Of the five rides I took in that locale, all of which would be classed as 'long distance,' four were with full time drivers. While that is a very high percentage of my rides, that should not be a surprise given that at the Southwest departures pick up point at San Francisco Airport alone, there always seem to be half a dozen or more people waiting for a pickup. As a data point, total passenger throughput at SFO in March 2016 was a staggering 4.1 million people. And let's not forget that San Francisco is the home of Uber.
On this occasion, the experiences of one driver in particular struck me as especially interesting. Here's what this naturalized American from El Salvador told me:
- Driving for Uber for 15 months.
- Average working week: 40-50 hours.
- Target pre-tax earnings: $850-1,000 but can go higher.
- Aims to clock up 120 rides per week to earn Uber's $500 bonus which he puts to one side for taxes.
- Likes Uber pool in the city because he can count two rides if he picks up three people.
- Does not specifically look for surge pricing times.
- Takes two weeks' holiday a year and occasional odd days off.
Does that sound like an 'ordinary' working week you'd expect to hear about? It does to me.
I was especially interested in understanding how my driver organizes his time. It seems that takes a little practice but once he got familiar with how certain routes work, then he could start optimizing how he spends time. So for example, he'd learned from experience that a run to the airport works out well provided that there are not too many other Uber drivers in the area and that it is a weekend, Monday or Wednesday. How many is too many? 'Less than a hundred,' was the answer. Apparently, Uber lets him know roughly how many other cars there are in a particular area so that he can plan and optimize his time in near real-time.
Plenty of observers have said that the Uber model can be easily replicated but having listened to his story for a good 40 minutes, I doubt that's the case.
Uber is constantly altering the model so that it optimizes the available fleet of vehicles while at the same time offering its 'best' drivers worthwhile incentives to do more.
On the rider side, I've seen Uber try a bunch of experiments, some of which work while others don't. This month for example, I've been able to take advantage of flat rate rides in the San Diego area by making an upfront payment of $20. I already know my average ride cost so quickly calculated that airport runs alone would see me at least break even. It's one more way that Uber keeps riders loyal.
All the drivers I spoke with seemed relatively happy with the job they do. They all feel as though they have a degree of mastery over their destiny which seems important to them in terms of job satisfaction.
The San Francisco/Bay Area may not be typical. An aging and over burdened public transit infrastructure combined with clogged roads provide the environment for an Uber to both thrive and survive. From personal experience, I'd rather be a passenger than a driver. Viewed i n those terms, Uber can be characterized as providing the right service for the right circumstances.
I asked my driver whether he'd got into Uber Eats, the food delivery service that Uber recently launched. Despite many requests from Uber, he chooses not to work on this service for two reasons:
- Very difficult to park in San Francisco.
- Food smells in the car.
I asked what he thought about autonomous vehicles. My driver was remarkably sanguine about the prospect. Despite the obvious long term threat, he was of the view that it would be a good five years before there was any significant impact and even then, he believes there will always be a place for the traditional form of cab ride. Time will tell but I was impressed by his optimism.
As I was processing everything the driver told me, it became clear to me that the notion of 'uberization' as a term to describe challenges to existing business models generally is likely far fetched. We already know that Uber does not work well in every location but needs certain pre-existing market and location specific characteristics. The flexibility of the Uber model is specific to that market, although it is easy to see how the model could be extended. It may be for example, that transport and logistics generally become super efficient and low cost through the introduction of autonomous vehicles.
Food delivery services like GrubHub (and Uber Eats) can be super convenient for consumers while at the same time expanding the potential reach of restaurants.
But you'd be hard pressed to say the same about those industries that rely upon significant investments in fixed capital. Oh wait a moment - those are already being automated through robotics.
Nevertheless, it was interesting for me to learn about the full time Uber driver experience which, in many ways, mirrors the industry it is replacing and those who have dedicated their working lives to providing that service. In that sense, Uber is way beyond a provider in the 'gig' economy. But the trick it is successfully pulling off is running enough experiments via its network application to allow business model optimization. That's something the taxi business in its current form cannot offer.