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).

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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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: 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?

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

The Supermarkets Demise – A Scenario

Back in November I wrote a post entitled: Are The Two Major Supermarkets in Australia Doomed?

If you are at all involved in the retail food chain I suggest you go and read it in full. The short answer is yes, but it will be a slow train crash.

A story in MIT Technology Review last week illustrates one of the possible models that can replace the supermarket model of today:

Autonomous Grocery Vans Are Making Deliveries in London

 

Of course supermarkets will be trying to incorporate such systems into their business model as well but my view is that because of their underlying legacy systems they will find the transition close to impossible.

The story is about a quite limited trial but it points towards a possible future:

“On the back of the vehicle are eight pods, each with a crate that can hold three bags of groceries. The van is filled by human hands from a small distribution center—in this case, a larger Ocado van, which stores 80 of those crates—and sets off following a route to its drop-offs, which is broadly planned in the cloud but ultimately executed by the vehicle. When it arrives at an address, the customer is alerted via smartphone and must press a button on the vehicle to open a pod door and grab the groceries.”

In terms of the final use case:

“Clarke imagines vehicles like these being used to provide on-demand delivery of groceries from a small nearby distribution hub, so that instead of booking a delivery slot customers hail their groceries—when they arrive home from work, say, even if it’s late at night.”

This ties in with an interesting analysis of the IPO for Blue Apron, the food company which delivers meal recipes and the main ingredients for those meals to your door. In that analysis in the New York Times, chef Amanda Cohen theorised that the Blue Apron model may destroy itself. She describes the fact (which went against her initial view) that many people she has spoken to said that the Blue Apron process had given them the confidence to cook more. If she is correct then this means that Blue Apron is training its customers not to need it any more, not a great business model as it means lifetime value of a customer may be severely limited.

The combination of these stories may point to a completely different future. As Amanda Cohen says:

‘” In Hong Kong, many people swing by a “wet market” on their way home from work and pick up the vegetables, fish or beef they’re going to eat that night. Same thing in France, Latin America, South Korea or pretty much everywhere people don’t load up their giant S.U.V.s with giant quantities of groceries to store in their giant fridges once a week. The meal kit model of keeping some staples in the cupboard and getting the fresh stuff as you need it is the market way of doing things”

One of the major problems with food delivery systems and in particular with automated delivery systems is what do you do with the fresh stuff because timeliness and the refrigeration process really matters. This is exacerbated by the fact that people are home at different times of the day or night and cannot necessarily take delivery when the delivery system wants to deliver . Various ways of solving this have been proposed including smart delivery lockers in apartment buildings or the local post office, etc. I can see that models emerging where all of the non-fresh goods can be delivered by an automated delivery system from a small local storage facility where you request delivery when you are home, just like you do when requesting an Uber right now. There may even be discounts for people who take quick delivery so storage space is always available, or people who will take a shared delivery and therefore will wait longer.

If this is part of a wider adoption of driverless cars then it can be part of a larger change. Driverless cars do not need to park, or at least do not need to park in busy or congested areas. I am an advocate for a driverless car adoption model where government or privately owned fleets provide transport as a service and surpasses the personal vehicle ownership model that has dominated the last hundred years. Even if that does not come true individual owners can hire out their driverless car when they are not using it so it does not have to be parked in front of the house or the office, or at the train station.

I I imagine a changed urban environment where mass adoption of autonomous vehicles changes the urban landscape by freeing up parking areas on streets and parking facilities . The freed up space on streets creates the capacity for more foot traffic, and increases in safe bike lanes while, driverless vehicles increase the capacity for people to travel for short trips locally. The parking facilities can be repurposed for storage and/or specialty markets for fresh products.
In that changed local environment we could see a model where large scale supermarkets are no longer the norm, where specialty fresh food stores spring up everywhere within easy travel distance of people’s homes. These specialty stores would be powered by the back end logistics that Amazon creates for Whole Foods, or their competitors (go read Ben Thompson’s excellent post: AMAZON’S NEW CUSTOMER for more details on their strategy) You would pick up your fresh product and speciality items on your way home from work or by a short walk or bike ride, or driverless car ride to the local store. Automated vehicles would deliver the staples to your door on request using pre planned orders or automated ordering systems like the Amazon Dash Wand.

In many areas this could revive the concept of neighbourhoods that really work in urban environments.

There are many ways the supermarket model will be attacked in the future. This is just one possible scenario. Given the pace of driverless car adoption and capacity for the car industry to deliver the full model is still a fair way off. The automated delivery system is not so far off. It fits the four level of automated driving systems by being in a geofenced area (local delivery only from a small storage/transfer facility), and carried out at low speed to reduce the risk of accidents. Full level 5 driving automation where vehicles can go anywhere in all conditions and no driver actions required are a lot further off. That does not mean there will not be continuing experiments with automated food delivery systems.

As Ben Thompson states in his article groceries are about 20% of consumer spending (USA). That is a big prize and lots of people are going to be going after it. Long term an automated vehicle delivery system will be a part of that. How big a part, and in what form remains to be seen.

 

I am writing a book on the adoption of driverless cars with Chris Rice entitled Rise of the Autobots: How driverless vehicles will transform our societies and our economies. Follow me here or on Twitter for more updates as we write and publish.

Paul Higgins

 

 

 

Strategy, Digital, and Governance

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

 

 

 

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

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

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.