Even as climate legislation, regulation, and taxation proceed slowly, some companies are responding voluntarily to the expectations of their environmentally sensitive shareholders and customers by starting the journey to decarbonize their supply chains. E-liability accounting, introduced in the November 2021 issue of the Harvard Business Review, enables organizations to build upon well-established accounting principles to address current shortfalls in measuring and reducing carbon emissions in complex supply chains.
Standard carbon-measurement approaches — notably the approaches recommended in the Greenhouse Gas Protocol (GHGP) and the life cycle assessments (LCA) used for environmental product declarations (EPDs) — are top-down hierarchical calculations in which each company seeks to estimate the emissions from every other company in its supply chain. The calculations are problematic since the estimates are usually provided by external analysts based on industry-average (secondary) data, not the actual emissions incurred by the company’s many suppliers. The standard approaches also require each company to replicate the calculations done by all others in its value chain, a costly and redundant process with multiple counting of the same emissions.
E-liability accounting, however, assesses a product’s carbon intensity (e.g., in kg of CO2 per product unit) through a recursive and informationally decentralized calculation. Each company requires emissions data only from its immediate suppliers and from its own operations to assign carbon intensity to its outputs of sales products. The company then shares the embedded product carbon information with its immediate customers who perform the same calculations with their purchased inputs and own operations for transmission further down the value chains. Collectively the approach tracks a product’s total cradle-to-customer carbon footprint, from mining the raw materials used in its manufacturing, to processing and transportation emissions, all the way to emissions from last-mile delivery.
In this way, and analogous to standard value-added calculations, E-liability accounting holds each business accountable only for its direct emissions and the actual upstream emissions embedded in the inputs it purchases from suppliers. Any reductions in a company’s direct emissions or the emissions of its suppliers will correspondingly lower the carbon balances of products sold and distributed to customers. What’s more, the emissions data for all products at each entity in a value chain can, in principle, be aggregated into company-level reports on total carbon emissions purchased, produced, and sold, much like a financial statement. Auditors and independent analysts can verify such entity-level reports, facilitating more effective green-finance investments.
While intuitive, E-liability accounting has yet to be widely adopted in practice, as companies continue to use the indirect and cumbersome GHGP and LCA approaches. In this article, we provide details on how early adopting global companies have obtained and leveraged carbon information from suppliers and their own operations to improve their own carbon footprints and offer customers the opportunities to improve theirs.
Managing Carbon Emissions
The first company is Singapore-based Giti Tire Group, one of the world’s largest tire companies, with clients in more than 130 countries and approximate annual revenues of US$ 2.5 billion. Giti uses large and well-known suppliers for its raw materials and semi-finished products, but, like most companies, relied on industry-level averages to calculate its Scope 3 emissions. Even this information was hard to come by. One of the principal sources of data on tire manufacturing emissions data came from a 2016 master’s thesis by a student in Finland. This static and now outdated data remained the basis for much of the sector’s own emissions estimates.
After learning about the E-liability method, the company’s CEO asked François Petiot, Giti’s director of quality assurance to develop a pilot at the company’s Indonesia subsidiary, PTGT. Petiot decided to calculate the emissions of just a single product, the standard passenger tire, which made up approximately 30% of PTGT’s tire production capacity. But even this seemed like an overwhelming task at first, since the tire was made up of more than 200 raw materials.
To make the challenge manageable, he applied the “Willie Sutton Rule,” named after the bank robber who defended his choice of occupation by stating “that’s where the money is.” Petiot applied the rule by estimating the emissions generated to produce four key input materials: synthetic rubber, natural rubber, carbon black (a soot-like powder used to strengthen the tire), and steel. Together, these components made up 86% of the tire’s weight and provided a starting point for inquiring into upstream supplier data. (See the first column in Table 1 for passenger car tire inputs by percentage of weight.)
Petiot recruited three managers for the internal pilot-study team. Chosen for specific expertise but also for their passion about emissions reduction, and their motivation to contribute beyond their everyday job, the team reached out to the suppliers of the four key raw materials to explain the E-liability pilot and to request their emissions data.
Although the suppliers were keen to cooperate, only a few were initially able to share specific emissions on their products sold to PTGT. For the rest, the pilot team relied on publicly advertised emissions factors, usually taken from the suppliers’ environmental product declarations. The team placed the suppliers’ estimates on a dynamic E-liability spreadsheet. The second column in Table 1 provides indexed values of CO2 emissions for passenger car tire inputs.
Petiot and his team then looked internally to develop a flowchart to identify the major emission sources when manufacturing the passenger tire. They homed in on the two most energy-intensive processes: compounding (mixing the materials that make the tire) and curing (applying pressure and heat to form the tire). They next calculated the company’s own direct emissions associated with these activities, along with the emissions inherent in their energy consumption.
In a final step, the team allocated the acquired supplier emissions and the incurred site emissions to the standard passenger-car tire, calculating the carbon tonnage per tire. This step revealed the emissions per tire that could then be transferred to PTGT’s own customers when the tire was sold.
Petiot had initially expected that calculating PTGT’s tire-specific emissions data would be a challenge. However, the pilot had taken only about two months, and Petiot realized that they already had much of the necessary data recorded on disclosures filed with regulators. The task at hand was then not to start from scratch, but to verify the accuracy of their already existing data, especially since such figures were not controlled by any audit body, and then, where possible, to get lot-specific data. This process had yielded a first approximation of the E-liability method, one that could be refined subsequently with more accurate data from their suppliers and their own processes.
Armed with a first pass of the E-liability of a standard passenger-car tire, Petiot and team started to identify areas where they could make emissions reductions. “Through the pilot, we found that our purchases of electricity and carbon black had been made without visibility into their less-than-optimal GHG emissions,” he said. “By measuring emissions for each of the suppliers, we could identify where changes could be made to reduce the carbon footprint of our tires.”
Once its suppliers realized that PTGT was actively invested in reducing its carbon footprint, they started to propose their own lower-emission alternatives. The carbon-black supplier suggested using circular production methods that reduced emissions by 38% by optimizing resource use over the products’ lifecycle. The natural-rubber supplier could reduce emissions by 27% by switching from a domestic-plantation supplier to a more productive one in Thailand. The steel supplier could reduce emissions by more than 43% by replacing virgin ore that required smelting in basic-oxygen furnaces with recycled steel that would be processed in lower-emission electric-arc furnaces. (See the third column, Emissions Savings in Table 1 for the benefits from the “cleaner” input alternatives.)
The PTGT team also examined where they could reduce emissions at each step of their manufacturing process, especially those that were energy intensive. The team estimated that using on-site solar power to replace some of its grid electricity would reduce purchased energy emissions by 18%, although this was an upper-bound estimate that did not include the upstream emissions from manufacturing solar panels. And using newer, energy-efficient natural-gas boilers could reduce emissions up to another 6%.
In aggregate, Petiot and his team estimated that by working with suppliers and adjusting their internal processes, they could, on a first pass, reduce the emissions of their passenger tires by about 22%. They began to study opportunities with additional input materials, such as bead, nylon, polyester, and certain chemicals, which expanded the coverage to 95% of the tire’s mass. Further, as an outcome of their pilot, PTGT initiated a collaboration with one of its steel suppliers to source low-emission, high-durability steel cords that could reduce fossil-fuel usage over the lifetime operations of a vehicle.
When PTGT took these pilot results to one of its major customers, the automaker was intrigued. It has asked the tire company to scale the pilot to its China factories that directly supply the automaker’s cars. With such customer support, PTGT hopes it can make decarbonization a competitive advantage.
Reporting Product-Carbon Intensities
The second company we studied was Germany’s Heidelberg Materials (HM), one of the world’s leading cement producers. Cement production is a major contributor to global warming, responsible for up to 8% of global CO2emissions. HM wanted to explore ways of reducing its contribution to that number.
Following the Willie Sutton rule, HM focused on the dominant contributor to cement-related emissions: the conversion of limestone (CaCO3) into clinker (CaO), the main ingredient in traditional Portland cement. The process emissions from this conversion account for two-thirds of the overall emissions from Portland cement production. HM, like other cement producers, had increasingly substituted low-carbon cementitious materials, such as fly ash and slag, for high-carbon intensive clinker. But HM had to navigate various regulatory standards to account for the embodied emissions in these materials.
HM was already producing environmental product declarations to meet regulatory requirements for cement products. But because each EPD estimates the CO2 emissions for one specific product, produced at a specific plant, in a specific period, the process takes considerable time to complete for each product, and any change in the production process, design, or sourcing requires a new EPD to be produced and validated. HM’s environmental team wanted a real-time management measurement system that reflected the actual carbon content from current cement recipes, production processes, energy purchasing, and materials sourcing.
HM sought an alternative measurement system to assign an appropriate share of plant-level, energy-related, and purchased emissions to each of the plant’s outputs. The system followed a multi-step process for allocating emissions to products, akin to an activity-based costing approach.
First, it accessed existing data about upstream emissions of fuels, limestone, and slag, the major purchased inputs together with electricity. It then estimated the plant’s direct emissions, primarily those from the fuel used to heat the kiln for the limestone-to-clinker chemical reaction, and the CO2 process emissions from the reaction itself. The system next assigned the direct and indirect emissions to three major processes at the plant: clinker production, slag grinding, and cement milling. In a final step, the system assigned the emissions from the three processes to the plant’s outputs, using appropriate drivers such as the product’s relative clinker or slag content, and its milling time.
Table 2 presents the data for three representative cement outputs, Cements 1-3. Cement 2, which replaces some clinker content with slag, is 15% less carbon intensive than Cement 1 but requires more drying time to achieve full structural strength. Cement 3, which uses much more slag in the cement mix, has a 58% lower carbon intensity than Cement 1 and still longer drying times than Cements 1 and 2 to achieve its full structural strength.
The carbon-accounting system enables HM to report credible and timely product-level emissions to customers, based on a product’s actual production process, recipe, and sourcing. Customers can then make informed decisions based on a product’s price, its carbon intensity, its drying time, and its structural performance.
. . .
These two case studies illustrate how companies can implement the E-liability framework to green their supply chains. As the practice spreads, it will become progressively systemized, eventually making emissions a factor in every business’s purchasing and investment decisions, like price or quality.
The infrastructure for this is already being assembled as leading firms develop software and blockchain solutions that enable and automate product-level emissions data, calculated according to the E-liability method, to be stored and validated at each node of a supply chain. The chemicals company BASF, for example, has developed a digital carbon-accounting tool to calculate the carbon footprints of its 40,000 sales products based on its own production processes and the carbon intensity of its more than 20,000 different chemical inputs. Suppliers can license the tool, through an independent third-party, to calculate the product carbon footprints at their own operations. Within one year, a notable share of BASF’s suppliers had subscribed and were using the tool to provide BASF with primary emissions data.