Supply Chain Management

Solar created the duck curve. Batteries are now flattening it. This chart shows median wholesale electricity prices in New South Wales during the second quarter of each year. In 2023, prices surged towards $300/MWh during the evening peak. In 2026, that peak is below $100/MWh. While the chart shows NSW, this same pattern is emerging across Queensland, Victoria and South Australia as well. The driver of this is becoming familiar: batteries. ✅ Batteries create demand during solar-rich daytime hours, preventing midday prices from falling as deeply. ✅ They discharge after sunset, adding supply when evening demand rises. ✅ This reduces reliance on gas and hydro during the evening peak, when they have traditionally set higher prices. The scale of the battery build-out is now large enough to reshape both electricity supply and demand. Modo estimates that registered home-battery power capacity across Australia's National Electricity Market has reached 7.8 GW, overtaking the 7.7 GW of operational grid-scale batteries. Those home batteries increasingly charge during solar-rich daytime hours, then meet household demand after sunset - reducing grid demand. Meanwhile, grid-scale batteries add supply directly into the evening market. Batteries are also increasingly determining the wholesale price. In Q2, battery charging and discharging set prices in 36% of NEM dispatch intervals, up from 17% a year earlier. During the evening peak, battery discharge was the dominant price-setter. The curve is therefore being flattened from both directions: more demand when solar is abundant and more supply when evening demand rises. As battery capacity grows, the gap between the cheapest and most expensive hours is narrowing. That means lower peak prices, less volatility and a more productive use of daytime solar.

Do you walk into board meetings with a slide deck? Or with an executive finance pack? One tells a story. The other drives a decision. A slide deck tells a story you want the board to hear. A finance pack gives the board what it needs to govern, challenge, and approve. If your board isn't asking hard questions, it's not because things are going well. It's because the information you're presenting doesn't invite rigor. And that’s a governance problem. Here's how to build a board-ready finance pack, from the foundation up: LEVEL 1: Strategic Thesis ↳ What is the company's capital strategy and where is value being created? ↳ This is the anchor. Every number in the pack should trace back to this thesis. LEVEL 2: Capital Allocation ↳ How is capital being deployed across the business? ↳ Show where dollars are going, why, and what return profile each allocation carries. LEVEL 3: Cash Position ↳ What is the real-time liquidity picture? ↳ Not just the balance. The runway, the burn context, the covenant headroom, the collection cycle. LEVEL 4: Scenario Map ↳ What happens if assumptions shift? ↳ Give the board two or three scenarios with clear triggers, trade-offs, and decision points built in. LEVEL 5: The Board Asks ↳ What questions should the board be asking based on this data? ↳ Pre-frame the governance conversation. Guide their attention to what matters most right now. Most mid-market CEOs build from the top down.  They start with what the board might ask and reverse-engineer a defensive narrative. That's backwards. When you build from the thesis up, every layer reinforces the one below it. The numbers have context.  The scenarios have grounding.  The questions have depth. Investor-grade governance doesn't require a Fortune 500 finance team. It requires a structure that makes the right conversations inevitable. If your board leaves the room without challenging a single assumption, the pack failed. Not the Board. Great CEOs don't just report to their boards.  They equip them to govern. That's financial intelligence at the leadership level. ♻️ Like, Comment and Repost to help your network. Follow Oana Labes, MBA, CPA for strategic financial leadership. -------- 📌 Ready to Scale with Full Command of your Own Numbers? Join The CEO Financial Intelligence Academy. 5* Curriculum. Coaching. Community. Your CEO Dashboard set up Day 1. Get your CEO Checklist here → https://bit.ly/4es64ye

Until this week, nobody knew how many agricultural fields existed on Earth. Now we do. There are 3.17 billion of them. This is the first global field boundary map at 10m resolution, covering 241 countries and territories across 2024 and 2025. Microsoft AI for Good, Taylor Geospatial, and Wherobots released it openly. For the first time, agriculture has a globally consistent unit of analysis that matches how it's actually organized on the ground. This is how they pulled it off. Running GeoAI at global scale is a systems problem much more than a modeling problem. Here's what that actually looked like: → Four cloud-free Sentinel-2 mosaics (planting and harvest, 2024 and 2025) across all land between 60°S and 84°N → 150 TB of feature data stored as a single global Zarr mosaic with 7.5 million logical chunks → 256 NVIDIA A10G GPUs running inference in parallel across overlapping 256×256 patches → 45 TB of predictions, vectorized into 8.2 billion GeoParquet rows → 348 TB of total output across 540,000 objects, reproducible with three API calls on Wherobots RasterFlow The validation problem was just as hard as the inference problem. You can measure precision by sampling what the model produced. You can't measure recall globally, because if you already knew where all the fields were, you wouldn't need the map in the first place. The team solved that with a 500m confidence layer that flags where predictions are reliable and where they're not. Full-country F1 scores hit 0.89 in Austria and 0.88 in Latvia. In Finland's boreal north, the model over-predicts on forest clearings and the confidence layer catches it. That's the honest part. This isn't a finished product. Smallholder systems get over-fragmented. Pastures and orchards are out of scope. Africa and South Asia are underrepresented in the training data. But for the first time, a globally consistent field-level layer exists and anyone can use it. Data is live at https://lnkd.in/eCVaeuFx 🌎 I'm Matt Forrest and I talk about modern GIS, earth observation, AI, and how geospatial is changing. 📬 Want more like this? Join 13k+ others learning from my weekly newsletter → forrest.nyc

Juniors Ignore Data Quality checks. Seniors use this 10 SQL checks👇 𝟭. 𝗡𝗨𝗟𝗟𝗦 Stop letting missing values break your averages. 𝟮. 𝗨𝗡𝗜𝗤𝗨𝗘𝗡𝗘𝗦𝗦 Imagine doubling the revenue by accident! 𝟯. 𝗜𝗡𝗧𝗘𝗚𝗥𝗜𝗧𝗬 (𝗥𝗲𝗳𝗲𝗿𝗲𝗻𝘁𝗶𝗮𝗹) Every order_id must link back to a valid customer. 𝟰. 𝗔𝗖𝗖𝗘𝗣𝗧𝗘𝗗 𝗩𝗔𝗟𝗨𝗘𝗦 Don’t let “weird” statuses creep into your reports. 𝟱. 𝗙𝗨𝗡𝗖𝗧𝗜𝗢𝗡𝗔𝗟 𝗥𝗨𝗟𝗘𝗦 Check business rules that should never be broken. 𝟲. 𝗥𝗔𝗡𝗚𝗘 Catch outliers before they skew the entire quarter. 𝟳. 𝗗𝗔𝗧𝗔 𝗧𝗬𝗣𝗘 Prevent the “Text vs Integer” nightmare. 𝟴. 𝗙𝗥𝗘𝗦𝗛𝗡𝗘𝗦𝗦 No more stale dashboards. 𝟵. 𝗧𝗘𝗠𝗣𝗢𝗥𝗔𝗟 𝗖𝗢𝗡𝗦𝗜𝗦𝗧𝗘𝗡𝗖𝗬 Time should move forward, not backward! 𝟭𝟬. 𝗡𝗨𝗟𝗟 𝗦𝗣𝗜𝗞𝗘 Spot sudden drops in data quality before they bite. --- Having bad data is worse than not having data at all. No data → You rely on intuition. Bad data → You make confident decisions that are simply wrong. Take Data Quality seriously! I prepared the SQL implementation👇 --- ♻️ Repost if you found it useful, please Follow 👉🏻 José for more about Data, SQL, and AI!

Everyone is talking about #AI in logistics. Some still believe logistics is simply about moving goods from A to B. And now headlines around the world are asking: Can logistics be replaced by AI-driven software? The answer is both simple and incomplete. ▶️ AI enables us to process billions of data points in real time. ▶️ It anticipates risk before it materialises. ▶️ It increases transparency across global networks. ▶️ It reduces manual errors while accelerating throughput. In short: AI drives efficiency. And further: There is no future for logistics without AI. But here is the real question: Will AI make supply chains more efficient or more human? Yes, you read correctly: human. Because efficiency alone is not the benchmark. #CustomerExperience is. Let me explain this by looking into the status quo. Already today, we use AI to: Predict more reliable ETAs by real-time recalculation. Detect disruptions earlier allowing for proactive route and capacity planning. Automate end-to-end workflows, reducing manual work, errors, and processing time across core operations. This is not theory, it’s no longer experimental, it’s daily practice. And there is a lot more to come. Yet, what matters most is this: The more powerful AI becomes, the more decisive the #HumanExpertise becomes. In an AI-driven world, customers will not differentiate us by who has access to technology. Technology will become mainstream. Customers will differentiate us by: ▶️ Who explains complexity clearly. ▶️ Who takes ownership when disruption hits. ▶️ Who anticipates consequences, not just data patterns. ▶️ Who acts as a strategic partner, not just a service provider. AI allows us to be faster. Customer experience requires us to be better. The real opportunity for our industry is not to automate relationships but to elevate them. AI can process billions of data points. But trust is built through clarity, reliability, and accountability. Kuehne+Nagel’s ambition is simple: Lead in AI. Lead in customer experience. Because the future of logistics will not be defined by algorithms alone but by how intelligently and responsibly we use them to serve our customers. We’ll share further insights into our AI strategy during the Kuehne+Nagel Conference Call on March 3, 2026.

The European Parliament has officially passed Extended Producer Responsibility (EPR) legislation that fundamentally shifts the responsibility for textile waste management to fashion brands and retailers – with far-reaching global implications. This new law requires all producers, including e-commerce platforms, to cover the full cost of collecting, sorting, and recycling textiles, regardless of whether they are based within or outside the EU. The financial burden of Europe's textile waste now falls squarely on the brands that create it. What are the critical business implications? UNIVERSAL SCOPE: The legislation applies to all producers selling in the EU market, including those of clothing, accessories, footwear, home textiles, and curtains. No company is exempt based on location. FAST FASHION PENALTY: Member states must specifically address ultra-fast and fast fashion practices when determining EPR financial contributions, creating cost penalties for unsustainable business models. GLOBAL SUPPLY CHAIN DISRUPTION: As the world's largest textile importer, the EU's new rules will ripple across global supply chains, particularly impacting exporters from Bangladesh, Vietnam, China, and India who supply much of Europe's fast fashion. TIMELINE PRESSURE: Officially adopted September 2025, this creates immediate operational and financial planning requirements. COMPETITIVE RESHAPING: Brands and retailers will inevitably pass increased costs down their supply chains, fundamentally altering supplier relationships and pricing structures globally. What are the implications for various stakeholders? For CEOs and board members: This represents more than regulatory compliance – it's a complete business model transformation. Companies must now integrate end-of-life costs into product pricing, rethink supplier partnerships, and accelerate circular design strategies. For sustainability and decarbonisation executives: This creates unprecedented opportunities for circular economy solutions, sustainable material innovation, and traceability system development across global supply chains. Link: https://lnkd.in/dTyHtHuD #sustainablefashion #circulareconomy #textilwaste #epr #fashionindustry #sustainability #supplychainmanagement #fastfashion #environmentalregulation #businessstrategy #decarbonisation #textilerecycling #fashionceos #boardgovernance #climateaction #wastemanagement #producerresponsibility #fashionsustainability #textileindustry #greenbusiness

♻️ Recycling, reimagined. I came across Ameru’s AI Smart Bin — and it made me realize something we rarely talk about in sustainability: We don’t fail to recycle because we don’t care. We fail because the friction is too high. This bin doesn’t just collect waste. It sees what you throw, sorts it automatically, and even gives you real-time feedback. The results? ✅ 95%+ sorting accuracy ✅ Analytics that show you how to reduce waste ✅ ROI in under 2 years 👉 Here’s the hidden insight: Let’s be honest: recycling is broken. Most of us want to recycle, but the system is designed for failure — too much friction, too many rules. The real innovation isn’t in AI or edge computing. It’s in making sustainability invisible. No guilt, no extra steps — just default behavior upgraded. 💡 Actionable thought: Whether you’re building tech, a product, or even a habit, ask yourself — how can I make the right choice feel effortless? Because effort scales linearly. But effortlessness? That scales exponentially. PS: Imagine when every trash bin becomes a data point in the circular economy. 👉 Do you think this kind of “invisible innovation” could transform how we recycle at home and at work? #GreenTech #AI #Innovation #Sustainability #CircularEconomy

Last month, we saved 5 lakhs in just 10 minutes by doing one thing. Let me tell you about this small adjustment that made a huge impact at Go Zero. Here's how our packaging works: → Ice cream goes into plastic cups → 12 cups go into cartons → Cartons go into crates for storage and transport And the cartons we were buying were the standard size in the market. So, each crate held 5 cartons = 60 cups total. One day, someone walked out of our cold room carrying these crates. And I noticed something - there was empty space in each crate. It got me thinking how we can fit one more carton in here. Tried it. Didn't fit. It was just 10mm short. Instead of accepting it, I did the math. We already had 5 cartons in the crate. If I reduced each carton's height by just 2mm, I'd free up exactly the 10mm needed for the 6th carton. The impact was immediate: 5 cartons per crate became 6 cartons per crate. Scale that up - every 100 crates now carry 600 cartons instead of 500. Same truck. Same storage space. 20% more product. All because of 2mm. Sometimes the biggest breakthroughs come from the smallest observations. You just have to be willing to question what everyone else accepts as "standard."

When packaging becomes part of you Wearable packaging is no longer a futuristic concept it's a growing design frontier that merges functionality, fashion, and emotional connection. Beyond the shelf: packaging you can wear From fragrance necklaces to ring-shaped lip balms and refillable compacts designed like jewelry, beauty brands are transforming packaging into accessories. The product becomes not just something you use, but something you wear turning daily rituals into statements of identity. Why it works In a world saturated with options, wearable packaging offers immediacy, memorability, and emotional value. It adds a layer of meaning: a perfume worn around the neck is not just a scent, it’s a story you carry. A lipstick shaped like a pendant becomes both utility and ornament. It taps into consumers’ desire for customization, portability, and aesthetic expression particularly among Gen Z and Millennials who seek objects that are both functional and symbolic. A new layer of storytelling Wearable formats create a deeper connection between brand and user. They’re conversation starters, collectible, and often more sustainable built for reuse and ritual, rather than discard. Design becomes not only a visual differentiator but a tactile, emotional experience that enhances the perceived value of the product. From beauty to fashion and back again This blurring of categories also opens doors to cross-industry innovation. When beauty products act like accessories, they enter the realm of fashion making room for brand collaborations, limited editions, and viral potential on social media. It’s no longer just about packaging design. It’s about presence. Relevance. And creating a product people don’t want to put away — they want to put on. Featured brands: Rhode Bubble Yepoda Laneige #WearablePackaging #CosmeticAccessories #FragranceOnTheGo #LuxuryPackaging #EmotionalDesign #GenZBeauty #FutureOfBeauty

𝟓 𝐏𝐫𝐨𝐜𝐮𝐫𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐬𝐬𝐨𝐧𝐬 𝐟𝐫𝐨𝐦 𝐚 ₹𝟏𝟗,𝟕𝟎𝟎 𝐂𝐫 𝐌𝐢𝐬𝐭𝐚𝐤𝐞 What every procurement leader must learn from the JSW–Bhushan Steel chaos 𝗕𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱 : In 2019 JSW Steel won the bid to acquire Bhushan Power & Steel under India’s Insolvency & Bankruptcy Code (IBC). Deal value : ₹19,700 Cr. Funds were infused. Operations taken over. 𝘊𝘰𝘯𝘵𝘳𝘰𝘭 𝘢𝘴𝘴𝘶𝘮𝘦𝘥 𝗕𝘂𝘁 𝗜𝗻 𝗠𝗮𝘆 𝟮𝟬𝟮𝟱: The Supreme Court has canceled the entire deal ❌ Declares the process illegal Orders liquidation instead That’s true a company that JSW ran for years is now off its books Overnight 𝗕𝘂𝘁 𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗛𝗮𝗽𝗽𝗲𝗻𝗲𝗱 ? ⛔ 𝐓𝐢𝐦𝐞𝐥𝐢𝐧𝐞 𝐛𝐫𝐞𝐚𝐜𝐡: IBC allows 270 days. This deal dragged on for over 500 ⛔ 𝐏𝐫𝐞𝐦𝐚𝐭𝐮𝐫𝐞 𝐜𝐨𝐧𝐭𝐫𝐨𝐥: JSW took over without full legal closure ⛔ 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐠𝐚𝐩𝐬: The resolution process lacked statutory rigor 𝘛𝘩𝘦 𝘊𝘰𝘶𝘳𝘵 𝘳𝘶𝘭𝘦𝘥 𝘵𝘩𝘢𝘵 𝘵𝘪𝘮𝘦 𝘦𝘹𝘵𝘦𝘯𝘴𝘪𝘰𝘯𝘴 𝘤𝘢𝘯𝘯𝘰𝘵 𝘫𝘶𝘴𝘵𝘪𝘧𝘺 𝘱𝘳𝘰𝘤𝘦𝘥𝘶𝘳𝘢𝘭 𝘷𝘪𝘰𝘭𝘢𝘵𝘪𝘰𝘯𝘴 𝐖𝐡𝐚𝐭 𝐓𝐡𝐢𝐬 𝐌𝐞𝐚𝐧𝐬 𝐟𝐨𝐫 𝐘𝐨𝐮 𝐀𝐬 𝐀 𝐏𝐫𝐨𝐜𝐮𝐫𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐚𝐝𝐞𝐫 : This is a brutal real-world case study in contractual discipline and risk management. 1️⃣ 𝗗𝗲𝗮𝗱𝗹𝗶𝗻𝗲𝘀 𝗮𝗿𝗲 𝗟𝗔𝗪 — 𝗡𝗼𝘁 𝗦𝘂𝗴𝗴𝗲𝘀𝘁𝗶𝗼𝗻𝘀 Contracts with statutory or regulatory timelines must be treated as non-negotiable. 2️⃣ 𝗟𝗲𝗴𝗮𝗹 𝗖𝗹𝗼𝘀𝘂𝗿𝗲 > 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 Never take charge of suppliers, assets, or projects until contracts are 100% sealed and validated. 3️⃣ 𝗣𝗮𝗽𝗲𝗿 𝗧𝗿𝗮𝗶𝗹𝘀 𝗣𝗿𝗼𝘁𝗲𝗰𝘁 𝗬𝗼𝘂 Assumptions don’t win in court. Documentation does. 4️⃣ 𝗜𝗻𝗰𝗹𝘂𝗱𝗲 ‘𝗪𝗵𝗮𝘁-𝗜𝗳’ 𝗖𝗹𝗮𝘂𝘀𝗲𝘀 𝗶𝗻 𝗛𝗶𝗴𝗵-𝗦𝘁𝗮𝗸𝗲 𝗖𝗼𝗻𝘁𝗿𝗮𝗰𝘁𝘀 Always draft contingency, rollback, and reversal clauses — especially in M&A, Capex, or long-term supply contracts. 5️⃣ 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗶𝘀 𝗡𝗼𝘁 𝗕𝘂𝗿𝗲𝗮𝘂𝗰𝗿𝗮𝗰𝘆 — 𝗜𝘁’𝘀 𝗜𝗻𝘀𝘂𝗿𝗮𝗻𝗰𝗲 Be the leader who slows down when it matters. Because speed without structure kills deals. Have you seen contract risks like this in your industry? #JSW #bhushansteel #India #Contract #Contractdrafting #Purchsing #Procurement #Industry #Mergerandaquisition #Riskmanagement #Leadership #CXOinsights #SMARTProcurement #ContractRisk #SCM