January 2020 - The Innovators by Walter Isaacson

Isaacson presents a comprehensive history of modern day technology, from Ada Lovelace to Larry Page. He weaves in intricate detail around the development of the computer, which provides the landscape on which all the major players of technological history wander.

Tech Themes

1. Computing Before the Computer. In the Summer of 1843, Ada Lovelace, daughter of the poet Lord Byron, wrote the first computer program, detailing a way of repeatedly computing Bernoulli numbers. Lovelace had been working with Charles Babbage, an English mathematician who had conceived of an Analytical Engine, which could be used as a general purpose arithmetic logic unit. Originally, Babbage thought his machine would only be used for computing complex mathematical problems, but Ada had a bigger vision. Ada was well educated and artistic like her father. She knew that the general purpose focus of the Analytical Engine could be an incredible new technology, even hypothesizing, “Supposing, for instance, that the fundamental relations, of pitched sounds in the science of harmony and musical composition were susceptible to such expression and adaptations, the engine might compose elaborate and scientific pieces of music of any degree of complexity.” 176 years later, in 2019, OpenAI released a deep neural network that produces 4 minute musical compositions, with ten different instruments.

   2. The Government, Education and Technology. Babbage had suggested using punch cards for computers, but Herman Hollerith, an employee of the U.S. Census Bureau, was the first to successfully implement them. Hollerith was angered that the decennial census took eight years to successfully complete. With his new punch cards, designed to analyze combinations of traits, it took only eight. In 1924, after a series of mergers, the company Hollerith founded became IBM. This was the first involvement of the US government with computers. Next came educational institutions, namely MIT, where by 1931 Vanneaver Bush had built a Differential Analyzer (pictured below), the world’s first analog electric computing machine. This machine would be copied by the U.S. Army, University of Pennsylvania, Manchester University and Cambridge University and iterated on until the creation of the Electronic Numerical Integrator and Computer (ENIAC), which firmly established a digital future for computing machines. With World War as a motivator, the invention of the computer was driven forward by academic institutions and the government.

Business Themes

1. Massive Technological Change is Slow. Large technological change almost always feels sudden, but it rarely ever is. Often, new technological developments are relegated to small communities, like Homebrew computing club, where Steve Wozniak handed out mock-ups for the Apple Computer, which was the first to map a keyboard to a screen for input. The development of the transistor (1947) preceded the creation of the microchip (1958) by eleven years. The general purpose chip, a.k.a. the microprocessor popped up thirteen years after that (1971), when Intel introduced the 4004 into the business world. This phenomenon was also true with the internet. Packet switching was first discovered in the early 1960s by Paul Baran, while he was at the RAND Corporation. The Transmission Control Protocol and Internet Protocol were created fifteen years after that (1974) by Vint Cerf and Bob Kahn. The HyperText Transfer Protocol (HTTP) and the HyperText Markup Language (HTML) were created sixteen years after that in 1990 by Tim Berners-Lee. The internet wasn’t in widespread use until after 2000. Introductions of new technologies often seem sudden, but they frequently call on technologies of the past and often involve a corresponding change that address the prior limiting factor of a previous technology. What does that mean for cloud computing, containers, and blockchain? We are probably earlier in the innovation cycle than we can imagine today. Business does not always lag the innovation cycle, but is normally the ending point in a series of innovations.

2. Teams are Everything. Revolution and change happens through the iteration of ideas through collaborative processes. History provides a lot of interesting lessons when it comes to technology transformation. Teams with diverse backgrounds, complementary styles and a mix of visionary and operating capabilities executed the best. As Isaacson notes: “Bell Labs was a classic example. In its long corridors in suburban New Jersey, there were theoretical physicists, experimentalists, material scientists, engineers, a few businessmen, and even some telephone pole climbers with grease under their fingernails.” Bell Labs created the first transistor, a semiconductor that would be the foundation of Intel’s chips, where Bob Noyce and Gordon Moore (yes – Moore’s Law) would provide the vision, and Andy Grove would provide the focus.

Dig Deeper

• Alan Turing and the Turing Machine

• The Deal that Ruined IBM and Catapulted Microsoft

• Grace Hopper and the First Compiler

• ARPANET and the Birth of the Internet

November 2019 - Brotopia: Breaking Up the Boys' Club of Silicon Valley by Emily Chang

This book details a number of factors that have discouraged women’s participation and promotion in the tech industry. Emily Chang gives a brief history of the circumstances that have pushed women away from the industry and then covers its current issues - weaving in great insights and actionable takeaways along the way.

Tech Themes

1. The Antisocial Programmer. As the necessity for technological talent began to rise in the early 1960s, many existing companies were unsure how to hire the right people. To address this shortfall in know-how, companies used standard aptitude tests, like IBM’s Programmer Aptitude Test, to examine whether a candidate was capable of applying the right problem solving skills on the job. Beyond these standard aptitude tests, companies leveraged personality exams. In 1966, a large software company called System Development Corporation hired William Cannon and Dallis Perry to build a personality test that could shed light on the right personalities needed on the job. To build this personality test, Cannon and Perry profiled 1,378 programmers on a range of personality traits. Of those 1,378 profiled, only 186 were women. After compiling their findings, the final report stated: “[Programmers] dislike activities involving close personal interaction; they are generally more interested in things than people.” Furthermore, Cannon and Perry’s 82-page paper made no reference to women at all, referring to the surveyed group as men, for the entire paper. A combination of aptitude tests and Cannon-Perry’s personality test became the industry standard for recruiting, and soon companies were mistakenly focused on stereotypical antisocial programmers. Antisocial personality disorder is three times more common in men than women. Given how early the tech industry was, compared to what it is now, this decision to hire a majority of anti-social men has propagated throughout the industry, with senior leaders continually reinforcing incorrect hiring standards.

2. Women in Computer Science. According to the book, “there was an overall peak in bachelor’s degrees awarded in computer science in the mid-1980s, and a peak in the percentage of women receiving those degrees at nearly 40 percent. And then there was a steep decline in both.” It was at this time in the mid-1980s that computer science departments began to turn away anyone who was not a pre-qualified, academic top performer. There was too much demand with a constrained supply of qualified teachers, so only the best kids were allowed into top programs. This caused students to view computer science as hyper-competitive and unwelcoming to individuals without significant experience. Today, women earn only 18% of computer science degrees – a statistic that shocks many in the industry. Researchers at NPR found that intro CS courses play a key role in this problem – with many teachers still assuming students have prior familiarity with coding. Furthermore, women are socialized in a number of ways to achieve perfection, so when brand new code is not working well, women are more likely to feel discouraged. It is imperative to encourage women to try computer science if they have interest, to combat these negative trends.

3. PayPal and Perpetuating Cycles. After the dot-com bubble burst in the early 2000s, several newly minted millionaires did the natural thing after selling a company for millions of dollars, became a venture capitalists. One of the major success stories of the era was PayPal. Among those newly minted millionaires were the PayPal mafia: Peter Thiel, Keith Rabois, Elon Musk, Max Levchin, David Sacks, and Reid Hoffman. Thiel and Rabois have a history of suggesting a meritocratic process of hiring where only the most qualified academic candidate should land the job, not taking into account diversity of any form. Furthermore, in his book Zero to One (which we’ve discussed before), Thiel proposes startups should hire only “nerds of the same type.” The mafia began investing in several new companies, seeding friends who were likely to perpetuate the cycle of recruiting friends and hiring based on status alone. Rabois, who is currently a venture capitalist has remarked: “Once you have alignment, then I think you can have a wide swath of people, views and perspectives.” These ideas seem more like justification for hiring large groups of white males who were friends of PayPal executives than a truly “meritocratic” process, which is not the best way of building a successful, diverse organization. Roger McNamee, founder of technology private equity firm, Silver Lake, suggests: “They didn’t just perpetuate it; they turned it into a fine art. They legitimized it… The guys were born into the right part of the gene pool, they wind up at the right company, at the right moment in time, they all leave together and [go on] to work together. I give them full credit for it but calling it a meritocracy is laughable.”

Business Themes

1. The Women at Early Google. A lot of people know the story of Sergey Brin meeting co-founder Larry Page. But few are aware of when Sergey and Larry met Susan Wojcicki, who is now CEO of YouTube. Sergey and Larry were looking for office space, and through a mutual friend, were introduced to Susan Wojcicki, who worked in marketing at Intel at the time. Though she didn’t jump on board immediately, Susan eventually came around and was instrumental in launching two of Google’s most important products: AdWords and AdSense. Wojcicki would soon be working closely with a newly recruited, Marissa Mayer, who after graduating from Stanford with a degree in Symbolic Systems, joined Google to help build AdWords and design Google’s front-end. Wojcicki and Mayer would soon be joined by Sheryl Sandberg, who came to Google in 2001 as Vice President of Online Sales and Operations. Another now-famous early female employee was Kim Scott, author of Radical Candor, who joined the company in 2004. All of these early, powerful female leaders, with the continued urging of Larry and Sergey (who wanted to achieve a 50/50 ratio of male to female employees) helped build a strong culture of female leadership. But as the Company scaled it lost sight of its gender diversity goals – “In 2017, women accounted for 31% of employees overall, 25% of leadership roles and 20% of technical roles.” Google claims it lost touch as it scaled, when the need for hiring outpaced the ability to find qualified and diverse candidates – but that sounds like an easy cop out.

2. Startups and Party Culture. Atari and Trilogy Software pioneered the idea of a work-hard, play-hard startup cultures. Nolan Bushnell of Atari would throw wild parties and have employees (including Steve Jobs) work late into the night, building for the company. Trilogy, a provider of sales and marketing software, extended this idea even further. It started with hiring, where, according to a former engineer, Trilogy’s ethos was: “We’re elite talent. It’s potential and talent, not experience, that has merit.” The Company regularly used complicated brain-teasers in interviews and attracted swaths of anti-social engineers with young and attractive talent recruiters. Joe Liemandt, the CEO of Trilogy, also moved the company to Austin, Texas; executives likened the tactic to marooning members of a cult. Co-founder Christy Jones remarked: “I didn’t go on vacation. We called holidays competitive advantage days because no one else was working. It was a chance to get ahead.” The Company had a strong drinking and partying culture and bares striking cult-like resemblance to WeWork, except it had a sustainable business model. Other technology companies have mixed constant alcohol and long hours, which has led to numerous assault charges at well-known startups including Uber, Zenefits, WeWork and others. Startup and party culture does not need to be so intertwined.

3. Hiring Practices to Encourage Diverse Backgrounds. Stewart Butterfield, the founder of Flickr (sold to Yahoo for $20 million in 2005), has focused on diverse hiring efforts at his new company Slack. According to Brotopia, “In 2017, Slack reported that 43.5% of its employees were women, including 48% of managers and almost 30% of technical employees – far better numbers than any tech company in Silicon Valley.” Butterfield, who grew up on a commune in Canada, recognizes his privilege, and discusses its not insanely difficult to create a diverse environment: “As an already successful, white, male, straight – go down the list – I’m not going to have the relevant experience to determine what makes this a good workplace, so some of that is just being open but really just making it an explicit focus.” Slack’s diverse recruiting team was given explicit instructions to source candidates from underrepresented backgrounds and schools for every new role in the organization. More companies should follow Slack’s lead and adopt explicit gender and diversity goals.

Dig Deeper

• Susan Fowler’s blog post describing terrible conditions at Uber

• Overview of gender and diversity statistics of major technology companies

• The Sex and Drug fueled parties of Silicon Valley VCs

• A recap of the Google Walkout over sexual harassment allegations

• The Tech Industry’s diversity is not improving

August 2019 - How Google Works by Eric Schmidt and Jonathan Rosenberg

While at times it reads as a piece of Google propaganda, this book offers insight into the management techniques that Larry, Sergey and Eric employed to grow the Company to massive scale. Its hard to read this book and expect that all of these practices were actually implemented – it reads like a “How to build a utopia work culture” - but some of the principles are interesting, and more importantly it gives us insight into what Google values in their products and operations.

Tech Themes

1. Smart Creatives. Perhaps the most important emphasis in the book is placed on the recruiting and hiring of what Eric Schmidt and Jonathan Rosenberg have termed: Smart Creatives – “people who combine technical & business knowledge, creativity and always-learning attitude.” While these seem like the desired platitudes of every silicon valley employee, it gives a window into what Google finds important in its employees. For example, unlike Amazon, which has both business product managers and technical product managers, Google prefers its PMs to be both business focused and highly technical. Smart Creatives are mentioned hundreds of times in the book and continually underpin the success of new product launches. The book almost harps on it too much, to the point where it feels like Eric Schmidt was trying to convince all Googlers that they were truly unique.

2. Meetings, Q&A, Data and Information Management. Google is one of the many Silicon Valley companies that hosts company wide all-hands Q&A sessions on Friday where anyone can ask a question of Google’s leadership. Information transparency is critically important to Google, and they try to allow data to be accessible throughout the organization at all times. This trickles into other aspects of Google’s management philosophy including meetings and information management. At Google, meetings have a single owner, and while laptops largely remain closed, it’s the owner’s job to present the relevant data and derive the correct insights for the team. To that end, Google makes its information transparently available for all to access – this process is designed to avoid information asymmetry at management levels. One key issue faced by poor management teams is only receiving the best information at the top – this is countered by Amazon through incredibly blunt and aggressive communication; Google, on the other hand, maintains its intense focus on data and results to direct product strategy, so much so that it even studies its own teams productivity using internal data. Google’s laser focus on data makes sense given its main advertising products harvest the world’s internet user data for their benefit, so understanding how to leverage data is always a priority at Google.

3. 80/20 Time. As part of Google’s product innovation strategy, employees can spend 20% of their work time on creative projects separate from their current role. While the idea sounds like an awesome to keep employees interested and motivated, in practice, its much more structured. Ideas have to be approved by managers and they are only allowed if they can directly impact Google’s business. Some great innovations were spawned out of this policy including Gmail and Google Maps but Google employees have joked that it should be called “120%” time rather than 80%.

Business Themes

1. Google’s Cloud Strategy. “You should spend 80% of your time on 80% of your revenue.” This quote speaks volumes when it comes to Google’s business strategy. Google clearly is the leader in Search and search advertising. Not only is it the default search engine preferred by most users, it also owns the browser market that directs searches to Google, and the most used operating system. It has certainly created a dominant position in the market and even done illegal things to maintain that advantage. Google also maintains and mines your data, and as Stratechery has pointed out, they are not hiding it anywhere. But what happens when the next wave of computing comes, and you are so focused on your core business that you end up light years behind competition from Amazon (Web Services) and Microsoft (Azure)? That’s where Google finds itself today, and recent outages and issues haven’t helped. So what is Google’s “Cloud Strategy?” The answer is lower priced, open source alternatives. Google famously developed and open sourced, Kubernetes, the container orchestration platform, which has become an increasingly important technology as developers opt for light weight alternatives to traditional virtual machines. They have followed this open sourcing with a, “We are going to open source everything” mentality that is also being employed, a bit more defensively at Microsoft. Google seeks to be an open source layer, either through Kubernetes (which runs in Azure and AWS) or through other open source platforms (Anthos) and just touch some of your company’s low churn cloud spend. Their issue is scale and support. With their knowledge of data centers and parallel computing, cloud capabilities seemed like an obvious place where Google could win, but they fumbled on building a great product because they were so focused on protecting their core business. They are in a catch up position and new CEO of Google Cloud, Thomas Kurian (formerly at Oracle), isn’t afraid to make acquisitions to build out missing product capabilities, which is why it bought Looker earlier this year. It makes sense why a company as focused as Google is on data, would want a cloud focused data analysis tool. Now they are betting on M&A and a highly open-sourced multi-public cloud future as the only way they can win.

2. “Objective” Key Results. As mentioned previously, the way Google combats potential information asymmetries by empowering individuals throughout the organization with data. This extends to famous venture capitalist (who invested in both Google and Amazon) John Doerr’s favorite data to examine – OKRs – Objective key results. Each Googler has a specific set of OKRs that they are responsible for maintaining on a quarterly basis. Every person’s OKRs are readily available for anyone to see throughout the Company i.e. full transparency. OKRs are public, measurable, and ambitious. This keeps engineers focused and accountable, as long as the OKRs are set correctly and actually measure outcomes. These fit so perfectly with Google’s focus on mining and monitoring data at all times: their products and their employees need to be data driven at all times.

Dig Deeper

• Recent reports highlight numerous cultural issues at Google, that are not addressed in the book

• Google Cloud was plagued by internal clashes and missed acquisitions

• PayPal mafia veteran, Keith Rabois, won’t fund Google PM’s as founders

• List of Google’s biggest product failures over time

• Stadia: Google’s game streaming service

July 2019 - Alibaba: The House That Jack Ma Built by Duncan Clark

This is an excellent book to understand Jack Ma, Alibaba and the Chinese tech ecosystem.

Tech Themes

1. Start with a Team: Alibaba’s 18 founders. At a young age, Jack Ma taught himself English by offering tours of his hometown Hangzhou to locals coming from English speaking countries. Jack went on to study English at Hangzhou Teachers Institute where he graduated in 1988. Following graduation, he taught English for a few years and because of his English skills, he was selected to go on a trip to America, on behalf of the Hangzhou government. While there, he tried using the internet to look up “beer” and noticed there were very few Chinese web pages. When he got back to China, he started China Pages, a custom website development shop for Chinese businesses. The business received funding from the Ministry of Foreign Trade and Economic Cooperation but was losing out to rival telecom company Hangzhou Communications that had recently started a competitor. China Pages was struggling to help customers realize return on their investments because there was so little business happening online at that time in China. Frustrated by competition and worried about the long-term effects of being funded by the government, Jack rounded up a group of 17 people - some were former students, some colleagues in the government, some employees at China Pages - and started Alibaba. Jack also met and recruited Joe Tsai, the first Taiwanese graduate of Yale Law School, who was then working at Investor AB on private equity investments, to join as CFO and founding board member. The team focused on the business to business market which they felt should gain more traction before business to consumer focused companies like Amazon.

2. Open Door Policies: How China became an economic powerhouse. In 2009, China became the World’s biggest exporter, a trend that until recently, seemed all the more likely to continue. But how did we get to this point in China? In 1979, Deng Xiaoping began a series of economic reforms in China that set the stage for enormous growth. The first major act was allowing Chinese individuals to start businesses, a practice that had been strictly forbidden during the previous political era. Next, Deng announced an Open Door Policy, to allow foreign business and investment to flow into specific, Special Economic Zones. This investment spawned incredible growth in now-famous Chinese regions including Shenzhen, which grew GDP on average of 40% per year from 1981 to 1993 and by 2005 became the world’s 3rd busiest port. This incredible growth has created massive companies and seen incredible innovation but has also created global pollution. How sustainable is this great economic expansion?

3. Right Place at the Right Time: The Importance of Timing in Innovation at Alibaba. When trying to build a business, timing can often be more important than the product itself. This can work in a number of ways - during the internet bubble, several entrepreneurs became millionaires on the backs of grandiose ideas without business models. Alibaba is the perfect example of excellent timing. Alibaba was founded in 1999, right as the internet bubble started to heat up. As valuations rose, institutional investors saw returns skyrocketing; this led Goldman Sachs to open up a dedicated Asia Tech fund, focused on investing small amounts into growing Chinese tech companies. Goldman led Alibaba’s first round in 1999 (a $3.3M fundraise), which allowed Alibaba to grow to significant scale with their tight founding team. The internet bubble also attracted a now re-famous Masayoshi Son, and his software distributor turned VC firm, Softbank, to start investing heavily in the internet. Aliababa was by no means the only fast growing Asian Tech company: Sohu (Founded in 1996 by Charles Zhang), Sina (founded in 1998 by Charles Chao who pioneered the Variable Interest Entity designation in China), and NetEase (Founded in 1997 by Ding Lei) were the famed Asian tech darlings of the day. In March 2001, right before the bubble burst, Softbank led a $20M round into Alibaba (which we discuss more below) that allowed Jack the flexibility to weather the internet bubble storm and keep Alibaba private despite growing losses. Sohu, Sina, and NetEase all needed to IPO and limped out into the public markets at poor valuations (Sohu dropped below $1 per share at one point), which caused a long-term drag on their stock prices and business performance. While Alibaba clearly had reached product-market fit by that time, their fortuitous timing (much like that of Amazon’s bond offering) allowed the Company to stay in business during a tough financial time.

Business Themes

1. Different Approaches to Similar Problems: Amazon vs. Alibaba. Alibaba is often hailed as the Amazon of China, but it’s actually, quite different in many major aspects. As discussed recently in this Stratechery article, Amazon’s core e-commerce business is about controlling inventory and logistics. Amazon buys at whole sale prices from brands, keeps the inventory in their 400+ warehouses and ships them out to customers. Retailers pay Amazon a fee on the sale as commission. While this revenue model is similar to Alibaba’s Tmall, a major brand e-commerce site that charges commissions on sale, Alibaba does not retain any inventory in the process. Furthermore, on Alibaba’s Taobao, independent small merchants can list any item for sale and pay no commissions, instead they pay for higher ranking on the site’s internal search engine, similar to Google’s revenue model. While Amazon boxes are delivered nationwide, primarily by Amazon, in China, Alibaba leverages a slew of 3rd party logistics providers to deliver packages any way possible: via bike, motorcycle, car, or on foot. This impacts profit margins as Amazon has to employ its entire logistics operation (350,000+ people) whereas Alibaba is comparatively smaller at 50,000 employees. Beyond their core e-commerce businesses, both Alibaba and Amazon have cloud computing offerings – as discussed before, AWS is the biggest platform in North America, and Alibaba is the biggest in China. While cloud in China is now growing more quickly than North America, it remains a much smaller piece of the overall global cloud landscape.

2. A Lesson in Investing: Analyzing Goldman, Softbank, and Yahoo’s Returns. Alibaba’s funding history is long and complex but illustrates a common dilemma faced by investors and shareholders in startups. Alibaba’s first funding round was led by Goldman Sachs at a $5M pre-money valuation. The next round was a $20M investment in Alibaba, led by Softbank to acquire 1/3 of the Company. At the next funding round in 2004, Softbank invested in an $82M round and Goldman sold its shares, thereby inking a 6.7x return in about 5 years, which by all means is a great investment. However, if Goldman had held on to that share, as Softbank did with its share, at IPO it would have been worth $12.5B, a 3,600x+ return. This is the dilemma faced by several VCs – do I sell now, ink a great return, and make my limited partners happy? Or do I risk it, let my winners ride and realize a potentially career changing win? Yahoo is another example of this complex dilemma. Yahoo invested $1B in Alibaba in 2005 for a 40% stake in the Company (a funding round that was allegedly hashed out over golf at Pebble Beach). After rebuffing Microsoft’s $44.6B offer to buy the Company, Yahoo’s stock price plummeted. A difficult fight with activist investors ensued, and Jerry Yang was eventually fired. This all set up nicely for new CFO, Scott Thompson to come in and promptly offload half of its Alibaba stake for $7.1B, two years later that would be worth $51B. Yahoo, now owned by Verizon, sold its remaining stake earlier this year, and its expected to net shareholders roughly $40B in value.

3. The Everything Companies: The Holdings of Chinese Internet Giants. The number and variety of companies owned by the major tech giants in China is simply staggering. Alibaba has bet big on a wide variety of companies including delivery giant Meituan-Dianping, Lyft, Snap, bike sharing startup Ofo, Chinese ride-hailing company Didi (which recently merged with Uber’s China business), fintech spinoff Ali-Pay and several others. Tencent, creator of the famous all-in-one application, WeChat, has invested in JD.com, League of Legends creator Riot Games, Fortnite creator Epic Games, and many more. Alibaba and Tencent are so competitive with one another that in recent years, the Companies have made thousands of investments trying to fund the next phase of growth in Chinese Tech. As the economist writes, “Tencent has a portfolio of 600 stakeholdings acquired over the past six years (see chart), many unannounced. There is barely a trace of bombast when Jack Ma, Alibaba’s founder, says that he eventually hopes to see former Alibaba employees running 200 of the top 500 Chinese firms.” It will be interesting to see how these investments mature – in 2018 rival delivery firms Meituan and Dianping had to merge to avoid going bankrupt despite billions in funding from Alibaba and Tencent.

Dig Deeper

• The Rise of China's Innovation Machine by WSJ

• Detail on the Uber-Didi ride-sharing merger in China from Business Insider

• 9:00am - 9:00pm, 6 days a week (9-9-6) is what Jack Ma wants out of his employees

• Jack Ma hated eBay

• Tencent’s Investment in Epic Games / Fortnite

May 2019 - The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone

This book is a great deep dive on the history of Amazon and how it became the global powerhouse that it is today.

Tech Themes

1. The Birth of AWS. We’ve looked at the software transition from on premise, license maintenance software to SaaS hosted in the cloud, but let’s dive deep into how the cloud came to be. The first ideas of AWS go back to 2002 when Bezos met with O’Reilly Media, a book publisher who in order to compete with Amazon, had created a way to scrape the latest book rankings off Amazon’s website. O’Reilly suggested creating a set of tools to let developers access Amazon’s rankings, and in 2003 Amazon launched Amazon Web Services (AWS) to create commerce API’s for third parties. Around this time, Amazon had centralized its IT computing resources in a separate building with hardware professionals operating and maintaining the infrastructure for the entire company. While parts of the infrastructure had improved, Amazon was struggling internally to provision and scale its computing resources. In 2004, Chris Pinkham, head of the infrastructure division, relocated to South Africa to open up Amazon’s first office in Cape Town. His first order of business was to figure out the best way to provision resources internally to allow developers to work on all types of applications on Amazon’s servers. Chris elected to use Xen, a computer that sits on top of infrastructure and acts as a controller to allow multiple projects access the same hardware. This led to the development of Elastic Compute Cloud (EC2). During this time, another group within Amazon was working on solving the problem of storing the millions of gigabytes of data Amazon had created. This team was led by Alan Atlas, who could not escape Bezos’ laser focus: “It would always start out fun and happy, with Jeff’s laugh rebounding against the walls. Then something would happen and the meeting would go south and you would fear for your life. I literally thought I’d get fired after everyone one of those meetings.” In March 2006, Amazon launched the Simple Storage Service (S3), and then a few months later launched EC2. Solving internal problems can lead to incredibly successful companies; Slack, for example, originally started as a game development company but couldn’t get the product off the ground and eventually pivoted into the messaging giant that it is today: “Tiny Speck, the company behind Glitch, will continue. We have developed some unique messaging technology with applications outside of the gaming world and a smaller core team will be working to develop new products.”

2. A9. In the early 2000s, Google arrived on the scene and began to sit in between Amazon and potential sales. Around this time, Amazon’s core business was struggling and a New York Times article even called for Bezos to resign. Google was siphoning off Amazon’s engineers and Bezos knew he had to take big strategic bets in order to ward off Google’s advances. To do that, he hired Udi Manber, a former Yahoo executive with a PhD in computer science who had written the authoritative textbook on Algorithms. In 2003, Udi set up shop in Palo Alto in a new Amazon subsidiary called A9 (shorthand for Algorithms). The new subsidiary’s sole goal was to create a web search engine that could rival Google’s. While A9.com never completely took off, the new development center did improve Amazon’s website search and created Clickriver, the beginning of Amazon’s advertising business, which minted $10B in revenue last year. Udi eventually became VP of Engineering for all of Google’s search products and then its Youtube Division. A9 still exists to tackle Amazon’s biggest supply chain math problems.

3. Innovation, Lab126 and the Kindle. In 2004, Bezos called Steve Kessel into his office and moved him from his current role as head of Amazon’s successful online books business, to run Amazon Digital, a small and not yet successful part of Amazon. This would become a repeating pattern in Kessel’s career who now finds himself head of all of Amazon’s physical locations, including its Whole Foods subsidiary. Bezos gave Kessel an incredibly abstract goal, “Your job is to kill your own business. I want you to proceed as if your goal is to put everyone selling physical books out of a job.” Bezos wanted Kessel to create a digital reading device. Kessel spent the next few months meeting with executives at Apple and Palm (make of then famous Palm Pilots) to understand the current challenges in creating such a device. Kessel eventually settled into an empty room at A9 and launched Lab126 (1 stands for a, 26 for z – an ode to Bezos’s goal to sell every book A-Z), a new subsidiary of Amazon. After a long development process and several supply chain issues, the Company launched the Kindle in 2007.

   Business Themes

4. Something to prove: Jeff Bezos’s Childhood. What do Jeff Bezos, Steve Jobs, Elon Musk and Larry Ellison (founder of Oracle) all have in common? They all had somewhat troubled upbringings. Jobs and Ellison were famously put up for adoption at young ages. Musk’s parents divorced and Elon endured several years of an embattled relationship with his father. Jeff Bezos was born Jeffrey Preston Jorgenson, on January 12, 1964. Ted Jorgenson, Bezos’s biological father, married his mother, Jackie Gise after Gise became pregnant at age sixteen. The couple had a troubled relationship and Ted was immature and an inattentive father. The couple divorced in 1965. Jacklyn eventually met Miguel Bezos, a Cuban immigrant college student, while she was working the late shift at the Bank of New Mexico’s accounting department. Miguel and Jacklyn were married in 1968 and Jeffrey Jorgenson became Jeffrey Bezos. Several books have theorized the maniacal drive of these entrepreneurs relates back to ultimately prove self-worth after being rejected by loved ones at a young age.

5. Anti-Competitive Amazon & the Story of Quidsi. Amazon has an internal group dubbed Competitive Intelligence, that’s sole job is to research the products and services of competitors and present results to Jeff Bezos so he can strategically address any places where they may be losing to the competition. In the late 2000s, Competitive Intelligence began tracking a company known as Quidsi, famous for its site Diapers.com, which provided discount baby products that could be purchased on a recurring subscription basis. Quidsi had grown quickly because it had customized its distribution system for baby products. In 2009, competitive intelligence reached out to Quidsi founder, Marc Lore (founder of Jet.com and currently the head of Walmart e-commerce) saying it was looking to invest in the category. After rebuffing the offer, Quidsi soon noticed that Amazon was pricing its baby products 30% cheaper in every category; the company even tried dropping prices lower only to see Amazon pages reset to even lower prices. After a few months, Quidsi knew they couldn’t remain in a price battle for long and launched a sale of the company. Walmart agreed in principle to acquire the business for $900M but upon further diligence reduced its bid, which prompted Lore to call Amazon. Lore and his executive team went to meet with Amazon, and during the meeting, Amazon launched Amazon Mom, which gave 30% discounts on all baby products and allowed participants to purchase products on a recurring basis. At one point, Amazon’s prices dipped so low it was on track to lose $100M in three months in the diapers category alone. Amazon submitted a $540M bid for Quidsi and subsequently entered into an exclusivity period with the Company. As the end to exclusivity grew nearer, Walmart submitted a new bid at $600M, but the Amazon team threatened full on price war if Quidsi went with Walmart, so on November 8, 2010, Quidsi was acquired by Amazon for $540M. One month after the acquisition, Amazon stopped the Amazon Mom program and raised all of its prices back to normal levels. The Federal Trade Commission reviewed the deal for four months (longer than usual), but ultimately allowed the acquisition because it did not create a monopoly in the sale of baby products. Quidsi was ultimately shut down by Amazon in 2017, because it was unable to operate it profitably.

6. The demanding Jeff Bezos and six page memos. At Amazon, nobody uses powerpoint presentations. Instead, employees write out six page narratives in prose. Bezos believes this helps create clear and concise thinking that gets lost in flashy powerpoint slides. Whenever someone wants to launch new initiative or project, they have to submit a six page memo framed as if a customer might be hearing it for the first time. Each meeting begins with the group reading the document and the discussion begins from there. At times, especially around the release of AWS, these documents grew increasingly complex in length and size given the products being described did not already exist. Bezos often responds intensely to these memos, with bad responses including: “Are you just lazy or incompetent?” and “If I hear that idea again, I’m gonna have to kill myself” and “This document was clearly written by the B team. Can someone get me the A team document? I don’t want to waste my time with the B team document.” Its no wonder Amazon is such a terrible place to work.

Dig Deeper

• How Amazon took the opposite approach that apple took to pricing EC2 and S3

• The failed Amazon Fire Phone and taking big bets

• The S Team - Amazon’s intense executives

• The little-known deal that saved Amazon from the dot-com crash

• Mary Meeker, Amazon and the internet bubble: Amazon.bomb: How the internet's biggest success story turned sour

• Customer Centric: Amazon Celebrates 20 Years Of Stupendous Growth As 'Earth's Most Customer-Centric Company

February 2019 - Cloud: Seven Clear Business Models by Timothy Chou

While this book is relatively old for internet standards, it illuminates the early transition to SaaS (Software as a Service) from traditional software license and maintenance models. Timothy Chou, current Head of IoT at the Alchemist Accelerator, former Head of On Demand Applications at Oracle, and a lecturer at Stanford, details seven different business models for selling software and the pros/cons of each.

Tech Themes

1. The rise of SaaS. Software-as-a-Service (SaaS) is an application that can be accessed through a web browser and is managed and hosted by a third-party (likely a public cloud - Google, Microsoft, or AWS). Let’s flash back to the 90’s, a time when software was sold in shrink-wrapped boxes as perpetual licenses. What this meant was you owned whatever version of the software you purchased, in perpetuity. Most of the time you would pay a maintenance cost (normally 20% of the overall license value) to receive basic upkeep services to the software and get minor bugs fixed. However, when the new version 2.0 came out, you would have to pay another big license fee, re-install the software and go through the hassle of upgrading all existing systems. On the backs of increased internet adoption, SaaS allowed companies to deliver a standard product, over the internet, typically at lower price point to end users. This meant smaller companies like salesforce (at the time) could compete with giants like Siebel Systems (acquired by Oracle for $5.85Bn in 2005) because companies could now purchase the software in an on-demand, by-user fashion without going to the store, at a much lower price point.

2. How cloud empowers SaaS. As an extension, standardization of product means you can aptly define the necessary computing resources - thereby also standardizing your costs. At the same time that SaaS was gaining momentum, the three mega public cloud players emerged, starting with Amazon (in 2006), then Google and eventually Microsoft. This allowed companies to host software in the cloud and not on their own servers (infrastructure that was hard to manage internally). So instead of racking (pun intended) up costs with an internal infrastructure team managing complex hardware - you could offload your workloads to the cloud. Infrastructure as a service (IaaS) was born. Because SaaS is delivered over the internet at lower prices, the cloud became an integral part of scaling SaaS businesses. As the number of users grew on your SaaS platform, you simply purchased more computing space on the cloud to handle those additional users. Instead of spending big amounts of money on complex infrastructural costs/decisions, a company could now focus entirely on its product and go-to-market strategy, enabling it to reach scale much more quickly.

3. The titans of enterprise software. Software has absolutely changed in the last 20 years and will likely continue to evolve as more specialized products and services become available. That being said, the perennial software acquirers will continue to be perennial software acquirers. At the beginning of his book, Chou highlights fifteen companies that had gone public since 1999: Concur (IPO: 1999, acquired by SAP for $8.3B in 2014), Webex (IPO: 2002, acquired by Cisco in for $3.2B in 2007), Kintera (IPO: 2003, acquired by Blackbaud for $46M in 2008), Salesforce.com (IPO: 2004), RightNow Technologies (IPO: 2004, acquired by Oracle for $1.5B in 2011), Websidestory (IPO: 2004, acquired by Omniture in 2008 for $394M), Kenexa (IPO: 2005, acquired by IBM for $1.3B in 2012), Taleo (IPO: 2005, acquired for $1.9B by Oracle in 2012), DealerTrack (IPO 2005, acquired by Cox Automotive in 2015 for $4.0B), Vocus (IPO: 2005, acquired by GTCR in 2014 for $446M), Omniture (IPO: 2006, acquired by Adobe for $1.8B in 2009), Constant Contact (IPO: 2007, acquired by Endurance International for $1B in 2015), SuccessFactors (IPO: 2007, acquired by SAP for $3.4B in 2011), NetSuite (IPO 2007: acquired by Oracle for $9.3B in 2016) and Opentable (IPO: 2009, acquired by Priceline for $2.6B in 2015). Oracle, IBM, Cisco and SAP have been some of the most active serial acquirers in tech history and this trend is only continuing. Interestingly enough, Salesforce.com is now in a similar position. What it shows is that if you can come to dominate a horizontal application - CRM (salesforce), ERP (SAP/Oracle), or Infrastructure (Google/Amazon/Microsoft) you can build a massive moat that allows you to become the serial acquirer in that space. You then have first and highest dibs at every target in your industry because you can underwrite an acquisition to the highest strategic multiple. Look for these acquirers to continue to make big deals when it can further lock in their market dominant position especially when you see their core business slow.

   Business Themes

Here we see the “Cash Gap” in the subscription model - customer acquisition expenses are incurred upfront but are recouped over time.

1. The misaligned incentives of traditional license/maintenance model. Software was traditionally sold as perpetual licenses, where a user could access that version of the software forever. Because users were paying to use something forever, the typical price point was very high for any given enterprise software license. This meant that large software upgrades were made at the the most senior levels of management and were large investments from a dollars and time perspective. On top of that initial license came the 20% support costs paid annually to receive patch updates. At the software vendor, this structure created interesting incentives. First, product updates were usually focused on break-fix and not new, “game-changing” upgrades because supporting multiple, separate versions of the software (especially, pre-IaaS) was incredibly costly. This slowed the pace of innovation at those large software providers (turning them into serial acquirers). Second, the sales team became focused on selling customers on new releases directly after they signed the initial deal. This happened because once you made that initial purchase, you owned that version forever; what better way to get more money off of you than introduce a new feature and re-sell you the whole system again. Salespeople were also incredibly focused on closing deals in a certain quarter because any single deal could make or break not only their quarterly sales quota, but also the Company’s revenue targets. If one big deal slipped from Q4 to Q1 the following year, a Company may have to report lower growth numbers to the stock market driving the stock price down. Third, once you made the initial purchase, the software vendor would direct all problems and product inquiries to customer support who were typically overburdened by requests. Additionally, the maintenance/support costs were built into the initial contract so you may end up contractually obligated to pay for support for a product that you don’t like and cannot change. The Company viewed it as: “You’ve already purchased the software, so why should I waste time ensuring you have a great experience with it - unless you are looking to buy the next version, I’m going to spend my time selling to new leads.” These incentives limited product changes/upgrades, focused salespeople completely on new leads, and hurt customer experience, all at the benefit of the Company over the user.

2. What are CAC and LTV? CAC or customer acquisition costs are key to understand for any type of software business. As HubSpot and distinguished SaaS investor, David Skok notes, its typically measured as, “the entire cost of sales and marketing over a given period, including salaries and other headcount related expenses, and divide it by the number of customers that you acquired in that period.” Once the software sales model shifted from license/maintenance to SaaS, instead of hard-to-predict, big new license sales, companies started to receive monthly recurring payments. Enterprise software contracts are typically year-long, which means that once a customer signs the Company will know exactly how much revenue it should plan to receive over the coming year. Furthermore, with recurring subscriptions, as long as the customer was happy, the Company could be reasonably assured that customer would renew. This idea led to the concept of Lifetime Value of a customer or LTV. LTV is the total amount of revenue a customer will pay the Company until it churns or cancels the subscription. The logic followed that if you could acquire a customer (CAC) for less than the lifetime value of the customer (LTV), over time you would make money on that individual customer. Typically, investors view a 3:1 LTV to CAC ratio as viable for a healthy SaaS company.

Dig Deeper

• Bill Gates 1995 memo on the state of early internet competition: The Internet Tidal Wave

• Andy Jassey on how Amazon Web Services got started

• Why CAC can be a Startup Killer?

• How CAC is different for different types of software

• Basic SaaS Economics by David Skok