Negotiation Automation Platform
2 MOTIVATION
Enhancing supply chain efficiency is of utmost importance . Failure to procure or supply appropriate products or services from or to the right partners at the right prices , quantities , timings , and conditions can lead to significant losses , such as shortages of raw materials or essential resources , increased inventory , higher internal management costs , and breaches of customer contracts .
Supply chain efficiency has two main challenges . The first is based on a company ' s ability to consistently provide high-quality products and services at low costs with timely delivery . This involves continuous efforts to improve production methods by implementing technologies such as AI and IIoT . The second challenge concerns the ability to reach agreements with trading partners as quickly , accurately , and cost-effectively as possible . However , in most current business practices , coordination relies heavily on human labor , issues like increased labor costs , decreased accuracy , and longer lead times .
Failing to address these challenges can have a negative impact on the survival of companies as well as the preservation of essential societal functions . Factors contributing to this situation can include trends in manufacturing to reduce lot sizes ( for mass customization ) and the intensification of competition for resources driven by disasters , wars , pandemics , and aging populations . Additionally , the increasing complexity of products and services , diverse customer demands , and heightened competition among companies exert pressure for faster , more accurate , and sophisticated agreement-making processes .
In this article , we introduce the Negotiation Automation Platform ( NAP ), an innovative solution that employs automated negotiation AI technology to streamline agreement-making between economic entities . We will discuss the platform ’ s concept , technical and business overviews , and case studies , focusing on the application of the platform in coordinating conditions between sellside and buy-side parties in manufacturing , trade and logistics service arrangement cases .
In Automated Negotiation , AI serves as an agent to conduct negotiations on behalf of individual companies with their trading partners . As an essential operation , automated negotiation AI can repeatedly create and send offers of agreement conditions to negotiation partners . It can also judge and respond to offers received from partners through messages via the platform , aiming to reach agreements with trading partners ( Figure 2-1 ). Compared to human-led negotiations , AI agents can execute these operations with much greater speed , accuracy , and sophistication , resulting in a higher likelihood of reaching a better agreement with counterparties . The main motivation for adopting NAP is to contribute to the second aspect of supply chain efficiency and the efficiency of coordinating transaction conditions between economic entities .
Journal of Innovation 55