The success of a climate tech business model is not determined by how much data it collects. We need to find out what decisions users need the data for, and on what terms they will pay for services that help them make those decisions. Chapter 9 of Technology and Solutions for Demonstrating Carbon Reduction presents the connection between carbon data and decision-making as the starting point for evaluating a business.
Define the concept and scope of application first
The differences between business models become clear when the deliverables for each service are made concrete. A farm alert service depends on which anomalies it checks for and how responses are recorded, while support for external reporting depends on the calculation rules and whether the materials can be reviewed again. Even when the same source data is used, costs and responsibilities differ. Contracts should specify delivery frequency, error correction, data handover, and termination conditions. Broad access rights to data do not by themselves permit reuse for every purpose. Repeated demand can be assessed only when customer workflows and authority are designed together.
Start by clarifying the boundaries of the term. Carbon Intelligence is neither the name of an international standard nor a certification scheme. This book uses it as an analytical concept to describe a practical framework that connects carbon data with costs, risks, productivity, and policy decisions. The term itself does not imply technological superiority or completed verification.
When data supply and verification work are connected, risks of self-review or commercial pressure can arise. Look beyond job titles or organization charts and examine revenue relationships, review authority, and requests to change results. For businesses that require third-party verification, check independence and eligibility separately according to the applicable requirements.
A data service is a business option to assess in its own right. The ability to produce reliable materials repeatedly can become a paid service when it reduces customer costs or improves decision-making. Confirmed customer demand and contracts are what turn that possibility into revenue.
Distinguish who needs what materials for regulatory compliance, supply-chain reporting, and farm operations. Do not assume that demand will remain even if regulations change. Review the term of paid contracts and their renewal and termination conditions, along with the cost to customers of producing the materials themselves.
Wider adoption may increase demand for data management, but it does not guarantee higher revenue. Assess price declines resulting from standardization, competition, data access rights, and customers’ willingness to pay together.
To judge recurring demand for a data service, check where customers use it and what their contracts say. The ability to produce accurate materials is necessary, but does not by itself guarantee purchase intent. Specify delivery frequency and quality, access rights and handover terms, error correction, and renewal and termination conditions. Regulatory compliance, supply-chain reporting, and farm operations call for different materials and decision timelines, so service scope and costs should also be assessed separately.
Disaster costs borne by the state and by farms can distribute the benefits and burdens of preventive investment. Climate resilience support should be designed by examining the damage and costs reduced by individual measures such as cooling and ventilation. Even when linked to a low-carbon feed business, reductions in livestock mortality or recovery costs should be attributed to the adaptation measures that actually produced those effects.
Conditions and limitations of field application
A farm manager may want to identify missed feedings quickly. A purchasing company may need emissions data within the scope set by its contract. Even when the same farm records are used, delivery frequency, review procedures, and access rights differ. If two hypothetical customers are grouped together simply as users of one dashboard, it is easy to overlook the features and costs each needs.
Verification provides a basis for assessing effects and costs. However, the fact that something has passed verification does not guarantee that it can substitute for a budget allocation or that the business is profitable. Link recognition requirements with economic assessment, while keeping a record of each decision separately.
Market access. The benefits of compost and liquid manure are realized only when there is farmland on which to apply them or a buyer. Links with crop farmers, local demand, and transport distance determine the actual benefits. In areas with a high concentration of livestock farms, supply can exceed demand, resulting in treatment costs instead.
Annual net cash flow and the maximum funding shortfall during a project are different indicators. If costs arise first and subsidies or purchase payments arrive later, more working capital may be needed than the year-end result suggests. Accumulate outflows and inflows by timing to identify the period when funds are most constrained. Review payment-delay conditions separately, and distinguish financing costs from existing farm operating funds when planning.
Evidence needed for investment review
Investors need to distinguish data collection contracts from actual purchase intent. They should check who pays, how much the service reduces existing work, and what is assessed at renewal. Even when the verifiability of materials is established, paid demand does not arise automatically.
Even if substitutability is established, there is no reason to set the full alternative cost as the compensation rate. Consider farmers’ additional costs and productivity benefits, existing support, procurement competition, and budget limits together. Changes in alternative costs can inform periodic reassessment, but should not become a rule that automatically raises compensation mechanically.
Consider shared services or vouchers so that small farms are not burdened with excessive costs for records and verification required for public purposes. The public value of common methods and published statistics differs from the nature of individual farm source data and commercial services, so not all verification information should be presumed to be a public good. Whether full funding or partial cost-sharing is appropriate should be judged by the scope of beneficiaries, participation constraints, and the cost-effectiveness of the budget.
MRV costs, therefore, should be assessed like any other investment in light of the required quality and decision-making value. If the verifiable scope is narrow, limit the claim; if the cost of additional materials exceeds the improvement in judgment, adjust the business design or the level of the claim. The mere fact that money was spent on verification does not justify the cost.
Criteria to keep in view when making a decision
A climate tech business model should be able to explain how data becomes part of a customer’s work. The expression “data asset” becomes concrete in business terms when customer-specific deliverables and responsibilities, usage rights, and recurring costs are presented.
About the author
Bongjun Lee graduated from the Graduate School of Management of Technology (MOT) at Sogang University. He spent seven years at Infitron Co., Ltd. and 20 years at Honeywell, working for a total of 27 years in gas measurement in service engineering, technical sales, and channel management. He is now the founder of AI Safety Korea Co., Ltd., where he is researching livestock methane monitoring and measurement, reporting, and verification (MRV) systems using sensors, AI, and data analytics.