Technology

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

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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).

bosch-x-spect-wand-7

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

 

 

 

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Sell Your Crash Repair Business Now*

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*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

and

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

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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: http://www.rms.nsw.gov.au/about/corporate-publications/statistics/registrationandlicensing/tables/table113_2016q4.html  – 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

 

 

What Jobs Will Stay?

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This week I had two very different experiences which had me thinking about the future of jobs. On Tuesday I was invited to a workshop host by Perpetual Trustees with the Stanford Centre for Philanthropy and Civil Society. I was there isn my role as a futurist and a venture philanthropist (I am a partner at Social Venture Partners Melbourne  See :  Summary Video). The subject for the session was Digital Technologies and Democratic Theory and involved a range of not for profit organisations, commercial businesses, and startups.

A lot of the discussion was on the effects of technology on our wider society, and our political systems in particular. Rob Reich and Lucy Bernholz from Stanford took the temperature of the room on whether we are optimists or pessimists about the effects and capabilities of technology. I was surprised by the fact that the overwhelming majority of the room was optimistic. I placed myself as pessimistic. I think that there is a lot to like about the capabilities of technology to connect people together, and for people to take action. I just think that the reality is a little more sobering, and that the effects of technology on our wider societies, in particular the future of work, will outpace the capacity of the technologies to bend the overall direction to the benefit of all.

While I am no means certain I fear a future where more jobs are eliminated than are created for the first time in our technological development. If such a change occurs it has the potential for both good and bad. The negative picture is one where more and more wealth accumulates in the hands of the few and is not distributed across the general population. That is a recipe for revolution. This is particularly troubling where public trust in our democratic institutions has fallen significantly.

driveway gate 1

My other experience is that we hired a handyman to move a gate in our driveway. For some reason I cannot understand the previous owners placed a gate part way down the driveway leaving a whole lot of unused space behind it. On top of that there are significant parking restrictions on our very steep street and so visitors have to park down the hill and walk up. This is getting to be a particularly serious issue as our parents age.

The original installation of the gate had not been particularly professional and so there were problems opening and closing the gate due to warping of the wood. When we got down to the details of the job we discovered that about 13 different types of bolts and screws had been used in the original gate installation. On top of that some were metric, and some were imperial (inches) and some seemed in between. On top of that some of the screws had been rounded out and were impossible to remove by standard methods. The problem was exacerbated by the fact that the concrete at the new position we were looking to install the gate on had three different levels.

Luckily we had hired an old time craftsman/handyman who had all the tricks and now the gate is safely installed (see picture). The dog has no chance of getting out, and our parents can now park in the driveway. Those are the sorts of jobs that are not going away in a hurry because of the levels of variation for each job. Our handyman (also Paul) says he reckons he has 20 years of work ahead of him in his semi-retirement. I think he is right and if you are concerned about the future employment of your children and they have aptitude for this sort of work (which includes plumbing) then keep encouraging them.

I realise that these two subjects are different ends of the same issue and the second one has no real bearing on the wider societal issues. I will keep trying to make a contribution to those wider issues.

 

Paul Higgins

Re-Purposed Electric Car Batteries and Its Effects on Electric Car Adoption/Driverless Car Adoption

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Last night I attended the Churchill Club event in Melbourne on the future of batteries. There was a great panel presenting and the discussions covered a range of battery technologies, including Ecoult which is commercialising the CSIRO ultracapacitor technology for lead acid batteries.

In particular I was interested in the presentation by Relectrify CEO and Co-Founder Valentin Muenzel who talked about Relectrify’s mission to use electric car batteries that were no longer useful in energy storage applications. This was interesting because as part of my research for a book that Chris Rice and I are writing on the future of driverless cars I had been looking at the adoption rates of electric cars as part of the rise of driverless cars. In that research I had come across an assessment by Ark Investments that had calculated the net present value of an electric car battery in a specific energy storage scenario as shown in the following table:

Ark Invest battery depreciation table

source: https://ark-invest.com/research/ev-batteries-value – accessed June 20th 2017

The basic principle is that while a battery in an electric car might have its performance degrade to a point where it is no longer useful for driving, that battery will still have significant storage capacity (think about your phone battery after 18 months – it still works but its capacity is reduced).  If you can buy that battery cheaply and adapt it to storage use then you have a cost effective solution.

Of course the Net Present Value calculation in the table is for a specified energy reserve use which has a higher price, and nobody buys an asset for its Net Present Value otherwise all you do is get your money back over time. In discussions with Valentin he told me that without giving away commercial secrets the model for them is about 50% of the value of a new battery. This is important because the cost of new car batteries is falling. An analysis of battery prices by Bloomberg New Energy Finance in January showed the pace of that change:

battery prices falling fast from Bloomberg

source: https://www.bloomberg.com/news/articles/2017-01-30/tesla-s-battery-revolution-just-reached-critical-mass  

Now this is the price of the battery itself which is not the same as an installed battery system but the progress has been amazing, and mirrors what we have seen in solar energy. No great basic technology breakthrough, but significant technology improvements driven by the cost learning curve. In a separate report Mckinsey has stated that electric vehicle batteries fell to $227/kWh in 2016 with Tesla claiming to be below $190 per kWh (Electric vehicle battery cost dropped 80% in 6 years down to $227/kWh – Tesla claims to be below $190/kWh) Rumours have also circulated that Tesla has got the battery costs down to $125 per kWh (Tesla is now claiming 35% battery cost reduction at ‘Gigafactory 1’ – hinting at breakthrough cost below $125/kWh) although the truth of that remains to be seen. There is no doubt about the rapid pace of changes occurring, just the quantum of that change.

Valentin and I also discussed the model for autonomous vehicles given that a fleet model or a car sharing model means that cars would travel far more kilometres in a year. For an electric car this means that the battery will reach its degradation limit more quickly as the battery would be charged and discharged more often. Interestingly for Valentin this meant that the battery would be worth more for repurposing, because outside of the energy capacity the battery still retained, its relative newness means the technology is likely to be more advanced, and safety and physical deterioration characteristics would be much better.

Given that storage is likely to become far more important in the future given changes in the energy generation mixes around the world it puts a slightly different complexion on the costs of electric cars. It is our view that the end game for driverless cars is mass fleets supplied as a service with hardly anybody owning a car. If electric car batteries only last 3 years in shared driverless vehicle but have significant re-sale value it lowers the lifetime cost of a kilometre travelled and therefore accelerates us to the point where the cost of running an electric car is lower than running a fossil fuel car. Lifetime cost factors less into individual car ownership decisions but if you own 50,000 cars in a mass fleet in a highly competitive market it becomes it becomes a much more important factor. This changes adoption rates and also the balance between fossil fuel and electric cars.

The effects of this will be lumpy as Valentin advised that different batteries have different degrees of difficulty for repurposing as stationary storage. This is related to the original design decisions made for the battery technology which were originally made with the purpose of electric cars in mind, not stationary storage. For example apparently Tesla has stated that their car batteries will not be repurposed and that is due to the design constraints in their battery technology.

A note of caution:

In a discussion with John Wood (CEO of Ecoult) he quite rightly warned me to be careful of the public statements of battery manufacturers and suppliers on their lifetime use. Given that we are talking about changes in technology and lifetimes of 10-15 years which are therefore untested in the real world, those are wise words.

 

Image credit: The featured image is from http://www.relectrify.com/

Strategy, Digital, and Governance

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Estelle Metayer (@competia) who I greatly respect as a futurist and governance expert tweeted out today this article:

Digital directors in industrial boardrooms

The thrust of the article is that digital strategy is so important these days that having a “digital director” is crucial to board room governance and strategy.

There is no doubting the importance of digital technologies in the current environment and for a more comprehensive take on this I recommend you read:

Which Productivity Puzzle?

by Bill Janeway. It is a great discussion around an issue that is getting lots of airplay (is that a thing any more?) – the question of why we are not seeing greater productivity increases from the adoption of digital technologies. The last part of the post looks at some of the data that clearly shows that productivity is increasing much faster than the average in “digital leaders”. Given that productivity is a key driver of profitability and general economic growth it seems obvious that successful digital strategy is a key component of the future of nearly every business.

If we take that as a given then we come to the question of whether there should be a digital director. My view is that you cannot have every technical/strategic/financial/legal capacity on a board or board size becomes unmanageable. In my experience big strategic failures arise when strategy is driven by technology adoption rather than being customer driven.  Also on boards where I have been a director I have seen too many times a board abrogate its responsibilities by deferring to the expert on a particular issue. Rather than taking an open and questioning approach boards will turn to the legal director or the risk expert and follow their view. This reduces the collective intelligence that is brought to bear on the issue.

My concern is that if there is a digital director then strategy around digital technologies will be driven by the views of that person.  I want the following things to be uppermost in the mix of skills on a board:

  1. Enough industry experience – so that the board is not naive.
  2. Enough outside the industry experience – so that the board is not captured by the thinking in that industry.
  3. A mix of males and female (see my comment on the Uber board around this )
  4. A large focus on customers.
  5. Strong strategic minds with  the capacity to question strategy proposed by management.

If you are able to get all of those things then I do not see the room for a director with specific (and probably narrow) digital expertise.

I am particularly taken by the view expressed in:

What a digital organisation looks like

by Janet Hughes, who views a digital organisation as essentially an organisation wide attitude to become open, responsive, and efficient. A single person that is deferred too cannot achieve that as Janet eloquently represents in her image:

digital super hero from Janet Hughes on Medium what does a digital organisation look like

Paul Higgins

 

 

 

Augmentation of Human Capacity

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On Friday I did the opening keynote for the Mindshop Australia conference. The title was “Bringing the Future into your Advisory Practice”. The focus was on ways of creating more value for the clients of advisors in the network. After the session there was much discussion from participants on the nature of work and the sorts of jobs that they should encourage their children to be aiming for.

My response to those questions was to use examples to highlight principles rather than recommend specific jobs because jobs will change. I used the example of the health sector and new AI developments in my presentation as well as in the discussions afterwards. For example:

Self-taught artificial intelligence beats doctors at predicting heart attacks

stylised heart image from sciencemag

On the weekend I was then reading Stowe Boyd’s  10 work skills for the postnormal era and I was struck by the statement on “Freestyling” from Tyler Cohen:

“When humans team up with computers to play chess, the humans who do best are not necessarily the strongest players. They’re the ones who are modest, and who know when to listen to the computer. Often, what the human adds is knowledge of when the computer needs to look more deeply”

This married up with the response I was giving to participants at the conference. The use of AI systems to augment the capacities of humans  does not augment everyone equally. In the world of medical specialists it is a commonly held view among patients that they will put up with specialists with poor social skills or high prices because of the knowledge they hold (putting aside the issues of the professions restricting supply to keep prices high).

If that knowledge moves largely to the realm of artificial intelligence then this re-weights the value of the medical specialist. If the machine can do things the individual or team cannot possibly do by being able to access more knowledge and make more connections in that knowledge than is humanly possible then it changes the system. Knowledge becomes less important and skills such as the capacity to work with the AI, patient empathy and general social skills become more important.

Augmentation  of human cognitive capacities will do that across sectors and industries.

 

The Future Competitiveness of Corporate v Individual Medical and Veterinary Practice Models. Is AI the key?

/ futuristpaul (Paul Higgins) / Leave a comment

Before Christmas I did some work on the future of veterinary surgeons and the education and regulatory changes that might have to occur to move with those changes. One of the things that occupied my mind with that work was the issue of artificial intelligence systems on the competitive position of veterinary practices. My belief is that artificial intelligence augmentation of medical/veterinary capabilities is coming quite quickly and a large scale corporate practice model has significant advantages in this space over the individual practice.

Increasingly we have seen a more large scale corporate model in the veterinary practice market in Australia and around the world. Examples in Australia include Green Cross for major city practices and Apiam Animal Health in rural practice.  This has followed similar trends in medical practices where you have organisations like Medical One and Tristar which started out in rural Australia but has expanded into the cities as well.

The basic business model and value proposition of the corporate model is:

  • Presenting a single branded product almost like McDonalds so a patient or client can be confident of going to the practice no  matter where they are.
  • Increasing purchasing power of all of the back end parts of the business from pathology services down to supplies of bandages, etc. This is more important in the veterinary model where practitioners are able to prescribe and supply vaccines and S4 drugs and make a profit from them.
  • Taking over the administrative and compliance parts of the business to allow practitioners to focus on patients. This can include the standardisation and delivery of training requirements, building management, OH&S requirements etc. It can also extend to the supply of consulting hours as a service package.
  • Networking and support for practitioners in smaller practices.
  • The spread of investment and risk over a larger geographic range and customer base.
  • A much more secure retirement/part time/business sale option for owners and practitioners. On a personal note my previous long time GP semi-retired by moving into a Medical One practice and then progressively handing over his clients to the other doctors in a very caring and professional manner.

These models have expanded quite significantly over the last decade which speaks to the financial viability of the model and while there has been the odd flare up and accusation of over-servicing in general the models seem to have worked. I originally started my working life as a general practice veterinarian and the corporatisation of veterinary practices is a hot topic at the reunions I have attended.

The competitive position of the individual practice has been built around personalised service and attempting to be portrayed as caring more for the animals they serve than the big corporate competitor. many of these practices are still doing quite well but the trend is towards the corporate practice.

Which brings us to future competitive positions. I believe that we are rapidly heading towards a future where augmentation of medical and veterinary skills via artificial intelligence is going to be  a ticket to play in the game. This is going to be a narrow focused intelligence rather than a general intelligence. In the medical space we are seeing story after story emerge of new models where AI systems are getting as good as human doctors or have an edge over human doctors:

This AI Can Diagnose a Rare Eye Condition as Well as a Human Doctor

eye image from motherboard vice artificial intelligence

Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features

AI is nearly as good as humans in detecting breast cancer

Self-taught artificial intelligence beats doctors at predicting heart attacks

All of the examples above are based on variants of machine learning and one of the defining characteristic of machine learning artificial intelligence systems is they need large data sets. In the heart attack example above the artificial intelligence trained itself on almost 300,000 case records. As we currently understand artificial intelligence, that system is not transferable to cancer diagnosis, it remains a specilaised cardiac application. The non-small cancer system above was trained  on almost 3,000 images and subsequent patient follow up records.

There are two ways to get a large data set to train on in the medical/veterinary field. The first is to work on aggregated image and case records as in the examples above. That will certainly be a major part of the market. Large capital expenditures will be required to assemble the required images/case files and process them in a way that improves patient diagnosis and outcomes when used in conjunction with human doctors. So we will see services offered for specialised areas such as heart attack prediction, organ by organ cancer diagnosis, etc. As always the areas that have the largest and most affluent markets will be the services that are first offered.

However we are also moving in to a world where artificial intelligence systems can be harnessed by smaller players at much lower cost. Take this example of How a Japanese cucumber farmer is using deep learning and TensorFlow:

cucumber-farmer-14 tensor flow artificial intelligence

The son of a Japanese cucumber farmer (who admittedly had some very good tech skills) built an artificial intelligence based cucumber sorting system for his parents. The problem was training the system required a lot of images and the process took a lot of computing power. More and more in the future you will be able to plug into a cloud based machine learning platform that will enable you to harness much more computing power that is specialised to do this sort of a job for you.

So a large network of medical or veterinary practices could offer services that are not offered in the general market by collecting all the data on their patients across all their practices and using machine learning platforms to train a system that is specific to their patient database.

This will be impossible for the individual practice to match. Is this the killer application for the corporate model to almost completely squeeze out the individual practice?

If so I will be watching for models emerging in the veterinary space because the regulatory hurdles and insurance requirements are much lower. If they are successful then I see those sorts of models flowing into medical practices.

 

 

The Future for Accountants

/ futuristpaul (Paul Higgins) / Leave a comment

The story for accountants the last few years has been increasing levels of outsourcing tasks to low wage environments such as India, and increasing levels of automation for their tasks and their clients. The early stage of that process has been the automation in accounting software systems such as QuickBooks and Mint. Increasingly this automation will move into more and more of the accounting space including real time artificial intelligence auditing systems, automatic preparation of increasing complex tax returns, and structuring credit arrangements.

These things generally start out small and at the less complex end of things and accelerate into more complex areas before people realise it has happened.

So where is the new value for accountants. Primarily this has to be in the process of value creation for clients. Therefore accountants need to move up the value chain and Examples include:

1/ Transformation of business processes around technology changes and the re-training of staff for their SME clients.

As I wrote in Questions on the Future of Work a recent McKinsey report has stated that

“According to our analysis, fewer than 5 percent of occupations can be entirely automated using current technology. However, about 60 percent of occupations could have 30 percent or more of their constituent activities automated”

This supports the notion that apart from a few isolated cases (e.g. truck drivers with driverless trucks) technology does not replace jobs but replaces particular skills or tasks. More importantly business processes and the ways in which we serve customers are changed by the introduction of various forms of artificial intelligence into technologies. This can be a customised approach for vendors like Salesforce Einstein which is adding AI services to its sales, and customer service offerings at around US$50 to US$75 per user per month. Or it can be more fundamental changes to value propositions and business models and the underlying capabilities required to deliver them.

Either way we appear to be entering an era where the jobs people will do will change even more rapidly than they have over the last 10 years and will constantly change rather than be part of a single change management process. In my experience most organisations with under 1,000 employees have little idea on how to approach this problem. This is a huge opportunity for accountants who already have close contact with their clients.

2/ Assisting clients with understanding their strategic landscape

In a world that is moving faster and changing more rapidly than ever before operators of SME businesses are facing greater uncertainty than ever before. They are also facing a paradox. The pressure on them means that they must spend more time focusing on the operational matters in their business but they are doing so right at the time that looking around to see what is happening becomes more important. Just last week I was working with an SME business that is very well run and focused on all the right things that need to be done for the next 12 months. At the same time they were not thinking very deeply about the future and that their decisions (that were absolutely correct in a short term sense) might mean for their long term future.

This means that there is great value for an independent adviser that sees a wide range of other businesses and can:

  • Provide a better strategic understanding of the industry in which the client business operates. Examples include looking at possible industry scenarios for 5 years time and trying to understand what the interim competitive position might be.
  • Cross pollinate ideas and ways of doing things from other businesses in other business sectors. Sometimes very simple tools and approaches from somewhere else can significantly improve a businesses bottom line.
  • Look at the business from a dispassionate but involved perspective and ask questions the business is not asking itself. Examples might include – does your logical short term investment in cost improvements weaken your balance sheet and capacity to respond to x/y or z which are significant risks?  OR What custom built systems are you using which can be supplied via industry standard products or new utility services.
  • Run a structured red team/blue team process to attacking and defending the business from an outside perspective.

 

3/ In the future: utilisation of AI to augment their own capabilities

The reality of artificial intelligence is narrow expertise systems rather than a general intelligence. So we will see artificial intelligence systems that can aid sales people and customer service people but cannot do other things (see Einstein above). We will see narrow artificial intelligence systems that can assist doctors but not do much else. The list goes on.

The modern approach to artificial intelligence systems is basically on of machine learning which requires large training data sets and a large market to justify to expenditure on development and training. Therefore we will see AI systems developing in markets where there are either a lot of customers, or high margin customers, or both. Given how many accounting practices there are around the world the accountancy business is one that is ripe for such a development.

Veterinary Schools as a Platform (VSaaP)

/ futuristpaul (Paul Higgins) / Leave a comment

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.