Driverless Electric Cars as a Service – One Adoption Scenario

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Self-driving Uber vehicles are lined up to take journalists on rides during a media preview at the company’s Advanced Technologies Center in Pittsburgh earlier this month.

As I ponder the changes that driverless cars will cause across our societies, one of the difficulties is trying to understand what the speed of adoption might be. That is because speed of adoption has huge consequences on the levels of disruption that will occur. The speed of adoption linked into all sorts of factors including:

  • Production bottlenecks in the supply chain such as raw materials, and battery supply.
  • Production capacity for manufacturing of electric driverless cars.
  • Technical issues in achieving true Level 5 automation (think no steering wheel).
  • Political and legal issues around liability and insurance.
  • The balance between the numbers of cars in personal ownership, and the number owned by big companies providing transport services (think Uber/Lyft/Didi and new entrants like Waymo).

 

In turn these factors will be affected by the business models and strategic thinking of the major players. This includes car manufacturers, car ride companies, and governments.
The competition is going to be brutal. Existing car companies will be going up against each other, and new competitors. The new competitors include car ride sharing companies, and new car manufacturers.

Some of the major problems in implementing driverless electric cars as a transport service can be largely solved by car ride companies. The problems include the following:

The Initial Scale/Network Problem

The problem if you want to offer transport as service is you have to get to scale before customers will even contemplate using your service. You cannot put 100 cars on the road and say here I am. This is like the network problem of the first fax machine but on a much larger scale. Who buys the first fax machine? You might buy half a dozen of them so you can communicate between distant offices of the same company. The real value comes when it is a standard system adopted by many people. The problem with transport as a service is that it is much larger. The reality is that people will not use your service until they can consistently get a car in a reasonable time frame to take them wherever they want to go. That needs massive scale and is the reason why Uber was so aggressive in recruiting drivers in target cities. They needed a critical mass to drive customer demand.
A new entrant with electric driverless cars can provide this service but they will need a lot of cars. If you need 100,000 vehicles at peak time in Melbourne (where I live) to supply that service it requires a lot of capital. If the cars cost $50,000 each it is going to cost you $5 billion just for the cars.  That is apart from the costs of the platform to run the system, plus the initial trading losses that will be incurred before breaking even. Not many organisations will have that sort of money, and that might just be for one city. Waymo or Apple might be an exception given the masses of cash that they have. The existing car ride companies got around this problem by using other people’s cars. Difficult to do that for driverless cars although we will explore a model for that in a later post.
The existing car ride companies (Didi, Lyft, Uber, etc) are already at the scale needed to supply the services for their existing customer base. Adding driverless electric cars into that service is somewhat analogous to the electricity grid. Once the standard utility service is in place (think poles, wires, plugs and standards for electricity, and roads and traffic systems for cars) you can make additions as long as they fit the system. You can add a new coal generating plant, or a new gas plant, or new solar capacity and power comes out at the socket. My desk lamp does not care how the power was generated. In the case of a car ride service as long as the customers accept a driverless car you can put that into your system alongside your existing fleet. You may need to drive (sic) demand by offering discounts for the driverless vehicle to get people past their first stages of discomfort. In my case the safety factor is likely to be the key initial driver for change but I am an outlier.

The Capital Problem

If you are a company that wants to supply transport as a service you will want to scale as fast as you can. Ideally you will offer a service in 50 cities in the first 3 – 5 years. If we assume that takes 100,000 vehicles in each city and each car costs $50,000 you now have a cost of $250 billion. If you add in technology platform costs , and initial losses you might have to find $350 billion. That is a lot of coin in anyone’s language. Even if the required vehicle numbers are much lower it is still going to be a massive capital investment.
Even if you don’t move that fast you will have to make large bets in the target cities where you first invest.
If you are a car ride company you can scale by steadily adding cars to your existing services in all those cities. That should have the effect of reducing your costs, and improving your bottom line at a much slower capital burn rate. You can also play a much more agile strategic game. If you perceive a threat in a particular market you can scale faster in that market and slower in other markets. If adoption rates are faster in one city you can rapidly scale up volume in that city by slowing each of your other markets just a little.

The Technical Problem

The technical problem is getting to level 5 automation as soon as possible. Level 5 automation is when there is no driver required in any location or conditions. Any driverless car company will have to convince the regulatory authorities of safety at level 5.  The existing ride companies have an advantage here. They already have masses of data on the travel their existing cars undertake. They can also start with say 100 driverless vehicles within their existing service. That will consist of testing them in real conditions with paid drivers in the vehicles. While a lot of advances in driverless car systems are being made using computer simulations nothing fully substitutes for real world data. Especially for politicians and for regulatory authorities.  That real world data can then be fed back into simulation systems to gain an advantage in simulation programs

Existing car ride companies are the most likely path to adoption of driverless electric cars. These types of cars provide significant reductions in the cost structures for car ride services. This means that if they sit on their hands someone will come along and blow their existing services out of the water. The car ride companies have the competitive imperative to go down this path. They also have some significant competitive advantages in executing the strategy. That does not mean they will be successful, just that they have a head start.

In our next post we will take a closer look at some of the players, and the tactics that might be involved.

I am writing a book on autonomous vehicles with Dr Chris Rice from Texas. It is called Rise of the Autobots: How Driverless Vehicles will Transform our Economies and our Communities. Stay tuned for more excerpts as we finalise the book.

Note: Featured image is from NPR

 

 

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Veterinary Schools as a Platform (VSaaP)

Late last year we worked with the Australian Veterinary Board Council and the Deans of all the Veterinary Schools in Australia and New Zealand looking at what the future of veterinary education and regulation might look like in 2031.  The date was chosen to be the time when a 12 year old just starting secondary school now would be a graduate of 2-3 years standing. We looked at a whole range of issues including availability of smart phone based diagnostic kits for pet owners, artificial intelligence systems for diagnosis, urban densification and its effects on pet ownership, veterinary practice corporatisation, international trade requirements, and the need for wide or narrow scope veterinary degrees.

One of the ideas that emerged from the process has stuck in my head and I think has great scope to revolutionise how we provide a much wider range of education at universities and for education post graduation.

Essentially the is one where  the veterinary school acts as the primary site of education for those subject areas that need face to face contact and technical expertise that cannot be achieved in an online, video, or virtual reality environment.

All other subjects/modules are accessed by the students via the school platform and the teaching material and processes that form the basis of those modules can be supplied by any accredited service across the globe. The model looks like the following diagram if we just look at one module, in this case cat medicine at the vet school at the University of Melbourne:

Vet school as a platform image

On the supply side of the platform (above the line in the diagram) cat medicine courses are supplied by all the possible services globally that wish to provide that service and who are able to meet the curriculum needs.  The platform would be agnostic on delivery systems as long as outcomes where met.

On the demand side (below the line in this diagram) each student in this model can choose who their supplier of education in cat medicine is. In the picture above Isabelle has chosen Sydney University because they have a great reputation but also provide face to face services at the school in Melbourne. Ivy and Anne have chosen Seoul National University because they have a great reputation and their virtual reality applications suit their learning style and they have been offered lifetime professional development at a low cost as part of  the deal.

The school accredits multiple providers from interstate and/or overseas for each module (the school itself can provide modules in competition with these modules if it desires). Students can choose the best provider for the module or subject they wish to complete.

Competition on the platform fosters innovation in teaching content, support and methodologies that best meet the student’s needs.

Collaboration may occur between schools with centres of excellence formed to compete with international providers. E.g. Sydney University could be the cat medicine centre of excellence that allows economies of scale to be achieve on content creation and methodologies (for example virtual reality technology is still quite expensive but spread over 1000 students the costs come down).

Uncertainty about the future education and information needs is dealt with by the system working as “plug and play” with new subject matter being able to be added as flexibly as possible, and many providers producing a much larger resource base. This should allow more rapid adoption of new content as the world changes (e.g. big data systems/network facilitation for clients with home diagnostic tests).

On top of the pre-registration process it could also be used for post registration professional development with or without limited degrees. Currently vets have to learn and qualify across a massive range of animal species but many go into small animal practice and never see a cow, sheep, or pig again. Shorter narrow species based degrees could be supplemented by post graduation systems that allow vets to qualify in other areas if they wish to change careers or specialties.

By taking advantage of education technologies to improve the efficiency and quality of education a school as a platform system. There are multiple advantages to this beyond what has been discussed above:

  • The time and costs of delivering some content can be reduced.
  • Greater value can be created in other areas by increasing the time and resources applied to the teaching of those areas.
  • Self paced degree systems could be put in place where the pace of learning is determined by the student rather than the needs of the lecturers or the school.

Regulatory/Accreditation issues could be relatively straightforward if the existing schools are accredited and the content partners are required to meet content and/or competency based assessments. Combined with limited degrees, intern models, etc. the issues can become quite complex. The accreditation process itself may need to become more flexible and capable of responding faster to changes in technology.

Technology in delivery of course and maximising flexibility in systems is rapidly advancing. For example the University of Texas has a major collaborative project going on with Salesforce:

UT System partners with tech industry leader to develop next-generation learning platform

The future is coming faster than we think and it has the potential to radically change education models.

 

Are we entering a world of the new portals?

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Yes we are, and it has serious possible consequences for a whole range of businesses.

Gather around children for a story when grandpa was young (in internet years anyway). Once in the deep dark history of the internet portals were all the rage. They were the place that companies hoped you would use as your stepping off point into the internet. If you were part of their portal and had it set up as your home page then they could offer you services, and make money from you being there rather than you wandering around on your own. Truly capable search killed off a lot of these efforts by allowing people to more easily find what they were looking for although portals still make sense in a number of areas. For example here in Australia the Our Community organisation which supports about 80,000 community organisations has a grants portal (Our Community) which aggregates all of the grant information across the country. Essentially it provides a specialised aggregation and search service. The government also offers a portal called myGov which aggregates a range of government services, offering both specialised search services but also common identification and log in systems.

Besides these sorts of services we seem to be moving into a new era of portals based primarily on mobile systems. On March 3rd TechCrunch stated that “Uber plans to turn its app into a ‘content marketplace’ during rides“. I have long believed that Uber is a data and services company with the transport model being an interim stage, and this fits perfectly with that theory (confirmation bias anyone). As a transport company they are in a brutally competitive world. They have already signaled their intention to be in the autonomous car business, but I think that business is going to be an even more brutal fight that will require huge reserves of cash. That fight will include the existing car companies and a host of new competitors and some will inevitably lose, and have their whole business model destroyed. In those sorts of fights technology plays a role but quite often it is a last player(s) standing sort of a fight where people bleed cash until they can no longer operate. In that sort of fight it makes sense to have multiple possible strategies rather than a single win or lose one. If, in the interim period before autonomous cars are widespread Uber can build a huge trove of data and insight for autonomous cars, but more importantly insight into the movement of people, and what they do during and after their trip then they have a separate strategy. If they are not able to slug it out in the transport space then they can supply data and services across the whole sector instead.

A content market place for Uber makes sense. According to the TechCrunch article they now are providing 10 million rides a day and to a large extent those riders are a captured audience for them. They also know in advance where you or I are going and when we will arrive which is enormously useful information. If they know you are going to a shopping centre then businesses at that shopping centre would really like to know that so they can send you offers in advance. If you are going to restaurant area at lunchtime, or an airport the same applies. If they can tie your trip data to what you do after the trip by tracking you through their application and partner applications then the value of the data increases astronomically.

In this new portal era they are the aggregators of customers for other businesses but they are also aggregators of data that increases in value as time goes on. In some ways it is the perfect business – profitable while it is building a new capital asset that is much more valuable.

There are lots of other companies that are pursuing this strategy. WeChat in China now has enormous capacity inside its app that is intended to keep you inside their ecosystem so they can aggregate demand and sell it to other companies ( WeChat is morphing so Chinese smartphone owners will never have to download an app again). Facebook is attempting to copy them while also trying to copy Snapchat and is a huge percentage of people’s mobile we traffic (Benedict Evans).

All of this raises a very serious question. Where will the profit accrue to in this new world? Here in Australia we have had retail dominated by two major supermarkets although this is slowly changing. As a result they  have had the highest retail supermarket margins in the world, which have now crashed back to earth due to competition (see my post: Are The Two Major Supermarkets in Australia Doomed?). Through that time the suppliers of food into the Australian markets have been mostly constrained by having to supply to those two companies in large volumes. If you are Coca Cola or Mars this has not mattered too much but it has mattered to most suppliers (hence the high margins).

The advent of the internet and the capacity to connect to anyone around the world even if you are a one person business was supposed to break some of this  down, to usher in a new age of commerce. To an extent that has been true. However I have been working with a couple of businesses that want to use some of the new technologies to connect directly to the customer rather than going through the major supermarkets as “the agent of the consumer”. One of the key concerns is whether they are swapping one master for another. If they end up with channels going through systems and applications like WeChat or Facebook does the profit accrue to them or the platform, and how much can they rely on the platform continuing to deal with them in a fair and consistent manner. In part that question is answered by platform economics – if the deal does not work for the customers on both sides of the platform then the platform disintegrates. On the other hand if you are not key to the relationship between the consumer and the platform itself it leaves you in a very weak position.

If we use that thinking and go back to Uber then I do not believe that a coffee shop at my local shopping centre is going to have the clout or expertise to efficiently partner with Uber to market specials through their App. It seems far more likely to me that another aggregation platform for coffee shops (and others) will partner with Uber and connect up the systems required to send me a notification of a special as I am on my way, or take my order via the Uber app as I travel . That means if there are three coffee shops at my local shopping centre, and Uber has a significant transport footprint, as soon as one of them has joined up the others are forced to do so or lose customer traffic. In that case none of the coffee shops actually wins because the actual customer levels between all of them are likely to be the same (ignoring any marginal traffic that may come from signalling). However the two aggregators (coffee shops and Uber) are going to want a cut of the action so it is likely that the profit margins of the coffee shops will fall.

So in a world that promised better contact and relationships with customers for small businesses the result may actually be less contact, more distant relationships, and less profits as a result. The advantages go back to the portal holders.

Of course in a modern world there is always the opportunity for the coffee shop to make a direct contact with me when I come to their shop. If they can establish a contact with me via my messaging App of choice (WhatsApp in my case) then they can form a direct relationship. However that relationship lacks a geo-location and proximity/arrival time context so unless my messaging App can supply that then the direct relationship is at a significant disadvantage. It also lacks the sophistication to be able to take my order, so unless another aggregator can link to my messaging app and provide those services the friction of the relationship will be too high. And so the dance continues.

The whole process is complicated by the fact that people actually use very few apps. In theory the coffee shop could have an App that does all these things and connects with me but given the limited real estate on my device and the fact that most people only really regularly use 5 apps that is not going to happen.

It is going to be very interesting to see where all this goes in the not too distant future.

p.s. – for those of you not from Australia the picture is one of Arnotts Tim Tams which one of the major supermarkets tried to force a price reduction on but was unable to do so because of their popularity. Therein lies a lesson. You should try them, they are awesome.

Addendum

An additional point is that this means that the brand reputation issues that are afflicting Uber today are far more important than might be thought. If one of your key strategy pillars is that people need to trust you to share their data with you then your culture, behaviour and leadership become critically important. Because of the network effects of the data collection and utilisation if volume falls in broad terms but data sharing falls more then capital value of the company falls far more rapidly. I am sure that the board is having that discussion with the CEO right now

 

 

Medium, Tumblr and Community Based Business Models

It has been a while since I wrote something here. Life has been getting in the way. However I noticed something form my colleague and friend Stowe Boyd which stimulated me to respond. Over at Tumblr Stowe posted:

Medium becomes more Tumblrish

Hamish McKenzie noted that Medium had become significantly more of a curated experience  in its recent facelift. But I think in his positioning of Medium and Flipboard as two competitors for our attention, he misses something important

He concludes with:

“I find it interesting that Tumblr seems to be changing so slowly — hardly at all — since being acquired by Yahoo. And one of the obvious ways to draw more interest to Tumblr would be the simple avenue of making the curated topics a/ public and b/ better looking. Right now they look like the (relatively unappealing) Tumblr dashboard, and there is little or no room for advertisements.”

“But I have made several of the curated topic feeds — like Tech and Design — a part of my central daily practice. I have not done that with Medium, although I do use Flipboard every day, too”

You can read the whole post by going to: http://stoweboyd.com/post/69485777176/medium-becomes-more-tumblrish

My response to this is:

I am one of the Tumblr tech curators/editors and I am not sure about how I feel regarding advertising on the curated areas of Tumblr. On the one hand I can understand the appeal and like Stowe have made looking at the curated areas part of my daily information practice. I can also understand that the service needs to make money to sustain itself and I am supportive of that as long as it is done in a way that is not intrusive on the reader/community. On the other hand I am somewhat leery of Tumblr/Yahoo making money on top of my voluntary efforts. I would need to balance off that against my view of my contribution to the community and also any value I feel the extra profile of a public and promoted page may do for me and our business.

This is the delicate balance of some of these new business models where the community is producing the product. Too delicate an economic business model may imperil the economic viability of the service, and too intrusive a model may damage the goodwill of the community and therefore make the whole thing evaporate or at least to a level that is non viable. Fundamentally I think that this is easier outside of a large company where transparency can allow the community to make finer grained judgements about the economic model and what it is delivering as long as it is transparent. That is much harder inside a larger company that tends not to publish data on the individual performance of its parts in a way that is clear for everyone to see.

I would be interested in comments.

Paul Higgins