Analysis Of The On-Demand Shared Mobility Value Chain

In the previous post I described a new value chain that will connect companies providing on-demand personal mobility services and three emerging models for this value chain. This value chain is the result of the consumer shift from a car ownership-centric transportation model to a hybrid model that blends car ownership with vehicle access through a combination of on-demand mobility services and public transportation. It is also based on the stated intent by the providers of certain of these services to adopt Autonomous Connected Electrified (ACE) vehicles. Various acquisitions, partnerships, including the recently announced partnerships between Waymo and Avis, and Apple and Hertz, and investments by automotive industry incumbents and by companies offering, or intend to offer, on-demand mobility services point to new ecosystems that will be developed around this value chain. In this post I provide a deeper analysis of the emerging value chain and explore investment opportunities in startups that will participate in it.

In my book The Big Data Opportunity In Our Driverless Future I identify two distinct value chains that have been established because of the car ownership-centric personal transportation model that has been dominant for the past 70+ years: the vehicle manufacturing and sale value chain, and the vehicle use value chain. The fleet-based on-demand shared personal mobility value chain (presented in the previous post) is an emerging third and is the result of the growing adoption of shared personal mobility. Participants in this value chain must have expertise in one or more of the following areas: 1) Vehicle Design and Manufacturing, 2) Fleet Acquisition, 3) Fleet Operations, and 4) Fleet Servicing and Maintenance.

It is important to analyze and understand this new value chain in order to:

  1. Establish where short- and long-term economic value exists, where it is decreasing, and where it can be created through the development of new solutions and business models. For example, controlling the Autonomous Vehicle Operating Platform will be very important and could provide long-term value similar to that accrued by Microsoft and Apple through their dominance of personal computer operating systems. This is the reason Intel acquired MobileEye. Through such analysis we can also distinguish where opportunities exist for startups and where for large corporations, including incumbents.
  2. Determine how transportation incumbents, and particularly automotive industry incumbents, will need to reconfigure their existing businesses, and what types of new businesses they will need to set up in order to fit into the new value chain. Through such analyses one can identify the opportunities for incumbent disruption. These areas will experience margin compression in the process becoming unattractive businesses. For example, cost-effective, small-batch vehicle manufacturing will become an extremely important area of expertise. Fleets offering on-demand shared mobility services will require vehicle designs that are customized to the service offered and to the location where it is offered.
  3. Identify opportunities for new partnerships, investments, and acquisitions to expand the ecosystems being formed in each part of this value chain. For example, could venture investors receive a quicker ROI by funding startups developing autonomous vehicles for on-demand shared personal mobility, or autonomous trucks to be used in long-haul logistics?
  4. Appreciate the complexities associated with global deployments of next-generation vehicles (financing, insuring, managing, maintaining, etc), many of which will be electrified and autonomous, and be in a better position to craft strategies for such deployments.
  5. Measure the impact of other industries on this value chain. For example, the impact on the energy, utilities, financial services, and insurance industries is expected to be positive, while the impact on car dealers, parking garages, and repair shops is expected to be negative.

In this analysis we consider four types of companies that in these early days have shown that want to play a leadership role in the emerging value chain: incumbent automotive OEMs, e.g., BMW, Tier 1 Suppliers, e.g., Delphi, Transportation Network Companies (TNCs), e.g., Uber, and Internet companies, e.g., Google/Waymo. Table 1 summarizes the types of expertise these four company types possess. It also shows the actions these companies are taking in order to either supplement their expertise, or start to establish competence in particular areas. Because of the important role the Autonomous Vehicle Operating Platform, the UX Platform, and Big Data and AI play in this value chain we break then out as separate rows in the table.

OEMs Tier 1 Suppliers TNCs Technology Companies
Vehicle Design & Manufacturing x
Autonomous Vehicle Operating Platform Started development & acquisitions Started development & acquisitions Started development & acquisitions Started development & acquisitions
UX Platform Infotainment only Today using smartphones Started development
Fleet Creation
Fleet Operation Reservations, ride management
Fleet Service & Maintenance
Big Data & AI x x
x strong capability
≈ some capability

Table 1: The areas of expertise among four types of companies participating in the fleet-based on-demand shared mobility value chain

Companies of all four types are developing complete Autonomous Vehicles Operating Platforms. Incumbent and newcomer automotive OEMs, such as BMW, Tesla, and Nio. Tier 1 suppliers such as Delphi, and Bosch. Internet technology leaders such as Google/Waymo, Apple, and Baidu. TNCs such as Uber, Lyft and Didi. Others are developing specific layers and partner in order to create complete platforms. For example, Mercedes and Bosch have partnered to jointly develop an Autonomous Vehicle Operating Platform. OEMs such as GM and Ford have acquired such Platforms (Cruise, and Argo respectively).

Corporations such as Audi, Tesla, SiriusXM, Samsung/Harman, Google and Apple, as well as many startups, e.g., Mojio, are developing either complete UX Platforms, or individual layers of this platform’s stack.

Within the next 5-10 years we will see increasingly larger scale deployments of next-generation vehicle fleets to provide on-demand shared personal mobility services. Today we are in a period of broad “experimentation.” During this period, we are seeing growing internal development efforts, investments in startups, acquisitions of startups, as well as conventional and unconventional partnerships around innovative technologies and business models. For example, for the time being, Waymo incorporates its Autonomous Vehicle Operating Platform in FCA’s minivans. Uber has ordered Volvo vehicles where it will likely incorporate its own Autonomous Vehicle Operating Platform. BMW has invested in a variety of startups from Zendrive (driver analytics), to Ridecell (fleet management), Moovit (multimodal transportation reservations), and Chargepoint (electric vehicle charging stations) among several others.

Companies that want to participate in this value chain, and more specifically companies that want to have a leadership role, must make strategic decisions. As we see in Table 1, each of the company types that are actively working on offering on-demand shared personal mobility services is missing key areas of expertise. These companies must determine which areas of expertise they will need to develop and which to access through partnerships, investments, and acquisitions.

Car rental companies and airlines offer important expertise areas

Car rental companies, and airlines could provide key areas of missing expertise and become important participants of the new value chain. More specifically, car rental companies offer:

  • Expertise on acquiring vehicle fleets (they order about 2M new vehicles every year from OEMs). However, despite the large number of vehicles they order they are still not able to customize the body or cabin of the vehicles they order because of the automotive industry’s scale-based manufacturing model and the pricing pressures it imposes.
  • Expertise with direct-to-consumer marketing and sales. In particular, they know how to acquire, retain, and upsell to consumers. Their experience in operating loyalty programs for many years is extremely pertinent and useful for fleet-based on-demand mobility.
  • Expertise of how to manage, service, and maintain such fleets over many locations. This, of course, doesn’t mean that the fleet management software systems rental companies already use will be sufficient to address the needs of on-demand mobility fleets. These systems were developed for the management of vehicles that are rented for one or more days at a time and not for vehicles that are used on a per ride or per minute basis. New software will need to be written from scratch, presenting opportunities for startups like Ridecell and Bestmile.
  • The physical locations to park, service, and maintain vehicles, as well as offices and call centers to provide services to consumers.
  • Global reservation systems. As next-generation mobility services companies move to offer multimodal transportation, they will need to augment their mobile platforms with multichannel reservation systems similar to those currently used by car rental companies. Car rental companies have long experience in this area even though their existing systems will need to be expanded to deal with the type of reservations mobility services companies require.
  • Three important types of data. First, customer data from their reservation and loyalty program systems that can augment the data collected by other companies in the value chain. Second, vehicle performance data from each vehicle in their fleet (past and present). This data will be particularly useful initially as companies deploy their autonomous vehicle stacks on conventional rather than electrified vehicles. Third, car rental companies can equip their vehicles with sensors to enable them to capture driving environment data (traffic infrastructure data, data about objects that can impact the operation of an autonomous vehicle, e.g., trees, barricades, pot holes, etc.) from every mile they travel.  This last type of data can be used to train the AI systems employed by autonomous vehicles but also to keep the various predictive models updated. It can also be used for keeping updated the high-definition digital maps utilized for the navigation of such vehicles.

Similarly, the companies that are part of the fleet-based on-demand ground mobility can learn a lot by understanding the commercial air transportation value chain and its various processes. That value chain consists of:

  • Aircraft manufacturers, like Boeing and Airbus;
  • Aircraft leasing companies, like GE Capital Aviation Services, AerCap, and  Avolon, that create fleets;
  • Airlines, like United and American, that operate fleets of aircraft; and
  • Fleet management and maintenance companies, like Lufthansa Technik, Aviall, and Timco Aviation Services, that take care of each aircraft in a fleet both after each flight, as well as when an aircraft requires more extensive maintenance.

While many of the similarities stop at this high level, many others, such as aircraft uptime optimization, aircraft selection to serve a specific route (or routes), route optimization to increase revenue-miles, and per seat price optimization, carry to lower levels of the value chain and will be the topic of a future piece.

Airlines possess expertise with:

  • Direct-to-consumer marketing and sales expertise which they use in ways similar to the car rental companies. They were early adopters of customer loyalty programs and associated systems.
  • Using regional partners, and their fleets, to service certain types of shorter-haul flights to less popular destinations. The regional partners are responsible for the maintenance of their fleets. In this respect, larger airlines behave in a manner that is similar to that of the ride-hailing companies that utilize privately-owned vehicles.
  • Global reservation systems that are similar to those of car rental and hospitality companies. They have also linked their reservation systems with those of companies that can help them provide complete transportation experiences such as hotels, car rental companies, and others.
  • Big data exploitation which, like in the case of car rental companies, they employ in many aspects of their business such as customer demand generation, price optimization for the maximization of revenue-miles, and many others. They also have significant expertise in the use of data in fleet leasing, insurance, operations, and management. It is interesting to note that airlines have better big data exploitation and insight generation capabilities than car rental companies.

Table 2 summarizes the areas of expertise car rental companies and airlines contribute to the fleet-based on-demand shared mobility value chain.

OEM Tier 1 Suppliers TNC Tech Company Car Rental Company Airline
Vehicle Design & Manufacturing x
Autonomous Vehicle Operating Platform started development & acquisitions started development & acquisitions started development & acquisitions started development & acquisitions
UX Platform infotainment only today using smartphones started development
Fleet Creation x x
Fleet Operation Reservations, ride management x x
Fleet Service & Maintenance x x
Big Data & AI x x x x
x strong capability
≈ some capability

Table 2: Areas of expertise contributed by car rental companies and airlines

Both car rental companies and airlines have long experience and know-how addressing transportation regulatory issues and dealing with federal, state, city and international governments regarding such issues. This experience will be extremely important while establishing the right next-generation mobility services and in addressing existing government regulations, as well as provide input to new regulations being considered by various governmental entities.

Finally, both car rental companies and airlines may have an extra incentive to enter into such partnerships because they feel pressure to get into higher-margin businesses. Both industries have been financially disappointing to their investors. Corporations in these industries have tried to improve their financial position through acquisitions. However, thus far they have not been able to demonstrate that such acquisitions improve the characteristics of their low-margin businesses, or that they can get into new, high-growth, and high-margin areas on their own.

While estimates (here and here) vary greatly, investment banks estimate the next-generation mobility market in the hundreds of billions of US dollars. Sensing the size of the market opportunity, automotive OEMs, Tier 1 suppliers, global TNCs, and large Internet conglomerates are already working to stake their positions in the emerging value chain. In addition to internal product and mobility solution development these companies are aggressively acquiring, partnering, and investing in established companies and startups. Table 3 below provides some examples of this effort to work across this value chain, using models I previously described.

Waymo Baidu BMW GM Lyft
Vehicle Design & Manufacturing FCA Chery, SAIC, BYD, BAIC, Ford BMW, FCA GM, SAIC GM, JLR, Ford
Operating Platform Waymo Baidu, NIO, Bosch Intel Mobileye Cruise Waymo, Baidu, Nutonomy
UX Platform Waymo Baidu, NIO BMW, (Zendrive) Lyft Lyft
Fleet Acquisition Avis TBD ReachNow Maven GM/Maven
Fleet Operation Avis TBD ReachNow TBD GM/Maven
Fleet Service & Maintenance AutoNation TBD TBD TBD TBD
Big Data & AI Waymo Baidu TBD OnStar Lyft

Table 3: Examples of how various corporations work across the new value chain

Even though I maintain a large database of all the relevant companies, their acquisitions, partnerships, and investments, the information in Table 3 is not meant to be exhaustive. For example, companies like Daimler, Delphi, and several others have not been included even though they are active in this value chain. Nonetheless, we can draw several conclusions:

  1. Between the information presented in the previous post and the information presented here, one can see how incumbents are experimenting with both next-generation vehicles and next-generation mobility services as they are trying to determine the role they want to have in the driverless future. It is also clear that not every incumbent automaker, Tier 1 supplier, large TNC or technology company would want to have a leadership role across the entire mobility value chain, e.g., Honda.
  2. Large companies are willing to experiment with startups but also with other large companies. For example, BMW has invested in and experimenting with several startups, e.g., Zendrive. Many of these experiments will remain small scale and will not be followed by larger deployments, even if they receive oversized publicity; a fact that startups should keep in mind as they consider business relations with large corporations.
  3. Large corporations have not figured out all aspects of this value chain, as demonstrated by the TBD entries in the table. They may only be able to reach decisions after costly experimentation.
  4. During this period of intense experimentation we will continue to see ambivalence leading to hedging, as demonstrated by what Ford is doing regarding mobility services with Lyft as well as on its own , what Lyft is doing regarding Autonomous Vehicle Operating Platform (Waymo, Nutonomy), and Baidu is doing about vehicle design and manufacturing (Chery, SAIC, BYD, BAIC, Ford).

The pace of activity around the new fleet-based on-demand personal mobility value chain will remain high for the foreseeable future as ACE vehicles move from experimentation, to larger scale trials, and ultimately to commercial deployment. Companies, including startups, which want to be part of this value chain, must clearly understand where their expertise and intellectual property will provide them with the best possible and enduring advantage. In the process they will need to establish a clear strategy about where and how much to invest, at what pace, who to partner with, and which company to acquire or be acquired by. The establishment of the right strategy will be particularly critical for companies that want to become market leaders in next-generation mobility. Many of the areas that today witness an investment frenzy will take longer to mature requiring more capital than originally expected. Others may ultimately not prove as strategic as initially envisioned. A third category may emerge as more strategic and critical than thought of today. During this early period, the larger corporations will continue to experiment with as many alternative strategies, technologies, and business models as possible. Startups and their investors will need to keep this in mind as experimentation should not be confused with scaled deployment.

The next article in the series

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