“I think Uber is just very different, there’s no model to copy.”
Travis Kalanic, FT.com March 3rd 2017
Background
In my role as Managing Director of Mclowd I recently caught up with an accountant in suburban Melbourne.
This practitioner provides bookkeeping services to a number of Uber drivers, whom he noticed had started declaring income from Taxify – an alternative ride-hailing network. In effect these drivers are operating across two competing networks, simply by keeping both apps open on their phone. A ‘split workflow’ if you will.
(While it would be more common in CBD areas for now, anyone wanting to confirm this can simply open the two apps and view the drivers in their immediate vicinity).
This conversation prompted me to publish a brief post on LinkedIn, which was viewed more than 1,000 times over the course of a few days.
On the basis of that response – along with the substance of the subject matter itself – I felt a more detailed analysis was warranted.
Introduction – Uber and the Process of Creative Destruction
If he was around today Harvard University Professor Joseph Schumpeter (who coined the phrase ‘creative destruction’ in the 1930’s) would no doubt be impressed with the entrepreneurial spirit exhibited by Uber’s founders Garratt Camp and Travis Kalanick.
The company has built a global network that has attracted millions of active users and vast amounts of capital at valuations that have soared into the tens of billions of dollars.
Recent issues as to governance aside, they have achieved enormous success over a relatively short period of time.
Taxify
Subsequent to that conversation I downloaded the Taxify app. Sure enough, it was quite clear that numerous Uber drivers (in Melbourne) are running the Taxify app concurrently.
Taxify charge a commission of 15%, significantly less than Uber’s 25%. This translates into a further 10% saving for the consumer. (To confirm this differential I recently took two trips – one outbound via Taxify and one inbound along the same route via Uber.)
There are two aspects here that are noteworthy – product lifecycle and network effects:
- I had only just settled into my participation with the Uber network and – given that the Taxify is comprised of exactly the same drivers / cars – am unlikely to ever need to use Uber again
- Notwithstanding its size, the network effects associated with Uber have been eviscerated because switching costs (on both sides of the network) are basically zero
Increasing sensitivity to price
Having always shunned taxis because of cost, Uber had been successful in changing my behaviour through dramatically lower pricing – approximately 50%.
But this is where things get interesting, for Uber as a company, its investors and arguably all of us.
Taxify is overcoming Uber’s network effects, and in doing so triggering (equivalent) migration behaviour based on an additional 10% per unit price deflation.
Having changed the customer paradigm with a radically different value proposition, Uber now appears vulnerable to a much smaller change in price. (Economists would describe this as increasing elasticity of demand).
Zero Marginal Cost and Its Implications for the Deployment of Capital
While I was not privy to the relevant decision-making processes, it is nonetheless clear that Uber’s investors have shown a collective willingness to deploy billions of dollars of capital at eye-popping valuations.
Unless they are economically irrational, this can only be because they were confident of either:
- The veracity / longevity of the underlying revenue model, or
- Their ability to profitably exit their investment (publicly or privately) before any weakness became apparent
However, Taxify and other market entrants such as Ola are now threatening the assumptions on which that capital was deployed, having delivered to me an equivalent outcome with a fraction of that capital base.
But it doesn’t end with Taxify and Ola. In fact there is considerable evidence that this process of creative destruction will continue ad infinitum until the price charged for access to the network collapses towards zero.
What is to stop a 15 year old kid from building an equivalent app (perhaps using open street map, along with blockchain for identity management / payments processing), sticking it up on Google Play / App Store, and just giving it away for free?
In that scenario virtually all of the capital that will have been deployed prior to that point will have been destroyed.
Conclusion
The Taxify/Uber phenomenon has profound implications both for Uber and the wider economy. I would now argue that:
- There is scant evidence that Uber can sustain its commission structure so far from marginal cost over the length of time required to generate the anticipated rate of return
- Uber’s failure to anticipate ongoing deflation (towards a marginal cost which is zero) will eventually impact on the entire process by which capital is deployed in the future
As this process gathers pace, the boards of joint stock companies will become increasingly unwilling to deploy capital, because they will no longer have any confidence that they can outrun the process of deflation that is now underway.*
The macroeconomic consequences of the above analysis are even more compelling.
Over the last 10 years in particular, fiscal and monetary authorities around the world have deployed vast amounts of capital (and encouraged wider debt-fuelled balance sheet funding on a biblical scale) in an effort to stave off entrenched weakness in terms of inflation.
But if price sensitivity is increasing and product lifecycles are shortening, it implies that deflation will continue to accelerate, eventually overwhelming even their most gallant efforts at stimulus.
No doubt those authorities would argue that the measures employed were part and parcel of their remit to ensure financial stability.
But if they have driven a process of massive leverage just before powerful deflationary forces become entrenched across the economy, they may well have delivered precisely the opposite outcome.
* The forces underpinning deflation are proliferating, strengthening and aggregating e.g. machine learning, renewable energy, blockchain, 3D printing, etc. What you are left with is the Collaborative Commons which Jeremy Rifkin predicted in his book Zero Marginal Cost Society.