Saturday, 27 February 2016

My free business lesson from an Uber driver

Want a free business class? Find out more about Uber (or try talking to more Uber drivers). Every Uber driver has at least some kind of opinion to share about the Uber business model (its upsides and downsides for drivers and passengers alike), and some drivers (if you are inquisitive) will provide you with additional business logistics. Occasionally you will receive an outlook on the (potentially sobering) present and future societal impacts of Uber. If you are really lucky, you will have spent the whole ride entertained by a detailed rundown of the business' history and how it has been continuously adapting to novel locations, changing consumer demands, and emerging competition. I found myself the lucky passenger of precisely the latter kind of Uber driver on my last trip from SFO to Palo Alto: a young latin American named Marcos, with a square jaw and an equally square baseball cap bill. I will endeavor to provide a recount of this conversation (really, a monologue punctuated by my occasional requests for additional details). I aim also for my recounting to have the properties of a conversation, in that regardless of the factual accuracy of individual details or the exact temporal sequence of events (potentially tainted by the knowledge of my driver and my interpretation), the general outlines of the high-level picture should nevertheless surface.

From my driver Marcos I learned that Uber sprouted up in SF to fill an existing gap in the market: the need for a professional and, importantly, reliable chauffeuring service. An emerging sentiment at the time was one of dissatisfaction with cab services, passengers having to unwillingly deal with unreliable service and rude or disrespectful drivers. The drivers seemed to have the upper hand in this market and behaved accordingly. 
Although I am not sure how widespread this sentiment was, I can attest to the fact that this is the reason I've never liked taking cabs.

Naturally, this was the sort of inconvenience and unpleasantness that the more financially-privileged were willing to pay to avoid. Uber saw this opportunity, and was perfectly positioned to take advantage of it: in a city with (1) a dense population packed in a relatively small (drivable) area, (2) large and growing tech companies providing a continuous supply of financially-privileged individuals, and (3) a traditionally startup-friendly environment, where bold new ideas regularly surface and are picked up by the wave of tech hype. And so, Uber was born (in 2010). As a professional and reliable chauffeuring service with a convenient mobile app interface (and up-to-date updates on driver location), passengers would be picked up in shiny black cars by courteous drivers in formal attire, offering additional frills like water and mints for the on-the-run business man. Sure, this was an expensive alternative to cabs, but to the users of UberBLACK, it was well worth it. Behind the scenes the structure was quite clever as well: Uber provided the cars and phones for the drivers (equipped with Uber app and Google maps), and regular people stepped up to provide themselves as drivers, no formal interviewing procedure required. Marcos dropped out of his community college to take on this new, respectable job that required a full-time commitment. As the success of a personalized on-demand transportation service had shown its colors, it opened up the market for new variants. And this is where Lyft comes into the picture. 

Lyft aimed to capture another SF-based market segment: the young crowd of current students and recent graduates, now employed at local startups. An alternative transportation solution was needed for the kind of person that ate Mexican from a food truck and sported giveaway t-shirts acquired at hackathons and career fairs. Lyft was marketed as an affordable ride-share, the distinctive pink mustache on car bumpers trumpeting the friendly, hip, and easy-going atmosphere that customers would learn to expect from it. In stark contrast to UberBLACK, passengers would sit in the front, engage in conversations with their casually-dressed drivers, and ride in whatever car the driver happened to own. Whereas Uber lent its drivers cars and phones, Lyft sent them giant pink furry mustaches. The latter was more financially viable, allowing prices to drop to student standards, well below cab fees. Importantly, Lyft drivers could work on flexible schedules, squeezing in rides in the free moments of the day, morning, evening, and between activities. Marcos could now go back to college and pick up passengers in his free time. 
Uber wisely recognized that much of its infrastructure was already in place to allow its service to be differentiated for different kinds of customers. Uber then branched to provide a new option: UberX. Learning from the successes and failures of the Lyft model, UberX allowed drivers to work flexible hours in flexible attire, operating their own vehicles – provided, and this is important, that the vehicles passed some minimal quality standards (Lyft passengers had begun to complain about the run-down condition of some of the cars). The water and mints were still there. Drivers were encouraged to be friendly and hip. 

Uber had a first-player advantage: it had been first in the market and thus enough time to acquire a good reputation and loyal customers through its UberBLACK service. UberX brought in new customers and gave the old ones a flexible option. Provided with the same reliability and courteousness, some of UberBLACK customers now opted for the cheaper, more informal option. It is part of SF culture not to flaunt financial well-being, as evidenced by the casual hoodies and slacks regularly worn by some top tech executives. So black cars became regular cars (that were nevertheless guaranteed not to be run-downs).

As an aside, Uber now has a variant that is intermediate between UberBLACK and UberX. Do you want to get picked up by a casually-dressed Uber driver but in a brand-name car like a BMW or Mercedez for an intermediate price? Well now you can with Uber Select. And if you don't want a fancy car to pull up at your office entrance in SF, you can stick to UberX. Different Uber options happen to be dominant in different cities. For instance, perhaps unsurprisingly, LA tends to prefer the luxurious option.

After the introduction of UberX, Uber's customer pool grew. This meant that the density of ride requests was often higher on Uber than on Lyft. Drivers had more customers overall and could cover smaller distances between ride requests. Marcos and his friends signed back on with Uber.

New measures had to be taken. Lyft gave its drivers new incentives: “complete X rides and receive a rebate on the hefty commissions paid back to Lyft”. Uber followed suit. The new incentives served an additional purpose: having to complete a minimum number of rides, many drivers could no longer afford enough time to work for both companies and still complete enough rides with each. Choices had to be made. Uber tried to give drivers incentives for accepting all ride requests in a row. Drivers obliged and accepted all that came their way. They accepted requests even if it required going around the whole block just to pick up a passenger directly on the opposite side of the street. Passenger wait times increased. Passengers were not happy. Uber pivoted its incentives structure.

A vicious price war ensued. The water and mints disappeared from Uber cars. With few noticeable differences between the two services from the customer perspective, customers went where prices were lower. Lower prices meant more ride requests and a quicker way to hit the incentive ride minimum. Drivers went where there were more customers.

As Marcos prepared to drop me off in Palo Alto, he got his Lyft app ready. He said he'd take the first request he got - Uber or Lyft. Palo Alto has longer ride distances and fewer customers per square area than SF. Time is costly, and Marcos would not spend it passenger-less. After all, he needed to be in class soon. He let me out.  My half-hour, 21-mile ride cost $37.78, including a $3.85 airport surcharge. Uber would take 20-30%, gas would cost Marcos another few dollars, and car depreciation isn't to be forgotten either. Marcos told me that the prices are more expensive in SF than surrounding areas. (In fact, my trip back to SFO from Palo Alto 2 days later cost $28.47). On my Uber app, I gave Marcos 5 stars and left some feedback about what a knowledgable guide he turned out to be. Then again, I don't remember the last time I gave a poor review.
Lowering prices means even more burden on the drivers. Already the fraction of a cab fee, Uber fees are reaching new lows. Two days later, I logged onto my Uber app at 5 a.m. to request a car back to the airport. I could see some cars circling around the Googleplex complex, 15 minutes from where I was. After about 2 minutes, an Uber driver accepted my request. Another minute later, he canceled the request. He'd probably gotten a more conveniently-located ride request and would make more money by keeping the distance driven without passengers minimal (and 15 minutes was already pushing it). His car stayed around the Googleplex complex. I placed another request, finding myself irritated that it was taking me longer than 5 minutes to get a car. My last dozen or so Uber trips involved instantaneous request acceptance, with a car picking me up 1-2 minutes later. How spoiled I had become. Finally, after another 3 minutes, my request was accepted by a middle-aged Latin American gentleman named Juan Carlos, and in 15 minutes, he was at my hotel.

I was really thankful to Juan for picking me up. He was surprised to find out there wasn't a swarm of cars ready to take me. Uber cars often outnumber passengers at this early time in the morning, he told me. I was in turn surprised to hear this, having spent that night tossing and turning in bed worried that no Uber drivers would be on the roads so early (I didn't even consider cabs as an alternative anymore). Our differing expectations for what would be the Uber availability situation that morning led me to thinking that there are too many variables at play to fully predict driver behavior. Uber drivers have to somehow optimize ride fares, company incentive structures, passenger availability, and competition with other Uber cars to figure out if a particular ride is going to bring them more than it will cost. Earlier that morning Juan had driven another passenger to San Jose airport - a 20 minute ride that cost the passenger $10, of which Juan would probably get less than $6-7.

I told Juan about one of my recent Uber experiences in Boston. I had decided to try UberPOOL for the first time: a variant where multiple passengers can share the same ride, with different initial and destination locations, as long as the trips are relatively in the same direction. Each passenger pays less in return for the potentially longer ride. If multiple passengers are picked up, the Uber driver can hope to make a sliver more in the same fraction of time by combining the trips. The interesting catch is: you get a guaranteed UberPOOL price regardless of whether another passenger is taken. In other words, you pay a lower price (even lower than UberX) just by agreeing to potentially share the ride. Talking to my other friends in Boston, it is pretty common for no additional passenger to show up. So my friend and I took an UberPOOL. We counted as a single passenger (it would be the same price if only one of us was there), but didn't end up picking up a third passenger on the way. Our ride was 10 minutes from Downtown Boston across the bridge to East Cambridge, and cost us a total of $6. Splitting it, each of us paid $3, almost the price of a subway ticket, but with the walking distance (from subway to house) cut from 15 minutes down to zero.

Who takes the loss when no additional passenger request is made on UberPOOL: the company or the driver? I asked Juan. Turns out, it's the driver (in Lyft's case, the company pays the difference). So if drivers are making so little money, how can Uber remain a viable longterm business model? Without missing a beat, Juan replied that it doesn't need to be viable for longer than a decade at the most. "After all, Uber is building a fleet of self-driving cars. No paid drivers will be needed." Juan paused. But there's a bigger problem: Juan is concerned about the strawberry-picking robots that are now working on farms day and night, 24 hours straight. Soon, there'll be even more robotic farm hands. Juan's family back in South America along with thousands of other people are going to be out of the farm jobs that provided their livelihood. "What happens then?"
Juan Carlos got some fraction of the $28.47 I paid via my Uber app, and 5 stars.


Further reading:

Dated sequence of events in Uber's history:

Saturday, 13 February 2016

On effective communication: because it matters.

I've been thinking quite a bit recently about effective communication, party because there were 2 seminars last month at MIT about giving good talks (one by Patrick Winston, one by Jean-luc Doumont), party because we recently published a paper about what makes visualizations effective (for communicating messages), and partly because I've been TA-ing a research course for undergraduates (with a large communication component to it).

I'll summarize here some notes from the talks I went to, as well as my own thoughts and insights. Though I'm sure I'll have lots more to say on this topic in the future.

Patrick Winston started off his talk with the following statement*: "you (the researcher) will be judged first by your speaking, then by your writing, and finally by your ideas". This is a common phenomenon: a great communicator can sell you on the simplest ideas and make you see beauty in them; a poor communicator can obscure the most beautiful of ideas. Both examples regularly occur in lectures, in research talks, and in business presentations (but I'll focus on the researchers, here). It really is a shame when beautiful ideas don't come to light because the researchers behind them lack in explanatory artistry. It is an art, this whole communication business - which is why it is not commonly taught in a formal manner. Aside from the occasional seminar, the occasional resource exchanged among students, and the occasional tip given by one researcher to another during a practice talk, aspiring researchers (e.g. students) get no formal coaching and are told to "just do good work". Feedback and tips from advisors can be quite uneven, depending on the experience of the advisors themselves. (luckily, MIT professors are very good at selling their research, judging by the content on the front page of MIT news every morning; as Winston puts it: "your ideas should have the wrapping that they deserve")

The point is: many (esp. young) researchers need formal communication coaching, and often they underestimate how important it is for their careers (it pains me to hear yet another graduate student proclaim: "boy, these talks and posters I have to present are such a waste of my time"*). I would like to applaud MIT's initiative: the new EECS communication lab (and similar ones in other departments) for providing resources, training and advisors to students, when they need them. Additionally, I think MIT's SuperUROP course for undergraduates is a super valuable experience (essentially a how-to guide to being a researcher), where alongside a year's worth of academic research, students practice and receive feedback on important communication skills: writing research abstracts, proposals, and papers; performing peer reviews, creating academic posters, and giving research pitches and presentations. And yes, as a TA in the course, I sometimes hear the same excuses ("boy, all these written assignments are such a waste of my time, why can't I just do the research"). But when you're in an environment where industry representatives, senior researchers, and MIT faculty are following what you're doing (as is the case for these students), being able to sell your work can mean a lot for your future career. Last semester, for instance, the students participated in a large poster session, where they presented their work to all the aforementioned parties. I gathered some advice, common mistakes, and helpful suggestions in the linked-to set of slides.

* Yes, yes, groundbreaking ideas can speak for themselves, but I guarantee that most ideas need someone speaking for them (at least to get them off the ground).

Note that from one set of communication-related slides to another, from one talk to the next, the same kind of advice surfaces again and again. Most often, the views and suggestions presented are not idiosyncratic, but common, accepted, guidelines. We've all been in the audience: we know what catches our interest and what bores us to death (and it's often not the content to blame).

Let me summarize (and paraphrase in my own words) some of Winston's talk advice:

  • start with an empowerment promise: give your audience a sense that they will walk away with something (e.g. some newfound knowledge or ideas) from your talk, so they know what to look forward to and why they should care
  • get your idea out quickly, and cycle back: don't expect that all your audience members will follow along with you until the end, and do not leave the most important to last ("avoid the crescendo, just blurt it out"); come back to, and reinforce your points
  • use verbal punctuation: people fog out, so bring them back once in a while, especially to accentuate a switching of topics, slides, etc. (kind of like an "ehem, you can wake up now, even if you've missed the last few minutes, I'm starting a new thread..."); 
  • avoid near-misses: foresee what the audience could be confused about and clarify your contributions
  • what you end with is the last impression: make it count, clarify your contributions, show your audience what they're walking away with; and remember: the final slide will be there forever, "don't squander this real estate" (is your final slide the infamous and content-less "thank you"?)
  • whether a poster or a presentation, what should come clearly through are your vision, steps, and contributions (Winston even advocates naming the relevant sections/slides accordingly)
When approached once by a young researcher looking to get advice on his job-talk slides, Winston proclaimed: "too many slides and too many words"
"How do you know?" the researcher asked.
"It's almost universally true."
(Winston later added that allowing powerpoint to have less than 30-point font is probably Bill Gates' biggest fault. When text has to shrink that much, there is too much of it on the slides.)

This is the kind of advice that will come up again and again. People have the tendency to cram as much as possible into very small (spatial or temporal) frames. Researchers want to talk about all the great work they've done (not realizing that they're drowning out the most important parts). Students put all the details of their projects on their posters (not realizing that the contributions get lost). Here's my suggestion: do one pass of the content from which you want to pull slides/talking points, and extract the most important points. Sleep on it. Then pick the most important points out of your selection, and scrap the rest. Repeat. With enough cycles, you would have cleaned away the debris, exposing the shine of the main ideas.

What I like about Winston's communication advice is that he comes at it from the perspective of a scientist (he is, after all, a computer science professor at MIT). Sprinkled throughout his talk are technical references and examples. Most of all, he emphasizes the importance of projections - the way an idea or a piece of work is communicated to an audience: the context, the stance, the voice, the presentation style, all of it.

Another individual with a great technical take on communication advice is Jean-luc Doumont (got a physics PhD from Stanford). Jean-luc (he prefers to be called by his first name) consistently refers to the importance of increasing signal and eliminating noise in a presentation, whether visual or oral. This concept is ever-present in his book: Trees, Maps, and Theorems - which I highly recommend. 

Note that "noise" can refer to many things at once. In the case of presentations, the noise is everything that is tangential to your main points - it is the 'ums' and 'likes' in your speech, the nervous pacing and awkward hand fidgeting, the excessive details on your slides (do you really need your institute's logo on every slide?). In the technical writing, noise includes all the superfluous words (why say it in 10 words when you can say it in 3? why talk like a politician?).

With regards to maximizing signal, Jean-luc also talks about maximizing effective redundancy - which is to say helping to carry the message across despite noisy channels (those you have no control over, like the audience's attention or knowledge; whereas noisy channels that you do have control over should be minimized). Redundancy can be verbal or nonverbal. It can be complementary. For instance, your slides could contain your main points, but you're also there to describe them. If someone misses it in your speech, they see it on the screen*. You can also get the important messages across again later, in the same or different words (remember the cycling that Winston referred to?).

* This does not mean that what is on the screen should be what is said. The slides complement, not replace, the oral presentation. If people are spending all their cognitive resources reading your slides, they'll fail to process what you're saying, and that is where the communication breaks down. 

Jean-luc's three laws to optimize communication are:
  • first law: adapt to your audience
  • second law: maximize the signal to noise ratio
  • third law: use effective redundancy
(but remember: second law > third law)

When studying information visualizations (graphs, charts, plots, etc.), our research team also found that when given visualizations with redundant encodings - i.e. when the message was presented in a number of ways (as a trend line, as an annotation of the trend line, as a description of the plot, in the title, etc.), human observers were more likely to recall the message correctly (different people might need to see things presented in a different way). Conversely, too many extra details, unrelated visuals, or metaphors led to worse recall and confusion, in that observers might recall only a piece of the main message, or misremember it entirely. The take-away? Make your priority getting the signal across, scrap the rest. You can do so quite effectively using the title. Importantly, if your title contains your message, more observers will remember and recall it. 

Here's a little piece of advice that also tends to repeat: make your titles count. Be it the titles of talks, slides, section headings, visualizations/graphs. Jean-luc places a lot of emphasis on this in Trees, Maps, and Theorems. He gives great examples of how scientists often caption their plots something like "Y as a function of X", where it is clear that what is plotted is, by no surprise: Y as a function of X. You haven't told the reader anything new or useful! Consider instead using this valuable real estate to convey the message of the plot, such as "Y peaks when X is at its lowest value due to the effect of...". After hearing all of Jean-luc's examples of the way scientists title their slides, figures, etc., I got to thinking. It's true, they do! 

I have since tried to be extra careful about my captions, my titles, my paper section headings, even my e-mail subject lines (I guess the current generations get a lot of twitter practice). I try to limit the noise, to imbue as much of the written text with meaning as possible, to carry across the most important points. In fact, when writing my master's thesis, I wanted the essence of the whole thesis to come through the list of contents, figures, and tables. I wanted the reader to walk away with the outlines of the story without even getting to the introduction. 

Importantly, if the message can come across simply and quickly, that is not a bad thing. If there's an easier way to say something, why not say it? Jean-luc had great anecdotes at his lecture on "Communicating science to nonscientists" about how unnecessarily jargon-filled scientific communication can be. Here are a few of my favorite anecdotes (again, paraphrased):
  • After a room full of experts took turns describing their own research topics to each other, they were asked: how many of those descriptions did you understand? Less than half. How many do you still remember? Maybe a few. And this is a room of scientists! Moreover, they consider this normal. How many talks do you remember from your last conference? How many were engaging from start to finish? (maybe... 1?)
  • When researchers are asked to describe what it is they do, and when they get to any specialized vocabulary, they tend to say it faster and to lower their voice. It is like they are trying to limit us the pain of trying to understand them by saying it fast and low. But that is exactly the opposite of what we need in order to understand! 
  • A student shows Jean-luc a passage he has written. Jean-luc looks confused and asks the student to explain what he meant to say in the passage. The student says: "Well what I mean to say is [blabla]... but I just don't know how to say it." Well in the [blabla] was exactly the explanation!
Jean-luc advises scientists "not to write complicated out of the principle of revenge" (for other scientists who write this way). Do not try to prove to the whole world how complicated your research is. Define technical words, avoid jargon, avoid synonyms, write simply. Provide reference points, comparisons, and examples. Give the why before the what.

I'll leave you on my favorite Jean-luc quote from Trees, Maps, and Theorems: "Effective communication is getting messages across. Thus it implies someone else: it is about an audience, and it suggests that we get this audience to understand something. To ensure that they understand it, we must first get them to pay attention. In turn, getting them to understand is usually nothing but a means to an end: we may want them to remember the material communicated, by convinced of it, or ultimately, act or at least be able to act on the basis of it."

And getting messages across first and foremost requires caring about the importance of getting those messages across. It is about recognizing and believing that effective communication matters. It is about adjusting your habits, your jargon, the amount of content on your slides, your projection, your figure captions and titles, and most importantly your awareness of all these things. Happy communicating!