- Dara Khosrowshahi, Uber
- 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.
- 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.
- Ajay Banga, Mastercard CEO
- sd
Sunday, March 31, 2019
Stanford GSB CEO interviews
Hottest S1 fillings of 2019
S1 fillings are great read to understand how these companies are doing and to also evaluate your current set of investments based on these learnings.
References
Top investment reads
Classics
- Jeff Bezos's letter to investors
- Warren Buffet's letter to investors
- Ray Dalio's - how the economic machine works in 30 minutes
- Ray Dalio's blog on paradigm shifts - this analyzes historical returns of different asset classes by decade
- Ray Dalio's Mechanics of war economy (covers Civil War, World War I, World War II)
- Boggle heads philosophy
- The intelligent investor
Blogs
- Morgan Housel's Collaborative Fund Blog
- The irrelevant investor
- Ofdollarsanddata
- a wealth of common sense
- Adventures in capitalism - I like this blog because of the very honest perspective and the market bottom timing during the covid crash, specifically this call on March 23.
- Gavin Baker's investing blog - former fidelity PM
- Oakmark funds
Investing thesis
Asset Relativity (Bay area housing vs Tech stock Index)
Last week a16z released a very interesting article on the correlation between bay area housing prices and high flyers of the last decade, Google and Apple stock prices. The conclusion was pretty clear as Bay area houses have become cheaper compared to not only Google and Apple stock, but also a tech stock index comprised of top tech companies in the bay area. To note, a lot of these companies provide equity based compensation for their employees who are buying houses in the bay area.
This article extends the thesis to QQQ which is the Nasdaq top 100 index.
The top 5 companies in QQQ are MSFT, APPL, GOOGL, AMZN and FB, all of which has atleast one engineering office in the bay area. These also are prime drivers of the thesis "Software eats the world".
Any common man without the ability to pick the winners in the tech index suggested by a16z could simply invest in QQQ index fund and have reaped the same results.
Disclaimer : The content is provided for information purposes only and should not be used as legal, investment or tax advice. The author bears no liability for how this information is used and the outcome thereof.
Memos : Famous critical points in businesses
This post contains a list of critical points that different companies and their CEOs faced in their history :
Microsoft
- Roadkill on the information highway by Nathan Myhrvold - this memo aged well and is one of my personal favorites
- Bill Gates memo to MSFT employees regarding joining "the internet tidal wave" - Gate's memo to the MSFT exec staff in 1995 asking them to pivot to the internet tidal wave
- Warren Buffet and Jeff Raikes email exchange on valuing Microsoft in 1997 - this is a great thread about how Raikes thinks about the MSFT software business as a royalty on every PC sold. Buffet agrees that the business is great but couldn't calibrate the durability of the business over 20 years. I think this also shows buffets thinking and how he made amends with his Apple investment in 2016.
- Windows : the next killer application on the internet - 1994
- Ray Ozzie's - The Internet Services disruption memo in 2005 - this is one of my favorites (link)
- Ray Ozzie's - Dawn of the new day
Uber
- Travis Kalanick's memo to the UberChina team regarding merger of Uber China and Didi - This is a very inspiring story about how a small team from Uber seeded and started the China venture and eventually earned 20% ownership of Didi Chuxing. Nobody in China had even heard about uber and this was one of the rare victories of a Silicon Valley startup in China except for Apple. Also everyone else (Google, Facebook, etc) is barred from doing business.
- An open letter to Uber employees from Benchmark - I like this letter for several reasons - it is one of the classic case studies of leadership conflict management. As a startup employee this is the last thing you want to see, your investor and CEO having a huge public fight. This is bad for business, bad for PR, bad for value creation. As an investor, this is something you never want to do because all the future CEOs are going to see this play out in public and are going to think twice before securing that investment from you.
- I must fundamentally change and grow up - apology letter from Travis - this is a stark reminder for all leaders about what not to do in business and scaling
- Dara Khosrowsahi's memo to Uber employees in the wake of a disappointing IPO
- How to miss by a mile - an alternative look at Uber's potential market size by Bill Gurley
Tesla
- Facebook's Mark Zuckerberg's memo to focus on user's privacy - In the aftermath of the cambridge analytica scandal, this is Mark's memo to refocus the facebook products suits towards privacy and to build with a privacy first mindset
- Mark Zuckerberg negotiating with Kevin Systrom over instagram acquisition - Two great product visionaries of our generation discussion what it would mean to work together for their products visions and for themselves
- Boz's memo Thoughts for 2020 - he describes 2016 US elections, how the campaigns used digital tools, election interference, facebook's role and the future build up for the 2020 elections
- Boz's blogs on Facebook's culture, business, organization, engineering, product and scaling all these aspects from a startup to a behemoth
- Mark Zuckerberg's email describing his vision of AR/VR
Nokia
eBay - Paypal
- Carl Icahn's activist letter that led to the eBay-Paypal spinoff - I like this letter as it clearly calls out conflicts of interest between the boards members investments and eBay's direction, Paypal's future and strategy. The spinoff ultimately led to immense value creation and Paypal stock 5xing in the next 5 years.
Others
Network effects and social networks
In the last post, we studied what network effects are and how it works for Uber. In this post, we will look at another way of thinking about network effects and how it works for social networks.
“Network effects are tricky and hard to describe but fundamentally turn on the following question: Can the marketplace provide a better experience to customer “n+1000” than it did to customer “n” directly as a function of adding 1000 more participants to the market? You can pose this question to either side of the network – demand or supply. If you have something like this in place it is magic, as you will get stronger over time not weaker.” Bill Gurley
How does network effects work for social networks ?
Social networks demonstrate the strongest network effects. If all of your friends are in a social network, you are going to join the same. You will gain value from the presence of the friends and from the connections with them. So the user acquisition cost for the social network goes down, the users who join produce content and value and the supply side dynamics get better and better. As more and more users join the social network, it becomes stronger and stronger as a network compared to other networks. This was one of the fundamental reason why Facebook grew beyond other social networks. Facebook also aligned their growth teams to solve for this problem. They tracked a metric where any new user on Facebook would be connected to 10 of their friends within the first 14 days. Facebook realized if this happened then the probability that the user would churn would go down significantly.
This phenomenon described above doesn't just hold true for social networks. This also holds for other kinds of networks like phone networks at&t. We will discuss the origin of network effects and the first time it was covered in literature in a future blog post.
References
1. Network effects and critical mass
“Network effects are tricky and hard to describe but fundamentally turn on the following question: Can the marketplace provide a better experience to customer “n+1000” than it did to customer “n” directly as a function of adding 1000 more participants to the market? You can pose this question to either side of the network – demand or supply. If you have something like this in place it is magic, as you will get stronger over time not weaker.” Bill Gurley
How does network effects work for social networks ?
Social networks demonstrate the strongest network effects. If all of your friends are in a social network, you are going to join the same. You will gain value from the presence of the friends and from the connections with them. So the user acquisition cost for the social network goes down, the users who join produce content and value and the supply side dynamics get better and better. As more and more users join the social network, it becomes stronger and stronger as a network compared to other networks. This was one of the fundamental reason why Facebook grew beyond other social networks. Facebook also aligned their growth teams to solve for this problem. They tracked a metric where any new user on Facebook would be connected to 10 of their friends within the first 14 days. Facebook realized if this happened then the probability that the user would churn would go down significantly.
This phenomenon described above doesn't just hold true for social networks. This also holds for other kinds of networks like phone networks at&t. We will discuss the origin of network effects and the first time it was covered in literature in a future blog post.
References
1. Network effects and critical mass
Top 5 must read Venture Capital (vc) and tech investing blogs
- Andresson Horowitz - a16z
- Benedict Evans
- My personal favourite is Ben Thompson's stratechery
- Paul Graham's essays - co-founder of Y-combinator
- Bill Gurley's above the crowd - Bill was the lead analyst in the Amazon IPO and an early investor in Uber through Benchmark capital.
- Adam Hartung's blog
- Scott Galloway
- Fred Wilson's vc blog
- Patrick Collision's blog
- Sriram Krishnan's blog
2020 Updates
- 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.
- List of blog posts for entrepreneurship crash course
- Alex Danco's blog - ex Social Capital
- 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
References
1. All about network effects
2. How to measure 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
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