Author: futuristpaul (Paul Higgins)

The Supermarkets Demise – A Scenario

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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

 

 

 

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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?

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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

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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)

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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.

 

Tech Toys When Simple Will Do – $100,000 V $500

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Give me $500 and I will fix the problem

 

On Monday there was a story here in Australia about traffic lights being installed in the pavement to reduce the risk of pedestrians crossing the road against the lights because they were looking down at their mobile phone screens: (Lights installed in Melbourne footpath to help distracted pedestrians cross safely)

pedstrians on phones abc traffic lights

source: ABC

Apart from the chorus of responses that people who were hit by cars when crossing against the light while looking at their phones is Darwinian evolution in action what struck me was the insane cost at $100,000 for one intersection. Now some of that cost is for the trial process but it would be enormously expensive to role out across the city. I am always reminded of the lyrics of 21st Century Digital Boy when I see this sort of stuff happening:

‘Cause I’m a twenty-first century digital boy
I don’t know how to live but I got a lot of toys

Not because of the phones but that we look at technology solutions when simple ones will do. Now some will argue that we should not be arguing about costs when lives are at risk but the hard truth is that if we spend money on this sort of thing then money is not available to spend on other things which may more effectively save lives.

Surely the simple solution here is to paint the approaches to the intersection a bright neon yellow so people who are looking down at know they are approaching an intersection and look up at the traffic lights, which are already there! This works for bikes on bike paths approaching risk areas. I have just come back from the World Science Fair in Brisbane where we walked in to South Bank from Milton each day and the bike paths/walking areas are great:

Bikeway_&_footpath_along_Brisbane_River_in_Milton,_Qld_07

Source: Wikimedia Commons

This issue is symptomatic of a wider problem across the community. As a futurist I talk to lots of people about technology, its impacts, and its capacity to change the way we live and work. However my constant refrain is if you lead a strategy with “shiny new toy syndrome” you will almost certainly fail.

Give me $100,000 and I will fix every intersection in the CBD with a paintbrush and a can of paint

Are we entering a world of the new portals?

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tim_tams

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Addendum

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

 

 

Questions on the Future of Work

/ futuristpaul (Paul Higgins) / 3 Comments

Mckinsey has released a long awaited (by me anyway) report on the future of work entitled A Future that Works: Automation, Employment, and Productivity. It is a very interesting look at the technologies which are affecting the future of human work. Every business and organisation should read it in full.

Mckinsey takes a distinctly different approach than the much discussed Frey and Osbourne Oxford report on the susceptibility of jobs to computerisation.

This difference can be best seen in the following graphic from the report:

mckinsey-work-report-2017-exhibit-e1-18-separate-activities-mapped

Instead of looking at what jobs might be replaced the team at Mckinsey have examined all the activities that each job in the USA job market entails and then looked at the various capabilities for each of those activities. They have then mapped those activities against the possible timelines of those activities being able to be performed by technology.

This is important because except for very limited cases technology replaces activities rather than whole jobs.

From this approach Mckinsey have created various forecasts for both the types of activities and the sectors of the economy as shown in the next graphic which shows their view about the ability to automate those activities.

mckinsey-work-report-2017-exhibit-e4-different-sectors-mapped

Taken in aggregate their predictions are shown in the next graphic which I have annotated

mckinsey-work-report-2017-exhibit-e6-adoption-scenarios-annotated

RED: Their median forecast that 50% of all current activities will be replaced by 2055

BLACK: The rapid adoption forecast that 50% of all activities will be replaced by 2035 (only 18 years away)

GREEN – The extrapolation of the rapid adoption forecast from 2035 that shows that over 90% of current activities will be replaced by 2055.

Mckinsey also states 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”

Apart from praising Mckinsey (which I do not normally do) for creating such detailed and interesting work, and also in highlighting the inherent uncertainty in any forecast, this raises several interesting questions in terms of impacts and change.

 

From an organisational perspective those questions include::

  1. Setting aside the changes the technology makes to our business models and speed of doing business if 20-50% of activities are going to be replaced over the next 18 years how are we going to lead our people through the continual change that is going to be required? If the average is 50% then many people will have far more of their activities replaced.
  2. If technology takes over more and more of non-routine activities in our organisation what are the skills we are going to need?
  3. If technology pushes people out of the lower skilled activities in the whole economy how many people in the whole community are capable of carrying out the higher skilled activities we will need our people to concentrate on? Will we be in an even fiercer fight to recruit the people we need?

An article in the New York Times on January 30th 2017 describes When the German engineering company Siemens Energy opened a gas turbine production plant in Charlotte, North Carolina:

some 10,000 people showed up at a job fair for 800 positions. But fewer than 15 percent of the applicants were able to pass a reading, writing and math screening test geared toward a ninth-grade education

Eric Spiegel, who recently retired as president and chief executive of Siemens U.S.A. said “People on the plant floor need to be much more skilled than they were in the past. There are no jobs for high school graduates at Siemens today.”

From a societal point of view this raises questions of:

  1. Are we heading into a period of increasing structural unemployment?
  2. How will we design an education/learning system which gives your young people the skills they need to work in the changed economy and our post school/university people the capacity to re-skill?
  3. If education is changing to be more focused on re-skilling people for jobs how do we still supply the wider general benefits of education?

Part of the answer to the second question is contained in the New York Times article where it describes the companies getting heavily involved in educating and training people with guaranteed jobs at the end of the cycle, and just as importantly no student loan debt. This was mirrored in my conversation in a trip to Austin Texas last year. Austin is growing at an enormous rate and part of the reason is that some of the major tech companies have realised that if they do not get involved with students before they graduate they may never get to hire them. So they are moving major parts of their operations closer to the Universities with strong reputations in the skills they need. University of Texas Austin happens to be one of those. Students are becoming heavily involved and supported by the companies.

When I work with clients on these issues they should be focused on the effects on their business or their organisation but the conversation always turns to the wider implications for society.

The techno-optimist argument is that technology has been destroying human jobs for hundreds of years and we have always created new ones. That is partly because we have created new capabilities that need people, but also because we have reduced the costs of inputs to make otherwise uneconomic business models viable. Mckinsey argues in their report that their median forecast results in job losses that have already been experienced in society as we reduced the human employment levels in agriculture, and then again in manufacturing. This is true if the pace remains the same.

On top of that they argue that the productivity improvements are required because we are losing the huge contribution that population growth rates have contributed to economic growth over the last 100 years. That is a good argument.

It is a brave futurist who says this time is different and it is completely plausible that the combination of new jobs being created, and the demographic change we are experiencing, particularly in developed economies will mean that we will still have close to full employment. It is also plausible that:

  • The pace of change will be at the rate that fulfills the rapid adoption scenario that Mckinsey has envisaged, increasing the rate of job losses above previous experience.
  • That as technology pushes people out of a whole range of human capability jobs we will find that a significant minority of people do not have the ability to carry out the jobs that are created.
  • That a significant group of people that have the abilities will be left behind because they cannot gain the skills required to harness those abilities.
  • That the combination of the two groups will either have to work for very low wages in order to not be replaced by technology or be permanently unemployed.

That is a recipe for societal unrest way beyond what we have seen in the rise of Donald Trump and Marie Le Pen. If the political response to the issues of the people that have expressed their frustration at the current system is to promise a greater share of the benefits of the economy and a genuine attempt to do that is derailed because of technology changes we could be in for a very bumpy ride indeed.