Companies face increasing pressure to set sustainability targets and implement emissions reduction initiatives. What are the most cost-effective ways to allocate resources to achieve these targets?
Marginal Abatement Cost Curves (MACCs) are commonly used to assess the opportunity, cost, and decarbonization potential of sustainability interventions. However, the main challenge with traditional MACCs is making them applicable across thousands of facilities and suppliers—each with local projects with unique geographic and technological characteristics.
This article examines how dynamic MACCs empower companies to optimize resource allocation for internal operations and supplier engagement. They enable precise, real-time decision-making, transforming the organization into a self-learning platform for capital allocation. Unlike traditional abatement cost analyses, dynamic MACCs allow companies and their vendors to make iterative updates in response to implementation processes and evolving business metrics.
A Marginal Abatement Cost Curve (MACC) illustrates the potential costs or savings from reducing one additional unit of emissions across a range of sustainability projects, compared to the anticipated volume of emissions they can reduce if implemented.
MACCs emerged as a helpful visual tool for cost-effective environmental planning in the 1970s and 1980s. However, the framework gained prominence with McKinsey & Company’s adaption to help businesses and governments understand the economic implications of greenhouse gas emissions reductions and prioritize cost-effective actions.
The graph below presents a MACC example that compares 14 abatement options. The horizontal axis represents the average annual greenhouse gas emissions reduction, measured in metric tons of CO2 equivalent. The vertical axis shows the marginal greenhouse gas abatement cost, i.e., the cost to reduce one unit of emissions, usually in dollars per metric ton of CO2 equivalent. Each bar on the curve represents a different abatement option, with the width of the bar indicating the abatement potential and the height representing the cost. The options are sorted by increasing marginal costs of carbon emissions reduction from left to right.
Abatement interventions can include any mitigation project, for example, installing solar energy systems, improving building efficiency with LED lighting, implementing high-efficiency motors, and more.
To calculate the marginal greenhouse gas abatement cost for an intervention, you can divide the total additional costs of implementing the intervention by the avoided emissions for a specific year or averaged across a time frame. The total additional costs often include both the initial investment and annual operational costs or savings to derive an annualized marginal cost. However, the specific methodology can vary based on the goals of the analysis and the nature of the abatement options.
The traditional MACCs are static and lack the flexibility needed for pragmatic strategy development. This limits decision-making capabilities by not allowing real-time adjustments to changing circumstances, regional and process variations, or emissions factors. To truly aid in strategic planning, MACCs need to become interactive, adapting to the dynamic nature of business and environmental conditions.
One of the significant hurdles in using MACCs effectively is the continuous updates with current, detailed financial and environmental data specific to location, technology, and projects. As companies evolve—through new investments, budget adjustments, or new projects—the MACC data must be updated, often through time-consuming, error-prone manual processes in Excel. For large companies, the challenge is magnified as resource allocation is centralized while projects occur globally across thousands of facilities and suppliers.
Static MACCs also fail to capture the fast-paced changes in technology effectiveness and costs, influenced by both private and public investments, including government subsidies. As technology evolves, so do emissions reduction opportunities. A dynamic MACC that adjusts to these changes is crucial for businesses to pinpoint and prioritize the most efficient and relevant abatement strategies.
AITrack, developed by Aligned Incentives, is an AI-powered enterprise sustainability planning platform trusted by the world’s largest organizations. Backed by cutting-edge life cycle assessment (LCA) expertise, data, and software, AITrack enables granular and scalable corporate footprinting, product assessment, strategy development, and reporting. Its strategy module includes dynamic MACCs to help companies build a cost-effective glide path to achieving their targets.
AITrack’s dynamic MACCs enable organizations to incorporate updated financial and environmental data specific to their projects, technology, and locations. It fosters a positive feedback loop and accelerates organizational learning— new insights from decentralized facilities and suppliers can be easily shared and adapted across different regions and contexts.
AITrack’s rapidly expanding libraries of interventions further enhance its decentralized adoption, resulting in more granular insights, broader use, and greater impact. This transforms strategy development from a centralized function, dependent on often outdated, generic data, to a decentralized approach with continuous resource optimization.
AITrack’s dynamic MACC function empowers users to design and test sustainability interventions tailored to their specific context and needs. Companies can incorporate their material issues and unique operations when exploring the abatement potential and financial forecasts. The MACC function is fully integrated with our custom process-based LCAs used to develop the GHG inventory. This integration ensures seamless alignment between financial and environmental data, enhancing the accuracy and relevance of analyses.
With AITrack’s dynamic MACCs, companies can foster close collaboration with suppliers by sharing data on mutual investment and cost savings opportunities. The ability to filter analyses by supplier enables targeted discussions to strengthen alignment with individual suppliers. As projects evolve, suppliers can also update their data in real-time, facilitating continuous improvement and shared ownership of decarbonization initiatives.
Users have the flexibility to customize parameters such as forecasted periods, budgets, and discount rates, facilitating scenario testing that can keep pace with your business growth. This customization allows companies to compare projected emissions reductions against target goals and timelines within their unique business context.
