Human-in-the-loop automation is emerging as the most practical path for warehouse robotics, as real-world supply chain variability prevents fully autonomous “lights-out” operations from delivering consistent performance.
Forecasting failures in supply chains persist not due to flawed analytics, but because of deeply embedded organizational culture, misaligned incentives, and fragmented planning processes that distort true demand signals.
Despite years of investment in digital tools and AI, supply chain organizations are struggling to turn visibility into action, revealing a growing execution gap driven by misaligned processes, unclear ownership, and limited ROI from technology.
One year after its rebrand, Infios is shifting from identity-building to execution, as rising demand, pragmatic AI adoption, and a focus on speed to value redefine how companies invest in supply chain technology.
UPS’s network-wide RFID rollout signals a shift from event-based tracking to continuous sensing, enabling real-time visibility that drives faster decisions, fewer errors, and greater supply chain flexibility.
Thursday, April 23, 2026 · Andrew Byer and Mike Dobslaw
Operational excellence in supply chain management goes beyond hitting KPIs by consistently delivering stretch-target performance that is efficient, predictable, and sustainable over time.
Wednesday, April 22, 2026 · Mel Mohamednur, Director Analyst, Gartner Supply Chain
Supply chain leaders must move beyond AI readiness to redesign talent, performance metrics, and workflows around human–AI collaboration to unlock real operational value.
Tuesday, April 21, 2026 · Nicolò Masorgo, PhD; Thu Trang Hoang, PhD; David D. Dobrzykowski, PhD; John E. Bell, PhD; and Morgan Swink, PhD
E-commerce late orders are driven by a breakdown between warehouse operations and transportation, and can be mitigated through early detection thresholds, strategic deprioritization, and simplified order flows.
Retail inventory inaccuracies are less about theft and more about outdated accounting methods like the retail inventory method that distort stock visibility, forecasting, and replenishment decisions.
Supply chains are no longer constrained by data scarcity but by slow, unclear decision-making processes that prevent organizations from acting on insights in real time.
U.S. importers are overwhelmed by supply chain data and trade signals, but the real challenge is not access to information, it’s assigning clear ownership to interpret risk, prioritize action, and respond in time.
Airline source-to-pay (S2P) transformation shifts procurement from fragmented cost control to integrated value realization by connecting contracts, systems, and operational spend across the enterprise.
Automation-first warehouses succeed or fail based on software architecture, specifically how SaaS WMS, automation systems, and integrations are orchestrated as a unified, event-driven platform.
AI does not eliminate supply chain constraints, it shifts them to data quality, decision governance, and human judgment, creating new operational challenges that determine competitive advantage.
Friday, April 10, 2026 · Prabhat Rao Pinnaka, Sukanya Bollineni and Senthil Thiyagarajan
Predictive models and control towers have given supply chain leaders more signal than ever. The problem is not the volume of signal, it is that signal without context cannot tell you what to do. That gap is where AI-driven risk management breaks down.
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