Troy Montgomery

Most organizations talk about visibility—but few truly achieve it. Are you one of them? In today’s fast-paced, disruption-prone environment, having real-time visibility across your supply chain isn’t a luxury—it’s a necessity. Yet, fewer than 10% of companies surveyed can say they have end-to-end insight into their supply chain operations. So what’s standing in the way? And more importantly—how do you overcome it? “Understanding the Foundation of Visibility” is the first whitepaper in a powerful new series by NCS Partners, designed to help supply chain leaders break down silos, align teams, and turn fragmented data into actionable insight. Download this white paper to learn how to: Identify the five most impactful focus areas for building end-to-end visibility Align leadership and secure cross-functional buy-in to drive transformation Build a clear vision and roadmap to avoid common visibility pitfalls Integrate distributed data sources to enable real-time, actionable insight Promote continuous improvement and communication across teams   Whether you’re just beginning your visbility journey or ready to refine your approach, this foundational guide offers expert-backed strategies used by top-performing organizations.   Download the “Understanding the Foundation of Visbility” white paper here to learn more  

Companies are rapidly integrating generative AI into procurement and sourcing decisions. The promise is obvious. AI can read thousands of pages of supplier proposals faster than any human team, summarize technical requirements in seconds, and create the appearance of consistency and objectivity in evaluation. But there is an important distinction managers are starting to overlook. The same AI system that performs extremely well at identifying whether a supplier meets minimum requirements may perform much less reliably when judging which supplier is truly better. Recent research published in the Journal of Business Logistics examined this issue by comparing how large language models evaluated supplier bids against evaluations completed by experienced procurement professionals. It analyzed 123 supplier proposals tied to 31 public procurement projects conducted by the State of Ohio between 2023 and 2024. The projects involved complex IT services contracts, many containing large, text-heavy bid packages requiring evaluative judgment rather than simple arithmetic comparisons. The researchers tested three reasoning-oriented AI models: OpenAI o3, Grok-3-Mini, and DeepSeek R1. They then compared their evaluations against human procurement scores. The findings revealed a surprisingly clear pattern. AI performed well when evaluating compliance signals. These are signals tied to baseline qualifications and technical requirements. Does…