Auto Supply Chains: Pinpointing the Commercial Case for Sustainability

Novelis and Sourced Economics have teamed up in recent months to pore through key academic literature, market research, and case studies with one goal in mind: to build an analytics toolbox for sustainability decisions, especially focused on environmental sustainability.

In automotive especially, a central industry for private and public environmental policy making, analysts struggle to pinpoint and quantify the commercial case for green initiatives. In this article, we share our key findings and methods on the topic to inspire more data-driven, targeted, and effective sustainability planning.

Companies are struggling to thread the needle in their efforts to address sustainability demands.

For all the investor reports, whitepapers, and webinars, sustainability appears to be an area still dominated more by rhetoric than reliable data. Too often, it is even viewed as disconnected from commercial objectives.

Sifting Through the Data Noise

Statisticians might generously describe the research on environmental sustainability as ‘noisy,’ or difficult to interpret. In industry, recent volatility and a plateau in the mentions of sustainability during company earnings calls have been widely reported on. Amid this uncertainty, allocating resources among the various initiatives underway to meet increasingly ambitious emissions targets or similar goals is proving to be a complex challenge for sustainability leaders.

Based on our research, within automotive, more than 60 distinct initiatives are underway across just the 10 largest automotive manufacturers, including recycling programs, electric vehicle rollouts, design changes, and numerous software projects. While precise estimates are hard to find, annual spending on these sustainability efforts almost certainly reaches billions, if not tens of billions, of dollars. And yet, taken together, these initiatives are neither delivering on emissions targets nor proving very profitable in many cases.

Regardless, automakers continue to worry about losing loyal customers, absorbing excessively high regulatory costs, suffering reputational damage, or missing out on key innovations, all of which could result from either under-committing or over-investing in environmental initiatives.

To sharpen sustainability planning across automotive and beyond, we find in the literature a straightforward yet effective modeling technique: treating environmental performance as a product feature, one of many that customers consider when making purchasing decisions.

Customers, on average, prefer lower lifecycle emissions just like they prefer better safety. Yes, really.

The environmental performance of a product is a feature much like its size, speed, or ease of use. Also like those other features, the average customer is willing to pay extra for a more environmentally sustainable product, generally measured by its lifecycle ‘use phase’ greenhouse gas emissions.

Our research, drawing on studies from 50 authors, primarily based at universities, suggests that consumers, on average, are willing to pay $58 more for every 1-ton reduction in a product’s greenhouse gas emissions.

This proposition flies in the face of a growing view in some circles that consumers claim to support ‘green products’ but are ultimately unwilling to pay premiums for them. Many have rightly noted that survey responses differ from actual purchasing behavior. To be sure, these concerns are valid, as we find the truth of the matter to be nuanced.

Estimating Consumers’ Willingness to Pay (WTP) for Green Features

The statistical results from these studies do not fall neatly into a tight and normal distribution of willingness-to-pay (WTP) estimates. Instead, they vary widely across industries and often reflect a ‘bimodal distribution,’ meaning there are two distinct groups with different levels of WTP.

Although an average WTP can be found, it may be low or even negligible for up to half of consumers. In nearly all cases, the average is much higher than the median, suggesting that a small group of highly environmentally conscious customers is especially influential.

These insights highlight the importance for companies to analyze customer preferences and prioritize marketing and investments accordingly. In automotive markets, WTP estimates for reducing emissions across a vehicle’s entire lifecycle by 1 ton widely range between $244 (adjusted for inflation) and $268 (adjusted for inflation).

However, regional differences are notable, with European consumers showing the strongest preference for more sustainable vehicles, followed by those in the Americas and Asia-Pacific.

Preferences also vary among automakers, largely influenced by vehicle price points. That is, consumers purchasing higher-end cars, who tend to have higher incomes and more education, show a statistically higher WTP for environmental benefits.

The estimates described here were not drawn from industry surveys. Instead, they were derived using econometrics from both observed purchasing data and more advanced ‘discrete choice assessments.’

In these experiments, car buyers choose between vehicles based on a range of attributes, with greenhouse gas emissions being just one factor. For reference, surveys that ask questions like ‘do you prefer purpose-driven brands that advocate sustainability?’ often exaggerate preferences by as much as 60% due to ‘hypothetical bias,’ whereas these discrete choice experiments typically yield closer to 35%.

Finally, note that while the results contained in these studies pass through a rigorous peer-review process before publication, we applied a similarly thorough process before incorporating them into our strategic planning recommendations and, for that matter, into this article.

Capturing the environmental premium is not a free lunch.

The obvious question we’ve yet to address is: at what cost can companies capture the environmental premium reflected in our WTP estimates?

Consumers undeniably value environmental performance, but it is just one among a multitude of product features they consider. Initiatives that enable companies to command a price premium for sustainability might inadvertently compromise other, potentially more significant, features such as safety, reliability, or performance.

To comprehensively forecast the costs and benefits of a green initiative, we leverage a simple yet powerful methodology: combining consumer WTP amounts across all product features with the initiative’s estimated impacts on those features into a single mathematical equation.

This multivariable scenario modeling approach provides a balanced view of trade-offs, revealing when and to what extent an environmental improvement is likely to succeed commercially. This type of analysis is rare, both in academic and industry research, which often take narrower approaches.

Counterintuitively, we find that the premium charged for enhancing a product’s environmental performance, given its relatively low ranking among consumer preferences, accounts for only 2% to 15% of the financial drivers behind such initiatives. This premium acts like a subsidy that complements but does not independently drive technological advancements. Therefore, though estimates of consumer willingness-to-pay for emissions reductions can be useful indicators in valuating environmental factors, greater context is clearly needed for strategic planning.

Exploring Vehicle Lightweighting

The case of vehicle lightweighting, unsurprisingly a major focus of our research at Novelis and Sourced Economics, illustrates the value of using advanced data science methods for sustainability and commercial leaders in the automotive industry. By reducing a vehicle’s weight through material innovations or redesigns, multiple benefits emerge, including improved acceleration, lower fuel costs, and reduced greenhouse gas emissions over the vehicle’s lifecycle.

Unlike earlier studies that primarily compare lightweighting costs against fuel efficiency gains, we consider the cumulative impact on all features. Within reasonable targets, the benefits of lightweighting substantially outweigh the associated costs given today’s supply and demand conditions.

What’s more, evidence of an ‘energy paradox’ is presented regularly across academic studies, implying an under-valuation of car buyers’ WTP for fuel efficiency.

As a result, the premiums generated for automakers through the technological advancements of lightweighting are greater than most forecasts suggest and, based on our models, solidly exceed the added manufacturing costs required. In fact, we anticipate that for the foreseeable future, automakers operating in suitable markets and willing to embrace these transformations can not only fully recoup lightweighting costs but also expand margins.

For reference, these results differ from the case of electric vehicle technologies, in which we expect automakers to face margin pressures through 2029. Higher manufacturing costs, coupled with persistent challenges such as limited driving ranges, are likely to constrain profitability.

Similarly, initiatives like recycling programs and carbon trading systems may remain uneconomical in the near term due to their limited effects on the operating costs of vehicles or, paradoxically, even on lifecycle emissions in some cases.

A key takeaway, for the automotive industry and beyond, is that aggressive technological innovation must go hand in hand with green initiatives and as well as the regulations that often drive them. And with stronger data and analytics capabilities, sustainability leaders can more accurately identify the investments most likely to succeed, balancing environmental goals with the need for reasonable financial returns.

Sustainability Goes Beyond Public Outcomes

As markets for green products become larger and more complex, data and analytics can no longer be neglected. The automotive industry serves as a compelling example that sustainability is not solely about achieving public outcomes, like reducing greenhouse gas emissions.

It’s also about driving the technological advancements that make those outcomes possible. In this article, we have outlined methods for forecasting and prioritizing green initiatives, though have only scratched the surface. Our hope is to encourage sustainability leaders and researchers not only to adopt these methods, but to refine and advance them, paving the way for more effective and economical portfolios and strategies for the future.