As Part 1 of this serios of installments began to explain, the key principle that matters in the success of any transportation mode, and frankly in countless other professions, is the concept of density. So before applying this concept to help the reader understand the extraordinary effect this single concept has on transportation, and how manipulating it (or perhaps stumbling upon it) by Uber and Lyft gave them a competitive advantage over taxicabs (operating in almost identical ways, with a few differences explored in Parts 1 and 3 of these series) , I thought it would be helpful to provide a simple model if how this concept affects the profitability of both owners and workers in a more simple business – where some degree of balance must be struck in order for owners to even have workers, much less better ones.
One easy illustration exists in a small restaurant. It has 20 tables. In Mara Lago, a restaurant with 20 tables might have 20 waiters and/or waitresses. But that’s abnormal. In a typical restaurant where normal people would dine, there is a tug of dynamics between two entities:
- The alliance of the diners and owners (an unusual alliance when compared to most other alliances) want the most waiters and/or waitresses, in order to get the best, if not superb, service. Because the fewer tables each waiter serves, the better the service is. So the waiters and waitresses want to have as many tables as they can, since with that relationship, they would make the most money (in tips).
- The owner has the opposite goal. Even while wages paid to waiters and waitresses is meagre (because they earn their money in tips), restaurant owners want only the smallest number of waiters and waitresses who can provide good or excellent (not necessarily superb) service to their clientele.
But the fewer the waiters and waitresses there are, the worse service becomes. So one can see why both owners and diners would be forced to strike a balance between service-to-customers and maximum profits (by employing the fewest waiters and waitresses.) One odd dynamic that has helped both reach such a balance – a balance removed this year by history’s most idiotic and ruthless national leader – has been the continued depressed minimum wage paid to waiters and waitresses, since most of their income is derived from tips — as he proposed eliminating taxes on tips. This is not a perfect model, because the more tables a waiter or waitress can serve while providing decent service, the greater would his or her tips. At he opposite extreme, when a waiter or waitress has too many tables, service declines, and tips decrease. Clearly, a savvy waiter or waitress wants as many tables as he or she can handle with excellent service (which depends on other variables like the size of the kitchen staff and their speed, as well on the items on the menu – some of which take more time to prepare).
All transportation modes follow some form of this model. But it is easiest to understand in the taxi and Uber/Lyft world (the latter classified by those in the profession as “transportation network companies”). With taxis, in the days of responsible government that kept the monopolies largely under control, cities regulated taxis by trying to match demand to supply – giving or selling licenses to companies or single vehicle owners so that (a) there were enough vehicles to reach those who needed them in a reasonable amount of time, yet so that (b) the taxis did enough trips (compared to “deadheading” to and from them) to earn their owners or drivers a living. (Depending on the city or metropolitan area, some allowed “owner-operators” [who owned and operated a single vehicle] and “cooperatives” [groups of owner operators].) And where the density of potential passengers was thick, and traffic manageable, response times were reasonable, passengers were satisfied, and owners earned a living.
All that changed when Uber and the corruption that unleashed its dominance to decimate various cities’ taxi industries (New York City and Boston are likely the best examples). The reader must keep in mind that government agencies rarely understand anything about even fixed route transportation. When demand-responsive modes, like taxis and limousines, entered the picture, providing only exclusive rides, regulation was still somewhat simple, since each trip was really nothing but a separate fixed route trip, and service simply strung them together, with a different origin and destination for each successive trip (airport trips are the exception). Another obvious difference between this form of demand-responsive service (door-to-door or curb-to-curb) and fixed route transit, schoolbus or motorcoach service is that every taxi trip was different, whereas every route provided by the others was the same – day after day, and hour after hour.
Things began to get trickier when these demand-responsive services began to provide shared rides. While horses learned to memorize a fixed route in a single day (see Part 1 of this series), few human beings could understand shared ride transportation, much less provide it efficiently. In the 30 systems I examined in detail during my direction of the USDOT’s first nationwide examination of special transportation service for elderly and disabled individuals, one system had a brilliant architect, two others at least had some semblance of a “system design,” while the other 27 were clueless.
This post could not be complete without a true story about extraordinary dispatching in a restaurant. Fifty years ago, playing piano in a restaurant run by a crime boss (such individuals always treated musicians with great respect), the owner hired a “bouncer” because he could not trust the “dispatcher” – the nephew of a huge crime boss, who had spent time in prison, but whose love was knifing people. (So if anything untoward occurred in the restaurant, everyone’s job was to grab the “dispatcher,” and let the bouncer handle the problem.) But the “dispatcher” was brilliant. So he served in a role I never saw duplicated in any restaurant in which I’ve ever played, or in any I’ve ever dined. He would stand at the doorway of the kitchen, while groups of waiters and waitresses (perhaps 12 to 15 it total) would approach him with their written orders – often complex because most tables were large and heavily occupied. These waiters could simply tell the “dispatcher” what they needed at their respective tables. He would write nothing down.
Instead, he would wait for five or six such orders, enter the kitchen, and re-organize a larger summary of what was needed: “7 steaks well done, two medium-rare, six order of chicken, other entrees, and countless sides orders and deserts”, and on and on – all by memory.
When the chef and cooks completed the orders, the “dispatcher” reassembled them into each waiters and waitresses’ needs, reappeared at the kitchen door with a huge metal tray with some waiter’s or waitress’s orders, sorted them out onto each waiter’s or waitress’ tray – precisely in accordance with the orders they had placed — then retreated into the kitchen to get the next batch, and again, allotted every waiter’s or waitress’ order to each of them. I don’t recall a mistake ever being made. But the interim steps every traditional large restaurant does instead – one waiter’s order at a time posted, in written form, and clipped to a revolving spindle, from which the various cooks and chefs read and prepared each order – and then bringing them out of the kitchen, one order at a time – was completely eliminated.
Witnessing this brilliance – long before I had entered the transportation field – was a thrill. I was a feat that didn’t seem possible. I have seen primitive imitations of this process in the computerized, touch-screen restaurants in some airports. But getting a glass of water with no ice, or any variation of an order, would be impossible. This comparison helps to explain why a good human scheduler can schedule more efficiently than a robot – a project I helped prove on a consulting project I directed in Edmonton, CA, in 2002. Now, software likely improved to a point where a live Earthling cannot compete with a digital scheduler. I’m not sure.
The point of this story illustrates both the importance of, and the limits of, excellence. And it documents the fact that excellence can be achieved – in transportation, just as it can be in a superbly-run restaurant. While I doubt what I witnessed in that restaurant will ever be repeated elsewhere, I never forgot it. And more than anything, it served as a model for my 50 years in the transportation field.
The famous coach of the Green Bay Packers, and briefly the Washington Redskins (during my first year in D.C.), Vince Lombardi, used to say, “You can’t catch perfection. But if you chase perfection, you can catch excellence.” During the decade I ran a 70-vehicle paratransit system, I must have told that story to scores of employees. It inspired them. And most tried to emulate it, turning our system into a “Swiss watch” in efficiency, on-time performance and safety. In what I estimated to be 59 million meles of service, we never had a wheelchair tipover. No one was every injured boarding or alighting – and we had only a single injury-incident involving one passenger – an incident that was largely my fault, and which, ironically, resulted from my zeal about efficiency and safety. What I witness as an expert witness is usually very different, and I have earned the right to criticize others. But public transportation can be provided safely. But for this to happen, everyone involved, from the General Manager to an entry level bus attendant must envision themselves as part of the virtuosity, and strive to perform his or her duties consistent with this goal.
#ubersafety #uberaccidents #ubercorruption #lyftcorruption #transalt