Fantasy Portfolio – Uber

I wrote a couple months ago about my fantasy startup stock portfolio and am finally getting the follow-up posts published. The list in my portfolio include

RobinhoodTwilio Sendgrid Fitbit – & – Uber

I am starting to think Uberconference may be a close second and SendHub is starting to get on my radar as a result of Uberconference. Both are worth more exploration. Let me dig into one in the portfolio though – Uber.

If you haven’t used Uber yet it is definitely worth a try.

Aswath Damodaran’s valuation in his post Bubble, Bubble, Toil and Trouble: The Costs and Benefits of Market Timing

Bill Gurley (Uber investor) attempts to refute Damodaran with an equally long read and important criticism of where models fall apart in his post How to Miss By a Mile: An Alternative Look at Uber’s Potential Market Size. Yes Damodaran did respond.

If you haven’t already put driverless cars and Uber together in your head, read this brief post by Seth Godin. There is much more extensive detail on ride sharing, the sharing economy in general, and driverless cars on last week’s EconTalk – if you want to understand the economics and regulatory logic better spend the hour on the EconTalk podcast (Btw, I recommend you subscribe to EconTalk and listen to at least one out of five podcasts regularly). Setting all that stuff aside though, the world would be a much different place if people were focused on other people during their meetings and saved looking at Tinder or their stock portfolio for their trip home when they no longer have to squeeze onto a bus, pay high rates for a driver, or the worst – actually have to sit behind a wheel where it is illegal in most states to play on your phone and generally dangerous in all parts of the world to play or talk on your phone. Now everyone can add 1-2hrs of productivity to their day and that is worth A LOT! An incredible amount of money is spent figuring out how to make people more productive, adding a couple hours to the day was generally thought not possible and driverless Uber-like car services do exactly that.

My favorite stuff is where the conversation between Damodaran and Gurley gets at the can there be MASSIVE changes in the world in a short period of time? Well the next time Damodaran starts his car he should ask himself where that gasoline came from – I doubt it was from oil imported from oversees as it was six years ago. I would bet it was pulled out of US soil via fracking which has taken over US oil production to a point where we are getting ready to be an oil exporter. This is a change on incredible scale for our country. Six years ago when “peak oil” was all the talk of the town this was an impossible thought – almost as impossible as thinking everyone will have a couple extra hours in their day to play Angry Birds without a significant cost increase.

Massive rapid changes happen and the data that can be extracted and re-used by companies like Uber are amazing. Feeding traffic behavior research can change the way our roads and cities are designed for the better and right now we don’t have this data. Traffic analysis does occur and we have video camera & bus GPS to thank for that – yet we’ve spent a lot of money to make that happen and we only have a subset of the data feeding those decisions. Government funded research and planning can make significant use of the data that Uber is uniquely positioned to offer.

Uber could be interesting if they owned the driverless car and the data platform – but why not just continue to be a platform? There is no clear sign that Uber actually wants to operate a driver service. I hope that they continue to operate this way and enable other driver services to evolve based on their platform. This is more open and allows businesses and innovation to thrive.

  • It allows for things like public operation of bus systems based on the Uber platform where bus routes, rates, and paths through the city are improved by Uber but not controlled by Uber.
  • It allows independence drivers and taxi services to remain in business – if they are sore about their medallion investment, sell it now and switch to Uber while they can still get someone else to buy their medallion. It wouldn’t be the first time an item of arbitrary value lost the value because something better was invented. First movers in these situations win more.
  • It allows private businesses unrelated to human transportation such as UPS and FedEx to purchase access to the data to supplement their own data and improve delivery times and convey more accurate delivery schedules to customers.
  • It allows flex expansion of package delivery at peak times. For example Amazon hires drivers in most major metros to deliver packages during the holidays to guarantee delivery schedules. Uber could enable this in broader use cases adding value to Amazon, Uber, the drivers, and consumers.

I don’t believe any of these four simple scenarios have been discussed much and may not even be on the current roadmap for Uber – so why bring them up. I bring them up because Uber is in a growth stage and it is difficult to tell where all of the value creating use cases are when there is a high-growth trajectory. This is the main point that Gurley is trying to make and he carefully outlines several scenarios that he can talk about publicly as an early investor in Uber. I am not an early investor so I can make up whatever I want about them and so can Damodaran. My scenarios may be more outlandish than reality – but I think any reader can easily see where the value would be in all four of those and how everyone in those pictures benefits. These revenue streams are examples of the kinds of things that end up in a DCF eventually to use in valuation – but there is no way to understand what they look like or even the real probability at this point, everything would be a guess.

The standard finance approach would be to assign some probabilities of those occurring and put them into the model. This means you have to guess at what every scenario could possibly be (You can’t imagine them all), then you have to guess at their probability (remember the US was NEVER going to be an oil exporter according to EVERY knowledgeable party in 1988, 1998, and 2008), finally you have to guess how much money that would mean (uh, so you’ve never seen anything like it and you don’t know if it will even happen and now you are supposed to guess the “correct” revenue value?). Now you can have a model and maybe you run a whole bunch of models with different values for those three inputs and get sort of a good guess. Even then – these are guesses and the problem that you are trying to solve is EXACTLY like predicting the weather patterns in ten years except for the fact that there will be a new type of weather that you’ve never seen before we’ll call it UberRain – and UberRain doesn’t behave like normal rain so all of the guesswork you put into the model doesn’t really mean anything anyway.

So what can you do and why do I like Uber? Well simple – (1) they have a clear means of making money today in what appears to be a sustainable and profitable way and (2) they have the opportunity to make a TON of money on top of that. The risk? They spend too much money chasing the second half of that sentence and kill the first half of that sentence. So I would invest as close to #1 as I could and understand that the owners of the company should want to move me as close as they can to #2. If we meet somewhere in between that we both like it is a good investment. I can calculate how far into #2 is worthwhile (my capital at risk) and they can calculate how close to #1 is worthwhile (their cost of capital). Note there is real money funding their efforts to get to #2 so it is a fairly well defined set of calculations here that aren’t just a bunch of guesses.

Would it be different if Uber was just an idea with no real revenue to understand – yes. Is it possible that their current valuation is closer to #2 than #1 – yes. Do I think it is way too close to #2 to actually make an investment? I think that is the question of the year really and it is really hard to say.

There is a valuation component and a preference/rights component. We know the valuation number but we don’t know what else is written on the papers where the valuation was put into place. How much money are people guaranteed to get out of the company in which scenarios is something we don’t know the answer to. Damodaran talks about preferred shares and voting rights in his books and classes but seems to ignore that part of the conversation when he values private companies. Later investors can have the same or better liquidation preferences, or other rights that effectively reduce the risk to the capital they are putting into the company regardless of the valuation label slapped on the company. When we compare two public companies we can see this data as it is public information and we can properly asses the capitalization of the business. When we compare private companies that we don’t have insider knowledge of we can only compare some of the data reported publicly and guess at the rest of the data to asses the capitalization of the business so again we’re guessing and that makes these public discussions on valuation difficult to have. I would invest all my money in Uber at any valuation if I have free reign to write in the rest of the terms of that agreement. These private agreements are not the same as public stock offerings.

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