In 2014, estimates suggested that PC makers controlling an aggregate of 60% market share (HP, Dell, Lenovo, Acer and Asus) made an average of less than US$ 15 operating profit per PC sold or less than 3% operating margin. In the same year Microsoft reported net income of $22 billion or a net margin of 26%, the largest part of which came from Windows and Office sales and licensing. Following the introduction of smartphones and tablets, the PC industry had been struggling and analysts suggested that this was due to a value trap, a combination of slumping sales, commoditization and the fact that PC makers had no way of capturing after sales revenue streams. This trend continued into 2015, however Apple was bucking the trend, increasing shipments and sustaining margins of the Mac.
In a similar yet different vein in a 2016 article in the Harvard Business Review (HBR), the authors noted that while in 2007 the five major mobile-phone manufacturers of the time -Nokia, Samsung, Motorola, Sony Ericsson and LG- collectively accounted for 90% of the industry’s global profits, by 2015 Apple through the iPhone singlehandedly generated 92% of industry profits. By Q3 2016 that figure had risen to 103%. In the same period Samsung generated less than 1% of industry profits while both LG and HTC posted losses. Other competitors such as Nokia, Motorola and Research in Motion, the purveyor of the Blackberry, had been crushed. What is more, Apple produced these results on the back of only 14% market share. The key difference to the PC case was that the market was growing fast.
The companies that Apple was competing against were world class: strong brands, excellent operations, high product quality and differentiation, big R&D budgets and favorable regulation. In contrast, when Apple brought the iPhone to market it had zero market share, 4% market share in desktop operating systems and while the iPhone’s design was sleek, it should not have been particularly threatening nor was it something that could not be reverse engineered and imitated if necessary.
What really explains the poor profitability of the other PC and smartphone manufacturers is that they had come up against platform business models and in these cases products, usually though not always, lose.
Platforms have been around for a long time in different guises -think of a town market or a shopping mall which bring together customers and sellers of consumer products- and have different forms (one-, two- or multi-sided). However, ubiquitous computing and the internet have allowed them to proliferate profusely and have increased the market power of the platform provider.
In relevant generic terms, a platform is a computing environment (hardware and/or software) in which applications may be run. Practically it means a set of tools, services and Application Programming Interfaces (APIs) that must be used to build applications and access data. There are many types of platforms from operating systems such as Windows or Linux to the internet itself to many things sitting on top, including, for example, social media platforms such as Facebook or Linkedin -they can be built on top of each other, serving as each other’s building blocks. One category are transaction-based platforms such as e-commerce (of different types) and payment platforms, platforms for financial services, and diverse others. These have market place characteristics in that third-party suppliers (of products, services, know-how, finance etc.) transact via the platform with customers. The platform facilitates or “orchestrates” the transactions and collects a fee or commission.
In today’s world, platforms are highly relevant and very disruptive. The fact that Microsoft and Apple (though with different strategies) operate platforms led to their accumulating immense market power and dominating their broader industries, accounting for very large shares of industry profit pools, something not usually seen in competitive markets. Due to their economic characteristics, particularly so-called network effects, platforms that win out (and they do need to be well managed) confer monopolistic power to their owners. With that comes pricing power and the ability to shape the industry. Let’s look at another example, this time from mobility services, namely the fast-growing ride hailing industry and the company Uber, one of the pioneers of the space (others include Lyft (US), Didi Chuxing (China) or Grab (SE Asia)). Uber brings together customers who want a ride with drivers with vehicles willing to take them to their destination for a fee. The economics are attractive and straightforward and the first industry to be disrupted and undercut in price was taxis: The taxi industry is regulated (usually by cities) and supply is controlled (limited), leading to higher prices than many potential customers would be willing to pay as well as less than optimal availability, particularly in times of peak demand. Uber drivers used their own vehicles (which were already used privately, depreciation therefore only partly entered the cost calculations) and surplus time to supplement their income (therefore did not expect high compensation) making the service ultra-competitive. As a result, taxi revenues in Boston have declined 30%, and taxi medallion (transferable licenses) prices in New York have dropped 80% in four years. The competitiveness of the platform attracted many customers and the increasing number of customers (therefore the potential to earn income) attracted increasing numbers of drivers, continuously improving the availability and reliability of the service in a self-reinforcing positive feedback loop. This is a good example of network effects in action with the platform becoming more valuable the more people (customers and drivers) joined. Network effects are also called demand side economies of scale because the benefits to users -the source of demand- grow as scale increases. And having built the basic platform infrastructure, the additional (marginal) cost to Uber to add another driver or another customer was negligible, allowing massive scaling in each local market, nationally and globally. Once scale was in place, platform functionality could be expanded and operations optimized further, based on huge amounts of data Uber has the possibility of collecting. Using data analytics, Uber can predict demand with significant granularity and can tactically pre-deploy drivers in right numbers at right locations and routes. It can implement revenue management techniques to maximize price for trips given prevailing conditions (time of day, weather, events, traffic) and incentivize additional supply to ensure availability when needed, while maximizing fleet utilization. It can develop and deploy advanced navigation systems to help drivers minimize travel time (avoid congestion), enhance safety and reduce cost (by guiding drivers to lowest price refueling options). Furthermore, it can develop additional services or variations (e.g. Uber Pool, where a driver can pick up additional customers going in the same direction and incentivize customers to use the service while earning a higher aggregate fee). And it can segment customers in many different ways and further refine its services to ensure customers are locked-in. On top of all of this it can fully automate back-office processes to ensure high efficiency and gain from supply-side scale economies.
This all is fairly straight-forward. Customers have benefited from high availability of mobility services at low cost (generating substantial consumer surplus) and competing traditional services, including taxis, limousines, even, in some cases, local public transport, have been disrupted and out-competed. However, the really interesting issue is not that Uber and others are out-competing taxis, but what impact they are having on the automotive industry.
As ride-hailing proliferates, some customers in urban centers are starting to ask why they need to own cars at all. Initially this was not just about cars: In a 2012 presentation, Goldman Sachs asserted that millennials are interested in access not ownership. This applied to music, luxury goods and other items and assets as well as cars. But in the meantime, it seems that not just digitally native youngsters are turning away from car ownership, even driving. In a study from 2015, University of Michigan researchers found that the percentage of people up to 55 years of age holding a driver’s license in the US is declining and has been doing so for years, though it is especially pronounced for younger people. In 2014, just 24.5% of 16-year-olds had a license, a 47% decrease from 1983. The decreases are inversely proportionate to age and among adults, the declines are smaller but still significant -16.4% fewer 20-to-24-year-olds had licenses, 11% fewer 25-to-29-year-olds, 10.3% fewer 30-to-34-year-olds, and 7.4% fewer 35-to-39-year-olds. For people between 40 and 54, the declines were small, less than 5% (though when older people made decisions about drivers licenses far fewer alternatives existed). These declines correlate well with increasing costs of maintaining, insuring and parking vehicles and, of course, the increasing availability of ride-hailing opportunities. When 18 to 39-year-olds without driver’s licenses were asked why they don’t have them the top three reasons were: “too busy or not enough time to get a driver’s license” (37%), “owning and maintaining a vehicle is too expensive” (32%), and “able to easily find transportation from others” (31%). In addition, there is the real issue of vehicle utilization about which people are becoming increasingly aware: Numerous studies have found utilization rates for private vehicles of between 5 and 15% and one study found that vehicles on average are parked 95% of the time. During that time wear, such as corrosion, leads to significant value loss. It is one thing to accept these “deadweight” costs when there is no alternative, quite another when there is.
The question then becomes whether the availability of ride hailing platforms will negatively impact vehicle sales and how and what will happen to auto manufacturers: Will the product mix need to change? Will marketing and sales channels and approaches change? What will happen to supply chains? Numerous studies, papers and articles have debated the problem and have attempted to provide answers, each with different spins, examples:
The Impact of New Mobility Services on the Automotive Industry (2016) – Center for Automotive Research (funded by the automotive industry)
Peak Car Ownership (2016) – The Rocky Mountain Institute (environmentalists)
Demographic shifts shaping the future of car ownership (2016) – Knowledge at Wharton
Automotive revolution: Perspective towards 2030 (2016) – McKinsey & Co.
Of course, at this time nobody really knows whether ride-hailing platforms (eventually over the next few years with autonomous vehicles without drivers, bringing the cost down considerably further) will displace car ownership and to what extent. But if it does, even by the small amount (for example, McKinsey estimates 10% by 2030), many things will change, often quite abruptly:
- More cars will be bought primarily for utility and cost (TCO) rather than design or driving performance -after all it is difficult to differentiate urban car trips significantly
- Car manufacturers will need to reduce capacity. How will this affect their cost structures?
- More customers (mobility service providers /ride hailing platforms) will be fleet buyers using sophisticated procurement methods, with large negotiating and purchasing power and may operate their own services and maintenance.
- Digital tools and services designed to improve vehicle utilization, availability and safety, reduce fuel consumption, increase revenue generation, and reduce operating cost will proliferate.
- Mobility service providers will compete on price, comfort and additional offerings and will try to increase customer retention by offering rebates, loyalty programs (frequent travel cards?) and other benefits (digital media services?) to customers.
- The car insurance market will be disrupted
- Some platforms may be open (for example to investors in vehicles or to third party service providers), others closed
The structure of the industry and the basis of competition will change. According to McKinsey:
“While other industries, such as telecommunications or mobile phones/handsets, have already been disrupted, the automotive industry has seen very little change and consolidation so far. For example, only two new players have appeared on the list of the top-15 automotive original-equipment manufacturers (OEMs) in the last 15 years, compared with ten new players in the handset industry.
A paradigm shift to mobility as a service, along with new entrants, will inevitably force traditional car manufacturers to compete on multiple fronts. Mobility providers (Uber, for example), tech giants (such as Apple, Google), and specialty OEMs (Tesla, for instance) increase the complexity of the competitive landscape. Traditional automotive players that are under continuous pressure to reduce costs, improve fuel efficiency, reduce emissions, and become more capital-efficient will feel the squeeze, likely leading to shifting market positions in the evolving automotive and mobility industries, potentially leading to consolidation or new forms of partnerships among incumbent players.”
This sounds very much like the value trap PC and mobile phone manufacturers encountered some years ago. But again, it isn’t really. It is the fact that products have significant difficulty competing with platforms, once the conditions for “platformization” of an industry are ripe. The changes may be profound, even if the total mobility market, including vehicle sales grows rapidly (displacing, for example, local public transport). Cars per se may increasingly be viewed as interchangeable, i.e. more like commodities. It may well be that electric vehicle batteries and the associated infrastructure is sold separately from the cars by specialist providers. Or that digital services and the necessary vehicle integration are performed by other specialists (Apple, Google, Amazon, IBM and many others come to mind). Auto manufacturers may then lack the market power to resist such developments which will squeeze margins and remove them from close contact with customers.
In any case the growth rates for On-Demand mobility can be considered disruptive.
And as we have observed in another article, the projected disruption impact has alarmed the automotive industry to such a degree that now virtually every major company has either invested in an existing carsharing / ride-hailing operator or is building these capabilities in-house. The urgency is also because first mover advantage can be highly significant with platforms if they can achieve customer lock-in. Facebook, for example, has a 70% market share in social media platforms, Google 80% in search and Amazon 43% in online sales. Such market shares are very rarely found in competitive product markets.
How the disruption will play out in the automotive industry is unknown, but as we noted previously:
… whether car manufacturers can be successful service providers is far from certain. Such a change in the business model requires radical changes in the ways they operate. The investment required and the complexity of car manufacturing has hereto erected barriers around that business. But a business based on infrastructural technology (software) has different rules. Furthermore a service business depends on constant engagement with customers, ability to manage ecosystems and crunching large quantities of data. If car manufacturers do succeed it will be quite unprecedented.
In addition success depends on positioning. If the vehicle gets commoditized, vehicle margins will decline. In addition some capacity may become idle (as demand for new cars declines). In that case a huge underutilized manufacturing operation and the ability to supply vehicles becomes a liability rather than an asset. Service companies unencumbered by huge manufacturing assets might make the running, for example managing a service platform and an ecosystem that integrates cars, buses, trams, trains, bicycles and anything else available and supplied by third parties at low cost.
We have seen how platforms can disrupt, even upend industries by changing customer preferences and commoditizing products. When products come up against platforms, the economics are stacked against them and they can seldom win. The question that needs analyzing now, is can this happen in industrial B2B product and service markets. We’ll look at this in the second part of this article.
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