Tech Supply Chain Solutions

Supply chain isn't 1 job. It's 12 roles in a relay, and AI is already running parts of the track. Most planners ask the wrong question: "Will AI replace me?" The honest answer: AI is not replacing roles. It's eating specific tasks inside each role. Some roles lose 60% of their daily work. Others lose 10%. And a few get harder, not easier. Here's how the 12 SCM roles look in 2026, and what AI is actually doing inside each one 👇 🔹 Demand Planner AI generates the baseline, cleans outliers, models promo lift. The planner stops tuning models to make the number look right. 🔹 Supply Planner AI nets requirements and ranks exceptions. Out of 5,000 lines, it shows you the 50 that matter. 🔹 Master Scheduler Solvers handled sequencing for years. Agents finally make the output usable on Monday morning. 🔹 Production Planner A line goes down at 09:00. AI reschedules the day before you finish your first coffee. 🔹 Inventory Planner Safety stock recalc, slow mover detection. In mature setups, 70% of this is already on autopilot. 🔹 S&OP / IBP Manager AI drafts the scenarios, the gap narrative, the exec pre-read. The planner still owns the room. 🔹 Strategic Buyer Co-pilots crunch spend data and build supplier shortlists. The negotiation stays human. 🔹 Tactical Buyer PR-to-PO, 3-way match, expedite chasing. This is the role most exposed to disappearance. 🔹 Logistics Planner Mode selection and load building used to be planner intuition. AI now optimizes both, hour by hour. 🔹 Warehouse Planner Slotting and labor balancing handled inside the WMS, with no meeting required. 🔹 Capacity Planner Concurrent planning made this a real-time job (Kinaxis, o9, OMP). Weekly capacity reviews are dead. 🔹 Control Tower Analyst Agents read the data and write the alert. The analyst still has to make the call. Every role still needs a human. But the work inside each role is shifting fast. The planners who'll matter in 3 years aren't the ones who fear AI. They're the ones who already let it do the boring 60%. 👉 Which of these 12 roles is yours? And how much of your weekly work has AI already touched? ♻️ Repost to share with a planner who's still asking the wrong question. 🔔 Follow Sergey Masyagin for insights on AI Supply Chain Architecture. Hashtags: #SupplyChain #SupplyChainPlanning #DemandPlanning #SupplyPlanning #S&OP #IBP #Kinaxis #ControlTower #SCM

The growing complexity of supply chain interdependencies is creating significant cybersecurity risks. In my latest article for the World Economic Forum’s Centre for Cybersecurity, I outline five key risk factors and what organisations must do to mitigate them: 1️⃣ Cyber Inequity – Large organisations are improving cyber resilience, but SMEs remain vulnerable. They must view cybersecurity as a business priority, while industry collaboration and policy support can help bridge the gap. 2️⃣ Limited Supply Chain Visibility – Expanding supply chains make it harder to assess supplier security. Without clear incentives, compliance gaps persist, increasing exposure to cyber threats. 3️⃣ Third-Party Software Vulnerabilities – AI and open-source adoption introduce new risks, yet only 37% of organisations assess AI tool security before deployment. A structured security framework is essential. 4️⃣ Dependence on Critical Providers – Over-reliance on a few key suppliers creates systemic points of failure. Resilient IT architectures and strong business continuity planning are critical. 5️⃣ Geopolitical Risks – Cyber threats are increasingly shaped by global tensions, disrupting supply chains and increasing attack sophistication. Organisations must integrate geopolitical risk assessments into their cybersecurity strategies. 𝗪𝗵𝗮𝘁’𝘀 𝗡𝗲𝘅𝘁? Organisations must prioritize visibility, support smaller partners, and invest in resilience. Strong business continuity planning, robust IT management, and proactive threat detection are non-negotiable. Cybersecurity is not just an IT issue—it’s a strategic imperative. Read the full article here: https://lnkd.in/g-yQ2QRa #CyberSecurity #SupplyChain #AI #RiskManagement

Indian drones just delivered food in Nepal where helicopters couldn't land and trucks couldn't reach. Last month at the South Asia Drone Forum, Skye Air delivered food and essentials in Kathmandu using their flagship drone. Far from being just another tech demo, this flight made history as Nepal's first commercial drone food delivery. This breakthrough addresses the unique logistics challenges that have plagued the Himalayan region for decades: ● Roads wash away during monsoons. In 2024 alone, floods and landslides in Nepal resulted in 224 deaths and 158 injuries ● Landslides block critical supply routes, affecting over 16,000 families during the 2021 Nepal monsoon ● Entire communities get cut off in winter, with delivery times slowed by up to 20 times compared to drone alternatives ● Emergency supplies face unpredictable delays, while drone deliveries can operate at 70% lower operational costs than traditional vehicles I've seen similar challenges in Northeast India. The mountainous terrain and seasonal flooding in states like Manipur and Arunachal Pradesh regularly cut off communities from essential supplies, sometimes for weeks at a time. The economics are compelling too. In terrain where a single truck delivery can cost ₹25,000+ and take up to a week, drone deliveries cost approximately ₹7,500 and arrive within hours. What's interesting is how Indian innovation is addressing these regional problems. Skye Air has already completed over 2 million deliveries across India. Now they're bringing that expertise across borders. This cross-border cooperation signals something bigger than that: 👉 India is becoming South Asia's drone innovation hub by creating faster, cheaper delivery networks that overcome natural barriers and save lives during emergencies. Consider how your business could incorporate aerial logistics to reach previously inaccessible markets. Which logistics problem could drones solve for you?

I watched a robot deliver food from a restaurant two blocks away. It was ridiculous and SO F**KING COOL! Who is shaping the future of autonomous food delivery? Coco: The new OpenAI partnership and fresh $122M in Series B funding for enhanced path planning lays the foundation for market dominance Manna Air Delivery: 3-minute drone deliveries are proving the speed advantage Wing: Multi-modal partnerships (see: Serve Robotics collab) are expanding their addressable market Nuro: Licensing pivot + deepening relationships with Uber highlights strategic focus to become the foundational autonomous vehicle technology provider Starship Technologies: With 8M+ deliveries; scaling from 50 campuses to 150 cities globally shows sustainable execution Zipline: Remains the drone delivery heavyweight with restaurant partnerships pushing beyond traditional medical deliveries Several key categories define the autonomous food delivery market: → Sidewalk Delivery Robots: Small autonomous robots designed for short-distance deliveries in pedestrian areas → Road-Based Autonomous Vehicles: Larger autonomous delivery vehicles capable of operating on public roads → Hybrid Remote-Operated Systems: Robotics solutions combining autonomous navigation with remote human oversight → Multi-Modal Delivery Platforms: Integrated systems combining various autonomous delivery methods with traditional logistics → Indoor/Controlled Environment Robots: Specialized robots for deliveries within buildings, hospitals, and controlled facilities → Drone Delivery Integration: Aerial autonomous delivery systems for rapid food delivery Market leaders in each category are emerging. But, while the market leaders are gaining commercial traction, winning key partnerships, and attracting funding, several players, including once-promising names are struggling to deliver (pun intended). In a market that once was betting on promise, execution is now table stakes. What recent highlights tell us about the evolution of the market: ↳Market leaders are now making millions of deliveries with 99% autonomy; proving scalability ↳Major platforms (Uber, DoorDash) are all-in with partnerships, driving adoption and revenue to fuel the next wave of innovation ↳Tech advancements and maturation are enabling the market shift from confined, controlled pilots to complex urban deployments ↳Investors are willing to write (big) checks to companies that are proving commercial traction with Nuro, Coco, Manna, and Neolix all raising fresh rounds this year We're witnessing the transition from “oh, look a robot” to "scalable last-mile infrastructure." 2025 is shaping up to be the year your Uber Eats or DoorDash driver isn’t a driver at all. P.S. Want more insights on the companies building the future of food delivery? Comment "insights delivered" below for *free* access to CB Insights' data and insights on the autonomous food delivery markets.

A quiet reminder for every technology leader: A malicious npm package recently infiltrated GitHub Actions pipelines by impersonating a legitimate module. No phishing. No user error. No suspicious email. Just a dependency that looked familiar… and slipped directly into CI/CD. This incident impacted teams across the US, India, and Europe, proving one thing very clearly: The software supply chain is now the primary attack surface. What happened here is not a “developer mistake.” It’s a systemic gap in how organizations treat pipelines and open-source dependencies. 📌 Most companies still operate with an outdated belief: “Secure the endpoints and the users, and the environment is safe.” But today’s attackers aren’t chasing employees. They’re targeting the build systems that ship your product. As leaders, we need to ask tougher questions: Do we have visibility into every dependency entering our pipeline? Do we validate integrity before automated builds run? Are we monitoring for package impersonation and typosquatting? And most importantly, who owns supply-chain security in our org? This npm incident is not “just another breach.” It’s a strategic signal. If attackers can compromise the pipeline, they can compromise the brand, the customer, the product and the trust we’ve built over years. Supply-chain validation, dependency governance, and CI/CD monitoring are no longer ‘future improvements.’ They’re core leadership responsibilities. The question isn’t whether your pipeline is targeted. It’s whether you’re prepared before it is. 📌 P.S. As a trusted cybersecurity specialist, I can help you assess your cybersecurity risks and recommend the right solutions for your business. Please feel free to contact me if you have any questions or need assistance. #cybersecurity

⚙️ Planning without constraints is just theory. Advanced Planning & Scheduling (APS) brings planning closer to real-world execution. Traditional systems often assume unlimited capacity — but factories, machines, labor, and transport all have limits. APS is designed to plan with reality in mind. Here’s what APS really does 👇 🧠 What is APS? A constraint-based optimization and simulation system that enables real-time, finite-capacity planning and decision support across the supply chain. 🔍 Core Capabilities ⚖️ Optimization Balances cost, service levels, capacity, inventory, and profitability. 🔮 Simulation (What-If Analysis) Tests scenarios like demand spikes, supplier delays, or capacity reductions before decisions are made. 🏭 Finite Capacity Scheduling Plans using actual machine, labor, and shift constraints. 🧩 Multi-Constraint Planning Simultaneously considers materials, lead times, transport, and operational rules. 📊 APS vs Traditional MRP MRP → Assumes infinite capacity & reacts after issues occur APS → Considers real constraints & enables proactive decisions 🧠 Simple Memory Framework MRP plans materials → ERP executes transactions → APS optimizes decisions Modern supply chains don’t just plan orders — they simulate outcomes before execution. Is your planning system reactive or predictive? #SupplyChain #APS #ProductionPlanning #SupplyChainPlanning #MRP #ERP #Manufacturing #OperationsManagement #DigitalSupplyChain #Industry40 #DecisionSupport #SupplyChainManagement

𝗕𝗲𝘆𝗼𝗻𝗱 𝗭𝗲𝗿𝗼 𝗧𝗿𝘂𝘀𝘁: 𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲-𝗦𝘁𝗮𝘁𝗲 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗣𝗮𝗿𝗮𝗱𝗶𝗴𝗺 𝗳𝗼𝗿 𝗚𝗹𝗼𝗯𝗮𝗹 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲𝘀 Zero Trust has become the dominant security paradigm, yet as I've implemented it across multiple global enterprises, I've observed a fundamental limitation: it's still anchored in a perimeter mindset with more sophisticated boundaries. The future-state security paradigm must evolve beyond this approach. After collaborating with security leaders across industries, I see the emergence of "Adaptive Resilience Architecture." Instead of focusing primarily on preventing unauthorized access, this architecture accepts breach inevitability and designs for rapid reconfiguration. It combines three capabilities absent from traditional Zero Trust models: 𝟭. 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴 Rather than static permission mapping, future security frameworks are integrating real-time behavioral analysis that can detect subtle pattern shifts even in authorized access. This helps identify compromised credentials and insider threats that pass traditional Zero Trust verification. At one financial services organization, implementing behavioral models identified 14 high-privilege accounts exhibiting anomalous patterns that perfectly matched authentication requirements but were actually compromised. 𝟮. 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 Security architectures are evolving from alerting to autonomous response. The most mature organizations can detect, contain, and remediate threats across their infrastructure without human intervention for common attack patterns. Through autonomous security measures, one healthcare organization reduced its response time from 42 minutes to 3.8 seconds, preventing what would have been a significant data breach. 𝟯. 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 The most sophisticated breaches now target upstream suppliers rather than direct infrastructure. The future security model extends behavioral monitoring, automated response, and continuous validation across digital supply chains. One manufacturer discovered their most significant security vulnerability in a third-party code library used by their IoT sensors—invisible to traditional Zero Trust models. The organizations achieving truly resilient security postures are those building adaptive architectures that don't just verify access but continuously validate behavior, autonomously respond to threats, and extend security governance across their digital ecosystem. The question is how quickly you can implement a truly adaptive security architecture before the threat landscape outpaces traditional approaches. 𝐷𝑖𝑠𝑐𝑙𝑎𝑖𝑚𝑒𝑟: 𝑉𝑖𝑒𝑤𝑠 𝑒𝑥𝑝𝑟𝑒𝑠𝑠𝑒𝑑 𝑎𝑟𝑒 𝑝𝑒𝑟𝑠𝑜𝑛𝑎𝑙 𝑎𝑛𝑑 𝑑𝑜𝑛'𝑡 𝑟𝑒𝑝𝑟𝑒𝑠𝑒𝑛𝑡 𝑚𝑦 𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑟𝑠. 𝑇ℎ𝑒 𝑚𝑒𝑛𝑡𝑖𝑜𝑛𝑒𝑑 𝑏𝑟𝑎𝑛𝑑𝑠 𝑏𝑒𝑙𝑜𝑛𝑔 𝑡𝑜 𝑡ℎ𝑒𝑖𝑟 𝑟𝑒𝑠𝑝𝑒𝑐𝑡𝑖𝑣𝑒 𝑜𝑤𝑛𝑒𝑟𝑠.

Applying Japanese Supply Chain Concepts — With Real Metrics That Matter 🇯🇵📊 Japanese supply chain philosophies aren’t just ideas—they translate directly into measurable performance. Here’s how I connect them to real planning and S&OP metrics: 🔹 Just-in-Time (JIT) Focus: Right inventory, right time 📊 Metrics: • Inventory Turns ↑ • Days of Inventory on Hand (DOH) ↓ • Obsolescence & expiry ↓ 🔹 Kaizen (Continuous Improvement) Focus: Small improvements, sustained results 📊 Metrics: • Forecast Accuracy (MAPE) ↓ • Bias reduction over planning cycles • Planning cycle time ↓ 🔹 Kanban Focus: Pull-based flow & visibility 📊 Metrics: • Stockout frequency ↓ • Replenishment lead time ↓ • Adherence to min–max levels ↑ 🔹 Heijunka (Demand & Production Leveling) Focus: Stability over reactivity 📊 Metrics: • Schedule Adherence ↑ • Capacity utilization stability ↑ • Expedited orders ↓ 🔹 Jidoka (Built-in Quality & Exception Management) Focus: Stop issues before they scale 📊 Metrics: • Exception resolution time ↓ • Service Level / OTIF ↑ • Planner firefighting hours ↓ These concepts reinforce a powerful truth: A mature supply chain is not reactive — it is leveled, visible, and continuously improving. Would love to hear how others link lean principles to KPIs in their planning processes.

BUILDING A TAX EFFICIENT SUPPLY CHAIN (TESC): LEVERAGING DTTs AND FTAs FOR GLOBAL SUCCESS INTRODUCTION: A Tax Efficient Supply Chain (TESC) minimizes tax liabilities and tariffs by leveraging Double Taxation Treaties (DTTs) and Free Trade Agreements (FTAs). This approach reduces cross-border costs, boosts profitability, and ensures compliance. DTTs: A TOOL TO AVOID DOUBLE TAXATION A DTT prevents income from being taxed twice — in the source and recipient countries. Key benefits include: Lower Withholding Taxes – Reduces taxes on dividends, interest, and royalties. Tax Credits/Exemptions – Offsets taxes paid abroad. Profit Repatriation – Ensures smooth profit transfers. Double Taxation Prevention – Covers goods, services, and IP. Example: A tech firm locates IP in Ireland, benefiting from reduced royalty taxes. FTAs: BOOSTING CROSS-BORDER TRADE FTAs eliminate or reduce tariffs and trade barriers. Benefits include: Tariff Elimination – Cuts import/export costs. Simplified Customs – Faster border movement. Rules of Origin (ROO) – Provides preferential tariffs. Market Expansion – Enables easier market entry. Example: A company sources from Vietnam and exports to the EU, enjoying zero tariffs via the EU-Vietnam FTA. INTEGRATING DTTs AND FTAs: 1. Hub Strategy: Establish hubs in DTT/FTA-rich countries (e.g., Singapore, Switzerland). 2. Import/Export Savings: Source raw materials from FTA partners. 3. IP Placement: House IP in DTT-friendly countries. DESIGNING FOR TAX EFFICIENCY: Align Transfer Pricing with Customs – Avoid disputes through DTT-compliant pricing. Bonded Warehouses – Defer duties until goods enter markets. VAT/GST Planning – Optimize indirect tax structures. CHALLENGES: Complex Compliance – Regular audits ensure smooth navigation of multiple treaties. Operational Costs – Conduct feasibility studies before establishing entities. Customs Risks – Keep detailed records to avoid misclassification. CASE STUDY: A global electronics firm used Switzerland as a hub, with manufacturing in Vietnam and China. DTTs and FTAs reduced taxes by 20% and tariffs by 15%, accelerating market entry. CONCLUSION: TESC – A WINNING FORMULA FOR GROWTH Integrating DTTs and FTAs into your supply chain is a strategic advantage that cuts costs, enhances profitability, and streamlines operations. A well-designed Tax Efficient Supply Chain (TESC) not only improves compliance but positions your business to thrive in global markets. Unlock new value today—optimize your supply chain with smart tax strategies!

#Agentic_AI_Is_Reshaping_Supply_Chains: Key Takeaways from AWS re:Invent 2025 #AWS_re:Invent 2025 marked a turning point for enterprise AI, over 1500 booths and various sessions. The message was clear: AI agents are moving from pilots to production, powered by industrial-scale infrastructure and a rich ecosystem of models and tools. For supply chain leaders, this isn’t just tech news—it’s execution at scale. What’s New from AWS? 🔴 Custom Silicon for Scale: Trainium3, AWS’s first 3nm AI chip, delivers 4.4× more compute performance and up to 50% lower training and inference costs—accelerating optimisation cycles for complex supply chain models. 🔴 Amazon Nova 2 Model Family: ✅ Nova 2 Lite: Cost-effective reasoning for everyday workflows like inventory planning. ✅ Nova 2 Pro: Advanced reasoning for multi-echelon planning and risk mitigation. ✅ Nova 2 Sonic: Real-time speech-to-speech for conversational AI in operations. ✅ Nova 2 Omni: First multimodal model for text, images, video, and audio—ideal for visual audits. 🔴 Agentic Platforms: Bedrock AgentCore now supports frameworks like CrewAI and LangGraph for orchestrating long-running workflows with compliance guardrails. 🔴 Natural-Language Interfaces: Amazon Q Business integrates with Bedrock, enabling planners to ask questions, trigger workflows, and get explainable recommendations—all in plain language. Why This Matters for Supply Chain Agentic AI is no longer theoretical. At Genpact, we’ve piloted Process-to-Agent (P2A) initiatives with AWS to automate inventory configuration using Bedrock, Q Business Workflow Automate, and EventBridge. Results: 📍 Dynamic parameter optimisation (safety stock, min/max levels, reorder points). 📍 80% first-pass automation, with human-in-the-loop for exceptions. 📍 Improved ROI over three years—reducing working capital days and boosting fill rates. This aligns with AWS’s vision: connected data + agentic orchestration + human oversight. Imagine planners focusing on strategy while agents continuously plan, simulate, and act. The Path Forward ✔️ Engage AWS Professional Services for production-ready Agentic AI solutions. ✔️ Adopt Amazon Bedrock AgentCore to build autonomous agents at scale. Leverage AWS Supply Chain+AmazonQ for predictive planning and risk mitigation. ✔️ Collaborate on GTM with AWS Practice teams for market penetration & monetisation. ✔️ Continue to integrate natural-language interfaces & plan for governance with AWS’s policy engine for AgentCore. The era of static supply chains is over. With AWS’s advancements & Genpact’s agentic roadmap, we’re moving toward near-autonomous, resilient networks that deliver measurable business outcomes. If you’re exploring how to make your supply chain future-ready, let’s connect—or set up a demo to see these capabilities in action. #SupplyChain #AWSreInvent #AgenticAI #AmazonBedrock #AmazonQBusiness #InventoryOptimisation #Resilience #AWSPartner Gopal VK | James Avellone | Shriram Bidkar