The Uber All Economy of the Future

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2 The Uber-All Economy of the Future F J. W S MITH ALKER he poster child for the economy of the future is Uber, the much ballyhooed (and much booed) on-demand mobile service for transportation. It’s more T than transportation, though. Every nook and cranny of the consumer economy is being “Uberized” by a business model that twins personal services with technology. Not only does this business model fit the competitive opportunities of today’s marketplace, but it also dovetails seamlessly with the larger dynamics shaping tomorrow’s marketplace. What’s ahead is a shift in the dominant business model, one in which all consumer goods will be available as a service and all consumer services will be available on demand. This is the Uber-All Economy of the future. Anticipating the future in this way is a bottom-up view of change. The usual line-up of macrolevel shifts in productivity-enhancing technologies and labor-force demographics will be critical, of course, but the most important dynamic is happening at the level of the firm. Companies will make money in different ways, and this will cascade through the economy. Changes in technology and in the labor force are setting the stage for this transformation not by enabling companies to do something old in new ways but by forcing companies to do something entirely new. The success of Uber and of companies with an Uber-like business model is particularly noteworthy in the context of a global economy struggling with slow growth. Technology is unlocking these opportunities. In particular, mobile applica- tions are enabling start-ups to aggregate sufficient demand to support this new business model, often by capturing unrealized value from assets these start-ups do J. Walker Smith is executive chairman of The Futures Company. The Independent Review, v. 20, n. 3, Winter 2016, ISSN 1086–1653, Copyright © 2016, pp. 383–390. 383

3 F 384 J. W ALKER S MITH not own. But even when new infrastructure is required, needed investments are lower, which reduces start-up costs and time to market. Equally important, technology is closing the gap between decisions made by consumers and the satisfaction of those choices. Speed has always been important, but immediacy will be the ante going forward. Machines are better at immediacy than people, not to mention more productive for both routine and abstract tasks. The displacement of people by machines will put the labor force under increasing pressure, with a shrinkage of jobs in many sectors and a growth of jobs assured only in personal services and technology, a duality of future employment that matches the twin elements central to the Uber-All business model. Every Category No business category will be unaffected by companies operating with an Uber-like, on-demand business model. For illustrative purposes, consider a well-established category such as laundry detergent. The competitive set for laundry detergents is no longer just the traditional products on a grocery store shelf but also includes compa- nies such as FlyCleaners, Washio, Rinse and Dryv in the United States, Laundrapp in the United Kingdom, and Edaixi in China, all of which operate through an on-demand mobile app. With the click of a button, consumers get their laundry picked up and returned right away, clean and ready to wear. Obviously, such a service is not directly substitutable with a bottle of liquid laundry detergent, but it is a direct substitute for the same benefit—clean clothes when needed. Every benefit can be addressed in many ways by solutions of many forms, and that is both the threat and the opportunity posed by the Uber-All Economy. Net benefits are all that matter to consumers. The Uber-All Economy is reshaping how benefits are delivered, thereby reframing what consumers expect and want. Even more broadly, if the need for clean clothes is better met through an on-demand mobile service, then it’s not just laundry detergent that’s no longer needed but also at-home washers and dryers, and if there is no need for washers and dryers, then there’s no need for a laundry room in the home either. Something similar is true for every category, such as meal-delivery services affecting kitchens and pan- tries or transportation services affecting cars and garages. As such trade-offs get sorted out in household budgets, the superior net value of on-demand mobile ser- vices will become more apparent, and as it does, the diffusion of the Uber-All business model will gather momentum. Business Model Two elements are critical to the Uber-All business model. The first is a personal service. Uber itself is a personal service of drivers. Washio or FlyCleaners is a personal EVIEW HE I NDEPENDENT R T

4 F E U BER -A LL HE CONOMY OF THE F UTURE T 385 service for cleaning clothes. But consumer goods are also affected because Uber-All companies want to substitute their personal services for these goods. The concept at work here is conversion—converting goods into services and converting underleveraged service assets into more valuable ones. For Uber, idle car-and-driver assets are converted from nonuse to use. Consumer goods must add a service or find a service within which to get embedded. Services need to innovate what they do to stay ahead of the broader conversion of value into something tied to a service in every category. The second element of the Uber-All business model is on-demand availabil- ity anywhere, anytime. Technology makes this possible. To date, mobile apps have been central to this model, but on-demand availability is fundamentally about fulfillment in whatever way is fastest. The specific technologies are sure to evolve. One important consequence of on-demand availability is tiered pricing tied to occasions. Many on-demand mobile services charge a premium today, but this is not the essence of on-demand pricing, and premium pricing will come down as competi- tion and scale grow. The essence is pay-as-you-go pricing. The Uber-All business model is pricing for usage rather than pricing for owner- ship or accumulation. In contrast, generally speaking, pricing today is based on accumulation, not on usage or demand in the moment. Stocking up or subscribing or collecting entail pricing by accumulation, not pricing by usage. With the Uber-All on-demand business model, a brand sells by the slice—no more than a consumer needs in that moment. This has two key implications. First, it erodes the need for ownership. Access replaces ownership at the center of consumers’ aspirational mindset. In addition, access instead of ownership means a shift toward consumers paying only the marginal cost of production, which in turn leaves less room for mark-ups by producers and retailers. Second, the priority in pricing shifts from targeting people to targeting occa- sions: no more flat rates that are the same no matter the occasion, but instead rates that better match demand on particular occasions. Most occasions will be ordinary, so pricing will have to be cheap. But some occasions will be extraordinary and special and thus able to command a premium. These are occasions that are so special or so critical that people of every means, high and low, are virtually indifferent to price. Uber calls its premium pricing “surge pricing.” But there are no “surge consumers” or “surge drivers” or “surge cars”— just “surge occasions” at which “surge pricing” applies to all consumers. This occasion-based bifurcation of pricing is on trend with a broader economy headed high and low. Scarcity of time or money doesn’t push people just to the low end; it pushes them to the high end, too. When there’s only a little time or a little money to go around, spending it on something average is just as big a waste as overspending on something bad. Neither offers full value for the scarce minute or scarce dollar. To put it another way, consumers want “Superstar” offers as much as V OLUME 20, N UMBER 3, W INTER 2016

5 F 386 J. W ALKER S MITH “Super-Sale” offers. Companies need a pricing proposition that unlocks both. The Uber-All business model does exactly that. Immediacy Another critical element of the Uber-All Economy is a shift in expectations toward immediacy. Uber and Lyft provide transportation within minutes. OpenTable books a reservation instantly. Breather and Airbnb instantly locate a room for rest, work, or play. DoorDash and Instacart get food to your door within an hour. New expectations of immediacy are forcing established retailers to adopt on-demand models. For example, Amazon (now an established, two-decade-old retailer) has always focused on speed of delivery, from 1-Click to Prime to PrimeAir to #AmazonCart to PrimeNow. It has relentlessly chipped away at the gap between order and fulfillment. PrimeNow is Amazon’s on-demand service, with two-hour delivery for free and one-hour delivery at a premium for occasions when immediacy is imperative. Amazon is pushing the envelope even more with Amazon Dash, though. Dash was first introduced as a handheld WiFi-connected wand into which consumers speak to add an item to their AmazonFresh shopping list. Dash Button followed as a small, wireless-enabled, product-branded button that consumers press to reorder that specific product. But neither the wand nor the button push the envelope of immediacy far enough because both require consumers to go online to confirm the order. So Amazon is going a step further with Dash Replenishment Services that enable devices such as coffee makers or washing machines or printers to automati- cally reorder when supplies get low. This is a pioneering move in what eventually will be the norm in a world transformed by the Internet of Things. Preemptive and even predictive ordering is not science fiction. Amazon has also filed a patent application for something it calls “anticipatory shopping software.” Based on a consumer’s browsing behavior, this software makes a prediction about whether a consumer is likely to buy the item being considered. If predicted to buy, Amazon will begin to ship that item before the consumer has clicked the button to buy. The future of on demand is “know demand,” if you will. That is, before consumers even know they need something, machines will have placed and filled the order. A world of Big Data and the Internet of Things will soon track consumers in real-time across all aspects of their lives. To get the most from this world, consumers will make increasing use of apps that act as personal assistants, sorting through the enormous array of options based on a profile of individual preferences. On demand will no longer be triggered by a request in the moment but by an algorithm that matches a stored profile of preferences with usage, availability, prices, and ratings (Miessler 2015). These personal-assistant algorithms will adapt and improve with experience as well as push those nudges and recommendations that help people stay on track with personal goals and objectives. EVIEW HE I NDEPENDENT R T

6 F E U BER -A LL T CONOMY OF THE F UTURE HE 387 From “Go to” to “Come to” In the Uber-All Economy, the relationship between consumers and producers or retailers changes from “go to” to “come to.” Heretofore, consumers have had to go to producers or retailers to initiate and complete transactions. In the Uber-All Economy, producers or retailers will come to consumers instead. This change from “go to” to “come to” shifts costs previously borne by con- sumers to producers or retailers. Added costs are normally absorbed as an expense that producers or retailers push back to consumers in the form of higher prices. But in the Uber-All Economy companies may be forced to turn to different strategies for managing their margins. Many consumers’ ability to afford higher prices is uncertain in a global economy struggling with slower growth. Add to that changing expectations about immediacy as a basic requirement, not an extra benefit that is worth paying extra for. Whether consumers are able or willing to cover the costs transferred to producers or retailers will be a critical driver of the structure and shape of the Uber-All Economy. Consumers currently must invest time and attention as part of the price they pay. They must take the time to go to the store, whether it’s brick and mortar, online, or pop-up. They must take the time to browse, decide, and check out, all of which requires a great deal of attention. In the Uber-All business model, the time and attention that were a cost paid by consumers become a cost of production for producers or retailers. Consider the half- hour it might take today for a consumer to go to the mall. In the Uber-All Economy, that is now a half-hour that producers or retailers must spend coming to a consumer. The cost of that half-hour transit time has shifted from consumers to producers or retailers. How that cost gets managed by companies is key. In all likelihood, it won’t be as simple as passing it along to consumers. Producers and retailers do things now to reduce the time and attention that consumers must spend, such as delivery, convenient locations, and express lanes. But these things are intended to reduce costs to consumers. They don’t transfer those costs in whole from consumers to producers or retailers. Consumers know the effort involved in the time and attention they spend but rarely think of it explicitly in terms of an equivalent dollar value. Because they don’t pay these time and attention costs directly from their pocketbooks, to a large extent they don’t see these costs. Hence, one of the key questions of the Uber-All Economy is whether consumers will be willing or able to pay with dollars for the costs of time and attention shifted to producers or retailers. Even if they are willing, they are unlikely to be able to pay enough of a premium to fully cover these shifted costs. In this case, producers and retailers won’t be willing or able to sell to consumers unless they can offset these additional costs with lower costs in other parts of their business model. Finding ways to rebalance costs is what Uber-All companies are focused on the most right now. The necessity to rebalance costs due V OLUME 20, N UMBER 3, W INTER 2016

7 F 388 J. W ALKER S MITH to the shift from “go to” to “come to” is driving everything else associated with the Uber-All Economy. One of the things that will separate winners from losers in the Uber-All Economy will be ingenuity in finding ways to provide immediacy of fulfillment at an acceptable margin without raising prices. Obviously, this is an ongoing imperative in every business, but it becomes a bigger driver of success in the Uber-All Economy because of the shift from “go to” to “come to.” Technology enables Uber and other companies such as Airbnb to lower costs by leveraging underutilized assets owned by others. All on-demand mobile services keep sales costs low by using an app for ordering, payment, and feedback. But the biggest part of this rebalancing is labor costs. As an aggregation and distribution channel for people providing personal services, a company with an Uber-All business model creates scale that has been difficult to realize heretofore. In addition, by engaging people to provide personal services on demand, companies can lower the overhead costs associated with full-time employees by taking advantage of broader shifts in labor markets. Labor Markets Robotics and artificial intelligence (AI) are restructuring labor markets. University of Oxford technology experts Carl Frey and Michael Osborne (2013) examined all job categories tracked by the U.S. Commerce Department to assess the medium-term impact of computerization. Using models that compared skills required for hundreds of individual jobs with computers’ myriad capabilities, they estimated that 47 percent of all jobs in today’s U.S. labor market have a 70 percent or greater likelihood of being displaced by computers over the next decade or two. This number may prove to be an underestimate because it fails to account for the likelihood that advances and practical applications in robotics and AI will begin to accelerate with more transformative impact over that same period of time. Frey and Osborne (2013) found that the jobs least likely to be displaced by technology are service jobs and “thinking jobs.” This finding mirrors the future of labor markets predicted by George Mason University economist Tyler Cowen in his Average Is Over book (2013). Cowen argues that the only jobs safe from dis- placement are jobs for people running technology or jobs for people selling personal services to the people running technology. There is a great deal of uncertainty about whether displacement means perma- nent job losses. By and large, economic historians read the record of technological disruption as one of short-term losses more than offset by long-term gains. But this time the outcome may be different. The complex of jobs associated with technology will not be as robust as they were previously. Horses and buggies couldn’t take care of horses and buggies. That was a job for people. Similarly, cars can’t take care of cars; airplanes can’t take care of airplanes; personal computers can’t take care of personal T HE I NDEPENDENT R EVIEW

8 F E U BER -A LL T CONOMY OF THE F UTURE HE 389 computers; and so forth. But robots will soon enough be able to take care of robots. AI is already self-referential and self-learning. Humans will be needed less and less. In previous eras, technology was engineered to make human toil unnecessary, but now technology is being engineered to make humans unnecessary. As far as the Uber-All Economy is concerned, though, it matters only that technology is changing the types of jobs that remain for people to do. There may be more or less jobs, but the jobs available will be either jobs running technology or jobs selling personal services. The Uber-All business model is built on precisely this two-fold mix of job skills, making it a perfect analogue for the future of work and thus a natural complement to macrolevel changes in labor markets. The Uber-All Ecosystem As on-demand mobile services become the dominant business model, a number of other things will spin out of this transformation. A few are worth a short headline here and greater consideration elsewhere. Investors and entrepreneurs will focus more attention on existing assets and infrastructure. Owners of existing assets will benefit from new income streams, but less in the form of traditional rents and more in the form of shared profits from greater utilization. This change in focus will spill over into regulatory policy. The search for new uses or greater utilization of existing assets and infrastructure will strengthen economic and political pressure against regulations that limit or proscribe uses and utilization. Consumer markets will experience a decline in variety seeking and impulse buying as personal-assistant algorithms tied to preference profiles become com- monplace. Although novelty and experimentation may be programmed as a prefer- ence, producers will resist it. They will look to lock in dedicated choices in their deals with device manufacturers and software programmers. Plus, consumers will be reluc- tant to experiment with new things sight unseen. Algorithms tied to preference profiles will narrow consideration sets consider- ably, perhaps even rendering that marketing metric irrelevant. As a result, awareness and trial will shift from marketing channels to lifestyle events in which sampling and virtual experimentation are woven into the entertainment. Trust will be distributed and secured from the bottom up by community con- sensus, not from the top down by authority or heritage. Reputation will be tracked by real-time ratings that can be accessed in the moment by personal-assistant algorithms. With the Uber-All Economy comes a new value proposition that has social ramifications beyond the consumer marketplace per se. The nature and meaning of work will be most affected, which may be the most hopeful aspect of this economic transformation. If everyone is embedded in a social context fundamentally grounded in service relationships rather than in the manufacturing and marketing of goods, V OLUME 20, N UMBER 3, W INTER 2016

9 F ALKER J. W 390 S MITH then networks of connection and contact will be a more pervasive part of life, rekindling community and nurturing relationships, long known to be the most profound sources of happiness and satisfaction with life. References Cowen, Tyler. 2013. Average Is Over: Powering America beyond the Age of the Great Stagnation . New York: Dutton. Frey, Carl Benedikt, and Michael Osborne. 2013. The Future of Employment: How Susceptible Are Jobs to Computerisation? Oxford: Oxford Martin School, Programme on the Impacts of Future Technology and Programme on Technology and Employment, Oxford University, September 17. At http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_ of_Employment.pdf. Miessler, Daniel. 2015. The Real Internet of Things. Blog, May 9. At https://danielmiessler .com/blog/real-internet-of-things/. T HE I NDEPENDENT R EVIEW

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