Economics of Angel Investing

After writing the last post I thought a bit about the further development of innovation. What would be if we could predict successful companies (ideas) with high probability? That would allow to reallocate human capital faster and thus leading to more successes.
And one idea is a prediction market for startups. You may think that sites like AngelList go in this direction. I’m not entirely sure about this. I will first take a view on Angel Investing from an economic standpoint.

Angle Investor and Entrepreneur
This is a typical Principal-agent problem. The Entrepreneur has more information than the Investor. Often happens exactly what you will expect and that is that the Investor will look for commitments of the Entrepreneur which reveal information about his private information. Examples for these commitments are quitting one’s job, using one’s own money for funding or buying an expensive domain. Furthermore, of course, they try to grasp personal attributes of the Entrepreneur and his team.

Angel Investor and other Angel Investors
This stage is more interesting. Let’s say that our Entrepreneur got his first funding from one Angel Investor. Depending on the status of the first Angel Investor there are two different scenarios.
Firstly, assume the first Angel Investor isn’t famous. The next Angel Investor will probably see that this investment could possible be profitable but he will with a high probability go to stage one again and use his own judgment.
Secondly, now assume that the first Angel Investor is famous, a top notch one. The second Angel Investor will probably trust the judgment of the first Angel Investor so much that he will skip the first stage or neglect some flaws that he found. This is herding and leads to incorrect pricing and maybe a bubble.

We could either try to make these investments anonymously but this would be impractical. However, we could at least correct the pricing allowing short selling.
This all sounds like a stock exchange and they have a similar function, i.e. funding companies.

However, I think there’s one problem of stock exchanges for Angel Investment and that is that the expectations of the participants are different. Some Investors want 2x exists, some 5x exists, some want it in the next two years other in the next five. This is totally OK if we use these mechanisms for allocating capital.

Yet, the goal is to predict future successes and here I think prediction markets are more suitable because there are clear goals. E.g. “Company X will reach 5m in sales by 31 December, 2016.” Prediction markets do these things really good. One of the biggest problems will be liquidity which can be partially solved using aggregation or even better attracting more people to the market.

Want Innovation? Lower the initial investment.

I read an article a few months ago where the author complained that there isn’t much innovation outside of web and mobile applications. I thought about what makes them special and came to the conclusion that their initial investment is extremely low. I’m part economists therefore investment shouldn’t just be viewed as monetary investment. There are different costs and factors. I will take web application development as an example for this reasoning.

Educational Cost These include the costs of learning the techniques of your trade. Today, you can build simple web or mobile apps in less than a year without previous knowledge of programming. For programmers it’s even faster, maybe two or one month.

Capital requirements This is was a business major understands under initial investment. In the case of a web app it’s probably a hosting space and a domain. Maybe $5 per Month.

Administrative Cost Do you need any special certificates or are they any regulations? For web apps there aren’t any special restrictions.

Social Cost of Failure I think this is an important factor in more risk averse cultures, like in Europe. Let’s say you build a web app for two months, launch it and it fails. OK, happens often, no big thing.

Let’s compare this to some other, less innovative, industries like mechanical engine design. The educational costs are high, often you need some sort of advanced degree. The capital requirements are tremendous, you’ll need a work shop with very expensive equipment and so are the administrative costs with insurances, worker safety. The social cost of failure is increased because of the high capital requirements.

So how can these factors be reduced? One thing are definitely hacker spaces or shared work spaces. BioCurious provides the required equipment for the biotech endeavors (capital requirements). Furthermore, they provide classes to learn how to use this equipment (educational cost). This will also lower the social cost of failure.

I can imagine that this concept will be transfered to other industries like mechanical engineering, chemical processing, etc.

#46/111: Startup

What is it about?

If you want to start a business, you need an idea and a business model and money. Elizabeth Edwards focuses about the latter. She shows you how to cut your personal expenses, how to calculate your financial numbers and why venture capital isn’t always the best option.

What can I learn?

Is your business profitable? Before starting your business, you should check if your business model can generate enough profit. How high is your initial investment and how much does it cost you monthly to operate your business? The next step is to calculate your profit on this basis. How long does it take you to break even, i.e. you aren’t losing money anymore? You should reject your idea if it will take longer than two years.

Capital can be expensive: Before you are going to look for venture capitalists, you should think about your need of outside capital. If you can do it alone, go for it. If you can’t do it without outside money, she recommends you to thoughtfully calculate your costs. Don’t forget to include your opportunity costs for searching investors.

Know your metrics: A business runs on numbers. You should monitor your industry key metrics (e.g. page impressions for social sites) and of cause your ordinary indicators like sales, costs and profit. Even if you aren’t a numbers person, learn how to read your key numbers.

Conclusion

This book is an accumulation of tips but lacks the explanation of why you should do they. This is a bit of a downer. The good parts of Startup were clearly the financial and legal knowledge. If you start your business in the US this information is possible pretty valuable. Lastly, besides of the financial and legal advice most advice is out of other books like Made to Stick or Business Model Generation. I would recommend reading those, if you want to deepen your knowledge.

#16/111: Leading The Revolution

What is it about?

Gary Hamel writes about the future of leading a company and explains that innovation will rather come from your normal employees than from the top management. He focuses on some outstanding companies like Cemex, Schwab or UPS.

Key points?

Encourage activism: A lot of front line employees see problems that the (top) management can’t see. You have to enable every employee to share their ideas.

Build internal markets for talents, capital and ideas: A great way to allocate resources are markets. Hamel recommends to build internal markets for these components to allow people to execute their ideas.

Measure your innovation progress: If a idea seems fertile let people test it. If it succeeds let them build ventures and if this venture is successful try to spin-off or reintegrate this venture in your company. You probably have to generate lots of ideas for one successful venture, so start filling the funnel!

Conclusion

Leading the Revolution is a great book for its time. There are some really neat ideas like internal markets which are now successfully adapted (e.g. at Google). Furthermore, Gary Hamel understood the idea of crowdsourcing long before it became familiar.