Uber S1 filing

The IPO season in 2019 is hot. Previously I shared S1 filings of Lyft and Pinterest. Now Uber has filed its S1. You can read it here : Uber S1

From the high level look, Uber is a much bigger business than Lyft has eats and freight. Freight is already bigger than I thought and could be a key differentiator in 1-2 years. I expect it to get to 1 billion revenue run rate in 2019 itself.

Stanford GSB CEO interviews

1. Dara Khosrowshahi, Uber
1. I am short term impatient and long term patient. If there is an idea that takes a week or a month or if something is long term, then come to me. Don't come to me for the in between.
2. Uber wants to be the amazon of transportation. It wants to provide the platform for all modes of transportation and no one company can provide all the modes. It will interface with multiple players. It also expects part of that to be provided by cities like bus service. 
2. Ajay Banga, Mastercard CEO
3. sd
4. 
   

Top 5 must read Venture Capital (vc) and tech investing blogs

1. Andresson Horowitz - a16z
2. Benedict Evans
3. My personal favourite is Ben Thompson's stratechery
4. Paul Graham's essays - co-founder of Y-combinator
5. Bill Gurley's above the crowd - Bill was the lead analyst in the Amazon IPO and an early investor in Uber through Benchmark capital. 
6. Adam Hartung's blog
7. Scott Galloway
8. Fred Wilson's vc blog
   
9. Patrick Collision's blog
10. Sriram Krishnan's blog

2020 Updates

1. Union Square Ventures - As we know it that mobile is hitting the top end of the S curve. There are 5.5 billion adults in the US and 4 billion people already have a mobile phone. Like mainframes(IBM), personal computers(Microsoft), web(Google), mobile(Apple) each of the paradigms reach a state of stable growth rather than disruption. We are in a phase where VCs are looking for a new paradigm. I am adding Union Square Ventures to this reading list because they are long crypto and view that crypto could be that new paradigm. 
2. List of blog posts for entrepreneurship crash course
3. Alex Danco's blog - ex Social Capital
4. Steve Sinofsky's blog covering Apple

What is network effects and how does it apply to Uber

One of the fundamental investment mental models in silicon valley and for evaluating startup investments is network effects.

What is network effects ?
“When the value of a product to one user depends on how many other users there are, economists say that this product exhibits network externalities, or network effects.” Carl Shapiro and Hal Varian

Examples of network effects :
1. Two sided marketplaces like eBay, Amazon, Uber
2. Social networks like Facebook

How does network effects work for companies like Uber ? 
In order to build two sided marketplaces like eBay and Uber, there has to be supply side liquidity and demand side needs. Supply side liquidity means more drivers on the platform. More drivers will attract riders (demand side needs) due to lower pickup times. As more riders come on the platform, driver earning potential will increase. Driver utilization rates per hour will increase. The driver will get more rides during every hour they spend on the network which will reduce idle times and lead to better network utilization. This will drop prices, attracting more demand and more riders. This ends up becoming a positive cycle that reinforces itself and the marketplace grows. 

Creating two sided network effects is hard because of the creation of both the supply side and demand side dynamic. Hence, Uber had to spend some money on fixing the cold start problem. At the same time, it is equally hard to kill two sided marketplaces because of the same reasons. For the driver, it pays off to be in this network compared to other networks because of better utilization rates. Also it pays for the driver to be in the bigger network because the bigger network is available in less densely populated areas. Most of the competitors of Uber are present in high density areas as they are local challengers and dont have the network strength to challenge in the outskirts. For the rider, it pays of to use the Uber network due to cheaper prices, lower wait times and better utilization rates in both dense and not so dense areas.

In the future articles, I will

• compare this with network effects in other companies like FB, Amazon
• how uber is strengthening the supply side and building a defensible moat over it

References
1. All about network effects
2. How to measure network effects