The blind helping the blind build our future

A blind man stands at the edge of a busy street clearly wanting to cross. Other pedestrians crossing stop and ask him if they can help. To each he asks "can you see?" and when the pedestrians answer that "yes, I can" he sends them on their way without crossing. Eventually, a pedestrian answers that "no, I can't see because I am also blind". The bind man quickly grabs the hand of this pedestrian and ushers them towards the road. "great, I feel much more comfortable crossing this road with someone who I have so much in common with!" 

We are all blind to something. Nobody knows everything or has such a diverse set of skills that they can look at a problem from all the angles at once. This is why diverse (I will define exactly what I mean by that world in just a second) teams are more creative, adaptive, and successful than homogeneous ones.  But in the investment world, this homogeneous approach is what persists: The folks who must make the decisions assemble blindly homogeneous teams to help them make those decisions. The result is predictable... failure. 

Efficiency: to much of a good thing

Efficiency is a concept that all people, not just engineers, grasp onto: an increase in efficiency is always good. While I have no issue with the general concept, it is dangerous oversimplification that implies efficiency is somehow a better metric. In reality, efficiency is only the easy metric, not the best metric and an over reliance on efficiency to sort technology into good and bad ideas leads to higher overall cost solutions and extreme waste. The problem is one of path functions. When a technology is created it starts somewhere on its cost-efficiency curve based on the constraints of the day. It is improved from there, at an increased cost, until we have a large understood technical space built up around the technology. This works great when constraints stay the same, but when the constraints change, the technology is now up a curve without a paddle. 

Blind Decisions

The extent to which we fail to choose good companies to invest in is often understated. Instead, it seems to be accepted that VC, grant, angel, or any other type of funding method just can't do that much better then other markets. Sure, a hotshot VC may outperform the stock market, but they are not going to get a 10x return on every investment they make. On average, VCs only get that kind of return on 20% of their chosen companies and the rest given them more or less no return at all. So overall, most give boring returns in the 10% range. In cleantech especially, investments has really failed to return the types of returns LPs were expecting (see mass exodus of LP support for cleantech based VCs) 

However, the simple fact that some investments do give yield massive returns should still encourage us to pursue better ways of choosing the companies that are invested in. This should be even more compelling in the cleanteh space where the potential markets are well established and gigantinourmous. But before we can really invent a new investment decision mechanism we need to take the current method, stab it in the heart with a wooden stake and put it in the ground.

To that end, I have recently been experimenting with very simple model that illustrates just how bad the current decision mechanism is at picking companies that will go on to be successful. The model is based on an allegory for our decision mechanism based on the "blindness" of the people choosing which companies should be invested in and which should not. The model gives some interesting insights into how terrible the current system is at really finding good companies to fund. 

TEDx

Last month, I had the privilege of giving a talk at TEDx MileHigh. It was a blast and the whole TEDx MileHigh crew was astoundingly effective. 

I wanted to tell the story of my company without selling the company. Instead, my goal was to show how we have found that focusing on small, tailored solutions lets us achieve lower costs and most importantly, a good chance of having some type of positive climate impact. I hope you enjoy it. 

Do you even buy what you are making

Ever see something like this when you try to take the price tag off something you just bought to put on display? Ever try to open a product you just purchased to find the bag does not reseal or the box rips apart in your hands so it's tabs are useless?

On Arrogance and Success

Arrogance is the destroyer of all things creative, innovative, and good. It blinds us to both the mistakes we are making and the opportunities we are missing. This is by no means a new thought. The concept of hubris is older then most other parts of our culture. Why then, are arrogance and business success linked so strongly in our society?  When a CEO like Elon Musk goes off about how clearly superior he is, we all roll our eyes and phrases like "well you can't argue with success" get passed around. We all seem to have been conditioned somehow to accept that success and arrogance are linked.

I would like to propose an alternate theory: Arrogance is counterproductive to success and instead, we are victims of an optical illusion that makes the fictional link between the two seem intuitive.

Perspiration and Cookies all in One Post

I can't vouch for everywhere in the world, but if you grew up in the US I guarantee that you have heard the following quote:

"Success is 10% inspiration and 90% perspiration" - Thomas Edison

Let me start by saying that this statement is completely factual as has been demonstrated to me on numerous occasions over the course of REbound's first year. However, it recently occurred to me that this quote also sums up how we erroneously think about new technology and startups in general. We tend to focus more on the capability of a team to perspire instead of inspire. In other words "can this team accomplish this work" instead of "is this a good idea in the first place". This can be dangerous because when you get down to actually developing a technology, bad ideas take just as much effort to develop as good ones. That is, until they fail.