receive a request to promise availability of a first quantity of the product having specific instances of the input quality parameters, simulate production of a second quantity of the product having the specific instances of the input quality parameters, output one or more promised delivery terms, and reserve resources in a production system for production of the second quantity of the product. The second quantity is smaller than or equal to the first quantity.

Abstract: The disclosure generally describes computer-implemented methods, computer readable mediums, and distributed systems for providing a message-based interface for exchanging customer requirement information. One method includes receiving, via a message-based interface derived from a common business object model that includes business objects having relationships enabling derivation of message-based interfaces and message packages, a first message for providing a notification of an update of product availability including a first message package hierarchically organized as a product available to promise update notification and fulfillment confirmation message entity and an accompanying set of specific, ordered packages, each including specifically ordered elements.

Abstract: A system and method are described for intelligently sourcing demand forecasts within a supply chain management (“SCM”) system based on a constrained supply chain model, in light of material and resource constraints. For example, a computer implemented method according to one embodiment of the invention comprises: calculating a demand forecast identifying anticipated demand for a product over a specified time period; identifying current sales orders for the product with delivery dates scheduled during the specified time period; generating an open forecast for the product based on the current sales orders and the anticipated demand; and sourcing different percentages of the open forecast from different plants, the percentages selected based on supply chain material and/or resource constraints. In addition, after the demand forecast is sourced, one embodiment of the invention employs additional techniques for intelligently sourcing new sales orders entering the SCM system.

Abstract: A business object model, which reflects data that is used during a given business transaction, is utilized to generate interfaces. This business object model facilitates commercial transactions by providing consistent interfaces that are suitable for use across industries, across businesses, and across different departments within a business during a business transaction. In some operations, software creates, updates, or otherwise processes information related to a customer requirement business object.

Abstract: A system and method are described for intelligently sourcing demand forecasts within a supply chain management (“SCM”) system based on a constrained supply chain model, in light of material and resource constraints. For example, a computer implemented method according to one embodiment of the invention comprises: calculating a demand forecast identifying anticipated demand for a product over a specified time period; identifying current sales orders for the product with delivery dates scheduled during the specified time period; generating an open forecast for the product based on the current sales orders and the anticipated demand; and sourcing different percentages of the open forecast from different plants, the percentages selected based on supply chain material and/or resource constraints. In addition, after the demand forecast is sourced, one embodiment of the invention employs additional techniques for intelligently sourcing new sales orders entering the SCM system.

Abstract: A method that is performed on a computer is used in managing a supply chain. The method includes storing a sales forecast in association with data defining projected sales in terms of product, location, and at least one other descriptive characteristic. The method also includes receiving a sales order and processing the sales forecast and the sales order.