Supply Chain Management

China is electrifying its trucking fleet so fast that it’s now reshaping global diesel demand. This has not been widely covered by the mainstream media. Here's how quickly things have shifted: ➡️ 2020: Nearly every new truck in China was diesel ➡️ H1 2025: Battery-powered trucks reached 22% of new sales ➡️ Dec 2025: Battery-powered trucks hit 54%, achieving a majority share for the first time China's sales of "New Energy Vehicle" trucks in 2025 were almost triple the 2024 total – and the share is now expected to reach around 60% this year. And what's driving this shift? Economics. Rapidly falling battery prices mean electric trucks are now cheaper to own and operate than diesel or LNG alternatives – with each truck saving fleet operators around $165,000 over a 10-year operating life. Fleet operators are also increasingly adopting depot charging, opportunity charging and battery-swap networks – removing the last points of friction. This is a market-wide shift in the most energy-intensive road transport segment in the world’s largest vehicle market. And it matters: road freight accounts for around one third of global transport emissions. The impact on oil demand is already visible: ✅ China's electric trucks are already cutting oil demand by the equivalent of more than one million barrels a day. ✅ China's transport sector is forecast to use 40% less diesel in 2030 than in 2024. So why did analysts miss this? Most models assumed heavy trucks would be the last segment to electrify — but China moved faster on battery-swap infrastructure, ultra-cheap LFP batteries, and high-utilisation urban freight fleets. The economics flipped earlier than the forecasts assumed. The result: diesel demand in China – the world’s second-largest consumer – could fall much faster than many predicted. And that's not all. Already the world's largest exporter of passenger cars, China is now eyeing the global electric truck market. Adoption is growing in the Middle East and Latin America and BYD is building a new electric truck and bus factory in Hungary. This is just the beginning.

𝗗𝗮𝘁𝗮 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗶𝘀 𝗼𝗻𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗺𝗼𝘀𝘁 𝗺𝗶𝘀𝘂𝗻𝗱𝗲𝗿𝘀𝘁𝗼𝗼𝗱 𝘁𝗼𝗽𝗶𝗰𝘀 𝗶𝗻 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲. Because most people explain it from the inside out: policies, councils, standards, stewardship. But the business does not buy any of that. The business buys outcomes: → trustworthy KPIs → vendor and partner data you can actually use → faster financial close → fewer reporting escalations → smoother M&A integration → AI you can deploy without creating risk debt Most AI programs fail for boring reasons: nobody owns the data, quality is unknown, access is messy, accountability is missing. 𝗦𝗼 𝗹𝗲𝘁’𝘀 𝘀𝗶𝗺𝗽𝗹𝗶𝗳𝘆 𝗶𝘁. 𝗗𝗮𝘁𝗮 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗶𝘀 𝗳𝗼𝘂𝗿 𝘁𝗵𝗶𝗻𝗴𝘀: → ownership → quality → access → accountability 𝗔𝗻𝗱 𝗶𝘁 𝗯𝗲𝗰𝗼𝗺𝗲𝘀 𝘃𝗲𝗿𝘆 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝘄𝗵𝗲𝗻 𝘆𝗼𝘂 𝘁𝗵𝗶𝗻𝗸 𝗶𝗻 𝟰 𝗹𝗮𝘆𝗲𝗿𝘀: 1. Data Products (what the business consumes) → a named dataset with an owner and SLA → clear definitions + metric logic → documented inputs/outputs and intended use → discoverable in a catalog → versioned so changes don’t break reporting 2. Data Management (how products stay reliable) → quality rules + monitoring (freshness, completeness, accuracy) → lineage (where it came from, where it’s used) → master/reference data alignment → metadata management (business + technical) → access controls and retention rules 3. Data Governance (who decides, who is accountable) → data ownership model (domain owners, stewards) → decision rights: who can change KPI definitions, thresholds, and sources → issue management: triage, escalation paths, resolution SLAs → policy enforcement: what’s mandatory vs optional → risk and compliance alignment (auditability, approvals) 4. Data Operating Model (how you scale across the enterprise) → domain-based setup (data mesh or not, but clear domains) → operating cadence: weekly issue review, monthly KPI governance, quarterly standards → stewardship at scale (roles, capacity, incentives) → cross-domain decision-making for shared metrics → enablement: templates, playbooks, tooling support If you want to start fast: Pick the 10 metrics that run the business. Assign an owner. Define decision rights + escalation. Then build the data products around them. ↓ 𝗜𝗳 𝘆𝗼𝘂 𝘄𝗮𝗻𝘁 𝘁𝗼 𝘀𝘁𝗮𝘆 𝗮𝗵𝗲𝗮𝗱 𝗮𝘀 𝗔𝗜 𝗿𝗲𝘀𝗵𝗮𝗽𝗲𝘀 𝘄𝗼𝗿𝗸 𝗮𝗻𝗱 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀, 𝘆𝗼𝘂 𝘄𝗶𝗹𝗹 𝗴𝗲𝘁 𝗮 𝗹𝗼𝘁 𝗼𝗳 𝘃𝗮𝗹𝘂𝗲 𝗳𝗿𝗼𝗺 𝗺𝘆 𝗳𝗿𝗲𝗲 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: https://lnkd.in/dbf74Y9E

📢 EU CBAM is Now Fully Operational: What You Need to Know On January 1, the EU’s Carbon Border Adjustment Mechanism (CBAM) came into full effect. Here are the key things sustainability, finance, and strategy teams should understand: 🔹 An overview CBAM is the first fully operational border carbon pricing system designed to prevent carbon leakage, the shifting of emissions-intensive production outside the EU, while protecting EU firms subject to internal carbon costs. 🔹 What has changed? Unlike prior pilots, the 2026 implementation bases costs on actual emissions intensity of imports. The EU has “externalized” carbon pricing beyond its borders, which has implications for supply chains and global trade flows, especially for goods like steel, aluminum, cement, electricity, fertilizers, and certain chemicals. 🔹 What do companies need to do? Importers and their non-EU suppliers will need to: - Map supply chains and embedded emissions - Coordinate with suppliers on verified emissions data - Assess carbon cost exposure and potential downstream price impacts 📈 The big picture CBAM goes beyond a compliance issue for firms and has real implications for supply chains and operating costs. Investors and businesses are beginning to factor in carbon pricing and supply-chain decarbonization into their financial decisions. We’ve been helping firms manage these shifts and respond strategically. Send me a message if you’d like to learn more. Visual courtesy of Carbonwise #CBAM #EURegulations #CarbonPricing #ClimatePolicy #SustainableTrade #ClimateRisk #SupplyChainEmissions #NetZero #ESG #ClimateFinance #Decarbonization

Procurement focus on OpEx 5x more than CapEx. Or get involved so late in CapEx it’s like lipsticking a pig. This can be dangerous to a company’s bottom line. So, how do we fix that? Let’s look at the differences first: CapEx Procurement: ➟ Purchases are often one-offs ➟ Large Purchases & for long-term use ➟ Likely custom made purchases OpEx Procurement: ➟ Weekly / Monthly payments ➟ Everything from software, raw materials to packaging ➟ Repeatable purchases How should we approach CapEx more effectively? 1. Don’t apply processes based on repeatability to CapEx CapEx is a one-time purchase and often something unique. Procurement teams working on CapEx projects need to focus on specifics: e.g. that all requirements are met, the budget & delivery timeline are delivered. 2. Track costs associated with change orders long after the contract has been agreed. Change orders can be a big part of Capital Expenditure and often even the scope changes long after the deal has been agreed. Procurement should ally with finance to keep track of the longer term financial outcomes. 3. Don’t muddy the waters between recurring costs and the one-time investment Specifications for CapEx are rarely “off the shelf”. You’re sourcing a unique product or deliverable. But some CapEx projects may have OpEx applicable components. E.g. a new building may well have recurring expenditures (e.g. network, maintenance, security). Keep visibility of these by separating them out instead of having them rolled into a blanket invoice. --- And here’s how Procurement can really add value in the sourcing process: ✅ In one major CapEx investment I supported 6 years ago, we put the emphasis on multimedia (blueprints, drawings, schematics) and full days of workshops and tours with all the bidders together in one place. This better communicates the requirements, helps the bidders ask the right questions and streamlines your time (not having to contact each supplier individually) ✅ Leave room in your RFP for true flexibility. Suppliers who deal with CapEx projects are often highly specialised and may well be in a better position to advise on the best approach to take than anyone from within your organisation. ✅ Make sure you have a detailed breakdown of costs in the bid responses. This helps proper analysis and supplier comparison. It also enables you to focus on the most expensive components to reduce the overall project expense. ✅ Use predictive insights and client reference calls By asking the right questions you can get a good barometer of how often and how much the change requests might cost. ——- What do you think of this advice? What would you add? Let me know in the comments. Hope that helps! Feel free to tag someone in your team who could find this helpful or ♻️ repost it to your network.

If sourcers aren't a part of your talent intelligence strategy, how complete is your strategy and what are you missing? I had an interesting discussion with a client the other day - they're looking to build a world-class talent intelligence function and were asking how to get granular data and insights. Companies often overlook a valuable source of insights: the conversations they have with every potential candidate, whether or not they progress through the hiring process. Even brief email exchanges with candidates who decline interest can provide meaningful information. These interactions are a rich source of market intelligence that many organizations fail to capture and analyze. Not every organization employs dedicated sourcers, but recruiters who actively engage in sourcing activities can collect vital market intelligence through their candidate interactions. Organizations that depend exclusively on inbound applications from recruitment marketing and employee referrals face a significant limitation: they only capture insights from candidates who apply. While analyzing inbound applicant data is valuable, it represents just one segment of the potential talent pool. Without active sourcing, companies miss out on understanding the broader talent market, including passive candidates' motivations and targeted competitor insights. Here's the bottom line: every candidate interaction - whether successful or not - can yield valuable market intelligence. Organizations that systematically capture and analyze these insights gain a significant competitive advantage in understanding talent markets, competitor dynamics, and their own employer value proposition. #sourcing #talentintelligence

Still printing, scanning, and emailing contracts? Missed renewal? Your contract management needs help NOW! Behind the scenes of many organizations' contract management functions are #struggling — and these struggles often go unnoticed until it’s too late! Contract Management | 06 JUN 2025 - Contracts are more than just paper, they are #strategic assets. Your “#contract #management function” is supposed to protect you — but what if it’s actually putting you in danger? Here are 9 #red #flags that signal your contract management needs #urgent attention: 🚩Missed Deadlines 🚩Lack of Standard Templates or Clauses 🚩Poor Contract Status Visibility 🚩Undefined Roles and Responsibilities 🚩Inconsistent Approval Workflow 🚩Limited Legal Vs Procurement Collaboration 🚩Ignoring Contract Data Analytics 🚩No Audit Trail or Version Control 🚩Lack of Centralization These red flags are fixable! If your contract management function is showing these red flags, it’s time to act before problems become #crisis. Recommendations: ✅Use centralized contract management system ✅Implement #dashboards for real-time updates ✅Regularly train your team on #best practices ✅️Create a #uniform process for contract creation, review, and approval. ✅Develop #standardized templates and pre-approved clauses. ✅Leverage contract #analytics to identify trends, risks, and opportunities. A mature contract management function not only mitigates risk but accelerates #source-to-#contract cycle, reducing supply chain leadtime driving business #growth. What’s one red flag you’ve encountered — and how did you overcome it? Let’s share insights below! #ContractManagement #RiskManagement #Procurement #Redflags

I’ve had 4 legal battles since starting my business. Could I have avoided them? Probably. But I didn’t have the funds for a proper lawyer. I didn’t have the founder network to ask the right questions. I was figuring it out as I went - like most of us do. So, let me help you not learn the hard way. Here are 5 clauses I now include in every contract to protect my work, my business, and my sanity: 1. Non-cancellable, non-refundable agreements If you’ve qualified your clients properly, this shouldn’t be a problem. But if someone signs, onboards, and then disappears? We still get paid. And so should you. 2. Immediate or short payment terms We don’t do 30- to 90-day terms. You wouldn’t work for 3 months without pay - so why should your business? Cash flow isn’t just admin. It’s survival. 3. Enforceable payment protection Your contract should include: Interest on late invoices A “stop work” clause if payment isn’t made A clause that guarantees you still get paid even if the client delays the project Your time is not free. Put it in writing. 4. Intellectual Property stays yours Anything we bring to the table = ours. Anything we create for you = yours. Clear. Simple. No grey area. We once had a client record a training session… and try to resell it behind a paywall. Now our contract includes a £10,000 fine per breach. And in that case, per breach = per view. 5. Don’t work with d*ckheads. Not a legal clause - more like legal wisdom... 😂 🚩 If they’re pushing for discounts before asking about outcomes 🚩 If they want to start work before signing or paying 🚩 If they delay, ghost, or act shady in the first 10 days… Walk away. Trust me. Yes, contracts are important. But court is expensive, stressful, and slow. The best legal advice I can give you; - Protect your business. - Trust your gut. - And don’t work with d*ckheads. Learning from someone else’s mistakes is a hell of a lot cheaper than learning from your own. You’re welcome 💜 😉 P.S - Want to finally get the confidence to start building your personal brand online? This is your sign. I’m hosting a FREE Zoom masterclass SEPT 10th. Join here: https://lnkd.in/gMwytmS3 and I'll show you exactly how to build your personal brand (and the life you want!).

Every cloud provider faces the same AI infrastructure challenge: chips need to be positioned close together to exchange data quickly, but they generate intense heat, creating unprecedented cooling demands. We needed a strategic solution that allowed us to use our existing air-cooled data centers to do liquid cooling without waiting for new construction. And it needed to be rapidly deployed so we could bring customers these powerful AI capabilities while we transition towards facility-level liquid cooling. Think of a home where only one sunny room needs AC, while the rest stays naturally cool – that’s what we wanted to achieve, allowing us to efficiently land both liquid and air-cooled racks in the same facilities with complete flexibility. The available options weren't great. Either we could wait to build specialized liquid-cooled facilities or adopt off-the-shelf solutions that didn't scale or meet our unique needs. Neither worked for our customers, so we did what we often do at Amazon… we invented our own solution. Our teams designed and delivered our In-Row Heat Exchanger (IRHX), which uses a direct-to-chip approach with a "cold plate" on the chips. The liquid runs through this sealed plate in a closed loop, continuously removing heat without increasing water use. This enables us to support traditional workloads and demanding AI applications in the same facilities. By 2026, our liquid-cooled capacity will grow to over 20% of our ML capacity, which is at multi-gigawatt scale today. While liquid cooling technology itself isn't unique, our approach was. Creating something this effective that could be deployed across our 120 Availability Zones in 38 Regions was significant. Because this solution didn't exist in the market, we developed a system that enables greater liquid cooling capacity with a smaller physical footprint, while maintaining flexibility and efficiency. Our IRHX can support a wide range of racks requiring liquid cooling, uses 9% less water than fully-air cooled sites, and offers a 20% improvement in power efficiency compared to off-the-shelf solutions. And because we invented it in-house, we can deploy it within months in any of our data centers, creating a flexible foundation to serve our customers for decades to come. Reimagining and innovating at scale has been something Amazon has done for a long time and one of the reasons we’ve been the leader in technology infrastructure and data center invention, sustainability, and resilience. We're not done… there's still so much more to invent for customers.

Replit's gross margins went from 36% to negative 14% in two months. Same product. Same pricing. Same team. The only thing that changed: they launched a more autonomous AI agent that consumed more LLM resources than their pricing covered. Traditional SaaS has 70-80% gross margins because one more subscriber costs almost nothing. AI products pay for compute on every prompt. Your best users are your most expensive users. That single fact breaks every pricing model designed for the SaaS era. I mapped pricing across the top 50 AI startups by valuation with Moe Ali. Six patterns emerged. The scariest finding: in most AI products, the P90 user costs 10-40x more than the P50 user. Both pay the same subscription. You're subsidizing your heaviest users with revenue from your lightest ones. And that subsidy grows as power users discover more ways to use the product. Cursor learned this the hard way. They switched from flat 500 requests/month to a credit pool system. A developer burned the entire monthly allocation in a single day. $7,225 invoice. The CEO published a public apology on July 4th. The plan description quietly changed from "Unlimited" to "Extended" twelve days after launch. Anthropic took a different approach. Their $17/$100/$200 tiers map to genuinely different user personas. A casual user, a power user, and a developer replacing an IDE. Those are different products with different willingness to pay. Then weekly rate limits targeting less than 5% of subscribers to push the heaviest users toward the API, where per-token pricing covers actual compute. The pattern across all 50 companies: pure flat pricing is dying. Nearly half use two or three models simultaneously. Here's the full breakdown: 1. Complete AI pricing guide: https://lnkd.in/gdKaQSMk 2. Replit guide: https://lnkd.in/gmA_c_AG 3. AI product strategy: https://lnkd.in/egemMhMF 4. AI agents guide for PMs: https://lnkd.in/eeey5Cxr If you can't estimate your cost distribution across P10 to P90, you're not ready to set a price.

CONVERTING SURPLUS DISEL LOCOMOTIVES OF INDIAN RAILWAYS TO ELECTRIC LOCOMOTIVES COULD BE A GREAT BUSSINESS OPPORTUNITY- Road Map 1. Technical Possibility A diesel locomotive can, in principle, be converted into an electric locomotive, though the process is not straightforward. It involves: Removing the diesel engine (prime mover) and auxiliaries such as turbocharger, fuel tanks, and radiators. Installing high-capacity transformers, rectifiers/inverters, and traction converters to work with 25 kV AC (or other relevant supply). Adapting traction motors – many modern diesel locomotives already use electric traction motors powered by a diesel-alternator set; these can often be retained with modifications to accept OHE supply. Adding pantographs, circuit breakers, and high-voltage cabling for overhead connection. Weight balancing and space optimization after engine removal. 2. Precedents Indian Railways – “Mission 3000 DTTX”: Large-scale conversion of WDG-3A diesels into WAGC3 electric locomotives. Success factors: Co-Co bogies, adaptable traction motors, and wide availability of redundant diesel units. Globally, examples are rare – most railways prefer fresh procurement. 3. Advantages Cost savings: Conversion costs about 40% of a new electric locomotive. Energy savings: Diesel – 3 litres (₹300) per 1000 tonne-km vs. Electric – 8 kWh (₹100). Engine repurposing: Removed diesel prime movers can be redeployed as high-capacity DG Sets for power backup in workshops, depots, and colonies. Lower emissions and reduced maintenance. 4. Strategic Impact With 100% electrification target of Indian Railways, nearly the entire fleet of diesel locomotives (~5,500 units) risks redundancy. Conversion + engine repurposing creates dual benefits:
 Redeployment of chassis as electrics for hauling. DG Set utility of released prime movers for stationary applications. Enables capital recovery and avoids wasteful scrapping of serviceable assets. 5. Limitations Older designs with DC motors may not be convertible without full replacement. Converted locos have lower performance than purpose-built electrics. Viable only on fully electrified routes. Space/cooling compromises affect reliability if not carefully engineered. ✅ Bottom Line Diesel-to-electric conversion is not only technically feasible but also strategically vital in India’s context: Cost-effective (40% of new build). Engine repurposing into DG Sets enhances asset utilization. Mass redeployment of redundant diesels offers a sustainable pathway as India achieves 100% electrification. #CleanEnergy #Decarbonization #EnergyEfficiency #GreenMobility #ClimateAction #GatiShakti #MakeInIndia #AtmanirbharBharat #TransportPolicy #FutureOfMobility #DieselToElectric #LocomotiveConversion #RailwayTechnology #EngineeringSolutions #InfraInnovation #EnergyEfficiency #SustainableDevelopment #CarbonReduction #ClimateAction #CircularEconomy #MakeInIndia #FutureOfTransport