Jamie Ross, explains that high-quality, value businesses can be found in the most unlikely places.

  Key takeaways:

  • Not all business models fit into the traditional teachings of value investing. Economic value creation often does not immediately translate into short-term profitability which can leave many high-quality businesses hiding in plain sight.
  • Investing in a new company at an early stage in its S-curve often requires specialised knowledge and confidence to be able to determine that the early indicators of a "winning" platform. The market often lumps all these companies in the same "too hard" bucket. These are the situations that attract us.
  • GEICO provides an interesting case study into the benefits of investing in a business early in its S-curve.


Our investors will have noticed that over the past year we have been increasing our exposure to internet and digital-enabled companies. As ever, we are looking for ways to add value as active managers and this area of the market is proving a fertile hunting ground for us in our quest to find high quality, well-positioned businesses with interesting structural growth dynamics.

These investment opportunities are offered to us simply because some other value investors may not be looking at these areas of the market. In our view, this dynamic is partly the result of the way that most value investors are trained. Under the teachings of traditional value investing, many currently loss-making internet companies look outrageously, incomprehensively expensive. This leaves many high-quality businesses hiding in plain sight, as economic value creation often does not immediately translate to short-term profitability (and nor should it – which long-term investor really wants short-term profits at the expense of the long-term health of a business?).

As such, these companies may sometimes be disregarded by even the most sophisticated investors – especially those who do not specialise in technology-related investments or who feel most comfortable in the far-right of the S- Curve* (the mature segment of the curve), where (short-term) valuation metrics are more understandable. However, our experience is that these 'cheap' securities are often value traps; often they are companies ailing from technological disruption and at the beginning of long-term decline.

*The S-curve can be used to describe the performance/growth of an innovative company over time. A slow beginning is followed by rapid acceleration in growth and adoption of the technology in the mid-stage, before this growth plateaus over time. 

Often, 'new' internet-related business models are not well suited to the traditional generally accepted accounting principles (GAAP) in financial reporting. That is because, with very low (or even zero) distribution costs, the optimal strategy is often to gain as many customers for the product/service, as quickly as possible. In digital businesses, there are often significant advantages to scale, and many of these companies operate in winner-takes-all or winner-takes-most markets. The name of the game is to build, grow, and then monetise. Thus, these new businesses spend to acquire customers upfront, and then recognise revenue from those customers over many years. Frequently, this means spending a lot of money on sales and marketing (customer acquisition costs), which then depresses short-term reported earnings in the income statement.

Some of the most successful internet-focused companies in the world spent many years growing, despite producing no meaningful accounting profits. However, they are usually very profitable in terms of unit economics and very profitable as a whole once they stop reinvesting every dollar generated into further growth. We expect the world to have more of these types of businesses in the future; we are not going back to the old world. The diffusion of the internet and cloud computing will see to that. We are looking to take advantage of this by aiming to identify and invest in a select number of exceptional businesses that are riding these trends.

Jeff Bezos has said in the past that he is willing to lose money for several years on any experiment before harvesting a return. Indeed, Bezos and his management team have studied the seminal work on disruption, The Innovator’s Dilemma, by Clayton Christensen. Reading the book, one has the impression that Bezos systematically built Amazon as a disruption antidote, doing the exact opposite of what Christensen explains is the problem with companies that get disrupted. This is one of the reasons that it has been so hard to compete with Amazon, and why the company has grown into a powerful competitor in general goods and an oligopoly in the compute economy (with Amazon Web Services).

Jeff Bezos put this much more eloquently in his 2012 annual statement.

An outside observer wrote to us: “Amazon, as far as I can tell, is a charitable organization being run by elements of the investment community for the benefit of consumers,” But I don’t think so. To me, trying to dole out improvements in a just-in-time fashion would be too clever by half. It would be risky in a world as fast-moving as the one we all live in. More fundamentally, I think long-term thinking squares the circle. Proactively delighting customers earns trust, which earns more business from those customers, even in new business arenas. Take a long-term view, and the interests of customers and shareholders align.

- 2012 annual letter, Jeffrey Bezos

No doubt there are also certain crazily valued companies with share prices based on hype. But generally speaking, expectations can be very low for certain innovative companies as there are some investors that are primarily focused on “will the business even reach profitability”, without contemplating the question “how valuable will this platform and ecosystem become in the future”.

We tend to focus on business models that are easier to monitor in their early stages by the tracking of key performance indicators and we try to identify the tipping point at which profitability starts to meaningfully improve. These models are almost always winner-takes-most, where competitive and economic moats are based upon network effects. We are not looking for short-term profits, but are trying to model the moment when the ‘flywheel’ kicks in and the business becomes self-sustainable; once that occurs, monetisation and significant profits could likely be around the corner. The flywheel is a concept used to describe the process and enormous effort taken to transform a business; the concept illustrates pushing a heavy flywheel until it builds up enough motion and momentum to breakthrough.

Another feature of these internet companies is that non-financial measures can be the best signals for value creation in the early stages. Thankfully for us, some investors seem focused mainly on quarterly earnings, which, in our view, cannot tell us anything meaningful about future prospects. While eventual cashflow is crucial to ensuring the success of any endeavour, focusing on other aspects in the short term may give us an advantage of looking where some humans and machines are systematically ignoring.

When researching the type of business described above, we are big believers in speaking to as many different involved people/companies as possible. We communicate with employees, merchants, customers, competitors, etc. to piece together as much information as possible. This type of information isn’t obvious, even though it is publically available to all and it often does not show up in the financial statements until after the fact (and after share prices have moved up accordingly). It is an approach based on soft-data points and on understanding the incentives of the involved players. The market often lumps all these companies into the same “too hard” or “unprofitable and bleeding cash, so it’s of zero value” bucket and the expectations bar may be quite low. These are the situations that attract us.

Although not an internet business, the Government Employees and Insurance Company (the second largest auto insurer in the US), or GEICO, is a good example of the potential benefits of investing in a business early in its S-curve.

In 1948, the most famous traditional value investor, Benjamin Graham invested 20% of his fund in GEICO stock. It wasn’t traditionally cheap. Graham himself noted that “Almost from the start the quotation appeared much too high in terms of the partners’ own investment standards,” referring to his and his investment partner’s traditional valuation metrics.1

Over the following 24 years, the stock went up 145 x, or about 23% compounded per year; clearly a fantastic result. Graham later wrote, “Ironically enough, the aggregate of profits accruing from this single investment decision far exceeded the sum of all the others realised through 20 years of wide-ranging operations in the partners’ specialised fields, involving much investigation, endless pondering, and countless individual decisions.”1

With the benefit of hindsight we ask: Would it have been possible to foresee GEICO’s success? After all, Graham thought it was a good enough business to make it a large position.

In 1948—indeed, decades earlier—it was clear that cars were becoming vital. Government data since 1900 shows that by 1947 the registration of cars and trucks in the US had grown at 20% compounded over the previous 47 years. The population of the country had compounded at 1.4% per year during the same period. There was only one car or truck for every four people in 1947.2 Looking at this data, it was clear that there was room for continued growth. It’s fair to say, then, that autos were clearly a growth industry.

The future unfolded like this: in 1948, there were about 0.28 cars and trucks per person in the US; this increased to 0.8 in the late 90s, up nearly three-fold. Similarly, there were 41 million cars and trucks in 1948 and 251 million in 2014, up six-fold.2

What else did GEICO do? It went direct-to-consumer, bypassing the sales agent and therefore offering a product at times up to 30% cheaper. It also had superior risk targeting, underwriting lower-risk customers like government employees, teachers and veterans.

GEICO worked out for Graham because of these superior characteristics: the company had the ability to grow, and to do so while earning high returns on capital. GEICO was therefore a superior, disruptive product, riding a growing S-curve (car and truck adoption).


Nowadays, the internet has enabled two very interesting dynamics: huge growth (with zero distribution costs, companies can scale globally), and the use of very little capital (no expensive factories and stores to build). Many internet-first businesses have historically scored very highly in the high growth, high return on capital metric. And as we know, this metric is highly correlated with attractive shareholder returns.

Past performance is not a guide to future performance.

If Benjamin Graham was riding the adoption curve of the automobile in the 20th century, which technology adoption curves are we riding with our investments? There are several of them. In general, we are riding the adoption of the internet and particularly broadband around the world. It’s hard to believe, but we’re only halfway through that curve (only 50% of the world by population has internet access). On top of that, we have the shift in computing platforms from desktop to mobile to account for; every new user accessing the internet is likely doing so on a smartphone, not a PC. On top of the smartphone, then, there are several S-curves unfolding: the rise of ecommerce, which even today is only 12.8% of US retail sales3; the rise of social media (49% penetration for active social media users globally4); video and music streaming; gaming and esports; travel and leisure; the secular shift in advertising from traditional media to online; ride-sharing and autonomous vehicles. We are currently investing behind these themes with a number of investments in the portfolio.

The future is already here – it’s just not evenly distributed.

William Gibson


1 The Intelligent Investor, Benjamin Graham, 1949

2 US Department of Transportation. State motor vehicle registrations data from 1900 to 1947.

3 US Census Bureau. Data as at end 2019

We Are Social / Hootsuite Digital 2020 report. Data as at January 2020