Opinions expressed whether in general or in both on the performance of individual investments and in a wider economic context represent the views of the contributor at the time of preparation.
Executive summary: Thematic investing is a core part of our investment process at Heptagon. Since 2011, we have published notes on over 35 distinct themes, and this constitutes our eighth annual review of the key long-term secular trends that we expect to grow in importance over time. The themes we have investigated, many of which are discussed in more detail later in this commentary, not only have the power to capture the imagination, stimulate and cause debate, but also drive a core part of our investment process. Investors can access a range of leading businesses exposed to these trends via the Heptagon Future Trends UCITS Equity Fund.
The past 12 months have proved to be busy for your author, who has travelled to 12 different countries across three continents in order to understand the future better and share his conclusions with potential investors. From Bergen to Boston, we met with management teams from over 50 corporates. We also attended trade fairs in London (AI Expo, Big Data), New York (#TechDay), Nuremberg (embedded world) and Hannover (CeBIT).
If one message proved consistent, then it is simply that the pace of innovation is accelerating. Put another way, just as manufacturing and industry were the main economic drivers of the 19th and 20th Centuries (and before this, cultivation and extraction), so those of the 21st Century will be compute power and human potential. It is interesting to note that the most applied for degree in the United States in 2017 was Machine Learning at Stanford (source: Bloomberg). We note consistently in our meetings with businesses not just that there appears to be a structural shortage of good technicians, particularly data scientists, but also that many are seeking to achieve differentiation relative to their peers through a process of out-innovation.
Regardless of the industry, technology is an enabler. When standing on a viewing platform at a salmon farm off the coast of the Norwegian sea earlier this year, the comment from our host that the process of fishing – something which humankind has done for thousands of years – was moving from ‘look and feel’ to ‘fact and information’ resonated strongly. Sure, it is possible to harvest salmon using the former approach, but by applying some of the more systematic elements of the latter, the efficacy of what you are doing can be enhanced significantly.
With the power of technology, all businesses are beginning to derive deeper insights into their operations. The term ‘artificial intelligence’ (or ‘AI’) is both over-used and often misunderstood. We would contend that rather than AI, IA is what matters. By ‘IA’ we mean ‘intelligent analytics.’ From this follows the ability to do (at least) two things: reimagine engagement and personalise at scale. In other words, the boundaries between what can be considered human-based impulse and what constitutes a machine-led input are merging, while large sets of data provide almost endless possibilities for tailoring, making outcomes more relevant for individuals. We have argued on many occasions that as future trends merge, they become mutually reinforcing.
However, despite technological change, more than half the world remains without internet access, over 1.2bn people have no access to electricity, more than 2bn do not have bank accounts and nearly a billion are short of food (source: United Nations). Put another way, although the rate of innovation is accelerating and progress has been made in so many areas, there is huge potential for so much more still to be done. Humankind has consistently shown a remarkable capacity for innovation and we do not expect this to be any different in the future.
We present our key insights below. Please note, this is a non-exhaustive list of the themes about which we have written and where we may currently be invested. Rather, the purpose of this document is to showcase how we think about the world, the way in which it is changing and what may be some of the ways to position for this from an investment perspective. Additionally, it should not be forgotten that given the nascent nature of many of these developments, several of the potentially most attractively-exposed businesses may still be privately owned rather than publicly listed.
“The market over-estimates the impact of technology in the short-term, and under-estimates the impact in the long-term,” Bill Gates, co-founder and former Chief Executive of Microsoft."
The data deluge is growing
2018 marks the first year in which more than 50% of the world’s population will be connected to the internet. This compares to a figure of less than 25% in 2009 (per Kleiner Perkins Research). Two ‘big bangs’ arguably have contributed to this growth, the first being the cloud and the second being consumer mobile. Consider that since the launch of Amazon Web Services in 2006, the number of services offered by Amazon has grown from 1 to over 140. Meanwhile, the iOS operating system supported fewer than 5,000 Apps at time of launch in 2007, compared to over 2m today (date courtesy of Amazon and Apple respectively). Thought of another way, innovation and competition are driving product improvements, usefulness and usage.
The average American adult now spends 5.9 hours a day on digital media (per Kleiner Perkins), with Facebook apps (including WhatsApp and Instagram) accounting for 32% of time and Google apps some 22% (per Visual Capitalist). No other businesses come close. Ranked by monthly average users, the social media universe can be ordered as Facebook at 2.2bn, YouTube 1.9bn, WhatsApp 1.5bn, Messenger 1.3bn, WeChat 1.0bn and Instagram 1.0bn (source: company websites). It is perhaps of little surprise that 26% of American adults now admit to being online “almost constantly” (per Pew Research).
Stop for a minute though and consider the following: a city of 1m people generates about 2m Gigabytes (GB) of data a day through its use of social media. However, this figure pales into insignificance when noting that aeroplanes generate 4m GB of data daily, while public safety systems, factories and buildings each generate around 50m GB of data (all figures per Advanced Materials, a semiconductor business). It is no surprise then, that the world is facing a data storage crunch. More data was created in the last two years than in the previous 5,000 years of humanity. In 2018, the world will only be able to store about 18% of all data generated, but on current rates of consumption growth/ storage technologies, this figure will shrink to 3% by 2030 (per Microsoft).
This conclusion has marked ramifications. First, it is necessary to prioritise which data are stored. Next, for the data to have any value, they need not only to be analysed effectively (and efficiently) but secured effectively too. Finally, while there are huge near-term opportunities within the cloud computing and artificial intelligence industries, it behoves corporates (and investors) to consider what comes next, hence why developments such as quantum computing will matter significantly. For more information, see our publications: “The Data Deluge” (March 2011), “Drowning in Data” (October 2012).
The cybersecurity opportunity
The World Economic Forum ranks cybersecurity as the third biggest risk facing the world, behind extreme weather and natural disasters. More than $55bn is spent annually on cybersecurity. Yet it still yields ineffective defences, with cybercrime having cost the world economy over ten times this figure last year, equivalent to more than 1% of global GDP (per the Ponemon Institute). The WannaCry and NotPetya attacks of 2017 have brought the issue firmly into the public domain. High-profile businesses including British Airways and Facebook continue to suffer data breaches. Indeed, since the start of this decade, there has been a 60% compound annual growth rate in cybersecurity incidents globally (per PWC), while at least 80% of European companies experienced some form of breach during 2015 (the last year for which the data is available, per the European Commission).
Only 7% of organisations are ‘extremely confident’ of their IT security protocol (per a 2017 survey by Check Point), with Chief Information Officers citing cybersecurity as their second highest spending priority (after cloud computing, per a recent study by Morgan Stanley). This should imply an acceleration of growth in spending, with the market for cybersecurity forecast to grow from $101bn in 2018 to $170bn by 2020, per Gartner. For more information, see our publications: “Watch out! The growing privacy invasion and cybercrime threat” (April 2014), “Cybersecurity: The next generation” (September 2017).
Can technology help us live longer?
Technology has undoubtedly changed how we lead our lives, but can it also help us live longer? This question matters since demographics and health are two of the most important drivers for long-term economic growth. Moreover, while there are currently around 840m people aged over 60 in the world, by 2050 this figure could reach 2bn, or more than 25% of the world’s population (per Bank of America).
It seems increasingly clear that medicine is becoming a data issue. The human body is estimated to contain nearly 150tr gigabytes of information. This is equivalent to some 75bn fully-loaded 16-gigabyte Apple iPads that would fill London’s Wembley Stadium around 40 times over. Each human genome alone consists roughly 3.2bn base pairs of DNA, equivalent to a text file of around 300 gigabytes (data per Visual Capitalist). Understand this data and scientists may understand how to save more lives.
The cost and time required to sequence DNA has come down rapidly and should continue to fall. Contrast 2011 figures of $6m per genome and a time to sequence of 10 days with current levels of $1000 and 6 hours respectively. Sequencing costs have fallen at a rate three times faster than Moore’s Law would dictate. Some 12m DNA samples have been genotyped or sequenced to-date (all data per Illumina). Today, genome analysis helps diagnose roughly half of rare disease cases six years earlier and ten times cheaper than conventional tests. Over 3,000 hereditary diseases have been identified using genome analysis, while genomics has already produced over 25 personalized drugs that are prescribed only when a patient has a specific mutation (per 13D Research). Looking ahead, the Broad Institute (a medical research centre operated jointly by Harvard and MIT) is currently decoding one human genome roughly every 30 minutes, and estimates that by 2025, some 1bn people globally may have had their DNA sequenced.
This matters since many drugs used on ill patients today are not effective (some $50bn is spent in the US on ineffective cancer drugs alone according to McKinsey), while many people that carry chronic conditions remain undiagnosed. Novo Nordisk, for example, estimates that around half of the people who have diabetes are not aware of their condition. The implications both for the healthcare industry (and for food manufacturers) are considerable.
The related dynamic is that there is increased scope for more efficient healthcare monitoring. 80% of consumers interviewed say they would adopt wearable/ implantable healthcare technology, if it made the treatment of their health more convenient. Forecasts suggest that by 2020, some 50bn devices connected to the Internet will track healthcare data, creating a market worth up to $1.6tr. Remote patient monitoring technologies could save the US healthcare system alone some $200bn over the next 25 years (all data per McKinsey). For more information, see our publications: “Reinventing healthcare: the coming of personalised medicine” (November 2012), “Healthcare transformed: how IT can save lives” (April 2013), “The man-machine merger” (September 2016).
Leveraging the Internet of Things
Under the scenario depicted above where health is monitored via wearable and/or implanted medical devices, humans can be thought of as similar to machines in the context of the internet of things. Indeed, by 2020, there will be some 20bn devices connected to the internet of things, per forecasts by Gartner. The rationale for connecting things up is simply to drive better outcomes, or efficiencies, whether these be in the field of healthcare, agriculture, science, government or industry. Many commentators believe that the largest opportunity (equivalent to 12bn of the 20bn devices forecast by Gartner) lies in industry. Whereas it may take some time for consumers to be enticed by the likes of smart fridges, the scope for improving industry efficiencies is significant.
At present, only 6% of factories globally are completely digitalised, hence why 9 out of 10 businesses say that they are currently investing in digital initiatives for their factories (per PWC). Industrial companies plan to spend up to $90bn over the next seven years on the industrial internet of things (sometimes also referred to as ‘Industry 4.0’) and are expecting $420bn of cost reductions and a $500bn revenue uplift by 2020, data again per PWC.
Much of this forecast expenditure is likely to be allocated to robots. There are currently around 1bn robots in operation globally. However, with the cost of robots falling at around 15% a year (per BCG), by 2020, this figure could reach 2.5bn, equivalent to one robot for every three people. The cost savings for a well-placed robot can be substantial. According to an example cited by the Robotic Industries Association, a trade group, a typical $250,000 installation, including training and parts, can pay for itself in two years in reduced payroll costs and increased productivity. Seven or eight years in, the cumulative cash flow gained can reach $1.5m, Once the upfront costs are paid, medium-size robots can cost just $0.50 an hour to operate, and large robots, $1.00. For more information, see our publications: “Connecting the unconnected” (July 2014), “The robots revolution” (July 2012), “Robotics 2.0” (April 2017).
The power of artificial intelligence
For data to have any value, not only does they need to be stored and secured, but they also needs to be analysed efficiently. The presence of powerful and low-cost processing chips, cheap storage capacity and the corresponding growth of massive databases of information have made AI both more potent and efficient. Simultaneously, the field of machine (or deep-) learning has expanded rapidly. Here, computer algorithms are able to recognise patterns in data and turn that data into knowledge. Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions.
When we met with NVIDIA management at their California HQ recently, they made the assertion that 90-95% of all data can have artificial intelligence (AI) applied to it. Much of what we do as consumers is indeed already driven by AI: some 80% of watch-time on YouTube music videos comes from AI-driven recommendations, while an estimated 35% of Amazon’s retail revenues result from just two features – ‘frequently bought together’ and ‘customers who bought this item also bought…’ – both the result of AI engines. Many consumers will also be familiar with interactions via AI bots (in a telephone or email format) as an alternative to functions traditionally performed by customer services or human resources.
However, the industrial opportunity is much more significant. Google has said separately that the application of its AI algorithms to its own data centres has resulted in a 40% improvement in efficiency. As the number of devices connected to the Internet grows, so should the artificial intelligence market. Microsoft believes that 85% of enterprises will use AI in at least one business process by 2020. Global AI-focused spending is therefore set to grow at a 48% compound rate of growth over the period 2017 to 2021, resulting in a $57.6bn market by 2021 (per IDC). For more information, see our publication: “The rise of the smart machine” (April 2016).
Using quantum computing to solve problems
If our expectations are that computer processing power will reach – and probably extend beyond – human capabilities, then we need a radical new way to approach computing. Quantum computers provide a solution. The systems they deploy no longer consider operations (or problems, questions) as binary, but instead ‘recognise’ all the right answers immediately. The corollary is exponential acceleration – computing power at a significantly faster rate than achieved with classical computers.
Each qubit added to a computer effectively doubles its processing power, an exponential gain not possible with classical computing (where adding bits provide negligible improvements). To provide some context: whereas a 300-bit classical chip could power a basic calculator, a 300-qubit chip has the computing power of two novemvigintillion bits (a two followed by 90 zeros), a number that exceeds the atoms in the universe. Put more simply, Microsoft believes that computers using a quantum approach will be able to perform tasks at speeds at least 400 times faster than that possible with conventional techniques.
Against this background, a quantum computer could be used to solve the problems with which humans and super-computers struggle today because they are exponentially complex. There are multiple uses to which this breakthrough could be applied. Many businesses across sectors as diverse as cybersecurity, healthcare and space/aerospace have already begun to experiment with the potential afforded by quantum computing. The quantum computing market could, therefore, be worth up to $50bn by 2030 (per BCG). IBM highlights that it already has 80,000 adopters of its commercial 50-qubit solutions. Google currently offers 72-qubit solutions and privately-owned Rigetti Computing says that it plans to launch a 128-qubit chip during 2019. IBM has suggested that quantum computing will be mainstream within the next five years. For more information, see our publication: “A leap forward” (October 2017).
The world’s largest challenge?
The world’s expanding population is posing a major test for policymakers: how to feed the world. Technology may be able to act as an enabler. Consider as a starting point that the world’s population is forecast to increase by more than 30% in the next 35 years, from 7.2bn to 9.6bn, according to the United Nations. On its estimates, by the end of the century, the world population could be over 11bn. Such growth implies an extra 220,000 people will require feeding every day. Against this background, the World Health Organisation believes that this expansion of the population implies a 70% required growth in food supply from current levels, or an expansion in farm output per hectare of at least 50%. The problem is also exacerbated by urbanisation and the corresponding advance in the middle class. By 2050, some two-thirds of the world’s population will reside in cities, according to the Economist Intelligence Unit.
Rising incomes mean changing diets. Annual meat production has risen six-fold since 1950 and by more than three times since 1970 (based on UN data). Meanwhile, a separate UN report shows that in 2014, the average person consumed 20.1kg of fish annually compared to 9.9kg 50 years prior. The problem is that animal protein production implies an accelerated drain on already-scarce resources. Consider that the production of a kilogram of beef requires around 7kg of grain and over 1,000 litres of water (data from Cornell University). At the same time, around 40% of the world’s crop production is lost annually due to weeds, pests and diseases, while around 70% of global potable water is used in agriculture (source: the UN). Moreover, the same report also observes that more than 80% of the world’s fish stocks are over-exploited, depleted or endangered. Add in the implications of climate change/ water shortages, and the gravity of the challenge is evident.
Synthetic biology (‘synbio’) represents one possible solution. The falling costs of DNA sequencing and a series of improving technologies mean that new biological entities that do not exist in the natural world can now be created. Thought of another way, engineering principles are being applied to biology for the purpose of designing and constructing new biological systems, or redesigning and modifying existing ones. Against this background, synthetic biology can therefore be thought of as providing part of the solution to the problem of peak food. The market opportunity is sizable. The global food and agriculture sector is currently worth $3.2tr, accounting for around 3% of global GDP, according to the World Bank. Within this, the meat, poultry and fish market is worth ~$740bn and the dairy industry ~$336bn. Meanwhile, the global market for flavours and fragrances is ~$20bn in size, based on data from IFF, a leading player in the sector. If synbio players could capture just a fraction of this, then it would be significant. Estimates put the industry at $4bn currently but forecast that it could reach $30bn in size by the end of the decade (per Allied Markets Research), equivalent to a compound annual growth rate of more than 40%. For more information, see our publications: “Food for thought?” (November 2016), “You are what you eat” (October 2014), “Gut feeling” (June 2018), “The curse of Coleridge (June 2011).
In the near-term, this may be the most pressing healthcare challenge facing the world. The number of overweight or obese people has tripled since 1980 with not a single developed world country having made progress in reducing these levels. Today, one-third of the world’s population (or 2.1bn) are now overweight including 671m who are obese (according to The Lancet). By 2030, this figure is expected to be 50% of the global population. Moreover, only around 55% of people with obesity have received a formal obesity diagnosis, while fewer than 2% receive some form of treatment. In the US alone, nearly 79m people are currently living (or c25% of the population) with obesity.
If left untreated, the global cost of treating obesity will expand from $0.8tr to $1.2tr over this timeframe. Moreover, people with obesity are three times more likely to suffer from a co-morbidity than non-obese people. This typically takes the form of diabetes, cardiovascular diseases or chronic kidney disease. Some 70% of people with diabetes, for example, die from cardiovascular disease, while ~40% of people hospitalised for health failure have diabetes (all data per Novo Nordisk).
Cases of diabetes are accelerating in every part of the world meaning that today, 1-in-11 adults live with the condition (per the World Health Organisation). If the above projections on being overweight and/or obese are correct, then world diabetes prevalence would reach 1-in-9 adults – a staggering 736 million people – by 2045. Consequently, annual diabetes-related health expenditure would spiral to more than $1tr in 2045, up from $775bn currently, an increase of over 29%. For more information, see our publication: “Fat profit potential?” (April 2012).
Making the most of energy
Powering computers, treating health issues and countless other activities rely on energy. Perhaps not surprisingly, global energy consumption is forecast to double over the next 50 years according to the Energy Information Administration, a US Government body. Efficient energy storage could therefore be a panacea for the energy industry, saving billions and making use of abundant natural resources such as sun and wind. The global energy storage market is therefore expected to increase six-fold by 2030, reaching $50bn in value, per Bloomberg New Energy Finance.
Over $5bn has been invested in battery storage technology projects in the last 25 years, during which time the cost of the storage battery has fallen by 90%. As a result, batteries are becoming increasingly cost efficient and are easily scalable. Against this background, some 50% of global energy could be provided by renewables by 2050 (all data per Bloomberg). Although Tesla’s gigafactory has received much profile, consultants such as Benchmark Intelligence believe that a further 22 such factories could be opened within the next decade, with storage batteries sold on a mass-market basis to utilities and heavy industry as well as to households for their own needs. For more information, see our publications: “Winds of change” (March 2018), “What if the sun always shone?” (September 2015).
The future is – by definition – unpredictable, but we know that innovation cycles are accelerating and that few industries will be untouched by change. Industries such as manufacturing and healthcare have already been disrupted as have those such as finance, retail and transportation, none of which we have discussed in detail in this commentary. Readers interested in these latter topics should refer to our notes of May 2013, February 2015, July 2015 and January 2018 regarding the future of finance (where cashless payments, digital currencies, peer-to-peer lending and blockchain respectively were discussed); of February 2014 relating to online retail; and April 2015/ February 2017 on the future of the car in particular and transportation in general. All our previously published thematic commentaries may also be found on Heptagon Capital’s website.
When we think further ahead, blockchain, gene-editing, implantable devices, nanotechnology, quantum computing, self-sufficient energy ecosystems and more will continue to change the world in which we live. Our process of research, investigation and identification of potential new businesses in which to invest remains an ongoing one. Expect more in 2019.
“This time is always different where technology is concerned. That, after all, is the entire point of innovation,” Martin Ford, academic
Alexander Gunz, Fund Manager, Heptagon Capital
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