Andrea Sassaroli

Most supply chain AI talk is still about better forecasts. The more interesting shift this week is AIs that negotiate and match with each other. Two new papers stood out: Researchers let AI agents act as buyer and supplier and negotiate thousands of deals. The AIs almost always reached agreement — but they took far too long. That delay alone wiped out a big part of the value both sides could have created. Which AI brand you choose often decided who walked away with more, more than how “smart” the model was. Another team built a small group of specialist AIs instead of one big model. One diagnoses what the buyer really needs, another finds options, another scores the fit. Working as a team, they clearly beat both old keyword search and single AIs at matching real supply with demand. The practical takeaway: Automating the transaction is moving fast. Automating trust, judgment, and the messy middle is not. If you’re connecting companies in 2026, the scarce work is no longer “can we call an API.” It is: Which agent is allowed to commit? How do we keep the relationship intact when things go wrong? Where does a human still need to own the outcome? If you’re testing agent-to-agent quoting, matching, or exception handling with real suppliers — not just a pilot slide — I’d like to compare notes on what actually held up.

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𝐒𝐮𝐩𝐩𝐥𝐲 𝐂𝐡𝐚𝐢𝐧 𝐃𝐞𝐬𝐢𝐠𝐧: Centralize for cost or Decentralize for speed? When designing a supply chain network, leaders face a foundational choice: Centralize or Decentralize key functions like warehousing, production, or planning. 𝐂𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐳𝐞𝐝 𝐦𝐨𝐝𝐞𝐥𝐬 (e.g., a few large distribution centers) drive economies of scale, leading to lower inventory holding costs and optimized transportation. But they introduce single points of failure and increase customer lead times for distant markets. 𝐃𝐞𝐜𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐳𝐞𝐝 𝐦𝐨𝐝𝐞𝐥𝐬 (e.g., smaller, regional hubs) significantly improve speed and responsiveness to local markets. However, they introduce inventory complexity and higher fixed operating costs. The Question for You: Given today's volatile environment, is the traditional pursuit of maximum centralization for cost-saving still a viable strategy? Specifically, when and why might you choose a more decentralized or hybrid supply chain design, even if the analysis shows a higher immediate operating cost? What is the value of that improved responsiveness?

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Gartner predicts that by 2030, 50% of new warehouses in developed economies will be designed as robot-centric facilities. In this model, the human role is increasingly shifting toward handling exceptions and making decisions that cannot be fully automated. This is also changing the role of WMS. Today, a warehouse manager often starts the day by checking: 📊 multiple dashboards, 📦 inventory levels, ⏱️ shift performance, 🚧 lists of delays and exceptions. Ultimately, the system should perform part of this analysis for them and answer a single question: “Which 3 things require my decision today?” For example: → the picking zone is operating below standard, → transit time between specific locations is increasing, → the turnover rate of a specific product deviates significantly from the norm. This is the direction we are taking with PINQUARK WMS - designing the system not just to collect data, but to help highlight where human intervention is truly needed. Because the future of WMS isn't about displaying more information. It's about displaying the right information at the right time.

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Italy’s leading book wholesaler, Emmelibri, boosted warehouse productivity by 25%—hitting up to 90 pick lines per operator per hour—after adopting Manhattan SCALE WMS. The unified, cloud-ready platform gave them the flexibility to adapt quickly to shifting market demands while maintaining speed and accuracy. As their Application Development Director put it, SCALE lets them meet “the new challenges of a continuously changing marketplace” with confidence. ➞https://bit.ly/4fvWl8u #WMS #Warehouses

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🔥 Smart KPIs for Modern Supply Chain Professionals (with Real Formula Impact) 🔥 💡 Every efficient supply chain runs on measurable intelligence, not assumptions. As a global supply chain professional, I’ve learned one universal truth — 👉 “If you can measure it, you can improve it.” Here are 7 essential Supply Chain KPIs every professional and student must understand 👇 1️⃣ On-Time Delivery (OTD%) ➤ Formula: OTD% = (On-Time Deliveries / Total Deliveries) × 100 ➤ Impact: Measures customer reliability. A 5% improvement = 2% increase in customer retention. 2️⃣ Inventory Turnover Ratio (ITR) ➤ Formula: ITR = Cost of Goods Sold / Average Inventory ➤ Impact: High turnover = faster cash cycle. Ideal: 6–10 turns/year. 3️⃣ Perfect Order Rate (POR) ➤ Formula: POR = (Error-Free Orders / Total Orders) × 100 ➤ Impact: Tracks end-to-end accuracy — from picking to delivery. Top companies maintain >95%. 4️⃣ Freight Cost per Unit (FCU) ➤ Formula: FCU = Total Freight Cost / Total Units Shipped ➤ Impact: Reveals logistics cost efficiency. Reducing FCU by 0.5% can save millions annually. 5️⃣ Warehouse Space Utilization (WSU%) ➤ Formula: WSU% = (Used Space / Total Available Space) × 100 ➤ Impact: Optimized layout = 15–20% more throughput without expansion cost. 6️⃣ Forecast Accuracy (FA%) ➤ Formula: FA% = [1 – |(Actual – Forecast) / Actual|] × 100 ➤ Impact: Every 1% accuracy improvement reduces excess inventory by ~3%. 7️⃣ Overall Equipment Effectiveness (OEE) ➤ Formula: OEE = Availability × Performance × Quality ➤ Impact: Gold standard for manufacturing. World Class OEE = 85%+. 🚀 These KPIs are more than numbers — they are decision enablers. ✅ Professionals use them to enhance efficiency. ✅ Students use them to understand real business logic. ✅ Leaders use them to drive transformation. 💬 Which KPI do you track most often in your organization? 🔁 Share this post to help your team or students understand practical supply chain analytics. #SupplyChain #SupplyChainManagement #OperationsExcellence #OperationsManagement #Logistics #Procurement #WarehouseManagement #InventoryManagement #FleetOptimization #Distribution #TransportationManagement #DigitalTransformation #SmartLogistics #DataAnalytics #BusinessAnalytics #SupplyChainAnalytics #PerformanceManagement #ProcessImprovement #ContinuousImprovement #LeanSixSigma #KPI #OEE #ForecastAccuracy #WMS #TMS #Sustainability #GlobalOperations #Leadership #BusinessIntelligence #SupplyChainStrategy #SantanuManna

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Supply Chain Watch — 3 Signals CEOs Should Not Ignore Three forces now shape supply chain performance more than cost or efficiency. 1️⃣ Critical Raw Materials = Strategic & Legal Risk China controls refining for most strategic minerals and is using it as leverage. Diversification is slow and often illusory. At the same time, criminal groups are moving into mining and logistics, creating sanctions and counter-terrorism exposure for unwitting firms. CEO takeaway: Critical materials are now a board-level risk issue. Map China-controlled processing, tier-2/3 exposure, and legal risk — not just suppliers. 2️⃣ Geopolitical Fragmentation Is Structural The global economy is splitting into blocs. Industrial policy, export controls, and “friend-shoring” are permanent features, not temporary noise. Neutral supply chains are disappearing. CEO takeaway: Design bloc-aware supply chains with built-in optionality. Assume policy shocks and avoid single-corridor dependence. 3️⃣ Skills Shortages Are the Hidden Bottleneck Capital and policy are accelerating reshoring, defence, and energy projects — but skilled planners, engineers, and trade specialists are in short supply. Complexity is rising faster than capability. CEO takeaway: Supply chain talent is a strategic constraint. Invest in skills, simplify decision-making, and reduce dependency on a few key individuals. Bottom line: Supply chains are now shaped by power, law, and people. CEOs who adapt their networks and talent strategies will gain resilience. The rest will keep firefighting. Watch the macro. Act on the micro. Patrick Daly ★ The Macro-to-Micro Strategist™

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Most supply chain decisions are still tested in production. And that’s the real risk. Digital Twins change that. A digital twin is a live, virtual replica of your supply chain, powered by real operational data, where decisions can be validated before execution. It allows teams to answer questions like: • What if we open more distribution centers? • What if fuel prices increase? • What if delivery frequency changes? • What if demand or supply shifts? Instead of guessing, teams can design, evaluate, and decide — without putting the business at risk. At CPP Consulting, we genuinely believe Optilogic (Cosmic Frog) is the best digital twin technology available today, because it supports real decision-making, not just modeling. Digital twins turn uncertainty into informed decisions. 👉 Let’s build your digital twin together.

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