Negotiation Automation Platform
delve into three comprehensive case studies regarding manufacturing and logistics in Section 5 Case Studies .
1.4 AUDIENCE
The primary audience of this article includes manufacturers , logistics providers , and other supply chain entities , with a particular emphasis on manufacturing and transportation and shipping sectors . Additionally , CxOs who are interested in enhancing social and economic efficiency , as well as contributing to the achievement of Sustainable Development Goals ( SDGs ), will find this information valuable .
1.5 USE
By leveraging the insights provided in this article , stakeholders in the supply chain can establish efficient and flexible coordination of trading conditions and foster cooperative relationships . An efficient and sustainable supply chain ecosystem can be constructed by adapting NAP to specific business requirements , benefiting all participants involved .
1.6 TERMS AND DEFINITIONS The following terms and definitions that are key to understanding this document are :
• NAP ( Negotiation Automation Platform ): a system that streamlines the negotiation process by utilizing AI to facilitate efficient and effective communication and decisionmaking .
• Automated Negotiation : a process to facilitate negotiations between parties without direct human intervention .
• IIoT ( Industrial Internet of Things ): a system of intelligent , connected devices that collect , process , and analyze data for industrial applications , enabling enhanced performance , efficiency , and business value across various industry sectors .
• ATP ( Available To Promise ): the quantity of a product that can be promised to customers based on current inventory levels and production capacity .
• BOM ( Bills of Materials ): a list of raw materials , components , assemblies , and other items required to produce a product .
• BOP ( Bills of Processes ): a list of instructions , steps , and procedures required to produce a product .
• CTP ( Capable to Promise ): a metric to determine the earliest possible delivery date for a product based on manufacturing lead time , resource availability , and production capacity .
54 August 2023