How Do We Pick Cleantech Winners?

The transition to a zero-carbon economy has many elements. The most obvious is the need for clean electricity, but there are hundreds or thousands of other sectors to be addressed, from energy storage to steelmaking to the manufacturing of fertilizer.

Often, there are many potential solutions under development. How do we pick a winner?

I found myself pondering this question after listening to a recent episode of the excellent climate podcast, Catalyst. Andy Lubershane of the climate VC fund Energy Impact Partners notes that startups are exploring an incredible number of approaches to pulling carbon out of the atmosphere:

I think we found a list somewhere and it's a pretty credible list of over 150 direct air capture startups. … It turns out that if you want to suck carbon dioxide out of the atmosphere and then dump it somewhere, there's a ton of different ways to do it theoretically.

Carbon capture may be an extreme example, but we also see a wide range of concepts being tried for energy storage and next-generation nuclear power (fission and fusion), and multiple approaches in hundreds of other sectors. Who decides which solution should win out?

I think the textbook answer is that, at least in the US, “the market” decides which technology should win out, meaning something like:

1. Inventors notice an opportunity – a new market opening up, or the potential to improve on solutions in an existing market – and propose solutions.

2. Investors decide which ideas look promising enough to deserve early funding.

3. Customers decide which offering best meets their needs at the lowest price.

But there’s a lot more to the story. Inventors, investors, and customers are fallible individuals and organizations, working from limited information, analyzing it imperfectly, and subject to ulterior motives. For a market like direct air capture – with many solutions on offer, none of them mature – it is difficult for participants to choose.

The podcast notes the valuable role played by sophisticated early buyers. Tech giants like Google, Microsoft, and Facebook built internal teams to evaluate sources of clean electricity for data centers. These teams had the resources to select promising solutions, and the buying power to help those solutions succeed. Something similar is now playing out in the carbon capture market, with Microsoft and Stripe as important early buyers.

Government agencies also play an important role, both through funding programs, and by writing rules which may explicitly or implicitly favor particular solutions.

Lubershane argues that the plethora of solutions in markets like energy storage or carbon capture leads to analysis paralysis. Investors and customers are hesitant to act; many different solutions struggle along at small scale, and it takes too long for a winner to emerge and begin climbing the scale and efficiency curves.

Governments or sophisticated buyers can help this along by channeling resources to the most promising solutions, but especially when the government is involved, this is called “picking winners” and has a bad name. In the worst case, the process may be influenced by vested interests, allowing flawed ideas (like corn ethanol in the US) to win out. But even without vested interests, a centralized decision making can lead to a monoculture, where some promising ideas don’t get a fair shake.

Famously, “the market” doesn’t account for externalities, such as the climate impact of carbon-burning technologies. Mission-driven inventors may choose to pursue clean technologies, but most investors and customers won’t adequately prioritize climate impact unless forced through government intervention, which is uneven and not always well-designed.

Once a solution has time to scale, it can be hard for another solution to come along and displace it. For example, lithium-ion batteries now benefit from massive economies of scale and highly optimized manufacturing processes. Any new energy storage technology, in its early days on the market, will have a hard time competing. This is not always bad; one reason lithium-ion has achieved such massive scale is that these batteries really do work quite well for a wide variety of applications, and there are benefits in using similar technology in applications ranging from electric vehicles to grid-scale energy storage.

But suppose an alternative technology were to come along that is fundamentally “better” than lithium-ion, in the sense that if it were developed to the same level of maturity, it would have large advantages in cost, weight, availability of raw materials, or other important considerations. That new solution might never be developed, because it would take an enormous amount of capital to catch up with lithium-ion batteries, and there might not be an investor with sufficiently deep pockets and enough risk appetite to make the investment.

This is known as “path dependence” – a technology may win out because we happened to scale it first, not because it is inherently superior. If history had taken a different path, a different (possibly better) technology might have won instead.

(Sometimes this problem can be overcome by finding niche applications where the new technology can find early success – such as Tesla starting out by making exotic sports cars, or lithium-ion batteries achieving early scale in laptops and cell phones before anyone considered them for powering vehicle. This allows the new solution to begin scaling.)

The challenge of allocating development funds and deciding which solution(s) to scale is an example of a classic problem, the explore-exploit tradeoff. We can devote resources to “exploring” new solutions, or we can use whatever information we’ve already gathered to pick a winner and then “exploit” it (put all of our resources into scaling up that solution).

The podcast host, Shayle Kann, refers to this as a choice to “develop” versus “deploy”, and notes that some people argue that the climate movement should shift toward deploying various promising solutions that have already emerged, rather than waiting to develop new solutions.

I’m sympathetic to the argument that we are exploring too many different solutions in areas like direct-air capture or next-generation nuclear, and that the best thing for emissions reduction would be to pick a few winners and focus on rapidly optimizing and scaling them. I’m also sympathetic to the idea that if we do this too early, we’ll wind up with another corn ethanol disaster.

I don’t know the best way to navigate this tradeoff. But I’m certain that our current hodgepodge of short-time-horizon investors, unsophisticated buyers, and markets that ignore externalities – even when supplemented by a handful of mission-driven investors, sophisticated early buyers, and sometimes well-designed government action – is not the best we could do. It would be nice to see the more explicit discussion of the develop-vs-deploy tradeoff with regard to clean technologies.

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If you’re interested in this kind of analysis of the central questions underlying an important topic, check out my AI blog, where I talk about where AI is going, what it will mean for the world, and what we can do about it.