Driverless Electric Cars as a Service – One Adoption Scenario


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




Electric Cars – Saving Real Money or Arbitrage Opportunity?

Electrek has reported an amazing set of numbers on a Tesla S:

A Tesla Model S hits 300,000 miles in just 2 years – saving an estimated $60,000 on fuel and maintenance

The vehicle is owned by Tesloop, a company that offers rides in Tesla vehicles.

A large part of this difference is due to the fact that the car is being used within an area that has extensive Tesla SuperChargers. So all the electricity is “free” (paid for as part of the purchase price of the vehicle). Also parts of the repairs and maintenance were largely paid for under the warranty. The powertrain warranty is for 8 years and includes unlimited mileage. This means that at the same annual usage rate the warranty would cover 1.2 million miles or 1.93 million kilometres.

The key question here is whether Tesla is losing money on this arrangement. If so, the savings are artificially inflated. The answer to part of that question is in the pricing models that Tesla introduced early in 2017. Before that date all Tesla S vehicles received free power on the Tesla Supercharger Network. After that date only the first 400 kWh per year are free. After that you get charged a fee for your power when charging . The fee varies between locations.

So there is no doubt that Tesla has been heavily subsiding the Tesloop operating costs. A smart business move to spot an arbitrage opportunity.

The 400 kWh is estimated to provide power for 1000 miles of driving (1609 kilometres). In Australia the current (sic) charge on the Tesla Supercharger is A$0.35/kWh.( so the energy cost per kilometre of driving is approximately 8.7 cents. This compares to my petrol Toyota Corolla Hatch at 8.1 cents per kilometre (combined urban/extra urban mileage claim of 6.7L/100km and fuel at  121 cents per litre). Fuel efficiency is worse in urban driving but the Tesla Superchargers are mainly for highway travel so that this is a fair comparison.

Two other comparisons bear looking at. In Illinois the charging rate is US$0.15 per kWh. This equals A$0.188 (RBA quoted exchange rate August 30th 2017) and changes the per kilometre cost to 4.7 cents.  Secondly, our current at home shoulder and off peak rates are A$0.1257, which reduces the per kilometre cost to 3.12 cents. Of course we would have to pay for a charging unit as well. If we amortise that cost then the total cost might be 4 cents per km. That is half my current fuel costs, or a saving of about $600 a year on 15,000 km.

If we use 4 cents as a reasonable figure then the cost difference for an electric vehicle travelling 100,000 km a year as a car ride service/taxi is $4,000. That is a significant advantage for an electric share vehicle over a fossil fuel vehicle. That number starts to really add up if you own 20,000 of them in a fleet ($80 million a year).

If we go to the non- fuel car costs. RACQ estimates that the private ownership costs of running a medium sized car in Australia are around 65-72 cents per kilometre. More than 50% of these costs are interest costs (about 8.2 cents) and depreciation costs (about 29.5 cents). Registration and insurance and other on road costs are at about 14.9 cents. This leaves about 7.5 cents for repairs and maintenance plus tyres after accounting for fuel costs. The vast majority of that being repairs and maintenance (median is about 7 cents). In the Tesloop case the scheduled repairs and maintenance costs were US$6,900 for 300,000 miles (482,802 km). This equates to A1.79 cents per kilometre. If we go back to my Toyota which has a fixed price service of A$480 a year then that costs is A3.2 cents per kilometre at 15,000 km per year. The reality is that I drive a little less so the cost is 3.7 cents.

If we go back to the RACQ numbers the Tesla Model S 75 version has fuel costs of 4.73 cents per kilometre. It also has maintenance costs of A8.91 cents. This seems high given the Tesla Loop experience but may just be a function of  the much higher mileage.

The Tesla S is a luxury vehicle and so its costs are likely to be higher than a standard vehicle. Lets look at the Chevy Bolt. In this analysis I have been helped by an excellent article by Steven Sinofsky at Learning by Shipping and Insideevs : Chevrolet Bolt Requires Almost No Maintenance For First 150,000 Miles.

The maintenance schedule (H/T Steven Sinofsky) for the Bolt is:

Chevy Bolt maintenance schedule Sinofsky

Insideevs estimates that if you do the very scant maintenance yourself the cost for maintenance for the first 150,000 miles (241,000 km) is US$150 (yes you read that right) while Steven says:

“Yep you read that correctly, during my entire three year lease there’s nothing for me to do. I never have to go to the dealer” – Steven Sinofsky

So one way or another routine maintenance is very low.

In terms of fuel efficiency the Bolt is rated at 238 miles (383 km) on a 60 kWh battery although city driving has a better range due to regenerative braking, and highway driving is poorer due to a poor drag coefficient.  This results in 6.38 km per kWh and if we use the off peak rate I pay then that is A1.97 cents per kilometre (note Steven was more conservative in his mileage calculations which work out to about A2.39 cents per km using my electricity costs).

This is a lot of figures so as a summary I have made up a small table:

Fuel Costs Maintenance Costs Total
Tesloop Tesla S 0 1.79 1.79
Toyota Corolla Hatch (Mine) 8.1 3.7 11.8
Tesla S (RACQ) 4.7 8.91 13.61
Luxury Vehicle (Ave RACQ) 7.06 10.2 17.26
Chevy Bolt (first 60,000km – but generally representative) 1.97 0 1.97

Now I know that I have not made a fair comparison between the Bolt and the Tesla S. In part because they are completely different vehicles, and because I have only included routine maintenance servicing for the Bolt.  There will be non -routine costs in the maintenance costs. The actual costs of those the owner will be in part determined by warranty systems. The RACQ figures appear to include a capped servicing arrangement with Telstra.

What we can say is that there are significant operating costs for the new electric vehicles, as compared to standard ICE vehicles. Even if we add in the Tesloop Tesla S maintenance costs as an estimate for the Bolt’s costs, the Chevy Bolt’s operating cost for fuel and maintenance is still only 3.76 cents per kilometre, compared to my Toyota costs of 11.8 cents. Even though I have only included my fixed costs servicing which is well below the costs shown in the RACQ figures.
That comparison is also unfair as the costs associated with the Tesla S are high due to its luxury model status. You can see the details of the repairs and maintenance receipts by going to : Tesla Model S Hits 300,000 Miles with less than $11,000 maintenance costs  and registering for their Google Docs page. These include warranty repairs done at no cost. I was unable to reconcile the costs to the article description as some costs appear to be missing but what is in there is in the following table:
Date Item Cost
18/08/2016 Replace 12V battery 171.33
24/10/2016 replace brake pads and rotors 1759.42
4/11/2016 Right Rear Door handle 961.96
21/11/2016 left front door handle 962.18
20/02/2017 wheel liner, rear diffuser, front aero shield, water ingress on headlights 2176.2
7/03/2017 Air conditioner , other pages to receipt are missing 2800.12
15/03/2017 Air conditioner, passenger door handle 656.64
Total 9487.85

As you can see the majority of the maintenance costs excluding the issue with the headlights and brake replacements related to the air conditioner and door handles. Some of these are likely to be costs associated with the luxury/technology parts of the doors, and early model issues. I would expect that costs for a standard production model would be much lower.

The point of all this analysis is work for our book to look at adoption timelines and business models for electric and autonomous vehicles.

In this case it is the headline number of how much it takes to run your car. That is because people get this in their face every week whereas the main costs of finance and depreciation are more removed from their experience. Once we move to the full question of costs we have to look at those more closely. we will do that in the next few days. Then we have to look at fleet options versus personal ownership.

We will do some more sophisticated modelling as we firm up the assessment for the book.

I am writing a book on autonomous vehicles with Dr Chris Rice of the University of Texas Austin. 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.








The Future of Food (and other retailing) : No Advertising?

Technology and information will increasingly determine our consumer product choices and change the way food and other consumable goods are marketed, distributed, and sold

I spoke at the Techspo Conference (Dirt-Data-Droids) in Western Australia last week on the future of agriculture in 2027. In part that future is tied into the future of retailing of food and fibre. On the consumer side I proposed that we are on the verge of a complete disruption of the retailing of food around the world. This will be led by changes in the advertising and distribution model as well as other factors. (see: The Supermarkets Demise – A Scenario which is also linked to an earlier post ). This piece expands some of the thinking in those posts further.

These changes to food retailing will be part of a larger change in retailing. Technology will play a much larger part in determining our purchasing preferences.  There will be two parts to this story.

Firstly, we will move some of our purchasing decisions into the hands of technology in a similar way that Nespresso has influenced the purchasing of coffee. It will be far more sophisticated, and less subject to product substitution by the consumer than the Nespresso process. This will be because the systems will provide complete supply solutions in a way that makes our lives easier. The technology and purchasing will disappear into the background, and it will be too much effort to change them. This will solidify our habits

Secondly, technology developments at the consumer level will facilitate the use of information in a way that has not been possible to date. This will increase the value of influencers. Additionally, new technologies will provide more detailed, and continual information about the products we purchase.
The combination of these two changes will alter the advertising and distribution models for consumer goods.

Jeff Bezos has long been famous for stating that “your margin is my opportunity”.  One of the major margins in consumer goods is marketing and advertising. It is the reason why branded products can sell at much higher margins than home brands. What if Jeff Bezos (and others) can eliminate most of the advertising costs. Statista has estimated that global advertising costs in 2017 will be US$547.37 billion. That is a hell of a margin to take advantage of. Statista has also shown that advertising has been steadily growing. This is happening even while digital advertising takes over from more traditional methods. This means that I am bucking against that trend so let’s look at the logic of how it might happen.

Last week CNET published an article on a concept scanner from Bosch (pictured).


The X-Spect scanner is a combination of two optical scanners. Together they are able to determine which stains are on your clothes, and how they should be washed. It does this by uploading the data it creates from the scanner to the cloud. An algorithm then determines the result which is sent back to the scanner. You can then send the washing instructions to your washing machine. It is not a long leap from that process to Bosch having partnerships with laundry detergent companies. Bosch will recommend, direct order, and deliver three or four varieties of detergent to go with several wash settings. Possibly in partnership with Amazon as a logistics back end. The process of washing your clothes will be: scan, separate into piles, press this button and add this detergent for the first pile, and so on. It is not hard to then imagine that the detergent will come in pods like your Nespresso machine and pressing the wash type button will add the decided detergent. As soon as that detergent type is below a certain level in your machine it will be automatically ordered and delivered to you. You do not care about your detergent type, you care about getting clean clothes. Think about Nespresso advertising. Are they advertising the coffee or trying to get take up of the machines to lock you in?

How Stuff Works says that the average life of a new washing machine is 11 years. If the system as described above works, you will hand over your preference for washing detergent to Bosch for 11 years once you buy the system. You are no longer a viable prospect for advertising for laundry detergent on any media. This adds to the fragmentation of audience that is occurring as media choices widen. If less people in a group are valuable to advertise to then you either target them more specifically, or you come up with an alternative model.

This is an extension of the sort of work that Amazon has been doing on the Amazon Dash Button and the Amazon Wand.  Amazon has been making these products free for Prime Subscribers (around 85 million people) by giving subscribers a credit to the Amazon store of equal or greater value than the hardware price. They are doing this in the same way that printers, and Nespresso machines are subsidised. They are chasing the lifetime value of the customer rather than the hardware margin. This is the opposite of the Apple model where the business is designed around locking you into constant high margin hardware upgrades. In Amazon’s case the prize is much larger than printer supplies, or coffee pods. They attempting to capture most of consumers spending on consumables, and consumer goods.
This sort of change drives changes around the retail market:
  • Direct delivery is determined by the technology. The machine will automatically replace its consumables. The button or wand will deliver products to you at the touch of a button. There is no longer any need or desire to buy these products at a shop. This reduces retail volumes at physical shops.
  • The Wand technology is more complex in that it is seeking to create a wider ecosystem using recipe recommendations. This is because food involves more detailed purchasing decisions. If it is successful then the results are similar – your influences and decisions are tied to the Amazon system and their direct delivery.
  • If advertising spend is reduced then Amazon (and others) can use that margin to compete and/or subsidise delivery systems.
So in a world that looks like this what happens to advertising and discovery?
  • First of all the advertising margin for the consumables could be re-purposed to reducing the costs of the hardware. Just like ink or laser cartridge margins are used to subsidise printers. Imagine a washing machine that can do all the things described above but is cheaper than a current model that can’t.
  • Secondly they could be tied to a leasing arrangement where you agree to a forward contract for consumables. The reduced advertising spend reduces your lease commitments.
  • Alternatively more marketing dollars will be focused at the point of purchase of the hardware.
  • fouthly information and influencers may become more important in these decision points.


If we look at this third point then obviously our decisions on food products can occur without connections to the technology discussed above. But they will still be mediated by technology. The launch of the Apple iPhone X may represent a tipping point here. The new iPhones have been built with augmented reality experiences in mind. We are already seeing some interesting applications using the developer kit. However, the process of pointing your phone or tablet towards an object to use augmented reality is still somewhat clunky.
What we need to remember is that the iPhone is 10 years old this year. If you compare the technology difference between the new iPhone and the original iPhone the changes are stunning. If we extend out another 10 years to 2027 we are likely to see a similar level of technology differences. We may be in the early stages of technology that powers glasses or contact lenses that can perform augmented reality processes. If this comes true then we will see information attached to every object in the world.
So if we look at food and other consumable goods, easily accessed information changes buy decisions. We are not going to dive down into every piece of information that is available every time we buy something. Most of us are too lazy or hardwired into habits to do that. When we look at discovery and trial of new products or an alternative it does matter. In this area information and influencers will be very important. In a shopping ecosystem like Amazon search is vital for discovery rather than advertising. Jeff Bezos does not want people spending on advertising inside the Amazon store. What drives purchasing decisions is a great search capability, and the capacity to look at the views of people that you trust inside the review environment. What happens if you can access that system and that information any time you are thinking about buying stuff? That is what augmented reality in a more usable form can bring. That can displace advertising.
Which takes us back to my presentation on agriculture. My key message was that information was becoming more and more vital to farmers. In agriculture we are starting to enter an era where farmers will have more and more information. They will be able to see continual streams of data from their land,crops, and animals using systems like The Yield. They will be able to get frequent data from the air using drone systems. Farmers will use this information to reduce their operating costs. At the same time they will be able to communicate more to consumers about their product. That communication can be direct to the consumer for farmers that are value adding their own products. It will also be a requirement of supply chains into larger scale markets.
A lot of people are concerned that the advent of augmented reality in glasses/lens form will result in a polluted visual environment where we are continually bombarded with advertising related to our location and our personal data. Paradoxically this may drive people towards less advertising. The changes i have described here may assist that change.
If I am right then the nature of shopping changes, and along with it the nature of advertising. Along with business models that depend on advertising. It could be a very different world.
Paul Higgins




Leadership in a Post-Capitalist (???) World

On Wednesday night I gave the opening address at Leadership Victoria on this topic. The audience was a group of 60 leaders across a range of organisations in Victoria. The question focused around some articles from Steve Denning, Jeremy Rifkin, and Paul Mason (see links at the end of this post). My purpose was to frame the rest of the discussion for the night, and highlight some possibilities about key leadership skills for the future.

As the background articles are now 2-3 years old it is an ideal time look at what has happened in the interim. The thrust of Paul Mason’s writing was that new tools were in the early stages of ushering in a new economic system. These changes included collaborative production, reducing information scarcity, and automation of work . Steven Denning was more circumspect about what was happening. While in broad agreement with some of the principles Paul was espousing, he had differing views on their effects and implications. Denning believed that it was a new era of capitalism rather than post capitalism. Jeremy Rifkin examined the implications of areas of the economy where the marginal cost of production is almost zero. In doing so he was more in agreement with Denning than Mason, while arguing that the collaborative commons was having a significant effect.

To clearly show my biases before I argued my proposition I put up the following quote from Amory Lovins:


“The markets make a good servant, but a bad master, and a worse religion”


because while it would appear I am arguing for hyper-competition, the outcomes need to be focused on how the system benefits the general population in our societies.


The Proposition

 I began my presentation, as is my wont, by arguing against the proposition of the title of the session. My view is that we are not entering a post capitalist world, but rather a real capitalist world. The technologies discussed in the articles are changing the way the world works. In doing so they are moving us towards real capitalism rather than the monopoly seeking, and rent seeking behaviours of the past. For the purposes of this discussion I defined real capitalism as:

“hyper-competition within the boundaries of a socio-regulatory system that steers the benefits to the general population rather than the few”

The reality is that true competition is hard, and so companies try to position themselves in protected positions . I have just been reading Kerry O’brien’s book on Paul Keating. In the chapter which deals with privatisation, Keating describes the Qantas and TAA privatisation process.  Peter Abeles who was part owner and CEO of Ansett Transport Industries but also a good friend of Prime Minister Bob Hawke was deeply involved. According to Keating the privatisation discussions were frequently attended by Peter Abeles who was interested in keeping a cosy duopoly. Keating states that this was because although Abeles thought they could compete with a restructured and privatised government airline, it was better if they did not have to.

This was the main purpose of strategic frameworks such as Porter’s Five Forces: position yourself where you had a strong position relative to suppliers, existing competitors, customers, and new entrants. True competition, where there is a relentless focus on the customer, continual innovation, and where new entrants can appear from anywhere is a highly uncomfortable environment. Therefore, companies and people have to have true competition forced upon them. This is fair enough, you would be stupid to force additional competition upon yourself (in the short term). This is partly the role of government and society in terms of the rules and norms that govern how things should work. The new tools and capabilities that the articles described are contributing additional forces.

Part of the arguments of the authors of the background articles was that increasing connectivity, improved collaboration tools, and wider access to information was increasing the capacity of the smaller players to compete with the bigger players. My proposition is that is true, but that but power is again accruing to the larger players. The combination is creating a world of hyper-competition. Let’s look at what some of the evidence says:

In 2011 I presented to a number of tourism conferences about Airbnb. At that stage it had been running for 3 years. I was continually surprised at the lack of knowledge about it in the tourism industry. The promise of Airbnb is that individuals can gain value from their existing assets, increasing the power of the individual. Putting aside some of the more outrageous events in rented out properties Airbnb has mostly delivered on that promise.

Yet, in these sorts of large platform business models power naturally moves back to the centre. Once there are enough buyers and sellers on the platform, it is hard for others to compete with the model because of network effects. The sellers are in hyper-competition with all the other sellers, hence it is a good example of a hypercompetitive world. It is a large market with transparent pricing.

In the more egregious cases of platform models we are seeing big problems. Uber stands out as a major example. Uber has serious internal problems which I think stem from excessive power issues. There are also lots of stories of low paid drivers, and conflicts about their status as employees or contractors. There is definitely a power imbalance with power accruing to the centre of the network.


Now lets look at the music industry which really should be a poster child for the sorts of changes the authors were describing. We have seen increased capacity to create and distribute music from musicians to their audiences. We have also seen marginal costs approaching zero with the creation of digital media. So what has happened? The following pictures from Digital Music News via Vox show some of the changes:

music sales 1998 from Vox


music sales 2013 from Vox

Digital technologies have transformed the way music is sold and consumed. Now streaming services have changed that again, as shown by the following graphic from Business Insider

streaming music from business insider and statista

all of this has resulted in the following revenue changes (via Benedict Evans)

global music recorded revenues from IFPI Benedict Evans

Buried in all this is the fact that Spotify is dominating the market for streaming services, with Apple a strong but distant second. Spotify’s revenue, according to Billboard is now over US$3 billion but it also lost US$581 million on those revenues.  So again we are seeing power accruing to the big players and many complaints from artists.


Hunter S Thompson once said:

“The music business is a cruel and shallow money trench, a long plastic hallway where thieves and pimps run free, and good men die like dogs. There’s also a negative side.”

I am not sure much has changed.


We are also seeing other examples of power accruing to the big organisations:


  • From 2001 to 2011 Walmart grew from 1.15million employees to 2.2 million employees.


  • Amazon is showing huge growth, and is now sending shudders through the retail food industry with its acquisition Whole Foods.




So my basic proposition is that:

  • The tools and changes described by the authors are not taking us into a Post Capitalist world. They are taking us into a true capitalist world. hyper-competitive world.


  • While small organisations and individuals now tools that make them more productive, and more able to connect to everyone else, power is still accruing to the large players.


  • The combination of those changes mean a changed way of doing things but only inside a world of hyper-competition.


So within my view of the world what are some key skills that people need to be leaders? I have chose four skills, that is by no means comprehensive:

Situational awareness

In a world where there are many more interconnected and moving parts, then we need better strategic understanding. What I mean by situational awareness is a detailed understanding of the various components of your sector or industry . It also encompasses a clear eyed view of where those components may be changing. Two of the models that we use for thinking about these things are Carlota Perez’s work on Technological Revolutions and Financial Capital, and Simon Wardley’s work on mapping.

Perez’s view is that there are clearly identifiable 50-60 year cycles of technological, financial and social change. Thinking about where we are in the current cycle can help us understand more about what strategic decisions we should be taking. These cycles run from technological revolution to a financial bubble, to collapse, to a golden age and then to political collapse. The five that she identifies are The Age of the Industrial Revolution, The Age of Steam and Railways, The Age of Steel and Electricity, The Age of Oil and Mass Production, and The Information Age.

Simon Wardley takes a more granular view while stil looking at cycles and movement. Simon posits that all technologies and practices move from their original genesis, then to custom built, then to product, and finally to utility or commodity. While this is a gross oversimplification of his work, understanding where each part of your value chain is is located within a map of this framework, and where it may be headed allows you to better understand where significant change may occur. He is writing a book on the subject and all the chapters are on Medium. I highly recommend you go read them.




I mean scepticism in its best possible meaning: questioning assumptions and evidence. This skill is vital when thinking about models. This is because all models are incomplete and inadequate representations of the real world . They are more useful when viewed with a sceptical eye. I can best express this in the statement:

Strong Views Weakly Held

For example if we look at Carlota Perez’s work it is clear that the cycles she has described are social constructs. Each occurred under a different set of political, technological and social  systems. It is also clear that 4 or 5 cycles, even if taken as true, are not a clear body of evidence of some sort of immutable laws in human society over time. So use models, think deeply about them but always with a sceptical eye.


The capacity to deal with uncertainty

The reality of the modern world is high levels of uncertainty. In my work I experience clients seeking to find certainty in the midst of uncertainty. An example is people trying to create scenarios in spreadsheets with probabilities attached to them. These sorts of reductionist approaches reduce the capacity of organisations and individuals to take effective action. They create an inherent disconnect between the organisations’ strategy and the real world they operate in.

While the scepticism I have described above is to some extent focused on making sure that we don’t take models as gospel, the capacity to deal with uncertainty is somewhat different.

The critical leadership skill here is the balance between acknowledging and working with uncertainty, while instilling confidence, purpose, and direction in the people around you. Different people have different needs in this regard. Some people want to dive into the uncertainty. Others just want to get on with the job. In a previous session with a Leadership Victoria year group there was vigorous debate on this issue. The room split down the middle. Half the room believed that it was their job to deal with the uncertainty. The other half believed that exploring the uncertainty with their staff was a critical responsibility.


The capacity to coach and stimulate networks

Networks and collaboration are a reality now in many organisations. The day of the strong visionary leader is ending, and the ability to lead and stimulate networks is critical. This applies both inside organisations and in collaborations between organisations.



I finished my presentation by analysing my relative strengths in those skills. I am pretty good at the situational awareness, and scepticism skills. I am less able in the dealing with uncertainty area, although better at work than in my private life. I am poor to average in network leadership skills. My main reason for that assessment is that the world has changed enormously in the last fifteen years. In that time I have been focusedon foresight and situational awareness when working with clients. It is a long time since I led an organisation on a day to day basis and network leadership skills in particular need deep and continual practice. The same applies to situational awareness and scepticism but I have been practicing those.


Paul Higgins


Background reading links for the participants:

The end of capitalism has begun

The End of the Capitalist Era, and What Comes Next

Is Capitalism Ending?


An Initial Model for Autonomous Trucks in Australia?

Updated with long distance vehicle announcements


A recent announcement in the United Kingdom has the government allocating 8.1 million pounds to a truck platooning trial:

Semi-automated truck convoys get green light for UK trials

Platooning is essentially like bicycle pelotons in road races like the Tour de France, where riders get sucked along in the slipstream. Until you have actually participated in one, you do not realise how much easier it is to ride in the group. I knew that intellectually, but the experience is something else. For trucks this means less congestion and less fuel use. In order to achieve these results the artificial intelligence and sensing systems that controls the trucks have to be much better than human drivers so that the trucks can drive closer together.  In the UK trial the speeds and steering will be controlled by the lead vehicle.

Total autonomy for vehicles on the road is known in the industry as Level 5 autonomy. This is where vehicles can control themselves in all road conditions. We are a long away from this technologically, so the trucks in the trials will have human drivers who can take the wheel at any time. The problem with this is that driver attention will naturally wane and this may impact on reaction time. In this trial this may be dealt with by periodic blocks of time where the human driver must take command of the truck – whether there is a need or not.

The medium term adoption pathway here in Australia may be different due to the road conditions and distances travelled. Here in Australia the situation for truck driving is a little different than the UK. There are much larger travel distances between the major cities, and the major inter-capital highways are less crowded. This is mirrored in the United States, especially in larger states such as Texas and California. This means that the adoption process of the technology may be significantly different.

There are a couple of technology issues in the adoption pathway that is chosen that flow into these sorts of differences and how we might choose to adopt the technologies.

Firstly there is a significant debate in the autonomous vehicle technology world about the approach of using maps versus continuous sensing. As humans we can navigate an unfamiliar terrain because our sensing and vision systems are good enough to recognise and continually process information at a level that is useful. The technology in autonomous vehicles is still not good enough to achieve that yet, and this is where mapping comes in. If an autonomous vehicle has stored in its system a map of the territory it is about to navigate, it only has to compare the environment it is encountering versus the map. This significantly reduces the job that needs to be done, reducing the pressure on the technology. In the long run it is likely that onboard vision and sense making systems will be good enough to do without maps. In the short term  having maps significantly improves performance. The timing of these changes, and the implications for strategic competitive advantage are critical when thinking about strategic decisions for individual companies, and what the overall outcomes might look like (see: Winner-takes all effects in autonomous cars for an excellent discussion on this).

Secondly, at what point will we be comfortable with no driver in the vehicle, and will this be at Level 4 or Level 5 autonomy. At Level 4 autonomy the vehicle can drive itself but is limited either by geography or conditions. This means that while the driver can be removed there needs to be some sort of geofencing, or emergency failsafe systems. For example trucks on the highway may automatically pull over if rain levels go beyond a certain level, affecting visibility. If adoption pathways can be achieved at level 4 rather than level 5 then adoption will occur more rapidly as the technology will not have to be as advanced to achieve the outcome.

So if we can build a model in a specific area of trucking where there are less complicated driving challenges, and mapping  makes a significant contribution we can create faster adoption. Which takes us back to the highways between capital cities in Australia.

In Australia 18-19% of total road freight movements are inter-capital freight movements (Truck Industry Fleet Report 2015), and there has been significant improvement in those roads over the last 20 years. For example once we get outside of the major urban areas of Melbourne and  Sydney the road between the two cities is excellent for trucks. An early adoption model for autonomous truck movements in Australia might start with transfers between Melbourne and Sydney and look like the following:

  1. Autonomous trucks operating the full distance between the two cities except for the last 30 kilometres (plus or minus) in each city.
  2. A truck changeover system on the outskirts of both cities where either the truck takes on a driver, or the prime mover is changed over to a non autonomous prime mover and driver. This is necessary in an early adoption model because the challenges of driving in the major cities are significantly higher than on the open highway.
  3. A cooperative mapping effort coordinated by the Federal Government where the road is mapped in its entirety.
  4. The formal mapping is supplemented by all autonomous trucks contributing their mapping and sensing data to a central system to continually update the maps. Therefore any new hazards or changes such as roadworks are rapidly incorporated into the maps that all autonomous trucks use.
  5. Autonomous truck support centres where the control of the truck can be taken over by a remote driver in the case of difficulties such as problems with sensors, or road conditions which are outside of specified parameters.

Many of the pieces of such an implementation pathway are already in place or soon will be. Autonomous trucks have been trialled in several locations around the world, and we already have remote control of mining systems (Mining industry looks towards a new wave of automation ,  Rio Tinto: rolling out the world’s first fully driverless mines ). We also have remote control of drones for military operations.

Around the world the trucking industry is seeing problems with an ageing workforce, with trucking jobs being seen as unattractive by younger generations (Wheels not in motion: Australia running short of truckies). A system as described above can solve some of this problem by:

  1. Autonomous trucks can operate for more hours than human drivers can, increasing efficiency of truck use and reducing overall demand for drivers.
  2. Increasing the attractiveness of trucking jobs. In many cases the long hours and time away from home are significant factors reducing the attractiveness of driving a truck. If the long distances can be handled by autonomous trucks, and the drivers can go home to their families at night then the job becomes more attractive.
  3. A truck driving job is more interesting, as the easy parts are taken over by autonomous trucks, and the more difficult driving conditions, unloading operations, and interactions with customers are covered by human drivers in short haul operations.

Eventually most trucking operations will be carried out by autonomous trucks If we want to address the shortage of current workers, reduce fuel consumption for long haul freight, and possibly reduce fatigue related accidents, a model which accelerates early adoption should be trialled.


Proterra has announced an 1100 mile (1772.2km) trip of its Catalyst Bus on a single charge. (Proterra Counters Tesla’s ‘Beast’ Of A Semi With 1,100-Mile Range Electric Bus). In addition Tesla will announce its new Semi truck in October. With distances between Melbourne and Sydney of approximately 865 km, Sydney to Brisbane of 928 km, and Melbourne to Adelaide of 725 km this seems to put the intercapital freight market in the sights of autonomous electric trucks.

I am writing a book on autonomous vehicles with Dr Chris Rice of the University of Texas Austin. 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: The featured image comes from: 










Sell Your Crash Repair Business Now*

*this should not be taken as financial or business advice. If you own a crash repair business please take professional advice before making any decisions.

I am just going through the process of getting some minor damage repaired on our car and have been ruminating on the future of the insurance and repair model when we have driverless (autonomous) cars. This was also prompted by a couple of stories in The Age here in Melbourne:

Crash repair: How Ray Malone became head of ASX-listed company AMA Group


Driverless vehicles technology to roll out on the Tulla under trial


The first story describes how Ray Malone has built a Australia’s largest crash repair business, and is aiming to grow it even further. That would seem to go against the title of this post but it actually feeds into my thinking because Ray’s company provides wholesale service aftercare which will be vital in the scenario I am describing.

The second story is about how trials of driverless cars are starting here in Melbourne. This follows a large number of trials that are being conducted in various countries around the world.

Once we move to a reasonably widespread adoption of autonomous/driverless cars the local crash repair business will basically disappear except for a few large operators like Ray Malone but even his business could be under threat . The key reasons for this are:

1/ It has been forecast that autonomous cars will significantly reduce the number of car accidents that occur. This is based largely on the statistics that human error causes more than 90% of traffic crashes. So if we can eliminate the crashes caused by idiots, people under the influence of drugs and alcohol, and people driving tired or angry (Police looked into the deaths of 86 people on Victorian roads last year and found that in more than 10 per cent of cases the driver had experienced a traumatic or upsetting event.) we can significantly reduce the number of accidents.

Against this argument is that autonomous cars supplying a transport service may result in people travelling further and perhaps take more risks. Certainly it will allow elderly people who cannot drive, and young people who do not have a licence to travel in cars more than they otherwise would. There have also been arguments that because we feel safer we may take more risks as pedestrians or cyclists.  If we are conservative and say that only 50% of accidents caused by human behaviour will be eliminated we still have a significant fall in accidents.

2/ It is highly likely that we will see large fleet models emerge where large numbers of people choose not to own a vehicle. If the overall travel costs are lower than owning your own vehicle, and you can get a vehicle anytime you need one then the convenience of transport as a service outweighs the personal ownership model.  The economics for fleet owners are different than for individual owners when it comes to crash repair services. Fleet owners will want large scale service operations to reduce costs or will pay far less for the services of smaller scale operators. This feeds into a large supplier (such as Ray Malone’s company) snapping up more business. Larger scale crash repair businesses will benefit from the economies of scale that allow them to use new technologies such as robotics to increase throughput and reduce costs.

3/ The model for crash repair business location will change. Currently crash repair businesses are located in scattered locations throughout the suburbs and inner city. This is because if I want to take my car in for crash repairs there is a significant time cost for me to take my car to a location that is not near to my house or business. I have to travel to the crash repair business, and then get back to my home or place of work. So I want the crash repair business to be reasonably close. The location is mainly driven by the customer. If my personal driverless car needs crash repairs it can drive itself to the crash repair site, and a fleet service or a shared personal car service can replace my transport needs in the meantime.

If I was asked to drive my car (actual damage pictured below) to a service centre 40 km away I would not be very happy, but if my car can take itself then location becomes much less important and the costs of the business become far more important. Locating the crash repair business in areas of lower property costs with good transport links makes far more sense. It also means that the employees of the business will have lower property costs if they live locally. We already see this model in light manufacturing and food processing/handling facilities locating around hubs on ring roads, away from  inner suburbs with high property prices.

If a fleet ownership model predominates over personal ownership this effect will be even higher as large scale fleets look for cost reductions through economies of scale.

corolla damage 1


So if we summarise all the factors together if we assume a 45% reduction in total accidents (50% of human error crashes) and a tripling of scale that comes from the changes described above we get an 82% reduction in the number of crash repair businesses in any city.  I believe that the changes in scale may be even higher and we may end up with only 5-10% of the number of current crash repair businesses being economically viable.

If I own a crash repair business in any suburb in any of our major cities I will come under pressure from a high scale panel beater business set up on the fringes of the city with lower property costs.

So, if you are a crash repair business:

  1. Assess whether now is a good time to sell to someone else who does not understand these changes.
  2. If you think I am wrong then you should suspend that thought for just a few minutes and  think about what it means to your business and your assets if I am right. Even if you think that chance is only 5% you should set up a series of questions for yourself to monitor in coming years so that you can change your mind if the changes start to happen. Those questions include:
  • Is the practical outcome of accident reduction matching the rhetoric of the technology experts and the modellers? Look for signs of early change, cities where adoption is at the forefront of the change and make an assessment as to whether the predictions on accident reduction are true (or even going to be exceeded) and then think about the timing of the implications.
  • Look for areas or cities where the first full scale mass adoption of driverless cars might take place. For example Singapore, with a small land mass, and a relatively authoritarian government might be one. This will give you early signs of what larger scale adoption might look like.
  • Is the adoption model going to be a personal one or a mass fleet one? If the model is primarily a personal one then you should be thinking about whether you can become one of the new mega panel beaters on the fringes of the city that will survive the change. If the model looks to be a primarily mass fleet adoption one then there are less possibilities. Those fleet operators will either run their own operations which are standardised and mechanised or they will use their economies of scale to drive down margins in the businesses that supply them. You can still run a good business that way but the opportunities will be limited and will require lots of capital to create the volume throughput and economies of scale required. You will have to compete with the Ray Malone’s of this world.
  • Are any early models of very large scale, city fringe located crash repair businesses starting to emerge anywhere around the world? Are they successful?
  • Are car companies changing their business models for car repairs. For instance electric cars have far less moving parts than internal combustion cars. Does that make a difference to your business model? Are modularised car construction and repair systems emerging that will increase the capacity to adopt robotic repair and maintenance systems that will advantage large throughput car repair and maintenance systems?

While these changes may take 15 years to start to significantly impact on the crash repair business, once they become obvious the window to realise the business value by sale will quickly snap shut.

This is just one of the many implications of change from the widescale adoption of driverless cars.I am writing a book on driverless vehicles with Chris Rice (@ricetopher). It is called “Rise of the Autobots: How driverless vehicles will transform our economies and our communities. Stay tuned for more writing as we develop our thinking further.


Paul Higgins

Electric Cars and the Legacy Issue

Chris Rice and I are currently writing a book on the rise of autonomous vehicles and their widespread effects across our economies (entitled Rise of the Autobots: How Driverless Vehicles will change our Societies and our Economies). One of the keys to looking at what these changes might mean and the rate at which they will occur is the speed of adoption speed of electric cars and autonomous vehicles combined together.

There have been lots of excited announcements about electric cars over the last few months including:

India to make every single car electric by 2030 in bid to tackle pollution that kills millions
The Electric-Car Boom Is So Real Even Oil Companies Say It’s Coming
When Will Electric Cars Go Mainstream? It May Be Sooner Than You Think

The reality is that the adoption of electric cars will have several bottlenecks including but not limited to:

  • Battery availability.
  • Production capacity for manufacturing.
  • The reluctance of people to adopt the technology until they are completely sure that the charging issues and the range issue have been adequately dealt with.
  • The long-term nature of the turnover of the vehicle fleet.

Both battery production and electric car production are ramping up but the last point is very important when we start looking at the critical mass needed to disrupt a range of industries, including petrol stations and their supply chains, maintenance and repair systems, and the electric power grid. Even when it becomes a sensible economic decision to purchase a new electric car over an internal combustion engine (ICE) powered car, someone with a 7 year old vehicle is not going to immediately changeover. This is both due to the capital nature of the change and the fact that if electric cars are more economical than ICE cars the resale value of second hand ICE cars will fall dramatically, reducing the interest and capacity of people to purchase a new vehicle (if purchase is the model). This will be exacerbated if the new electric vehicles also have significant advantages in autonomy.

To illustrate this issue we took a look at the vehicle fleet in New South Wales in Australia If we look at the statistics at the end of the fourth quarter in 2016 it gives us a snapshot of the vehicle legacy issue. The following graph shows the year of manufacture for light vehicles registered in NSW at the end of 2016. The majority are passenger vehicles:

light vehicle registrations in NSW 2016 Q4

Source:  – accessed July 24th 2017

While the 2016 manufactured vehicles are under-represented in this graph as many 2016 vehicles are registered in 2017, it nevertheless gives a clear picture of the ownership structure of light vehicles. If we look deeper in the data we see that 20.1% of the registered light vehicles are manufactured prior to 2001.

If we look at heavy vehicles we get a similar picture albeit with different percentages:

heavy vehicle registrations in NSW 2016 Q4

There are some differences in the data between light and heavy vehicles:

  • The first is that there are significantly more 2007 heavy vehicles registered than any other year. This probably relates to GFC issues.
  • The second is that the heavy vehicle curve is lower than the light vehicle curve. This probably reflects a pattern of use where heavy vehicles are sold into a secondary market that will discount vehicles significantly if the economic model is significantly different than the new vehicle one, extending the useful economic life of the vehicles. This means that the percentage of total registered heavy vehicles prior to 2001 is 34.2%, much higher than light vehicles.
  • The third is that there are many more vintage models in the light vehicle category, reflecting the motoring enthusiast and restoration market. So there are 3,379 registered light vehicles manufactured 1900-1949, but only 21 heavy vehicles for the same period.

A very simplistic look at this data says that even if every vehicle sold new in Australia was electric from say 2025 was an electric car, and the purchase patterns remained stable after 5 years we would have between 31% and 40% electric light vehicles on the road and in 10 years it would be somewhere between 50 and 60%. This pattern is highly unlikely and so the real adoption rates will be well short of that. Every year that the purchase pattern is 50% electric and 50% ICE will slow the transition as those ICE cars will be on the road for a long time.

This adoption cycle is complicated by our view that increasing automation will result in more fleet ownership models, and shared car rides, reducing the total sales of new vehicles. While this means that battery and electric car manufacturing do not have to ramp up as much to get to 100% of new sales it changes the adoption curve.

Now both those simplistic analyses assume the normal pattern of car purchases and ownership will remain in place. That is also unrealistic. All we do know is that the adoption rates will be relatively slow because of the legacy issues and the turnover of the vehicle fleet as a whole. Cars are not smartphones. We will be doing some more modelling on the possible scenarios over the next few weeks. Follow us here if you want to see them and help us think through the changes.


Featured Image is from :

Top 8 Secrets for Competitive Electric cars-Tips for Auto Manufacturers by Ameen Shageer