Day: September 10, 2013

The New (Profitable) Model of Cleantech Innovation

Innovation is easy, right?  

Software/Web innovation has their model nailed. The wham-bam-thank-you-Y-Combinator process combined with caffeine and electrons rapidly ramps companies, creates whole new sets of things consumers never knew they needed (but now simply can’t live without), and delivers market index +3 returns to LPs who continue pouring money into the space. It took a market crash and 15 years to get there, but hats off, it works. Software creates money.

But Cleantech creates jobs , and the kind of jobs American cities need most. It’s also species-survial-mission-critical, unless you think all the crazy weather (and mounting insurance and ancillary costs) are just a rogue anomaly.  But building stuff is hard work, and the Valley of Death is a lot longer and more treacherous.  We’re still figuring out the money part, but that’s progressing by leaps and bounds.

What is the right model for Cleantech innovation?

It’s one that fosters technological breakthroughs, efficiently grows companies, ensures investment returns commensurate with risk, and delivers deployment where most needed. The key lesson from the last 7 or 8 years is that the push model that Software/Web utilizes just doesn’t work very well in this sector. We aren’t dreaming up new wants. By and large, the problems Cleantech solves for are understood: use less energy, use less water, create less carbon, etc, and the conditions bounding these problems are pretty well understood too. Even the markets they encompass can be projected with relative accuracy. What is more difficult, however, is the time it takes to get the solutions developed and manufactured, the challenges of deploying against legacy systems and incumbents, and the unforeseen role regulations can play in market structure and economics. All doosies compared to apps that let you blow up smirking pigs.

Cleantech entrepreneurs have the same challenges as others:

  • What to do
  • When to do it (collectively, “experience”), and
  • How to acquire the resources and expertise required (“relationships”)

These are similar challenges to what software entrepreneurs also face, the difference is the time and cost of pivoting. Retargeting Yelp is different from retargeting Solyndra, a kayak turns faster than a tanker, electrons rearrange faster than iron atoms. The end result is that there is a lot less room for error for Cleantech entrepreneurs.

What do they spend most of their time doing? A couple of core things. Learning about their industry, performing market analysis, perfecting their solution and developing networks of contacts. In cleantech you’re generally not creating entirely new markets, you’re fracturing existing ones and that bedrock is dense. Overall, it can be a grossly inefficient and capital intensive process, especially as it’s currently done. So, what’s a better way?

It takes a village to raise a Cleantech startup.  

It takes a village to profitably raise a cleantech startup, which is why a new tough-love-make-a-wish approach is necessary. There are two pieces to the equation.
  • Incubation involves wrapping a team of seasoned mentors, advisors, service providers, and domain experts around the startup, plus a dose of targeted training, office/lab space and technical resources for little or no cost, that provides non or low-dilutive value and is cash efficient. The incubator provides this by being regionally supported (by visionary civic and industry leaders!) and aggregating and coordinating the various components of the ecosystem. It’s like the startup getting an entire team working on their behalf for very nearly free. And free is about as capital efficient as it gets.
  • Market Pull (our Wishlist™ program) involves turning the traditional innovation model on its head. Instead of researchers/entrepreneurs coming up with cool new ideas then trying to find markets that will enable them to make money, we go directly to the market itself and figure out what it needs, then pull the solution across the Valley of Death. As a case study, a large regional utility has identified three technology areas that are critical to their long term growth and sustainability. As part of the project they have: bounded the current problem set (e.g. it costs us $$ per XX to deliver XX), identified the sought after solution set (e.g. needs to produce XX per XX for $$), approximated the addressable and global markets, committed to demonstration testing of promising technologies, committed to provide investment capital ($1M), and promised to deploy the solution broadly within their territory. Our job? Research the verticals globally, figure out the most promising solutions, vet the technology, recruit the entrepreneurs to LA, fund them, incubate them, and help them set up manufacturing locally and go to market. Making the entire process much more efficient for everyone.

What makes this a better model?

In a nutshell, it’s faster and light years less risky. We’ve significantly removed many of the uncertainties around each element of the company’s growth and development:

  • Market Risk: by having the end user define the economics of the problem AND the targeted solution, as well as their own addressable market and the estimated macro market, the entrepreneur has a target to work against and a clear understanding of the economics. No more guessing about what is required for the solution to be successful.
  • Customer Engagement Risk: the end user agrees UP FRONT to demo, test and deploy the technology if it works to spec. All the entrepreneur team has to do is execute against the technology development strategy.
  • Sales Risk: understanding and cracking the sales process and replacement cycle for utilities, large industrials and government is expensive and time consuming. Under our model the entrepreneur is guaranteed access to at least one large customer, and also is able to get an insider’s perspective on how to ramp up sales to others in the sector.
  • Product Validation Risk: the end user provides affirmation to investors and other buyers that the technology is sound, driving growth in other areas of the market.
  • Regulatory Risk: large end users have the resources to track regulatory trends and plan strategically. By defining their core focus areas they are able to give the entrepreneur and investors comfort that the regulatory environment will remain aligned as the technology comes to market.
  • Startup Risk: by embedding the entrepreneur within an incubator they vastly increase their odds of success. 85% of incubated companies are still in business 5 years later.
  • Financing Risk: all of these factors combined contribute to a much lower risk profile, significantly increasing the odds of investor support and favorable terms
How’s it going so far? Curious how we make it happen? We’re going to devote a whole day to talking about it. Come to our November conference to learn about all the details….