During my first coding class, after the obligatory “Hello, World,” my assignment was to find the least cost path in a matrix of values (linear programming). The computer took some time to crunch the data to come to a solution. Now, this is an app on your phone.
Or what has become lately is an app for your world. What we are looking at is the data and mobile communications infrastructure now available to drive instant gratification in all manner of goods and services: “A decade ago, we got iTunes, and the ability to buy a song bought and delivered with the push of a button. Then Facebook helped us stay in touch with our spread-out friends and family from the comfort of our couch. Then Netflix DVDs started coming over the air instead of to our mailboxes. Now it’s not just Web pages that we can load up instantly, it’s the physical world.”
<re/code> has written a really nice series covering this industry. This retry of the instant delivery services form the dot-com era has been made possible by the omnipresence of smartphones.
Much like retail is trying to get back to the service levels and customer interaction of the corner store, but now stocked with everything all the time, the instant gratification industry is getting back to our village economy roots. “Pishevar,,,, holds the popular Silicon Valley mindset that the Uber model can be replicated for all sorts of things. He describes this as a boomerang back to a village economy. After years of trends toward suburbs, big-box stores and car ownership, smartphones could be helping us get back to where we came from. The combined forces of urbanization, online commerce and trust mean that people can efficiently share goods and services on a local level, more than ever before.”
As for what is Uber and “Uberization”: “Uber is a company that owns nothing. It connects available drivers and their cars to people who want to be their passengers. By juicing supply with surge pricing and demand with discounts, Uber is able to create — out of thin air — a reliable service that exists in 140 cities around the world. Without fail, instant gratification startups say they will win because they are smart at logistics. Describing his business, Instacart founder and CEO Apoorva Mehta says, ‘It really is a data-science problem masked into a consumer product.’ Instacart is now perhaps the largest startup in the space, with operations in 12 cities and $55 million in funding. DoorDash’s Xu describes his purpose as a machine-learning problem: Discovering ‘the variance of the variance’ so his algorithm can reliably estimate prep and delivery time based on factors like how long a type of food stays warm, what a restaurant’s error rate is (the norm is 25 percent) and how fast a particular driver has been in the past. Uber aims to match up a driver and passenger as quickly as possible. Food delivery is more complicated, according to Xu. ‘It’s almost never the driver that’s closest to the restaurant when the order is placed,’ Xu says.”
A key for the new industry being profitable vs. the dot-com failures is the lack of an owned and costly infrastructure. Instead, data and logistical analytics connect all the moving parts necessary to drive the delivery of goods and services. “… They don’t necessarily need traditional infrastructure — warehouses, vehicle fleets, even employees. Unless they want to burn through hundreds of millions of dollars, like online grocer Webvan and on-demand deliverer Kozmo did in the dot-com era, they’ve got to think smarter. Redefining delivery for a new era of customers who want everything right away requires rethinking operations. By focusing attention on creating a powerful logistical system, and tying into the “sharing economy,” many of the new crop of startups in the on-demand space are trying to offer faster service at a much lower operational cost. And so the young players in the instant gratification economy are ferrying cargo across town via crowdsourced workers.”
Today, I would imagine the cliental are mostly the wired-in urban population. However, with the Boomers becoming less and less physically mobile as they age, I can see a huge new population that would prefer “everything all the time,” which is after all a concept from the 80’s. All this made possible by your friendly data analytics and the ubiquitous mobile computers that fit in your pocket or on your wrist.