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The power of network effects and how they work
The Power of Network Effects and how they work This blog has been written based on the book “The Cold Start Problem” by Andrew Chen. It is an exceptional book written from his experience at Andresen Horowitz - a very successful and well know VC fund. We have struggled to find a concise resource that unpacks network effects and this was a great book to develop our understanding. Network Effects A network effect describes what happens when products get more valuable as more people use them. The network effect was first described by AT&T President Theodore Vail who described the telephone as useless without someone on the other end of the connection. As highlighted on the cover photo, AT&T advertised the value of connecting with others, not the telephone hardware. In the case of the telephone, there are two things at play; a) the physical telephone and b) the network of connections that you can call. A successful network requires both a product and its network. For example, Uber has an application (product) and active users to request a ride (network). In today’s world, many network effect products are made of software and the network is the people that are connected to each other. How to tell if a business has a network effect? 1- Does the product have a network of users? Does it connect people with each other whether for commerce, collaboration, communication, or something else? 2- Does the ability to attract new users become stronger as the network grows? Often the answers to the above are not binary and have different degrees of strength. The History of Network effects There was tremendous excitement about network effects in history and the 1999 Dot Com boom was amongst the greatest. From 1995 to 1999 the NASDAQ rose over 400%. In 1996 only 20M users had access to the internet and this connection was 24kbps dial-up speed. Today there are 5B internet users with an average speed of 80Mbps (3,000x greater). Despite how early we were in internet adoption the market became excited, at its peak, AOL was worth $224B and was one of the most valuable companies in the world. The early excitement stemmed from a principle called Metcalfe’s law which is defined as: The systemic value of compatibility communicating devices grows at the number of connections squared. This is arguably why valuations of internet and technology businesses are initially so confronting - the growth is non-linear and therefore difficult to value on a static valuation. As a company doubles its users the network's value is 4x not 2x. Metcalfe’s law however has some drawbacks because it is solely quantitative. It fails to take into consideration the quality of engagement, the differences in network types, and the crowding effect to mention a few. Network effects don’t only exist in PC networks they exist in biology where some animals live longer when in a large group (safer from predators, finding food, etc). This is knowns as the Allee effect. There is a point known as the Allee threshold were below this point growth turns negative, These groups tend to go toward zero. It goes without saying these principles apply to technology products, until you hit density people don’t have a lot of incentive to connect, beyond this tipping point the benefits rapidly accelerate. Networks can become overcrowded though for example when a communication product starts sending too many irrelevant messages or a social product filling up with irrelevant content or too many listings for a marketplace. This overcrowding among other contributors can lead to a network collapse, and this relationship works in a similar way, when a few nodes disconnect the value reduces slightly but when they reduce beyond the tipping point the value disappears rapidly. Self-sustaining small networks and Slack Given the power of network effects, it obviously begs the question of how to get beyond the tipping point to allow the network to create the perpetuating value. Chen outlines in the Cold Start problem that to start a new product with network effects the first step is to build a single, tiny network that’s self-sustaining on its own. This sounds straightforward but it is not. An extreme example of building a small network was Tiny Speck. Tiny Speck was a company that raised $17M from top investors and was led by star founders who had done it all before, they went on to hire 45 developers and build a multi-player game called Glitch. It was a complete flop and within 4years it was shut down. It was observed during prior analysis that 97% of the players that signed up left within 5 minutes and given the benefit of the game was derived from the interaction with other players it seems clear in hindsight that the rapid churn was the issue. It simply never got the scale to produce any benefits for players. The great irony from this story was that the derivative effect of developing Glitch was that Tiny Speck needed a way for the 45 engineers to communicate with each other (The Tiny Speck Network). At the time (2009) communication tools supporting remote work were near non-existent. The team used an old tool called Internet Relay Chat (IRC) which was clunky, but it did the job, to improve it the team built some additional functionality to make their work easier. When Glitch eventually failed Tiny Speck focused on this IRC product which they renamed to “Slack”! it ended up being taken over for $28B by Salesforce. Once companies started communicating with Slack it became self-sustaining as a communication utility, a slightly lower churn rate than Glitch! The key to getting a small self-sustaining network cranked up is to capture the “hard side” of the network – the small percentage of users who do most of the work on the network. Once you have captured the network the point at which they become self-sustaining depends on the product, some examples are: Slack: Requires 3 people to really work but according to founder Stewart Butterfield after 2,000 messages 93% of people are still using Slack today. Zoom: You just need 2 people – one who wants to call someone else. Airbnb: According to Co-Founder Nate Blecharczyk 300 listings with 100 reviewed listings was the magic number to see growth takeoff in a market. Uber: ETA’s down below 3minutes on average and get 15-20 online cars on the road at the same time. The overall key takeaway is to add a small group of the right people at the same time using the product in the right way. A common thread among the big network effect companies is that they all started small and built these small networks into large groups of networks. The 1% - Hard Side of the network As mentioned earlier a key contributor to building the first network is winning the key network contributors. Nearly every network has them, the starkest example is Wikipedia. Wikipedia is one of the top 10 visited websites in the world and generates 18 billion views and 500 million visitors a month. It is a networked product with editors contributing articles and visitors reading them. Since it was founded in 2001, more than 55 million articles have been written and are over 90 times larger than the Encyclopedia Britannica. The amazing story of Wikipedia is that this enormous amount of content has been created by a minuscule population of only around 4,000 active editors. One extremely hyperactive editor is Steven Pruitt; he is a US customs officer during the day and in his spare time voluntarily edits for Wikipedia. He has made nearly 3 million edits and written 35,000 articles. He was named one of the most influential people on the internet in TIME magazine for his contribution. When you look across user-generated products this is the norm, not the exception, some more examples are outlined below: Uber: 100 million riders, 2 million drivers, 20% of these drivers create 60% of the trips. YouTube: Two billion active users but 2 million users that upload videos. Consumers are typically easier to capture and retain than contributors and this is mainly due to the 1/10/100 rule: 1% of the user population might start the group or thread within a group 10% of the user population might participate actively by authoring content or responding 100% of the user population benefits from the activities of all the above groups (Lurkers). The 1% of users becomes extremely valuable to a network and this is because of what’s known as the “Power Law”. Instagram and YouTube both refer to this power law as the top 20% of influencers or content creators capturing most of the engagement, attracting millions of followers and tens of millions of views. It’s important to understand the motivations of these key contributors and focus on aligning product functionality and the business model towards them, some examples are below: Social Media: Status – Social feedback loop. Would the creator be disappointed if no one saw it? Communications Apps: Utility - Deepening relationships with friends. Marketplaces: Economics – making money Multiplayer Games: Fun and status – enjoyment. Marketplaces Marketplaces tend to revolve around sellers, these are the users that are difficult to get. It’s referred to as “supply” and is the workers and small businesses who provide the time, products, and effort to try and generate some income on the platform. The first move for a marketplace is to build a critical mass of supply onto the marketplace. Once you collect the supply, typically you need to bring on-demand but then follow up with more supply quickly. The normal order of events is supply, demand, supply, supply, supply! Sometimes the easiest supply to capture is assets or time that are underutilized: Airbnb: Underutilization of guest bedrooms and second homes Craigslist and eBay: Selling the stuff you don’t want anymore Uber: Using your car to earn some income Killer product – sometimes doesn’t need to be new or complicated Zoom is the best example of a killer product unseating long-standing providers with the best killer feature of all - the “it works” feature. Zoom was founded in 2011 and grew from 10 million daily meeting participants at the end of 2019 to over 300 million just a few months later. The Zoom product that seemed too simple allowed a frictionless experience of inviting and having a meeting that ultimately enabled and accelerated the viral expansion which continued to reinforce the network effects and kept engagement high as its user base grew. It is easy to think that Zoom’s simplicity was its competitive advantage, but this kind of simplicity is very hard to implement in practice. It is a distinctive quality of networked products - they do one thing well. Networked products such as Zoom and Twitter facilitate an experience of interacting with other users. This is why they appear to feature not products. Contrast this to traditional products which attempt to build out functionality improvements which improve the engagement with the product. Eric Yuan, Zoom founder, said when studying the network experience “...I studied the Dropbox pricing strategy and wondered why did they start charging at 2GB instead of 1GB and I realized the more you use a good product the more likely you are to pay – I started Zoom pricing at 40mins so people could get the full experience”. Networked products love to be free. In summary, the ideal product to drive network effects combines both factors: simple to use and understand at the same time. It needs to bring together a network of users that is hard to copy by competitors. User Experiences to build the network One of the most important parts of building a good experience is avoiding what Chen refers to as “Zeroes”. These are events where the experience of the user is a zero. When building a network effect it’s crucial to avoid these user experiences, some examples are below: Uber: Rider opens the app to hail a ride and there are no drivers available Monday: User logs in and missing documentation needed for work that no one has filled out Slack: Log into contact another user and that user hasn’t downloaded yet Social Network: Sign up and no friends or favorite content is available To avoid these zeroes is not as simple as adding a user, it needs constant activity to be built substantially. The real cost of a zero experience has lingering destructive effects because users churn and don’t believe in the reliability of the service so can be lost forever. The Tipping Point There are many ways to get to the tipping point but ultimately it is the point at which the virality, stickiness, and monetization start to scale on their own, “when a product can grow to take over a whole market”. There are many ways to nurture the scalability of growth such as: Invite Only strategy: LinkedIn, Facebook, and Gmail used this approach. The main reason it works so well is that it naturally provides a good experience where your known connections and friends are already connected because they invited you – ensuring you get a good first experience. Come for the Tool, stay for the network: Instagram is probably the best example. It unseated Hipstamatic because they attached a network to a photo filtering app. The tool attracts users, but the network makes them sticky. Some more examples are: Instagram: Create photos + Share Asana: Organize + Collaborate GitHub: System of Record + keep up to date with others Glassdoor: Lookup + Contribute with others Paying up for Launch: It's sometimes smart to get the market quickly by paying up for density. Coca-Cola did this best with coupons - handing out free coupons to everyone to redeem at the store (resulting in lots of stores stocking Coca-Cola). Visa also did this by mailing out credit cards to attract merchants (resulting in the new Visa card being accepted at hundreds of stores). Partnering: Piggybacking off an install base can leapfrog adoption and be a smart way to hit scale quickly. The best example in history of this is Microsoft/IBM. MS-DOS was custom built for IBM and got the immediate scale to attract the most developers, which then went on to attract users and then PC makers. MSFT went on to capture 80% market share for operating systems. Competitive advantage of Network Effect businesses In summary, the competitive advantage of a network effect business model comes from its users, not the product, and this is difficult to replicate. This has been highlighted several times with the best-case study being Airbnb vs Wimdu. Wimdu vs Airbnb: The Samwer brothers in Germany almost exactly copied Airbnb’s website design and business model and scaled extremely fast raising $90M (The largest investment in a European start-up ever) and hiring 400 staff in less than 100days. Wimdu went on to attract 50,000 listings and $130M of revenue within a year. However, within 2 years Wimdu went to zero. All the scale they rapidly attracted was poor quality and the users had a poor experience. One of the early employees at Airbnb quoted: “Not all supply is created equal, Wimdu’s top 10% of inventory was our bottom 10%. Customers were unhappy with their experience, and you need this high NPS to get viral growth”. I would encourage anyone who enjoyed this blog to buy the book as it covers much more detail than I have highlighted here. I hope you enjoyed the read. Regards, Shaun Trewin CA Quality Compounders
The everything store - The pessimists sounded smart ... while the optimists made the money
Good morning, In 2007, the consensus analyst forecast for Amazon's 2020 sales revenues ranged from $26 billion to $27 billion. In 2020, Amazon achieved $386 billion. The pessimists armed with their myriad of reasons continually sounded smart undercooking their forecasts, while the optimists made a killing! The pessimists sounded smart in 1996 outlining why Barnes and Nobel would crush Amazon’s bookstore. They sounded smart when eight executives and one board member left between 2002 and 2003. They sounded smart in 2005 when google (who had a large market cap at that point) launched their eCommerce offering – Froogle … and few sounded smarter than hedge fund giant, George Soros when he told the investment community that he was short Amazon in the depths of the GFC. The Amazon story has been retold thousands, if not, millions of times by journalists, analysts, students, and industry participants. Despite this, we still think it is worth taking the time and trying to understand why so many missed it and how one man managed to disrupt two major industries – retail and computing. The everything store, authored by Brad Stone, is possibly the most comprehensive recount of Amazon’s journey from start-up to 2014. Stone does a great job, detailing the major events in the business’s life through 300 interviews with former staff and from fifteen years of reporting on the company for the Newsweek, the New York Times, and Bloomberg Businessweek. Amazon’s skeptics have been well documented through time, none more than Jacqueline Doherty, the Barron’s journalist who published the article Amazon.bomb in May 1999 (attached). However, it was only when reading Stone’s book did, I really grasp the sheer number of times the ‘pessimists would have … sounded smart’ over the past 25 years. For investors, the big gains only come through holding compounding machines over long periods of time, which is far easier said than done. There are few better examples of this than Amazon, trading at $86 ($30.05 billion market cap) and 70x sales in March 1999, before falling 93% over two years and nine months to $5.97 ($2.21 billion market cap) or 2x sales, in September 2001. Today, the stock 547x higher, at $3,271 a share ($1.6 trillion market cap). Like all great founders, it was the crisis that defined Bezos. Prior to the ‘.com crash’, capital allocation was aggressive, with Bezos using debt to bet big on anything that was a ‘.com’. However, it was only the busting of the bubble along with meeting two retailing greats in Sam Walton (Walmart founder) and Jim Sinegal (Costco founder) did Bezos reassess and turn his laser focus to lower prices, developing technology organically, and only betting on an acquisition when he knew the flywheel was turning. Using Stone’s work, I’ve tried to document the many times the ‘pessimists sounded smart’ and how ‘the optimists made money’ in one of the greatest compounders of all time. How the pessimists sounded smart Short sellers & Bezos sell down There are few pessimists who can sound smarter than a short seller armed with a few expert calls and a short report. Amazon was publicly shorted not once but twice! The first by a 28-year-old Lehman Brothers convertible bond analyst – Ravi Suria who drafted a research paper shortly after the Nasdaq peaked in March 2000, outlining why Amazon would run out of cash ‘in just four months’. Ravi continued to pummel the company with negative reports throughout the summer of 2000 causing the stock price to fall from ~$57 to $33 and also causing suppliers to start to question the businesses viability. Adding fuel to the fire was a $12m sell down from Bezos which lead to an SEC investigation after it was found that Amazon had seen a Lehman’s negative research report prior to it being published to the market. It was during this period that Bezos wrote on the wall of his office “I am not my stock price” … telling his staff … ‘don’t feel 30% dumber when your stock is down 30%’ … and … ‘don’t feel 30% smarter when it is up 30%’. Amazon was again shorted in 2008 by one of the biggest names in the business – George Soros. At a hedge fund conference in New York during the depths of GFC Soros name just one stock that he was shorting as the world was falling apart: Amazon. Culture & staff turnover Former staff are rarely a source of unbiased opinion however poor staff reviews coupled with high staff turnover can often tell you something is awry with management. A common quote amongst Amazon employees was ‘if you’re not good, Jeff will chew you up and spit you out. If you’re good, he will jump on your back and ride you into the ground.’ There were numerous bouts of layoffs in key management, Stone noted staff turnover was typically high however the period following the tech bust from 2002 to 2003, was one of note with departures from: Doug Boake, Business Development Executive David Risher, Head of Retail Joel Spiegel, VP of engineering Mark Britto, SPV, Worldwide Services and Sales Harrison Miller, VP, and GM of Platform Services Chris Payne, VP (numerous departments) Warren Jenson, CFO Scott Cook (founder of Intuit) - left the board for eBay Amazon once had a management policy in place that required managers to fire a certain percentage of underperforming staff each year. However, this policy was revoked when managers were found to be hiring those, they knew they would fire! Dealing in the grey market Initially, Amazon faced the ‘chicken and egg’ problem. Customers would only shop where they were offered an adequate range and suppliers would only supply where there was adequate demand. Early on, the likes of Toshiba, Sony, and Samsung viewed internet sellers like Amazon as ‘sketchy’. Their views were only confirmed when Sony executives who were visiting an Amazon fulfillment center, found unauthorized stock all over the floors! Debt used to fund failed acquisitions Between 1998 and 2000, few companies bet bigger on the internet than Amazon, who raised $2.2b via convertible bond offerings to fund acquisitions. To help the process, Amazon hired Randy Tinsley from Intel in 1998, who said to Bezos … “I’m really looking forward to going shopping with you.” Bezos and Tinsely acquired movie database IMBD.com; the British Web Bookstore BookPages; the German Web Bookstore Telebuch; the online marketplace Exchange.com; the pioneering social-networking service PlanetAll; and a data collection company called Alexa Internet. They also acquired same-day delivery business kozmo.com and comparison website Junglee, which was shut down quickly after it was diverting traffic from Amazon’s website. In addition, Amazon’s venture arm invested in pets.com, gear.com, wineshopper.com, greenlight.com. homegrocer.com – almost all of which went bust in the .com crash. Aggressive accounting Following the late 90ies acquisition binge and the attention Amazon was getting from short-sellers, Bezos reviewed the cost base and in early 2001 wrote an internal memo to staff declaring that the business would be breakeven by the fourth quarter that year. Bezos announced this publicly to investors later that year, stating that the company would be profitable based on ‘Pro-forma numbers’ which excluded stock-based compensation and some other expenses. Competitors The wall of competition Amazon faced was nothing short of intense. The first major threat came just two years into business (1996) from dominant book retailer, Barnes, and Noble. Founders, the Riggios brothers, told Bezos over lunch that they intended to launch their own website to directly compete with Amazon. At the time, Barnes and Nobel was doing $2 billion in sales v Amazon's $16m. A year later, Barnes and Noble filed a lawsuit just prior to Amazon’s IPO, alleging that Amazon was falsely advertising themselves as the ‘world’s largest bookstore’. In 2005, Google showed up, launching Froogle. A direct competitor to Amazon’s eCommerce business. In 2010, Walmart, Best Buy, Home Depot, and Sears coordinated in backing a new organisation called the Alliance for Main Street Fairness - designed to lobby against online retailers to start collecting sales tax – a significant advantage Bezos didn’t want to lose. In a similar attack, over the course of 2009, the chiefs of the six major US publishing houses – Penguin, Hachette, Macmillan, HarperCollins, Random House, and Simon and Schuster – gathered allegedly to discuss their shared predicament of the Kindle’s $9.99 new releases. How the optimists made money While the pessimists piled on reason after reason, the optimists saw a rare founder CEO who had significant skin in the game and was obsessively frugal and customer-focused. Who instilled a culture of learning and decentralized thinking. Who communicated in an extremely shareholder-focused manner and incentivised his staff to think and act with only one-time horizon in mind: long term. Thanks for reading. Lachlan Morgan, CFA
Watching out of FOG
FOG … ‘Fact Obfuscating Generalisations’ … or as Ray Dalio (founder of Bridgewater – one of the world’s most successful hedge funds) would call it … ‘mouth farting’. FOG is a term I discovered in the book … Investing between the lines by LJ Rittenhouse. Investing between the lines caught my attention whilst skimming the shelves of ‘The Bookworm’ – the local Omaha bookstore at the Berkshire Hathaway annual meeting. Rittenhouse makes the point that a CEO's letter is a far more powerful research tool than many investors appreciate – a conclusion we strongly support. As Mark Twain would say … ‘the difference between the right word and the almost right word is like the difference between lightning and the lightning bug’. We believe the annual letter is the only opportunity that CEOs can address all businesses ’ key stakeholders at once. The annual letter is a document that can be read by shareholders, customers, potential customers, employees, potential employees, suppliers, and in some cases, regulators – hence we find it amazing that most CEOs are willing to outsource a document that could potentially impact both the quality of employees and customers the business could attract. How do we know so many CEOs outsource the writing of their annual letter? Because they are full of what Rittenhouse calls ‘weasel words, cliches and jargon’. Words such as ‘solid, momentum, enhancing, eco-system’ or cliches such as ‘we are a customer-first company’. These words left on their own or lacking context indicate that a CEO potentially doesn’t have a strong grasp on what is happening at the ‘coalface’ of the business. Rittenhouse provides many examples throughout the book, the most notable being that of notorious corporate failure - Enron. Rittenhouse noted the following passage in CEO Jeff Skilling annual letter from the year 2000: ‘Our talented people, global presence, financial strength, and massive market opportunity have created our sustainable and unique businesses. EnronOnline will accelerate their growth. We plan to leverage all of these competitive advantages to create significant value for our shareholders.’ In one short paragraph, Enron introduced six popular clichés: Talented people Global presence Market knowledge Financial strength Leverage competitive advantages Significant value for our shareholder We look for CEOs who can simply explain, through vivid examples the link between employee and customer satisfaction … with shareholder value. As Rittenhouse explains - without a commitment to transparency from the top, lawyers, professional directors, and communication consultants will do their best to dilute the CEO’s message and keep readers confused. Investors who find CEO letters riddled with generalizations need to ask: does the CEO not understand the business or does he or she not want the owners to understand it?!?! A long-term holding in the Quality Compounders portfolio – Mainfreight – is one of the best examples of a management team that more than understands the importance of using their annual report to communicate to their various stakeholders – the 2021 annual report (attached) is indicative of their typical annual report: Chair, founder, and Mainfreight’s largest shareholder, Bruce Plested mentions ‘customers’ three times and ‘employees’ four times CEO and Mainfreight’s fifth-largest shareholder, Don Braid mentions ‘customers’ 14 times and ‘employees’ nine times Every employee’s name is listed in the annual report … under the heading ‘Thank you to this extraordinary team …. You are our heart and soul’ Key operating statistics - which include things such as Transport loading errors; Number of training courses completed by their staff; Inventory Record Accuracy … these statistics are provided with year-on-year comparisons … just think how powerful this is when pitching a new account! ‘Five-year road map’ – where management provides details on their key growth initiatives along with targets for these key initiatives Explicit statements about their culture and values ‘staying our 100-year course’, ‘culture continues to forge our future’, ‘there is no place for mediocrity’, ‘look after our people and look after our customers’ Well-considered annual letters and reports are few and far between thus we believe it can offer one of the simplest and most effective ways to assess the quality of a manager. A list of the best CEO letters we’ve studied include: Warren Buffett, Berkshire Hathaway Jeff Bezos, Amazon Mark Leonard, Constellation Software Tom Gainer, Markel Corporation Jeff Lawson, Twillo If you know of any exceptional CEO letters – please let us know. Thanks for reading, Lachlan Morgan, CFA
Rags to Riches – The story of the humble uniforms and laundry 400 bagger!
“Pinch Pennies. Work Hard. Make Sacrifices. Reinvest in the business. And go for the long term” Cintas. What an incredible founder-led story about a family-owned business growing up to a 400 bagger since IPO in 1983. Cintas was listed in 1983 at an equivalent share price of $0.94 and has grown to over $400 in 38 years, generating a share price CAGR of ~17.3%. Compounding is the never-ending lesson; these numbers still surprise me. In May 2004 when this book was written, Cintas had completed its 35thconsecutive year of growth in sales and profits. At the time of writing the only other public company to have achieved it was Wal-Mart (a few others reached the benchmark but couldn’t maintain it for so long). Cintas achieved a 35yr record of 23% CAGR in sales and 30% CAGR in profits to 2004. What a compounding machine. There are some distinct patterns evident in the way Cintas achieved such enormous scales as decentralized management, incentives, and culture. The book Rags to Riches is written by Richard T Farmer who was the president and second-generation family founder, Richard’s grandfather ‘Doc’ Farmer was the original founder of the business which was invented out of the “grinding poverty of the great depression”. A summary of some elements of overt high-performance culture through the Cintas history include: A 10yr stock option plan with none vesting for the first 5 years and then 20% each year after. Cintas managers always wear business attire, no casual Fridays, our business is making people look sharp - lead by example. Operate exceedingly clean plants, Farmer used to inspect the bathroom as a key indicator of manager quality Even while a private company the profit and loss was shared with all employees every year To improve profitability incentivize the team to satisfy customers, increase competitive advantage and be more productive. Cintas started its life as Acme Wiper and Industrial Laundry. Acme Wipe’s core business was collecting used towels from industrial factories, These towels were then washed and resold back to industrial customers. Acme Wiper then discovered they had a core competence in servicing customers with regular clean garments which eventually lead to outsourced cleaning and provision of uniforms. The business has since grown into one of the largest service businesses in the world. Culture “You’ll hear lots about culture in this book. It is, without doubt, our most important competitive advantage. Competitors can copy our sales material, our products, and even some of our systems but they cannot copy our culture”. Farmer outlines at the end of the book that to achieve the grand ambitions he needed very talented people however, he was always more comfortable with “partners” than “employees” so whenever he came across exceptional people, he saw to it that they were owners and partners in the business, not just employees. Farmer outlines that the best way to communicate the culture of a business is by telling stories about where and how it came about, this is almost exactly the way Bezos describes culture at Amazon –“stories of past successes and failures that become a deep part of company lore”. Some of the stories about how Cintas grew its culture came from near-death experiences. In 1945 when Cintas was a small family business with 12 employees the factory burned down and although there was insurance it wasn’t enough to truly rebuild the business. Doc Farmer exclaimed that “we are not out of business! you can take our equipment, but as long as we have our people we’ll be okay”. Having to rebuild from nothing with only your staff teaches you the true enduring nature of your people. Another story about the workplace environment was developed through many experiences including Richard working in the drying room which was stiflingly hot, lifting heavy drums of wet rags that were 200 pounds apiece, eating lunch in the restrooms because there was no lunchroom, scooping out grease from the sump pit by hand in waist-deep oil and grease. All these examples enforced the culture to provide a safe and enjoyable workplace. Incentives – the rule of 35 “I’ve always believed there is nothing more motivating than ownership” There were a lot of factors involved in creating such a motivated group of people but one element was how we compensated them. The compensation program worked like this. A General manager of a plant was paid a salary of $10,000 a year. That’s it. Everything else depended on how they performed. They were entitled to six percent of the profits after expensing all corporate overhead and taxes. And Cintas still do it that way today. Each business unit (Plant or branch) would have a separate profit and loss statement and the GM is totally responsible for that P&L. They are running their own business. Each GM reports to a vice president who also only earns a modest salary and earns a profit of the group of business units reporting up. During the 80s the rule of 35 was born. It was designed out of the experience that a GM could greatly increase short-term profits by cutting back on investing in advertising and sales. Conversely, a manager could invest in future profits by ramping up sales growth. Some markets also had differing sizes and opportunities. Farmer announced at a managers meeting “wouldn’t we be just as happy if a manager increased sales by 25% and had a profit margin of 10% as we would be with 25% margin and 10% sales growth?”. The rule of 35 was born. The nexus of the Cintas stock option package started in 1967 when Farmer employed Bob Kohlhepp. When Farmer met with Kohlhepp it was suggested they become partners it worked like this, Farmer sold stock to Kohhlepp at a fair price, instead of paying in cash the company lent the money and kept the stock as collateral. This loan was non-interest bearing but would be terminated if certain events occurred such as departure from the company. Farmer always focused on finding ‘partners’ not ‘hired hands’. Vision “I painted my vision for our people at every chance I had – that was their light at the end of the tunnel. That was the great motivator when times got tough” Farmer tells the story of a man walking down the street in the middle of a big city and how he came across a construction site. He came across three men in a ditch, he asked the first man what are you doing? “I’m digging a ditch,” the first man said, he then asked the second man what are you doing? “We’re digging a ditch for the water line for that building going up over there”. He then asked the third man what are you doing? The man looked up and said, “we’re building a cathedral. It will be big and beautiful with five big spires and large stained windows and it will seat 500 people the biggest in this city”. The third man is proud of what he is doing because he shares the vision. This simple story demonstrates why it is important to have a vision and share it with everyone. Tom Dick or Harry? “One of the disappointments I’ve had over the years is watching promoted individuals experience failure – It’s a fact of life that some people are more talented and capable than others” When conducting performance review Farmer continuously used the Tom Dick or Harry story and it went like this. There was once a gentleman in New York City with three sons. All of his sons had the same education, same household, and worked for the same company but one was much more successful than the others. One day the father called into their place of work to see if he could understand what was happening. After he met the owner and asked “could you explain to me why Tom is doing so much better than the others” the owner said of course why don’t I show you. The owner called Harry into the office and said “Harry, there is a Russian ship that just arrived at the dock. I understand it has some beautiful furs. Would you go down and check it out and let me know what you think I should do?” Harry disappeared and came back shortly after “you’re right boss there is a Russian ship there. They have lots of furs and would like to sell them if possible, would we have any interest?”. The boss said he would consider it. The owner then asked Dick to undertake the same errand. Dick returned and said, “You’re right boss. There is a ship loaded with magnificent furs. They have 5,000 mink furs. 2,000 sable furs, and 3,000 lynx furs. They want $1.3M what should I tell them?”. The owner said he’d think about it. The owner then called in Tom and asked the same. Tom returned and gave his report “Boss you’re right. There is a Russian ship loaded with outstanding furs. They have 5,000 mink furs. I took three people down with me to inspect them. They are A-Grade quality. They have Sable and Lynx furs which we inspected also. They want $1.3M I offered them $1M cash payable in 10days. They agreed and I have the purchase order for you to sign if you would like to proceed. I have also organized our warehouse to take possession, if you sign this I will make it happen”. The owner of the business said to the father – see your other two sons are great but Tom is a star. After telling this story in the performance review Farmer would ask so which son are you? It was a great way to explain the different values. The Cintas Growth Engine “I was aware early on that our industry was going to consolidate” In the 1940s and 1950s, there were numerous family-owned breweries in a single city, by the 1960s these were gone. The dairy industry was the same. The Cintas strategy was to play a major role in the consolidation of the uniform industry. Cintas made very few acquisitions during the 1970s except for one small company in 1973, this was because of the new fabric technology (Permanent press uniforms). Cintas began making acquisitions from family-owned businesses that didn’t even keep accounting records. By the mid-1970s Farmer and the team figured that there were some 1,000 companies in the uniform industry, most of these were family-owned and operated and the majority had made the upgrade to the new fabric. The team made a list of them and graded them by priority. Alongside the acquisitions, Cintas was rolling out new factories in new regions that leveraged their network. As Cintas continued the aggressive rollout across the country, they encountered some resistance (legal and illegal), when they entered the Cleveland market a large competitor called WorkWear decided to counter-attack Cintas on their home turf in Cincinnati. WorkWear approached every Cintas customer and offered to slash prices, to defend the home market Cintas went and visited every customer and offered them a piece of paper and a pen with the opportunity to “name their price” most customers handed it back and ignored the opportunity for the discount. The IPO At the time of the IPO in August 1983, Cintas had 23 operations and a little over $60M in annual revenues. The company is listed with a market cap of $110M (an adjusted share price of $0.95 today). The stock price was a 50 bagger from the IPO price to December 1999 (26% CAGR), after this it went sideways for almost 14years after which it added another $400 per share or 400bags from the initial investment. Cintas has grown revenues from $60M in 1983 to over $7B today. What an incredible story of growth! Hope you enjoyed the read. Shaun Trewin CA Quality Compounders
The power of Increasing Returns, Lock in and Learning Systems
The insights from this blog have been drawn from the book Complexity by M. Mitchell Waldrop. This book outlines how a group of diverse Scientific luminaries including several Nobel Laureates developed the Santa Fe Institute to study complexity – how single elements organize themselves into complex structures. This think tank made several revolutionary discoveries that impacted many sciences from biology to economics. Sounds heavy. There were a few key points my small IQ could understand. Increasing Returns Why have high tech companies scrambled to locate to Silicon Valley? Why did the VHS system take the market from Beta despite it being technically inferior? ‘increasing returns’ is a mental model that is well known in Biology and Engineering also referred to as positive feedback – like mild tropical winds growing into a hurricane, seeds and embryos growing into fully developed creatures. The neoclassical economics theory assumes the complete opposite that the economy is dominated by negative feedback – the theory of diminishing returns being that twice the fertilizer doesn’t produce twice the crop yield and that the economy finds an equilibrium and harmony. In some cases, this is very true take for example a business enjoying a large margin with no competitive advantage a competitor is incentivized to enter and share the margin with the incumbent hence finding an equilibrium rather than the incumbent continuing to grow and taking the entire market. Technology however is different. Take for example the QWERTY keyboard, this was invented by Christopher Scholes in 1873 specifically to slow typists down to prevent jamming in typewriters, this technology was then mass produced by the Remington Sewing Machine Company which meant the entire market was trained using this layout, therefore locking this in as the standard forever. Consider the VHS videotape format that by luck gained a slightly larger market share initially which was compounded by the big incentive of video stores wanting to stock only one format and users only wanting one video player which led to VHS dominating the market despite it being inferior to Beta. Interestingly, in any system there are patterns that are the result of a rich mixture of positive feedback and negative feedback. For example, spilling some water on a polished tray would result in a complex pattern of beads that forms as the result of 3 things: Negative feedback system of gravity forcing the water flat, Positive feedback system of surface tension attracting water molecules together, and LUCK through tiny accidents of history small dust motes and invisible irregularities of the tray Its not a linear process from adoption to lock in and many feedback systems contribute to it, some of which are unpredictable. Technology Lock In An intriguing example of technology lock in is the internal combustion engine. Gasoline powered engines were considered dangerous, less efficient, noisy and gas was hard to obtain in the right grade. Despite all these shortcomings it did eventually win out as the locked in technology arguably due to several lucky events: In 1895 A gasoline powered Duryea won a Horseless-carriage competition that led to Ransom Old’s 1986 patent and mass production of gasoline vehicles. In 1914 there was an outbreak of hoof and mouth disease in North America that led to the withdrawal of horse troughs which were the only places where steam cars could fill up with water. At the point in time where gas vehicles were being mass produced. Despite improvements in technology by the Stanley Brothers condenser and boiler system that didn’t need to be refilled the steam engine never recovered as gasoline power quickly became locked in by gas car owners, gas stations, refineries etc. Increasing returns isn’t an isolated phenomenon at all: the principle applies to everything in high technology. Take for example Microsoft Windows, The company spent close to $50M in Research and Development to get the first copy out the door. The second copy costs ~$10 in materials, it’s the same story in electronics, computers, pharmaceuticals even aerospace (The cost of the first B2 Bomber was $21 billion, cost of the next copy $500 million). High Technology could almost be defined as “Congealed Knowledge” whereby the marginal cost is virtually zero, this makes every copy that is produced cheaper and cheaper. Furthermore, every additional copy that is produced offers the chance for scale efficiencies and improvements. From a customer perspective there is an equally large reward to flock to a standard. For example, an airline would prefer to own a fleet of the same jet, so pilots and engineers don’t have to be retrained and switch. Another customer example is an office choosing one type of software which ensures support and training is more efficient. When you compare all the above to standard bulk commodities industries such as grain, coal, or cement. The know how of this production was acquired many generations ago. Today the direct costs are labor, land and raw materials, areas where diminishing returns can set in easily. (farmers producing more grain resulting in less productive land being utilized). These industries tend be described and understood better by standard neoclassical economics of equilibrium vs increasing returns. Linear vs Non-Linear Systems The name linear refers to the fact that if you plot a relationship on a graph the plot would be a straight line. A lot of study in science has been focused on linear systems in which the whole is precisely equal to the sum of its parts this implies that each part is free to do its own thing regardless of what else is happening. An awful lot of nature works in a linear fashion such. Sound for example can act in a linear way which is why we can hear and recognize two different instruments. Light is a linear system which is why we can recognize and identify a walk/don’t walk sign in daylight. In some ways an economy is linear in that small economic agents can act independently when someone buys a newspaper at a corner store it has no effect on your decision to buy a tube of toothpaste. However, our brain is certainly non-linear which is why the combined sound of multiple musical instruments which becomes music in your brain is worth more than all of them individually. The economy is also non-linear in that millions of buyers can reinforce each other and create booms and busts. As outlined earlier many systems share both properties in differing conditions, and quantities. This is the theory of emergence. The point where one system transitions from linear to non-linear relationships. Take water for example there is nothing very complicated about a water molecule its behavior is governed by well understood equations of atomic physics. But now put a few zillion of these molecules together and you suddenly have a substance that shimmers, sloshes and gurgles they have collectively taken on a new property that none of them possessed alone – liquidity. The non-linear systems thinking is perhaps why stock market behavior is so unexplainable when zillions of rules and expectations are introduced, they create a new property as a collective. Technology networks and change Conventional economic theory of technological development was that technologies came at random and were made possible by inventors that were exogenous to the economy. Another economic model viewed technology development as purely a commodity of Research and Development, if you spent X you delivered Y as an outcome over time. When you look through economic history as opposed to economic theory technology is not a commodity at all, innovations are like an evolving ecosystem and rarely developed in a vacuum. They are made possible by other innovations already in place for example a laser printer is basically a Xerox machine with a little computer circuitry inside, the former enabled by the two latter technologies, also only possible at scale because of the need for high-speed printing. The technological webs are highly dynamic and unstable and can grow in an organic fashion. For example, laser printers give rise to desktop publishing software and desktop publishing opens the need for graphics programs and more powerful hardware and better peripheral devices and on it goes. These technological webs undergo bursts of evolutionary growth and mass extinction events just like biological ecosystems. Say a new technology comes along - the automobile and replaces the old technology - the horse, along with the horse goes the blacksmith, watering troughs, stables and so on. The whole subnetwork collapses below but the automobile brings with it paved roads, gas stations, fast food restaurants, motels and new network is developed. Another example of increasing returns, once a technology is embedded the networks are heavily incentivized to help it grow and prosper. To dislodge an incumbent technology the hurdles are greater than simply the functionality improvement, each technology is different but as an example see below some key elements that are required to be surpassed by sheer new technology functionality: Adaptive Systems Complex systems contain clusters of subs systems that interact and as they continue to interact they reinforce one another. Once a cluster becomes stable it moves on to become a building block for a larger cluster and so on. This hierarchy of building blocks transforms the entire systems ability to learn, evolve and adapt. Take the concepts of red, car and road once these building blocks are understood and refined through experience it can be adapted and recombined into many new concepts such as a “red Saab by the side of the road” this is much more efficient than creating something new and starting over from scratch. It is akin to pattern recognition and identifying similar business models to assign to valuations. Instead of moving slowly through the immense space of possibilities step by step an adaptive system reshuffles its building blocks to take giant steps quickly. A great illustration of this concept is the way police artists used to work in the days before computers when constructing a drawing of a suspect to match a witness description the idea was to divide the face up into 10 different sections (Building blocks) each with 10 strips of paper with different options of noses, ears, eyes, forehead etc. These building block decisions were easy to dissect but together they combine into a complex possibility of over 10 Billion different faces, to identify a face from 10 Billion is almost impossible. Using the building block method can describe a great many complicated things with relatively few building blocks. These building blocks can be informally organized, In the cognitive realm anything we call a “Skill” or “expertise” is an implicit model – or more precisely a huge interlocking set of standard operating procedures (building blocks) that have been inscribed on the nervous system and refined by years of experience. The best example of this is medieval architects who created gothic cathedrals, they didn’t have the tools of modern physics or structural engineering they learned standard operating procedures from rules of thumb passed down from master to apprentice many of these structures are still standing thousands of years later. This system of learning receives environmental feedback, this was Darwin’s great insight. If a model survives in the environment, then it improves through natural selection and this steady improvement is called evolution. Learning Classifier Systems A learning classifier system is a rule-based machine learning method that combines a discovery component with a learning component. Classifier systems seek to identify a set of context dependent rules that collectively store and apply knowledge in a piecewise manner to make predictions. In 1978 an early classifier system was tested to learn how to run a simulated maze and ended up being 10 times faster than the incumbent method. This classifier system also exhibited transfer which is that it could apply learnings from previous mazes to the current one. From this development further applications were built in Poker and Chess to test their effectiveness they worked with great success. The most impressive application of the Classifier system was applied in 1982 to solve the pipeline problem. Running a Gas pipeline is a complex problem that involves hundreds of compressors pumping gas through thousands of miles of large diameter pipe all while customers demands change hourly and pipes and compressors spring leaks continually. Safety constraints demand that pressure remain at certain levels and everything effects everything else in the system. Pipeline operators learn their craft through long apprenticeships and then drive their system with “feel” and “instinct”. The classifier system learned to operate a simulated pipeline beautifully, starting from a set of totally random classifiers it achieved expert-level performance in about 1000 days of experience. The most insightful outcome of the classifier system in the pipeline problem was the way the system organized knowledge about leaks it developed rules and then adapted the rules when the facts changed. The three key principles that underpin the classifier system are: Knowledge can be expressed in terms of mental structures that behave very much like rules; Rules are always in competition so that experience causes useful rules to grow stronger and unhelpful rules to grow weaker Plausible new rules are generated from combining old rules These three rules create a hierarchy of the structure of human knowledge. Artificial Life Imagine a machine that floats around a pond filled with lots of parts, this machine is a constructor and given a description of itself it could construct another machine once it locates the proper parts. That sounds like re-production; however, it isn’t. The newly created copy of the machine won’t have a description of itself which means it won’t be able to make any further copies. Therefore, to achieve true re-production the original machine also requires a description copier, a device that will take the original description, duplicate it, and then attach the duplicate description to the offspring machine. Once that happens the offspring will have everything required to re-produce. To restate this in a more formal way, the genetic material of any self-reproducing system natural or artificial must play two fundamentally different roles: A program/algorithm that can be executed during the construction of the offspring, and Serve as a passive data, a description that can be duplicated and given to the offspring to pass on. This theory was espoused by John Von Neumann in the late 1940’s before Watson and Crick discovered the double helix in 1953. This turned out to be an incredible prediction considering that what we went on discover about DNA and cell division process. Corporate culture is the DNA of a business and the ability for a company to truly replicate its business model to grow requires a) the algorithm of the business model and b) the passive data (Culture) to pass on to the employees that will become the next generation within the business. Without firstly the corporate culture of beliefs, myths, rules and ways of doing things nothing can be passed on at all, secondly that DNA map needs to be implanted in the expanded operations strongly. The Artificial Stock Market One of the most difficult chestnuts to crack in economic theory is stock market behavior. Considering that neoclassical theory considers that all economic agents are perfectly rational then all investors must be perfectly rational. Moreover, since everyone shares the same information, they will always agree about what every stock is worth – simply the net present value of its future cash flows discounted by the interest rate. Therefore, this perfectly rational market will never get caught up in bubbles or busts. Therefore the New York Stock Exchange trading floor would be a quiet place, in reality of course the NYSE is a barely controlled riot, with multiple bubbles and crashes, fear, uncertainty, euphoria and every combination. A Martian that read the Wall Street journal might think that the “market” was a living organism that had moods of being jittery, depressed, upbeat, and confident. If you replace the above assumptions of perfectly rational agents and replace them with Artificial intelligence agents that can learn, adapt, and classify rules they will act more like a human does. The Santa Fe institute modeled this change with one stock that the agents could buy and sell and as they learned rules for trading you could observe what rules they developed and which ones were reinforced and prioritized by different participants. The model began with a stock that had fundamental value of $30. The agents were then introduced to the market with total stupidity, random rules were developed from experience, as expected they learned energetically. On the second run of this model, it was observed that some the agents had developed a primitive form of technical analysis reinforced by positive outcomes from random rules which further reinforced more positive outcomes for new agents further reinforcing these rules even further which ran the price up to $34. In different models the exact opposite happened, and the price fell to $25 as agents tried to continue selling reinforcing further selling. The fascinating reality is that the market is combination of participants that have rules developed and reinforced by individual experiences that drive different expectations of outcomes. Monetary reward is a powerful incentive to overcome especially when reinforced with consecutive positive outcomes, hence as markets rise they can continue to rise for a long time. I hope you enjoyed the read. Thanks, Shaun Trewin
The second most expensive words in investing ...
If the words ‘I’ve missed it’ … are the most expensive words in investing … then the second most expensive words are ‘I’m waiting for the pullback’. The below extract from REQ Capital’s August newsletter does an incredibly good job of encapsulating the cost of waiting for the correction …
The 'awful' track record of box tickers
A recent conversation with a former ASX director provided the inspiration for this blog post – after we were given a rare, front-row view of an ASX board seat during a time of crisis, such as the COVID-19 pandemic. The insights provided were things we’d suspected but have never heard firsthand and only confirmed some of our beliefs about professional directors. As the COVID-19 pandemic gripped markets in March of 2020, sending the index down 38% in just three weeks and credit markets into a freeze, CEOs and boards scrambled to comprehend what this meant for the liquidity of their businesses. Do we have enough cash to see this out? Can we get access to debt or do we need to raise equity? As these conversations played out … lurking in the background of corporate headquarters were the investment bankers and consultants - armed with pitch decks painting the most dire of outcomes for balance sheets and thus director liabilities should liquidity become a serious problem. Our director went on to explain that after the board had rejected investment bank after investment bank, trying to entice the company into a dilutive equity raise … one banker correctly assessed that although this board was strong as a whole, they were weak as individuals and proceeded to call and email individual directors discussing how they could be potentially liable if they are proven negligent. The banker stressed that with a number of litigation financiers actively looking for cases, shareholders could easily finance a trip to the courts should they be willing … This threat … coupled with the uncertainty of COVID-19 pandemic saw the bankers earn their payday as these professional directors couldn’t hit the capital raising button fast enough. Directors hold the keys to arguably the two biggest controllable of a business – those being - incentives and capital allocation. Unfortunately, only a small minority really appreciate this. One founder within this minority is Mark Leonard, Chairman of TSX listed Constellation Software – a serial acquirer of vertical market software businesses. Leonard is more than believable on all topics around vertical market software and corporate governance. Constellation’s track record is remarkable and one that we believe all investors should study. Since listing at around $18 per share in 2006, CSU is up 116x or 37%pa !! (the average 100 bagger takes around 20yrs or 25%pa!). We’d argue that most, if not all companies, particularly founder-led companies, have the same corporate governance choices, yet only a very few have the discipline, patience, and foresight to ensure that shareholders are appropriately represented …. And we believe these choices are indicative of the types of decisions that are being made across the rest of the business. Leonard’s 2018 letter (attached) is a master class in how boards should be selected and structured. Many boards could save many hours and many millions in consulting fees if they took just 10 minutes to read Leonard’s wisdom. Leonard opens the topic of corporate governance highlighting that the performance of most boards has been ‘awful’ …. Qualified and competent directors are rare, and not surprisingly, the track record of most boards is awful. According to the 2017 Hendrik Bessembinder study of approximately 26,000 stocks in the CRSP database, only 4% of stocks generated all of the stock market’s return in excess of the one-month T-bill rate over that period. This means that 4% of boards oversaw all of the long-term wealth creation by markets during that period. Even more disturbing, the boards for over 50% of public companies saw their businesses generate negative returns during their entire existence as public companies. Leonard then goes on to state that the typical tools for dealing with corporate governance, being - Director Independence, Diversity and Term – are a reasonable starting point for most companies however these tools fall well short for those seeking long term outperformance. Leonard emphasises governance is only one part of a director’s role and limiting the tenure of a capable director will do more harm than good. Governance is necessary, but it is not sufficient …. Helping extend the extraordinary track record of building intrinsic value should be the board’s primary function. You are unlikely to achieve that by replacing their proven and obviously very rare Directors and Officers with new ones who are statistically unlikely to have ever experienced anything like consistent high performance.’ Leonard stresses that for a business is to achieve sustainable long-term performance, the directors must assume the role of ‘mentor’ … not ‘governor’. Unfortunately, that means that the default role for most directors is as a governor ,not a mentor. Some investors find that acceptable. I’d argue that governing is table stakes. Coaching and talent nurturing are the places where directors can make a significant contribution and help a company become part of Bessembinder’s 4%. Leonard believes that there are only two reasons why someone should consider joining a company’s board: A way to invest a significant portion of their net worth and be able to watch it closely Learn and apply those learnings to their own career and investments Finally, Leonard outlines to readers the 'search criteria' for a potential CSU director (table below). Many agree that CSUs search criteria an extremely, high-quality way in which to select a director and they also appreciate the poor track record of most boards. However, we’ve seen few investors incorporate the quality of a board into their assessment of a management team and its ability to allocate capital … despite it clearly having such a massive impact on the long-term performance of a business. One measure we use to assist in our assessment of a company’s board is the ‘business savvy to compliance ratio’. This ratio shows the number of board members we consider to be ‘business savvy’ to those we consider ‘compliance professionals’ … where a business-savvy board member is someone who has either a very successful capital allocation and/or operational track record. A few notables within our portfolio that sit high on this ratio include – Objective Corporation and Lovisa with ‘business savvy’ to ‘compliance’ ratios of 100% and 80% respectively. If you know of any businesses that practice this type of ‘shareholder friendliness’ – please let us know – we love investing in them! Thanks for reading, Lachlan Morgan, CFA
The Salesforce Playbook & yet another founder paid a $1 salary!
An investment in Salesforce.com at the 2004 IPO would have yielded a ~100x return ($1.1B market cap in 2004 to $242B today), this sort of performance is worthy of an understanding in our view. Marc Benioff started Salesforce in a rented apartment in 1999 with the goal of making enterprise software as easy to use as a website. The overarching goal was to make applications deliverable over the internet - quite a revolution at the time. Even from an early age at college when Marc was developing his own software, he had a blinkered focus on customer feedback with a continual loop incorporating this feedback into development. Salesforce is arguably the founder of the SaaS market having delivered the first cloud-based enterprise software package for a monthly fee. There are the normal warning signs of a 100 bagger in the Salesforce S-1 that hit you in the face such as a $1 salary, very strong revenue growth, Customer obsession, and large insider ownership. The lessons that Marc outlines below have been taken from his book Behind the cloud – the untold story of how salesforce.com went from idea to billion-dollar company and revolutionized an industry Salesforce S-1 Extracts: Very strong revenue growth almost doubling each year into the IPO, with revenue per customer spend growing from ~$551 per year to over $650 while volume also grew from 9,800 customers to 147,000. This volume of revenue would literally become a rounding error in the decades to come. Yet another founder CEO that is paid a $1 salary! Seriously how many times does this correlate! Marc not only founded the business with his own savings he then proceeded to participate in every capital raise along the journey, this resulted in him retaining ~28% of the issued capital of Salesforce post IPO: Salesforce.com revenue growth has been incredible since the IPO revenue has grown every year, even though the GFC and COVID revenues continued to grow. The Larry Ellison Playbook Larry Ellison was Marc's most trusted mentor during his 13-year career at Oracle, Larry believed so much in Marc's vision he invested $2M in seed capital in Salesforce (Now worth over $200M). The key lessons Marc outlines from his time with Larry were: o Accomplishments are fueled by faith. o Always have a vision for what you want to achieve o Be passionate o Act confident even when you are not o Think of it as you want not as it is o Don’t let others sway your point of view o See things in the present even if they are in the future o Don’t give others your power. Ever. The brand A brand and a logo are different, a logo is simply a graphic representation of a company, a Brand is more. It must be a collective set of memories. To be an effective brand it must be consistent, a company must use its people, its product, and its messaging to consistently reinforce the same points – for example, a delivery service that promises to care about your packages must not have dirty trucks (Think Mainfreight!) Brands that break promises destroy customer trust. Salesforce’s brand stood for the message of no more software, at times keeping this brand promise cost the company but it was vital to remain true to this purpose. Street Teams: Make Customers part of your Journey – MC Hammer The street teams concept involves cultivating a group of salesforce enthusiasts that encourage other enthusiasts to follow, it was introduced to Marc Benioff by MC Hammer of all people. For Salesforce it was adopted in the city tour program where local networks of people were adopted to attend presentations, these enthusiasts act as the best salespeople and new customers find them much more believable it also acts both ways where existing customers are locked in by their own testimony as well as encouraging further customers. The way this strategy was adopted first revolves around your customer and to adopt them you need to: - Give them a service or product they love - Elicit customer insight – and use it! This reinforces the love from active involvement - Provide a platform for customers to share their enthusiasm - Operate locally to build teams that influence others on a community level and act collectively on a global level. There have been several companies that come to mind that adopt this strategy such as Jack Henry & Associates who have customer advocacy days where key customers are given the opportunity to voice their feedback publicly to the company and other customers. Salesforce found early on that by bringing customers to key events was a powerful network and a very efficient platform for growth. Sell to the end-user The major growth inhibitor of enterprise software has been the channel to market, most enterprise software is sold to executives that control the budget instead of targeting the end-users. Salesforce focused on the user, not the company, and made them “customer heroes” – they went as far as blowing up big pictures of them to post at events and include in company materials. This strategy had a Win/Win result in that the companies received ownership by the key individuals which resulted in better implementation and Salesforce had an identity to leverage for customer advocacy. A sign that this strategy was starting to work was when Job Adverts started claiming Salesforce Experience as a key skill. Salesforce also aimed at taking all friction out of the sales process where the product was so simple it was a DIY subscription process with a fixed price and no lengthy consultation, presentations, or quotation. Salesforce found that they capped out at $50k - $70k per salesperson per month and the main impediment to sales growth was the volume of people. It was found in the early days that roughly 25%-50% of the employee base needed to be salespeople. During the 2000 crash where venture capital financing capacity dried up salesforce was required to focus on cash flow, to turn this around they moved their subscription model from paid monthly to paid yearly in advance, this simple change switched the company from Cashflow negative to Positive. Key metrics that Marc used to monitor sales team success were: o Inbound sales o Raw Web Traffic o Capture rate o Lead conversion rate o Close rate o Average deal size o % of sales that are new vs up sales – if you are upselling more customers than you are adding then next year will be harder o Sales cycle length o Average sales volume per person. Hiring Principles & Culture Marc has a group of rules that he adhered to when building the Salesforce team: - Don’t wait for resumes to come to you: always continue to search for good people and always search the top 5-10% of talent and competing organizations - Consider recruiting to be part of your job: Marc personally still holds one meeting every day that he considers a job interview and he continues to stay connected to good people. You must continue to follow up with good people. - Include employees in the talent quest: Employees are the best source of top talent, good people always know other good people. Salesforce offers a $2k - $10k incentive if a referral is hired. - Add people at your leadership level first: you need to set the foundation with exceptional people so that it flows down from there. Once a person is hired in Salesforce it became a rule that you had to ensure the new hire had lunch plans on the first day, this was a good platform to set the message and make them feel involved. The company went beyond this to ensure the culture was upheld by offering a fully stocked kitchen, a company-paid gym membership, free yoga classes, and discounted air flights. Another incentive program that was put in place that had a great return was Breakfast at Tiffany's, each year the company took the top-performing salesperson and their significant other to a four seasons resort in Hawaii to have breakfast and champagne before a personal shopping trip at Tiffany and Co before the store is open to the public, this made employees and their family feel special and was a unique experience. The company culture was to hire fast and fire fast, it became company policy that although everyone does their best sometimes people aren’t suited to the organisation, firstly it is important to recognize this and move them into an area that might be better suited if this doesn’t work out it is time for them to move on. The key test for whether this person should leave is the following question: “If person A were to walk out the door would you regret losing them?” The company put in place the following checklist to measure the success of managers and strives to ensure employees can check off each of the below: o I am doing the best work of my professional career o I have the opportunity to do what I do best every day at work o In the past 6 months I have talked with someone about my progress o There is someone at work who encourages my development o I have opportunities to learn and to grow at work o My opinions are sought after and seem to count o My supervisor or someone at work seems to care about me as a person o I have a support network at work o My coworkers are committed to doing quality work o I am recognized and rewarded for my contributions I hope you found this a worthwhile read. If you come across any companies that are founder-led (~30% founder-owned), with modest compensation, and growing revenue rapidly please let me know on Shaun.email@example.com If you would like a copy of the Salesforce S-1 please also reach out.
The incentives driving Facebook's CEO v Commonwealth Bank's CEO
With Facebook crossing $1 Trillion in market value this week, we thought it would be worth highlighting the striking difference in incentives of a great founder-lead business in Zuckerberg/Facebook versus a stock held by nearly all Australian Super Funds - Commonwealth Bank. Immediately, two Charlie Munger quotes come to mind: “It is the unlikely extremes in outcomes – good or bad – that often instruct best” “Show me the incentive and I’ll show you the outcome” A few interesting points from the data presented in the tables below for the period FY12 (when Facebook listed) to FY21: FBs market capitalization in FY12 was $70.8b v CBA of $88b Zuckerberg’s total salary for the period was $500,008 (note he is currently being paid $1 per annum and has been since 2013) v Narev and Comyn’s of $19.1m Zuckerberg’s total package (salary + stock options) for the period was $101m v Narev and Comyn’s of $82.1m Zuckerberg’s value creation for the period was $775b v Narev and Comyn’s of $69b (adjusted for share issuances) Zuckerberg’s has been paid an extra $20m for creating an extra $706b in value for shareholders I’m sure there are many counterarguments to this comparison ie. this isn’t 'apples-to-apples' … banks v a social network. However, our point is a ‘directional one’ … given the vast number of opportunities (stocks) to invest in, why would you place your capital with professional CEOs whose payoff for a poor decision/s is a salary of a few million a year ?!?! Core to our investment philosophy is backing great founders in great business models and making probability-weighted bets on which ones are most likely to outperform the market. We believe shareholder-friendly behaviours such as: low salaries coupled with aligned incentives; high insider ownership; clean accounting; a board of business savvy individuals; transparent communication … and most importantly …. very careful issuance share capital ….. tilt the probabilities of successful investment performance in our favour. Thanks for reading, Lachlan Morgan, CFA
Peter Lynch said Fred Kobrick was one of the best stock pickers he has ever met… ever heard of him?
Kobrick has some interesting history at State street research capital fund generating great performance, however, most importantly he documented his first-hand professional investment experience through 1980–2000s, these are exceptional observations on the ground floor of many multi-baggers that are worthy of understanding. Whether or not Kobrick compounded capital as well as others of his time these are must-read lessons and decisions that were made at the coal face with all the real-time uncertainties. This blog has been written from my reading of The Big Money – Peter Kobrick. Buy the hardcover. it is one for the bookshelf! McDonald's - You need a system to scale It's important to understand the system a business has in place to implement its strategy. For example at the time of the IPO McDonald (MCD) on the surface was just another Fast Food chain however if you had gone to the stores and met with management you would have gained invaluable insight from how focused management was on their system. MCD knew that pre-slicing hamburger buns saved time to toast (17seconds), how many rows and columns of burgers fit on a grill, a higher temperature was needed for quarter pounders and that each batch takes 15minutes. This precise understanding of the process allowed the company to lower the price of hamburgers from 30c to 15c while maintaining profit margins which drew in more diners. Kobrick says in his first visit to company headquarters in Oakbrook Illinois he was shown the “Amber Room”. The Amber Room was a circular room lit by amber light with a circular waterbed in the middle the walls of the room formed a conical shape sweeping up to a point in the ceiling. The Company host explained to Kobrick that “scientists have proven that the amber light and relaxing atmosphere stimulated the brainwaves most responsible for creativity, and creativity and innovation are at the core of our culture”. When you compare McDonald's, which was corporatized in 1961 when Ray Kroc bought out the McDonalds brothers there were a number of fast-food restaurant chains around but very few became great long term investments for outside shareholders. MCD had a systemized operating model, Real Estate plan and financing to become a mega-chain. Ray Kroc the founder of MCD credited the system to the success of the business, by 1979 MCD had a 35% market share of the burger industry vs Burger King at 11% and Wendy’s at 8%. The Home Depot – Audacious goals Over the years the best investments were the growth stocks that started their run when they were rather small, The Home Depot (HD) was one of these. In 1981 when HD listed it had 4 stores and annual sales of $22M, it now has over 2,200 stores producing almost $150B of sales, see below the first annual report as a listed company. HD was focused on attracting a more sophisticated DIY customer with its new format for home improvement. There were a lot of doubters of the company at the time because of its very small size, grand ambitions, and aggressive expansion plans. Adding to the market's concerns about HD was the business model that required experienced salespeople and higher staff costs to offer advice to customers. At the time of the IPO the 4 existing stores had only been operating for 2 years which also made investors nervous about the big promises. 8 years after the IPO the store footprint grew from 4 stores to 100 stores and in 1990 it was the largest home improvement retailer in the USA. At the time of the IPO, the stock traded around its listing price for several months while people who expected a large jump sold out. As the revenue and earnings grew the stock took off and was a 10x from the IPO in less than 2 years. The founder's first letter to shareholders is also attached at the bottom of this blog if you’re interested in reading it. Nike – Phil Knight, founder & long term focus Nike went public in 1980 when it was doing $270M of sales, the backdrop to this IPO was interesting because there was a view in the market that Nike was scratching the itch of the running boom that was occurring at the time, it was estimated that 25M Americans took up some aspect of running between 1970 and 1980 and there were many small fitness companies emerging. The sales growth at the time of the IPO had been 100% every year for the past 4 years (see below), Phil Knight’s founder letter also attached at the bottom of this blog. What mattered that drove the adoption of the Nike brand was the ability to convince the best and most prominent athletes to wear their shoes in competition – in 1983 Joan Benoit set a Marathon world record wearing Nike shoes. The insight that Kobrick had at the time was that Nike was gaining market share rapidly and was spending considerably more on marketing and advertising, however, during this time Reebok started to respond and became more aggressive on price which resulted in Nike's net earnings falling from $40M in 1984 to $10M in 1985. In 1985 Phil Knight returned as president to the business and assisted with the turnaround. The insights during 1985 were: 1) Phil Knight was exceptional, and he responded to changing conditions 2) Nike was taking market share 3) Kobrick owned some Nike runners, ran 5ks a day, and loved them 4) Retailers and running gurus loved the product Yet another example of the customers 'love' of a product leading to the success of the company. Observations from the Microsoft IPO – Bill Gates 25 year old wizard When Microsoft was completing its IPO in 1986 Wall Street held Bill Gates in very high regard calling him the “technology wizard” and always had great excitement when he was present at Management presentations. Kobrick recalls that it was explained at the time that Gates quit College at Harvard University to pursue his burning desire to start a business in the brand-new computer industry "before it was too late". Gates said being first or at least early was critical. He had a view that customers would want software to carry out powerful functions on their computers but they would want uniformity and continuity so that users would not learn something only to have to undertake an entirely new learning process in the future. The Microsoft IPO pitch centred around three assumptions: 1) Customers would have a critical need for standards and therefore would stay with a provider through all the product cycles if it performed. 2) The early leaders would set these standards. And these standards had to dominate the market early. 3) Technology had to be the best or close to and the customers had to believe it. Kobrick recalls the fascinating story of Gates’ urgency to get scale which was epitomised in his determination to win IBM, he made a deal to develop an operating system for their hardware. Microsoft was not ready in time for IBM so Gates quickly completed a $75k acquisition of a company called 86-DOS which was then renamed MS-DOS, which was then licensed to IBM for a fraction of the price of the alternative bidder (Digital Research). The genius in this deal was not in the pricing to IBM it was the fact that the deal was non-exclusive. The non-exclusivity allowed Microsoft to retain ownership of DOS, develop it in conjunction with IBM and then sell it to other hardware providers. IBM were so focused on Hardware they never thought to consider the software business. Gates was only 25 years old at the time – imagine backing a 25yr old CEO making decisions like this. MSFT completed its IPO at $21.00 per share, at the time of the IPO it had ~25M shares outstanding, making the market cap ~$525M or around 22x P/E. Gates retained 49% of the company post the IPO and paid himself a salary of $130k per annum!. Based on today's market cap of ~$2T, MSFT has been a 3,800 bagger, look at the revenue growth prior to IPO in 1986: If you would like a copy of the IPO S-1 from 1986 please email me and I can forward it to you, a great read for some software history. Shaun.firstname.lastname@example.org Compaq and Dell – Same business but a different business model One day in 1982 two ex-Texas Instruments managers and a VC manager got together and came up with the idea to start a PC company to go after IBM, the three men started this company and called it Compaq Computer Corporation, in their first year they generated $111M of sales the highest first-year sales in the history of American Business!, a year later they went public. Compaq went on to become the youngest company to be included in the Fortune 500 and then became the youngest company to reach $1B of sales. Moving forward 5 years after the Compaq IPO the PC industry growth had been enormous, industry sales of Intel-based PCs leapt over 10x from 700T units to 7M by 1988. Compaq had secured a 5% market share during this time. In the run-up to 2000 Compaq sales grew to over $42B: In mid-1988 along came Michael Dell and took Dell computer public (another college dropout who didn’t want to miss the opportunity). Michael was 23 years old at the time of the IPO with a tiny amount of experience and wanted to take on IBM and Compaq. This was an audacious goal and took some believing especially considering that at the peak of PC industry growth there were about 1,000 companies around the globe making PCs! this was like the combustion engine manufacturers of the 1920s. When Kobrick looked at the prospectus it was clear that Dell was doing something right because they were gaining market share, growing sales and expanding profit margins. The heart of the Dell business plan was different than the rest of the industry, selling direct to customers and not using intermediaries – primarily through telemarketing. Dell saw themselves as much a marketing company as a hardware company, sales staff trained for six weeks before taking their seats at the phonebanks, they were incentivized to upsell memory or built-in modems and troubleshoot problems. This direct to consumer model allowed Dell to cut prices but most importantly it allowed them to get close to the customer and collect data on their preferences, this knowledge of the customer was all the difference. Because Dell was selling direct to the consumer, they didn’t need to support a pipeline of dealer inventory and they were also able to cut out the retailer and advertise these discounts directly. A particularly useful insight of Kobrick into the quality of Michael Dell came from a meeting he had with him a few years after the IPO. Prior to the IPO Andy Grove from Intel had put a supply stop on Dell because of a shortage of chips and at that time Dell was one of the hundreds of emerging PC companies, Michael said he flew to San Jose California; walked into Intel Headquarters and said he was Michael Dell of Dell Computer and wanted to meet with Mr Grove, Andy said he was too busy so Michael waited the whole day, then came back the next day and sat in the foyer, the same happened for a few days and Michael said he would camp in the lobby until he got 10 minutes, They eventually did meet and ended up speaking for over an hour, the plea for parts was honoured and the two have had a great relationship since. Only a founder would have this focus and determination for the company! Dell completed its IPO in 1988 at a market cap of $85M by 2000 the market cap had swelled to $100B a market cap it has not reached since. This expansion in valuation was fuelled by exceptional fundamentals, revenue grew from $159M in 1988 to over $25B by 2000, however, the ultimate creation of economic value was the inventory turn which shot up from only 3.2x in 1988 to over 60x by 2000: National Semiconductor vs Intel - The power of focus NSM was founded in 1959 its earliest integrated circuits were targeted at the space program, scientific applications, and consumer markets. In the 1970’s it then started aggressively targeting markets including calculators, watches, grocery checkout machines. It then expanded to speech synthesis chips and mainframe computer chips constructing three factories in the 1980s. The company continued to develop a huge number of products for numerous end users, the company then acquired Fairfield Semiconductor in 1987 and introduced new graphics chips. During this time Intel focused their R&D efforts and capacity on personal computers which resulted in the lions share of product design contracts eventually becoming the most important market but also led to significant IP being co-developed with hardware manufacturers. Intel was founded in 1968 by Gordon Moore (The now-famous Moores Law) and Robert Noyce, while led by Andy Grove. In 1974 Intel released a new PC chip, the Intel 8080 which received glowing reviews. The lead extended and in 1982 when they released the 286 chip which cemented their supremacy in microprocessors. PC’s became Intel’s primary business and during the 1990s Intel invested heavily in this market to control the direction of the industry. During the 1980’s Intel’s revenue surpassed National Semiconductor. The most impressive results of Intel during the ’80s was the disciplined investment in R&D, even during the 1987 crash they increased R&D spend: Andy Grove’s leadership of Intel was widely heralded as exceptional. From 1980 to today Intel has been a 160 bagger, however, in 1980 focusing on this new market for “Personal Computers” would have seemed far from obvious and highly risky. Staples – Tom Stemberg A great example of exceptional management was Tom Stemberg from Staples. Stemberg took Staples public in 1989 and raised capital from several private equity groups in conjunction with own severance pay he received from his prior employer. Interestingly Office Depot went public one year earlier and was founded by three very able and experienced founders. Staples and Office Depot opened stores rapidly, collectively over the next decade opening nearly 2,000 office warehouse stores between them. The competition further intensified but despite this Stemberg managed to grow EBIT from $37M in 1993 to $1.2B at the time of his retirement in 2006. Great management makes great business models, remember that! Great business models do not exist without great management. It is management that creates great assumptions, execution, and the rest. Over time these models need adjusting for competitive conditions. Make sure you identify the traits of great managers to recognize another Bill Gates, Jeff Bezos, Ray Kroc, Bernie Marcus or Steve Jobs if they emerge. Kobrick outlines his experience in observing Gates, Dell, Marcus and others: a) The top person had a vision and could translate that into a strategy to make the company a long-term winner not just a good story for a year or two. b) The top person was very competitive, not a risk-taker but showed a plan to dominate the industry and become number one. c) Each person had already done something right, had a good business model and showed how they would excel in the industry and become highly profitable. d) Each company was positioned in an industry that was taking off and looked to be a huge industry well into the future – not shrinking. Xerox – The training ground Xerox listed in 1959 and was making the first automatic office copying machine to use regular paper. Kobrick worked with a mentor while analyzing this company that leads him on the path to becoming one of the best stock pickers in his time. The lessons learned while studying Xerox were: - The efficiency improvement was vast, to make paper copies at that time you were required to use carbon paper in between two sheets of paper in a typewriter. - The technology was expensive at the time so extensive customer interviews were required to estimate a rough earnings model – simple models are always the best. - Xerox came about before personal computers and even word processors, It was very early! - There were many doubters of the technology that claimed it would be unaffordable for broad market adoption and the technology was slow and noisy, these doubters shook countless investors out of the stock. - The main difference with being able to hold onto a multi-bagger is building a thorough knowledge of the company this knowledge keeps you in the stock while the market fluctuates, it allows you to have conviction. Xerox turned out to be more of a great product than a great company and failed to develop a technology culture to develop and innovate new products. The key lesson Kobrick discusses with his mistake of continuing to hold Xerox was that the company became complacent and when its patents expired it experienced intense competition. Market Bubbles and Mania Kubrick's observations of bubbles and mania are very interesting, he considers a mania leads to bubbles. “A mania is simply something that is more emotional than tangible or rational, so it can be thought of as irrationality”. The irrationality is not easy to see at the start because since there would be no bubble if it was easily visible. Normally bubbles emerge when knowledge is incomplete or wrong and has the story of unlimited potential. It happened with electricity to households, the advent of canals, railroads, and radio in the 1920s. With all bubbles, there is an element of mystery, in the internet bubble of 2000 many investment professionals thought there was unlimited demand for many communications and internet stocks. Kobrick observed three interrelated bubbles in 2000 which is what made it so extreme: 1) Stock Market bubble: Internet, telecommunications and various technology stocks were overhyped – “The Internet Changes Everything”. 2) Capital Spending by corporations in the ‘Great telecommunications build out’. The same hype that caused the stocks to soar was driving the capital spending and vice versa. 3) The US economy reached peak growth rates of the decade of 5.28% during this year. Crashes are always the way that manias end, in the UK the famous railway mania led to the Britain financial crisis of 1847. Like most manias, the fundamentals of economic improvement was very sound and genuinely creating economic expansion. I hope you enjoyed the read. Regards, Shaun Trewin CA
Largest market 'tail risks'
Following on from my post, Adding a pandemic to the list, Chris Mayer, (author of the book ‘100 baggers’), made a similar (and more instructive) point in his recent post Buying and Selling. Chris was kind enough to share with me the survey he referenced by Bank of America, which was published in the Financial Times, showing the 'Largest market tail risk by the percentage of respondents ', over the past ten years. Due to the quality of the image (below), I’ve summarised these tail risks over the that respondents (who were ‘professional money managers’) were most fearful of: 2010 to 2012: ‘EU sovereign debt funding’ 2013: US ‘fiscal cliff ’ 2014: China ‘hard landing’ 2015: Geopolitical crisis 2016: China ‘hard landing’ 2017: Political populism 2018: Quantitative tightening 2019: Trade war 2020: US Presidential election 2021: Coronavirus From 2010 to 2021, whilst market participants were worried about these ‘tail risks’: The ASX200 accumulation has risen from 32,768 to 82,641, 9.6%pa The S&P500 from … 1,268 to 4,223, 12.7%pa The NASDAQ from … 2,489 to 14,096, 18.69%pa In short … worry less … invest more
Price makers v price takers
Price maker: Realestate.com (REA.ASX) operating earnings (REA is Australia’s leading property portal) Price taker: Mirvac Group (MGR.ASX) operating earnings (MGR is an Australia based property developer)