Role of Technology in Supply Chain

What is the potential of technology to meaningfully reduce fresh food waste, and in doing so significantly alter a grocery retailer’s P&L? Heading into Groceryshop later this month the challenge of escalating shrink is top of many minds. Much focus is understandably on increasing theft and the impacts of organized crime on retailers and their employees. The largest source of loss for many grocery retailers, though, remains fresh food wastage. Fresh food waste can cost up to 3% of total turnover for some grocers, therefore significant reductions here have the potential to transform the economics of grocery stores that run on such wafer-thin margins. And there’s a greater opportunity, as between 40-60% of fresh produce grown globally is wasted. There’s a clear sustainability and moral imperative to do better. Around the world we’re observing a range of technologies emerging that seek to reduce fresh food waste, and which fall into four broad buckets: 1. Dynamic Pricing tools that utilize AI to automate the mark-down price to ensure products sell out before date expiry, like Ahold Delhaize's Albert Heijn chain is trialing in the Netherlands 2. Produce coatings or protective stickers, that utilize natural antimicrobial compounds to protect against disease and extend shelf life, like Apeel, AgroSustain SA or Stixfresh 3. Ordering or inventory management tools powered by AI that optimize order quantities, manage in-store positions or empower store teams to efficiently allocate rescue channels, such as those from Picadeli, Afresh or Smartway.AI 4. Hydroponic vertical farms, located in-store to dramatically shorten the supply chain and respond quickly to changing demand, like SweGreen currently in ICA Gruppen Sweden and now expanding in EDEKA ZENTRALE Stiftung & Co. KG supermarkets in Germany I’d love to hear your thoughts and other solutions you’re seeing or trialing. Let's chat at Groceryshop!

When I started out in RFID, we worked intently on product-first strategies, how to ensure the right inventory could be in the right place at the right time. As time passed, I worked more on location analytics and then the product cloud concept, exploring how digital twins would live in a universe of interconnected product clouds that shared information. Everything would become smarter, and we would get ecommerce-style data unlock in physical retail. Now we are working on the biggest shift. At Kezzler we're calling it the Data Marketplace. It would have been impossible to deliver without all of the work described above, but is definitely a next chapter. We’re moving to a shared architecture, where suppliers and retailers are connected through a common event repository, using a single language, EPCIS 2.0. It’s not theoretical. It’s working today, at companies like Migros, where together we are delivering: Events, not estimates — decisions based on what actually happened, not batch-level assumptions One version of the truth — suppliers and retailers working from the same data, not reconciling mismatched spreadsheets Frictionless compliance — regulatory reporting that’s a byproduct of good architecture, not an afterthought System-level efficiency — reducing delays and disputes by aligning upstream and downstream processes in real time We're doing this not by the open heart surgery required to build a centralised platform to replace every system, but by connecting existing systems through standards and translation. This isn’t about future potential. It’s about results that compound. And it’s the reason I believe product digitisation matters more today than it ever has. I’d love to hear how others are thinking about this shift — are you seeing signs of a data marketplace in your world too? #DigitalID #DataMarketplace #SupplyChain #Traceability #EPCIS #ProductDigitisation #Kezzler

The efficiency of modern transportation depends on a seamless flow of data, where real-time insights empower fleet managers to optimize routes, reduce delays, and ensure cargo integrity, making every decision more precise and responsive to unpredictable challenges. The transportation ecosystem relies on interconnected systems that transform raw data into actionable intelligence. Sensors track vehicle performance, cargo conditions, and driver behavior, generating real-time data on fuel consumption, harsh braking, or temperature fluctuations. This data is transmitted through advanced communication networks, where it is aggregated and structured for analysis. AI-driven systems identify inefficiencies, predict maintenance needs, and optimize logistics by adjusting routes dynamically. Fleet managers use these insights to improve safety, reduce costs, and enhance delivery reliability. By leveraging technology, businesses can respond swiftly to disruptions, ensuring supply chains remain resilient and adaptive. #SmartLogistics #DataDriven #FleetManagement #DigitalTransformation #SupplyChain

Still managing documents like it’s 2010? 𝐁𝐢𝐠 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐚𝐫𝐞 𝐛𝐥𝐞𝐞𝐝𝐢𝐧𝐠 𝐦𝐢𝐥𝐥𝐢𝐨𝐧𝐬 𝐛𝐞𝐜𝐚𝐮𝐬𝐞 𝐨𝐟 𝐨𝐮𝐭𝐝𝐚𝐭𝐞𝐝 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭. Emails, PDFs, invoices, contracts... scattered, slow, insecure, impossible to track. The real pains we see every day: • No scalability. • Impossible search. • Security gaps and privacy risks. • Compliance failures (GDPR, HIPAA, CBP…). • Skyrocketing operational costs. • Low user adoption (because clunky systems kill adoption). • Outdated, inconsistent, and risky content — created without validation or alignment to company messaging. How do we fix it? ❌ Not with another document system. ❌ Not with off-the-shelf AI. 🎯 𝐈𝐭 𝐭𝐚𝐤𝐞𝐬 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬-𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐜, 𝐝𝐨𝐦𝐚𝐢𝐧-𝐭𝐫𝐚𝐢𝐧𝐞𝐝 𝐀𝐈. What we’re seeing in the real world: • Millions of documents classified and indexed automatically. • Natural language search (“Show me the GDPR contract from 2022”). • Dynamic data protection, spotting risks before they hit. • Automated compliance handling. • AI-generated content aligned with corporate messaging, validated against trusted sources. • Key processes running 25–50% faster. We’re already doing this for logistics, pharma, oil and gas, insurance, and banking leaders. Plain Concepts 🚀 The companies that move first are turning their scattered data into real-time strategic decisions. This isn’t the future. This is happening. Now. Still filing PDFs manually? Your competitor’s AI is already making decisions while you’re still searching for page 12. #GenerativeAI #EnterpriseAI #DigitalTransformation #LIPostingDayApril 

🚢 What’s Shaping Supply Chains Right Now? The past 60 days have brought big shifts in supply chain conversations. Companies aren’t just reacting to disruption anymore—they’re talking about reinvention, exploring new strategies, and figuring out what’s actually feasible. Here are the key themes emerging: 🔹 AI & Automation – The buzz is turning into real-world applications in forecasting, risk management, and decision-making—but many are still in the early stages of understanding how to implement it effectively. 🔹 Resilience & Agility – It’s a priority, but the path isn’t always clear. Companies are testing scenario modeling and AI-driven insights to build flexibility into their operations. 🔹 Visibility & Transparency – Whether through IoT, blockchain, or digital twins, businesses are pushing for better end-to-end visibility—especially in maritime logistics, where tracking remains a challenge. 🔹 Geopolitical Risks & Trade Complexity – Uncertainty in regulations and trade policies is forcing companies to reassess sourcing and compliance strategies—often with no easy answers. 📖 Read the full article below for deeper insights The direction is clear—companies want to be more agile, data-driven, and resilient—but the reality is that execution takes time. What trends are you seeing in your supply chain? Let’s discuss. #SupplyChain #AI #Resilience #Logistics #TradeCompliance #DigitalTransformation

The Rise of the Agri-Tech Startups: Transforming the Food System #agriculture #innovation #foodsecurity The global food system faces a multitude of challenges: inefficiency, resource scarcity, climate change, and limited access to fair markets for farmers. Enter Agri-Tech startups! These innovative companies are leveraging cutting-edge technologies like AI, IoT, and Big Data to revolutionize agriculture. Here's how they're making a difference: Increased Efficiency: Precision Agriculture: Utilizing data to optimize resource use (water, fertilizer) and maximize yields. (e.g., Deere & Co.'s self-driving tractors) Vertical Farming: Growing crops in controlled environments, minimizing land and water usage. (e.g., Plenty) Sustainable Practices: Microbial solutions: Improving soil health and reducing reliance on chemical fertilizers. (e.g., Indigo Agriculture) Insect farming: Offering a sustainable protein source for animal feed. (e.g., Ÿnsect) Empowering Farmers: Digital Marketplaces: Connecting farmers directly with consumers, eliminating middlemen and ensuring fairer prices. (e.g., KhetiBuddy) Data-driven tools: Providing farmers with real-time data and insights for informed decision-making. The Future of Agri-Tech: AI-powered solutions: Automated pest control, yield prediction, and personalized farm management. Advanced Robotics: Performing tasks like harvesting, weeding, and sorting crops with greater precision. Big Data & Blockchain: Ensuring transparency and traceability throughout the food supply chain. Collaboration is Key: Governments, research institutions, and private companies need to work together to: Facilitate technology adoption for small-scale farmers. Bridge the digital divide in rural areas. Develop regulations that promote innovation while safeguarding data privacy. Agri-Tech holds immense potential to create a more: Productive Sustainable Equitable food system for the future. Let's harness this potential together! #Agritech #FoodTech #Sustainability

𝓦𝓱𝓮𝓷 𝓹𝓪𝓷𝓲𝓬-𝓫𝓾𝔂𝓲𝓷𝓰 𝓼𝔀𝓮𝓹𝓽 𝓪𝓬𝓻𝓸𝓼𝓼 𝓽𝓱𝓮 𝓰𝓵𝓸𝓫𝓮 𝓲𝓷 𝓮𝓪𝓻𝓵𝔂 2020, 𝓻𝓮𝓽𝓪𝓲𝓵𝓮𝓻𝓼 𝔀𝓮𝓻𝓮 𝓫𝓵𝓲𝓷𝓭𝓼𝓲𝓭𝓮𝓭 𝓫𝔂 𝓮𝓶𝓹𝓽𝔂 𝓼𝓱𝓮𝓵𝓿𝓮𝓼 𝓪𝓷𝓭 𝓫𝓻𝓸𝓴𝓮𝓷 𝓼𝓾𝓹𝓹𝓵𝔂 𝓬𝓱𝓪𝓲𝓷𝓼. 𝓦𝓪𝓵𝓶𝓪𝓻𝓽? 𝓣𝓱𝓮𝔂 𝓱𝓪𝓭 𝓪 𝓷𝓸𝓽-𝓼𝓸-𝓼𝓮𝓬𝓻𝓮𝓽 𝓮𝓭𝓰𝓮: 𝓭𝓪𝓽𝓪 𝓪𝓷𝓪𝓵𝔂𝓽𝓲𝓬𝓼. Walmart’s Data-Led Response to Pandemic Panic 🔍 Real-Time Inventory Intelligence By leveraging predictive models, Walmart tracked SKU-level movement across thousands of stores—restocking in real time, right where it mattered most. 🔍 Agile Supplier Collaboration Data helped forecast supply-side disruptions, enabling Walmart to reroute shipments, adjust SKUs, and keep shelves stocked. 🔍 Empowered Local Decision-Making Instead of waiting for top-down instructions, store managers used localized data to act fast—serving real needs in real time. The result? While others ran out, Walmart stepped up—ensuring availability, reducing chaos, and reinforcing customer loyalty. 📌 Takeaway: In a crisis, data isn't just a strategy tool—it’s an execution engine. 💬 𝑨𝒓𝒆 𝒚𝒐𝒖 𝒖𝒔𝒊𝒏𝒈 𝒓𝒆𝒂𝒍-𝒕𝒊𝒎𝒆 𝒅𝒂𝒔𝒉𝒃𝒐𝒂𝒓𝒅𝒔 𝒐𝒓 𝒅𝒂𝒕𝒂-𝒍𝒆𝒅 𝒐𝒑𝒔 𝒊𝒏 𝒚𝒐𝒖𝒓 𝒃𝒖𝒔𝒊𝒏𝒆𝒔𝒔? 𝑯𝒐𝒘 𝒉𝒂𝒗𝒆 𝒕𝒉𝒆𝒚 𝒉𝒆𝒍𝒑𝒆𝒅 𝒚𝒐𝒖 𝒏𝒂𝒗𝒊𝒈𝒂𝒕𝒆 𝒖𝒏𝒄𝒆𝒓𝒕𝒂𝒊𝒏𝒕𝒚? #WalmartCaseStudy #CrisisResponse #SupplyChainAnalytics #DataDrivenDecisionMaking

Food parks are large-scale integrated clusters that bring farms, food processors, cold-storage, logistics, and markets together in one ecosystem. They reduce inefficiencies, cut waste, and improve farmer earnings by processing agricultural produce into value-added products near the source. # How Food Parks Work: Farmers supply raw produce (grains, fruits, vegetables, spices, dairy, seafood). On-site facilities include sorting, grading, cold storage, and advanced food processing units. Logistics enable direct movement of goods to retail chains, exports, and e-commerce. Shared infrastructure lowers costs for small and medium businesses who cannot afford independent facilities. Testing labs and quality certification ensure products meet global export standards. # Key Purposes: Minimize post-harvest losses (India loses up to 30–40% of perishable produce). Support startups, SMEs, and big brands in food processing. Generate employment across farming, manufacturing, packaging, and logistics. Enable value addition (e.g., ready-to-cook meals, frozen foods, spice blends). Boost exports by meeting international compliance and branding. Increase farmer incomes by linking directly to markets. # India’s Mega Food Park Scheme: Launched by the Ministry of Food Processing Industries (MoFPI). Provides grant support to create clusters with central processing hubs and collection centers. Each park typically spans 50–100 acres and can host multiple food processing units. Examples: Mega Food Parks at Tumkur (Karnataka), Aurangabad (Maharashtra), and Jangipur (West Bengal). # Reliance’s ₹40,000 Crore AI-Driven Food Park Plan: Reliance Industries is planning modern agri-food parks integrated with AI, IoT, and data analytics. First project to begin in Andhra Pradesh,: focusing on items like spices, noodles, and packaged foods. AI will be used for: Yield prediction and farm-to-factory supply chain planning. Smart cold storage and energy-efficient logistics. Real-time quality testing and food safety monitoring. Optimized retail distribution through Reliance Retail’s network (Reliance Fresh, JioMart). This initiative aligns with India’s push for self-reliance in food processing and exports, while offering farmers better price realization. # Summary of Key Differences: Reliance’s parks harness AI and robotics for extreme efficiency, predictive supply chain management, and smart quality control, whereas regular Mega Food Parks rely on legacy industrial setups and manual operations . Reliance centers have deeper integration into branded FMCG goods, directly serving national chains like Reliance Fresh and JioMart, as well as export ambitions; traditional parks mostly provide infrastructure for SMEs to process local produce. In conclusion, Reliance’s AI-powered food park model represents a leap toward a high-tech, pan-India FMCG manufacturing and export ecosystem—far more advanced in digital integration and global reach.

#Blockchain in Surface Transport: A Game-Changer for #Asia & #Africa Asia & Africa move on wheels. From the rugged haul trucks to refrigerated trucks, #Surfacetransport is the backbone of commerce across these vast and diverse continents. But with that scale comes massive #challenges: 🔁 Multiple handovers ⛰️ Bad terrain and poor infrastructure 📝 Paper-based documentation ⚖️ Disputes in delivery, fuel pilferage, and route manipulation 📉 Inefficiencies across the value chain Enter: #Blockchain. • A single source of truth. • Tamper-proof records. • Real-time visibility. • Automated trust. #Roadmap to Blockchain Efficiency in Surface Transport: 1. #Digitize Consignment Notes & #PODs (Proof of Delivery) Eliminate paperwork delays and fakes. 2. Implement #SmartContracts. Automate payments upon delivery confirmation. 3. Track Trucks with #GPS + Blockchain Logs Immutable trip logs = zero manipulation. 4. Create a #SharedLedger for Stakeholders Shipper, driver, transporter, client – same source of truth. 5. Use Blockchain for Fuel Records Stop #pilferage. Validate fuel usage route-wise. 6. Integrate #Maintenance Logs. Every breakdown, repair, tyre change recorded immutably. 7. Customs & Border Records on Chain. Speed up #crossborder movement, reduce bribes and bottlenecks. 8. Load Verification & #TamperAlerts Seal, sensor + blockchain = cargo integrity across terrain. 9. Invoice #Automation Reduce DSO (Days Sales Outstanding) and disputes. 10. Enable #ESG Compliance & Audit Trails Prove carbon footprints, route optimization, and ethical sourcing. #Blockchain is not just a tech buzz . it’s an enabler of transparency, efficiency, and trust in some of the world’s toughest logistics environments. 🚀 The future of transport will not just be diesel-powered. It will be #data-powered. #Blockchain #SurfaceTransport #FleetManagement Pic Location - Road to Siachen Glacier

For years, the industry has been chasing a comforting myth: the idea that real-time #visibility is just a "switch you flip". Lately, that promise has evolved into "instant onboarding". It sounds impressive. It makes for great headlines. But for many supply chain leaders, it’s a gamble that ends in a cycle of failed projects and data that teams simply cannot trust. The uncomfortable truth? Connectivity alone has never been the hard part. A connection is just a pipe. If what flows through it is incomplete, inconsistent, or poorly governed, you haven’t solved visibility – you’ve just automated a data junkyard. Real visibility is a deployment challenge, not a software install. It requires organisational readiness: cross‑team alignment, clear ownership, and a project‑based approach. It requires active involvement from procurement teams to ensure carriers provide the right data points – and continuous follow‑up to keep that data complete and reliable over time. At Shippeo, we’ve always viewed this differently. We don’t treat visibility as a passive software install or a "black box" of automated connections. We view it as an engineering discipline. We call it Visibility Engineering. That’s why we don’t just “onboard” carriers. We work across the full deployment lifecycle — from internal readiness to carrier engagement to ongoing data quality controls. And it’s why our Visibility Assessment isn’t just a technical checklist. It’s designed to answer a harder question: is your organisation actually ready to operationalise trusted data at scale? And most importantly, it’s the only reason we can confidently offer the industry’s only SLAs for Tracking Compliance, ETA Accuracy, and Carrier Onboarding. In a world where the window between planning and execution has shrunk to near-zero, you don't need more "pipes". You need engineered trust. Read more about the rise of Visibility Engineering here: https://lnkd.in/eb9uRcHT #SupplyChain #VisibilityEngineering #RealTimeVisibility #Shippeo