Part 9: Potential Traps
Chapter 1 of The Climate Startup Playbook from Third Sphere
Hard to Decarbonize or Hard for Incumbents to Decarbonize
Dieselgate was in 2015. Until this moment, auto manufacturers were promoting the idea that fossil fuel auto emissions had been (mostly) solved. The framing was ideal in many ways. Incumbent auto manufacturers could build on existing internal combustion engine expertise and continue to benefit from a mature fuel distribution system (aka gas stations). Part of the “clean diesel” answer came from capturing various pollutants via reactions with exhaust gas, not unlike what’s possible with carbon capture.
Here’s a 2010 Super Bowl ad for clean diesel.
At the same time as “clean diesel”, most auto manufacturers were also working on and even delivering EVs. But there was a problem. The required investment in the design and manufacture of entirely new drivetrain, charging infrastructure, etc, would require much more investment, with much less certain outcomes. This wasn’t appealing to shareholders and no doubt there were also concerns from labor representatives and key suppliers. There was also a concern about consumers — first generations of EVs meant higher costs, reduced range, and the inconvenience of slow charging.
12 years later, the Super Bowl was overrun with EV ads. What happened? Certainly Tesla happened. But also China’s massive investment core components like batteries along with notable progress in the Chinese EV market. And clean diesel turned out to be more marketing and a lot less reality. And the signal from customers was pretty strong.
It’s worth considering incumbent framing of “hard to decarbonize” processes like long haul trucking, cement, and shipping. A big part of what makes electrification hard is not technology but existing investments, relationships and healthy cashflows, that don’t need to be completely re-invested into R&D.
It’s already clear that the EV passenger car market is rapidly creating new winners and losers. Faced with the prospect of disruption, it’s usual for incumbents to use all available tools that avoid R&D spending and risk. They’ll lobby to delay or dilute regulations and use PR (public relations) to create fear, uncertainty, and doubt. This isn’t unique to climate and or transportation; it’s always been part of tech disruption.
When thinking about climate startups, it’s always worth a look at industries that have yet to experience tech disruption. Many of them are in industrial sectors or agribusiness. There is very likely an opportunity for better, faster, and cheaper that also shifts to zero emissions electricity or more resilient solutions. And most incumbents tend to struggle in the face of fast-moving new competitors, even if they have a clear idea of the solution.
Incumbent auto manufacturers had talented EV development teams and even shipped compelling products — Toyota shipped products with Tesla (hard not to think of the Apple + Motorola lovechild, ROKR). It wasn’t a lack of talent, skill or motivation. It’s extremely difficult to simultaneously manage a legacy business while you try to ramp up something new. This is a huge advantage for startups. They can just focus on the new thing.
Mind the Forecasts
The IPCC report is a wonder of the peer review process. But it’s not without controversy. The language related to the scale and the timing of carbon removal, in the April 22, 2022 report is frequently referenced by founders and investors. But this language, was controversial for multiple reasons, starting with incumbent lobbying. Even without the controversy, models are ideal to help us think, but it’s very hard to resist the urge to point to models as forecasts.
In 2010, the International Energy Agency (IEA) predicted that it would take 40 years for the price of solar panels to drop significantly enough to compete with incumbent, mainly fossil fuel–based electricity generation. In fact, it took only 10 years, as government subsidies, manufacturing breakthroughs, and customer behavior drove solar module prices downwards. Climate models depend on assumptions like how quickly we can shift to zero emissions electricity generation; these in turn require assumptions about technology and humans, which have always been exceptionally hard to make. Forecasts about warming sit atop these assumptions, too.
Predictions and models go wrong for many reasons. Model-builders and the sources of data they rely on are animated by different motivations. Scientists view the world through one lens, activists through another, policymakers through a third. The findings of industry-funded participants are subject to charges of self-interest. But even independent researchers can succumb to siloed methodologies, bias, and tunnel vision, leading to unreliable findings.
Potential traps have always been part of large technology shifts. Incumbents have an incentive to stall, so they’ll emphasize narratives that suggest that climate action is harder and will take some time. Forecasts are designed for various audiences, though most often they are addressing incumbents and their audiences — startup usually cannot afford to pay for the research.
But this is where startup opportunities are created. Understanding customers and technology learning curves is the key to interesting climate startup ideas. And while there are early adopters in climate, customers are buying much more than planetary impact. Fortunately, incumbent solutions were never that great, so it’s possible to deliver not just better, faster, and cheaper, but also mitigation and adaptation.
Key Takeaway: Pay special attention when you see that something is “hard to decarbonize”. Understand that models are useful to help us think but tend to fail at modeling customer adoption, especially when this involves cost curves.
