If you can't provide credible carbon emissions data, the market may not wait for you to catch up. Your bank may use proxy figures, your insurance may price the risk, your customer may choose a supplier who can prove what you can't, and increasingly, missing carbon data won't look like a blank sell in a spreadsheet. It'll look like a warning label. Because accurate emissions data is no longer just for shiny PDFs, it's becoming your company's permission to sell. Good morning, good afternoon, or good evening wherever you are in the world. Welcome to episode two hundred and eighty of the Climate Confident Podcast. This is a bonus episode, so Climate Confident Plus, and I'm your host, Tom Raftery. Today's topic is one I think is becoming central to the next phase of climate action carbon emissions data. Not carbon data as an annual reporting chore, not carbon data as a few figures buried in a glossy sustainability PDF, not carbon data as something the ESG team spends three months chasing before everyone else forgets it exists. I'm talking about good carbon emissions data as a core business system. And here's a sentence I want you to remember from this episode. Accurate emissions data is not just for shiny PDFs anymore. Increasingly it is becoming your company's license to sell. Or permission to sell if you prefer the slightly less dramatic version. Either way, the point is the same. Carbon data is moving from reputation to regulation, from disclosure to procurement, from sustainability teams to finance teams, from nice to have to market access. And if companies do not understand that shift, they're going to find themselves surprised in expensive and deeply avoidable ways. A few years ago, poor carbon data was mostly embarrassing. Maybe your sustainability report looked weak. Maybe an investor asked an awkward question. Maybe procurement raised an eyebrow. Maybe someone suggested hiring a consultant, building a dashboard, holding a workshop because obviously no corporate problem exists until twelve people have been trapped in a room with sticky notes. But the consequences were manageable. That's changing. Bad emissions data now can affect your ability to win tenders, to get insured, to access finance, to import goods, to satisfy customers, to retain talent, and to defend claims. It can determine whether your product looks compliant, risky, expensive, or simply too much trouble. And that phrase matters, too much trouble because no customer wants your carbon uncertainty inside their scope three inventory. If you're a supplier, your weak data becomes your customer's reporting problem, their regulatory problem, their investor problem, their procurement problem, their risk problem, and increasingly their AI optimization problem. When a supplier becomes a problem, procurement eventually starts looking for another supplier. That's where carbon data becomes commercial. Let's ground this in the numbers. CDP and Boston Consulting Group reported that corporate scope three supply chain emissions are on average twenty six times greater than direct operational emissions. Twenty six times. That is not a rounding error. That is the main event. Scope one is what a company directly emits from the things it owns or controls. Scope two is the emissions from purchased electricity, steam, heat, or cooling. Scope three is everything else across the value chain. It's your raw materials, suppliers, logistics, product use, waste, business travel, investments, and so on. In other words, the difficult bit. So naturally the bit where most of the emissions are hiding. The same CDP and BCG analysis found that upstream emissions from manufacturing, retail, and materials alone were one point four times the total carbon dioxide emissions of the European Union in 2022. That's the scale of the issue. And yet many companies are still behaving as if emissions management is mainly about offices, electricity bills, and the occasional symbolic campaign to remove disposable cups from the canteen. Nice, perhaps, yes. Material? Often not. This came through strongly in my recent resilient supply chain conversation with John Beat. John's point was wonderfully practical. Companies often assume the carbon problem is where they see activity, their own factory, their energy bill, their fleet, their facilities. But when you do a proper life cycle assessment, the hotspot may be somewhere else entirely. It may be raw materials, it may be aluminium, it may be packaging, it may be a component from a supplier two tiers upstream, it may be the useful life of the product, it may be the energy mix in the country where a material was processed. And this is why primary data matters. Primary data means data from the actual process, supplier, site, product, or material involved, not an industry average, not a generic database estimate, not a number borrowed from a vaguely similar process on another continent and then treated as truth because it sits nicely in a spreadsheet. Let's be careful. Industry averages are not useless. They're often essential at the start. They help companies estimate, screen, prioritize, and identify likely hot spots. For many smaller suppliers and for many early stage measurement efforts, averages are the only practical place to begin. The problem is not using averages, the problem is getting comfortable with them. Averages are a map. They're not the territory. They can tell you where to look. They cannot prove what's actually happening in your supply chain, in your product, in your supplier's process or in your customers' regulatory filing. So the goal is not perfect data everywhere by next Tuesday. That's a fantasy. And corporate fantasy already has enough market share. The goal is better data where it matters most. High emissions materials, high volume suppliers, strategic products, regulated markets, tender critical customers, places where a better decision could cut emissions or reduce risk or protect revenue or improve resilience. And this is where the finance and insurance piece becomes very real. In another recent resilient supply chain conversation, Cynthia Lai, a former banker who worked in HSBC and Bank of China, made a point that should get the attention of any supply chain or sustainability leader. If you cannot provide credible emissions figures, your bank or insurer may not simply shrug and move on. They may use proxy data, they may use industry averages, they may use reference figures. And here's where it gets tricky, because those assumptions are unlikely to flatter you. If the data is missing, the market fills in the blanks and rarely with generosity. For banks, your emissions increasingly sit inside their financed emissions exposure. For insurers, your operations sit inside their insurance associated emissions and wider risk portfolio. So if your emissions are high, unclear, or poorly evidenced, you may look riskier. That can affect your interest rates, it can affect your insurance premiums, it can affect your approval processes, and in some cases, if you cannot get operations insured, getting finance becomes much harder because banks like protection. So the question for leaders is not only what emissions data do we need for reporting, it's also how does our emissions data make us look to our bank, our insurer, and our largest customers? That's a very different lens. The regulatory pressure is accelerating too. Europe is probably the sharp edge, but this is not just a European story. The EU carbon border adjustment mechanism, or CBAM, is moving into its definitive regime. For covered goods such as cement, iron and steel, aluminium, fertilizers, electricity, and hydrogen, importers need to declare embedded emissions and surrender certificates linked to those emissions. Put simply, carbon is becoming part of the cost of crossing a border. If your products depend on carbon intensive inputs and your emissions data is poor, that's not just an administrative inconvenience. It can become a cost problem, a compliance problem, and a competitiveness problem. Then there's the EU eco design for sustainable products regulation and the growing move towards digital product passports. Digital product passports sound technical, but the principle is simple. Products will increasingly need structured, accessible, trustworthy information about what they're made from, where materials came from, how repairable or recyclable they are, and what environmental impact is embedded in them. The QR code is not the strategy the data behind it is. Batteries show where this is going, packaging is moving to, deforestation regulation is coming, forced labor regulation is coming, different rules, same message. Prove it. And beyond Europe, California's SB two hundred five three will require large companies doing business in California with more than one billion dollars in annual revenue to disclose scope one, scope two, and scope three greenhouse gas emissions. That matters because California is not exactly an irrelevant provincial market. What it requires will ripple through supply chains far beyond California itself. Then there is IFRS S two, the climate disclosure standard from the International Sustainability Standards Board. It focuses on climate related risks and opportunities that could affect cash flows, access to finance, and cost of capital. Those are not sustainability side quest words. Cash flows, access to capital, cost of capital, that's CFO language, investor language, credit committee language. This is where the old boundary between sustainability and business collapses. If climate risk affects your cost of capital, it's not an ESG issue, it's a finance issue. If carbon data affects tender eligibility, it's not an ESG issue, it's a revenue issue. If product carbon footprints affect market access, it's not an ESG issue, it's a commercial issue. And if AI systems are starting to make or recommend decisions across procurement, planning, product design, logistics, finance, and risk scoring, then weak sustainability data becomes a technology governance issue too. In my recent climate confident conversation with Stephen Jameson from SAP Sustainability, he made a point that should make every AI happy boardroom pause. Businesses are excellent at measuring cost, they're excellent at measuring revenue, they're excellent at measuring utilization, margin, inventory, throughput, working capital, delivery times, and financial performance. So when AI systems are introduced into business decision making, what do they optimize for? The strongest data in the system. If carbon, water, recycled content, supplier resilience, and wider sustainability factors are not in that same decision environment, they risk becoming secondary or worse, they risk getting optimized against. AI will not wake up one morning with a conscience. It would not look at a procurement model and say, hang on, this cheaper supplier has a higher embedded carbon footprint and greater climate risk exposure. Perhaps we should think systematically. No. It'll optimize for what the system tells it to value. And this is not limited to internal AI systems. Cynthia Lye also made the point that banks are already using AI and data models to assess customer risk. ESG and climate factors are becoming part of that credit risk picture. So weak emissions data may not just be reviewed by a sustainability analyst or a relationship manager, it may be ingested into a risk model. It may shape how your company is categorized. It may influence whether you look like a lower risk or higher risk customer. That should focus minds. Because if your competitors can provide clearer, more credible, more decision grade emissions data and you cannot, the comparison may become visible not only to customers, but to lenders, insurers, and the systems they use to price risk. If carbon data lives in a sustainability platform updated once a year while finance, procurement, manufacturing, and logistics run on live operational data, sustainability will lose. Not necessarily because anyone is evil, because the system was designed badly. Efficient nonsense is still nonsense. So when I say carbon data is becoming your license to sell, I do not just mean compliance. I mean operational intelligence. Carbon data needs to live where business decisions happen, inside procurement systems, inside enterprise resource planning, inside product lifecycle management, inside supplier onboarding, inside manufacturing systems, inside logistics planning, inside finance, inside AI enabled decision workflows. Otherwise, companies are effectively asking the sustainability team to influence decisions from the car park while everyone else is in the boardroom. And then executives wonder why progress is slow. Here's the caution. Technology systems matter. Buying another platform is not the same thing as solving the problem. A dashboard is not decarbonization, a product carbon footprint database is not decarbonization, an AI sustainability agent is not decarbonization. These things can help, sometimes enormously, but only if they change decisions. If the data does not affect procurement, product design, supplier engagement, logistics, capital allocation, energy purchasing, manufacturing processes, and customer conversations, then what you have is not transformation, it's reporting with better lighting. This is also why global standards and data exchange work matters. WBCSD's Partnership for Carbon Transparency or PACT is trying to standardize how companies calculate and exchange product carbon footprint data using supplier specific primary data. That may sound dry, but it's not. It's plumbing, and plumbing is only boring until it fails. Now, what should leaders do? First, stop treating emissions data as an annual reporting project. Annual reporting is too slow. By the time the report is published, supplier mixes have changed, energy prices have shifted, regulations have moved, customers have asked new questions, and competitors may already have better data. Carbon data needs to become part of the operating cadence of the business. Second, take an eighty twenty approach. Don't try to perfect everything at once. Start by identifying the suppliers, materials, products and processes most likely to drive the bulk of your emissions and commercial exposure. Which twenty percent of suppliers are responsible for the biggest share of your emissions, which products depend on high carbon inputs, which materials are exposed to CBAM or other carbon related rules, which customers are already asking for product carbon footprints, which suppliers would cause the biggest problem if their data proved weak. That is not sustainability reporting, that's risk triage. Third, build a climate data bill of materials for your priority products. For those products, know the materials, suppliers, production sites, energy inputs, logistics routes, emissions factors, recycled content, packaging, primary data availability, and evidence gaps. Yes, it sounds boring. So does cybersecurity until the ransomware note arrives. Fourth, talk to your bank and your insurance broker before the renewal conversation becomes painful. Ask what emissions data they're starting to require. Ask how climate risk is being factored into lending, premiums, and portfolio assessment. Ask what credible transition plans or supplier improvement programs would help. And if you're investing in emissions reduction through electrification, renewable energy, supplier engagement, energy efficiency, lower carbon materials or logistics changes, ask whether there are financing structures that can support that. Don't wait until the bank or insurer has already put you into a risk bucket that you don't like. Fifth, use averages intelligently, but don't hide behind them. Start with averages where you must. Use them to screen, use them to prioritize, use them to identify likely hot spots, but then move towards primary data where it matters most. Your high volume products, your high margin products, your high emissions materials, your strategic customers, your regulated markets, your tender critical categories. And be honest about data quality. Not all carbon data deserves the same confidence. Some figures will be measured, some will be supplier reported, some will be modeled, some will be estimated, some will be frankly shaky. That's okay, provided companies are transparent about it and improve over time. False precision is dangerous. A number with two decimal places can still be nonsense. Sixth, connect emissions data to decisions. If lower carbon materials increase cost slightly, but reduce CBAM exposure, improve tender eligibility, protect a strategic customer, or reduce future regulatory risk, that belongs in the decision. If a supplier is cheap but has poorer emissions transparency, weak energy resilience, and questionable traceability, that belongs in the decision. If an AI planning system recommends a low cost option that increases carbon exposure, that should be visible. Carbon data shouldn't be a comment field after the decision has already been made, it should be one of the variables shaping the decision. And seventh, build a credible plan before you have perfect outcomes. Banks, insurers, customers and regulators know companies cannot transform complex supply chains overnight, but there's a huge difference between saying we don't know and saying we've identified hotspots, prioritized the top suppliers, started pilots, improved data quality, and built a timeline. That plan matters. It tells the market you understand the risk. It tells customers you're not hiding behind averages, it tells banks and insurers. You're managing the exposure. And it also tells your organization that emissions data is no longer a reporting scramble, it's how the business is run. And finally, leaders need to stop pretending that delay is neutral. It's not. I'm genuinely frustrated by how slow many companies are to move on this, and I'm even more frustrated by those actively backsliding. Given the number of stakeholders involved, customers, employees, suppliers, investors, insurers, regulators, communities, and frankly, everyone who has to live with the consequences of climate breakdown, delay is reckless. Not cautious, not pragmatic, reckless. Because the direction of travel is obvious. Data requirements are rising, regulations are tightening, customers are asking harder questions, capital is becoming more selective, AI is accelerating operational decisions, supply chains are being repriced around risk, and physical climate impacts are not waiting politely for someone's twenty twenty nine transformation roadmap. The companies that act now will not get everything right. No one does, but they'll learn faster, they'll find the hotspots earlier, they will support suppliers sooner, they'll design better systems, they will answer customer questions with confidence, they will defend claims, they will reduce friction in procurement, they will protect market access, and they will be better positioned as carbon becomes a commercial condition, not just a reporting metric. The companies that wait, on the other hand, will discover that the transition didn't pause for them. It just rooted around them. So the takeaway is simple. Accurate emissions data is not just for shiny PDFs anymore. Increasingly, it's your company's license to operate, your permission to compete, your evidence base for customers, your input for AI, your defense with regulators, your conversation with finance, your signal to investors, your proof to employees that the company is serious. But data alone isn't enough. Averages aren't enough. Platforms aren't enough, targets aren't enough. The data has to become decision infrastructure and the decisions have to cut emissions. That's the standard. If you do not provide credible data, someone else may assign a number to you, and you may not like the number they choose. Carbon data is no longer a sustainability accessory. It is commercial infrastructure, risk infrastructure, market access infrastructure, decision infrastructure, and increasingly the companies that can prove it and act on it will be the companies that get to sell. That's it for this Climate Confident Plus bonus episode. If you found this useful, please share it with someone who needs to hear it, especially someone in finance, procurement, product, operations, policy, or leadership who still thinks carbon data is mainly around reporting. And send me your comments, challenges, or suggestions for future Climate Confident Plus bonus episodes. These are meant to be timely, topical, and genuinely useful, so your input helps shape where I go next. And next week's regularly scheduled climate confident episode will be out as ever on Wednesday, the seventeenth of June. That episode is my conversation with Claire Smith, CEO of Beyond Investing, and we get into ethical investing, capital allocation, climate, and what it really means to align finance with the world we need to build. Until then, thank you for listening. Stay curious, stay constructive, and keep pushing for the data because in this next phase of climate action, the companies that can prove it and act on it are the companies that get to sell.