Enhancing Sourcing Efficacy Through Fact-Based Negotiation: The Role Of Supportive Intelligence

Abstract

In the context of global procurement and sourcing strategies, the integration of Fact-Based Negotiation (FBN) with artificial intelligence (AI) and machine learning (ML) technologies marks a crucial transformative step. This research proposal, entitled
"Enhancing Sourcing Efficacy through Fact-Based Negotiation: The Role of Supportive Intelligence," delves into the significant role AI and ML play in refining FBN—a data-driven approach that embraces objective, transparent and informed decision-making in contract negotiations. The study demonstrates how the adept incorporation of advanced analytics and automation can substantially streamline negotiation processes within organizations, leading to improved outcomes, higher efficiency, and reduced costs.

This research heralds the importance of systematic and data-centric approaches in today's digital era, where data equates to value. It advocates for novel sourcing negotiation strategies through a meticulous literature review and empirical analysis, specifically exploring AI and ML within the parameters of lean thinking. The literature reviewed highlights the urgent requirement to modernize conventional negotiation practices to excel in the evolving data-centric business environment.
Moreover, the research illuminates the pivot essential to adapt sourcing methodologies, proposing that the synergistic application of FBN, AI, and ML can induce a paradigm shift in procurement processes. This alignment is anticipated to set a new standard for management and operations, applicable across various industry sectors.