Comprehensive information about global sourcing and procurement strategies, covering software, spending analysis, order management, supplier evaluation and e-Procurement.
Agentic AI is transforming supply chains from deterministic, rule-based systems into adaptive, insight-driven networks that prioritize real-time decision-making, root-cause analysis, and capital-efficient innovation.
Procurement is shifting from cost-driven spend aggregation to risk-adjusted sourcing strategies as tariffs, geopolitical volatility, and supply chain disruptions force companies to prioritize resilience over pure savings.
Monday, March 16, 2026 · Eva Ponce, Vi Duong and Nic Holwerda
Dynamic Multi-Echelon Inventory Optimization enables supply chain leaders to balance service levels and working capital by optimizing inventory across the entire network rather than individual locations.
Procter & Gamble’s One Supply Chain strategy is an example of how aligning operations, forecasting, logistics, and supplier collaboration around the “Perfect Order” framework enables companies to deliver the right product, at the right time and cost, while turning…
True supply chain visibility in 2026 depends less on tracking shipments and more on synchronizing data across systems, ensuring a trusted single source of truth, and building AI-driven decision tools on high-quality, interoperable freight data.
Despite shifting headlines in the freight market, cargo theft, fraudulent carriers, regulatory enforcement, and tightening capacity are quietly increasing transportation risk, making continuous carrier vetting, human oversight, and proactive risk management essential for…
While enthusiasm for generative AI in supply chains is high, most companies remain trapped in pilot programs because successful deployment requires workflow-level problem definition, embedded agents, and disciplined governance rather than simply applying new AI models.
Pharmaceutical supply chains are among the most complex in the world, combining global sourcing dependencies, strict regulatory oversight, temperature-controlled logistics, and geopolitical and cybersecurity risks that make planning, manufacturing, and distribution far more…
Tuesday, March 3, 2026 · Saravana Venkatachalam and Arunachalam Narayanan
Supply chain planning tools are not new. Most organizations today rely on established systems for demand planning, supply planning, inventory optimization, and network design. These tools are typically operated in a human-in-the-loop model: planners run scheduled processes…
Circular supply chains are emerging as a foundational operating model for the circular economy, enabling organizations to drive sustainability, resilience, and long-term value through closed-loop material flows, strategic partnerships, and disciplined execution.
Tuesday, March 3, 2026 · Mark Trowbridge, CPSM, CSP, C.P.M. MCIPS, President of Strategic Procurement Solutions LLC
Suppliers can “evaporate” without warning, making proactive supply chain risk management essential. Procurement leaders can take “intelligent risks” rather than defaulting to overly cautious, bureaucratic processes that hinder performance. He outlines five practical,…
Tuesday, March 3, 2026 · Kevin O’Marah, co-founder, Zero100
Global trade wars and geopolitical tensions in 2026 are not breaking modern supply chains, but the rising cost of resilience is increasingly being passed on to consumers, creating price pressure, brand risk, and trust challenges.
Monday, March 2, 2026 · Christopher A. Boone, Ph.D., Associate Professor, Mississippi State University; Karl B. Manrodt, Ph.D., Professor, Georgia College and State University; M. Douglas Voss, Ph.D., Professor and Scott E. Bennett Arkansas Highway Commission Endowed Chair, Uni
Our survey team discovers a persistent gap between knowing what’s possible in logistics and actually putting it into practice. From AI adoption to talent development and technology integration, leaders understand the path forward, but action still lags.
APQC research shows that while organizations pursue aggressive AI adoption and Net Zero emissions goals, most fail to account for AI’s energy use and GHG impact—creating a growing disconnect between digital transformation and climate commitments
Supply chains are expanding the use of AI across functions, and that expansion means more data storage and more computation, which all require more electricity use and potentially more greenhouse gas (GHG) emissions during electricity production.
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