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October 2022 - Amp it Up by Frank Slootman

This month we cover our third Frank Slootman book, Amp it Up! It covers Slootman’s overall philosophy with a specific focus on achieving significant growth at scale and how companies can push the boundary of their growth potential. Frank only wrote the book because Snowflake’s CMO encouraged him to do so.

Tech Themes

  1. Expanding the TAM. One core idea that Slootman has used across both ServiceNow and Snowflake is the idea of expanding the TAM. By expanding the TAM, you lengthen your growth runway because there are more people who are capable of using your software. Slootman employed this strategy perfectly at ServiceNow. When on the IPO roadshow for the company, analysts at Gartner kept telling potential investors that ServiceNow had a small TAM of only $1.5B. An old short report of ServiceNow by Kerrisdale Capital highlights this confusion: “ The overall ITSM market size is only $1.5 billion, less than one-third of NOW's $4.7 billion market capitalization. Leading technology research firm Gartner estimates that the IT Service Management market opportunity is $1.5 billion, and is growing at a modest 7% per year. Furthermore, Gartner's research predicts that only 50% of IT organizations will move to SaaS by 2015, implying that the total market opportunity for NOW's ITSM business is less than $1 billion. Given emerging competition from other SaaS ITSM service providers, we believe that the company will have a difficult time exceeding 30% market share. At $207m of LTM revenue, NOW appears to already control 10% to 15% of the market. So even if NOW's market share rises to 30%, which we don't see happening until 2014 at the earliest, NOW's ITSM business should be generating less than $600m in revenue with limited additional growth opportunities. The result of the limited market size and increasing competition will be flattening growth over the next few years.” Kerrisdale was clearly incorrect. Market size estimates are now closer to $12-15B. Slootman and the team realized that to complete the full remediation of issues, more people in the organization needed to access ServiceNow’s tools and core ticketing system. They deliberately went function by function (network engineers, sys admins, database admins) and added specific functionality to enhance the user experience of these groups. One of these product enhancements was ServiceNow’s configuration management database or CMDB, which keeps a log of every device and its exact specifications to allow for faster triage of issues. Slootman has taken this approach to Snowflake, which started out by focusing on just the data warehousing workload but has since expanded into seven unique workloads: data warehouse, data engineering, data science, collaboration, data sharing, unistore, and cybersecurity. These workloads now bring in more people to the Snowflake platform: database administrators, data engineers, analytics engineers, data analysts, data scientists, and cybersecurity analysts. Each new set of tools added, enhances the overall value of the platform and the stickiness of the solution within the organization. This is a great roadmap for how to keep growth elevated in horizontal markets.

  2. Strategy vs. Execution. “Culture eats strategy for breakfast.” Peter Drucker, a famous consultant, and author of the Concept of the Corporation, believed that culture was far more important than strategy. Slootman agrees and even takes it one step further: “Execution has to be your number one goal. Strategy can’t be mastered until you can execute. Great execution is rarer than great strategy.” Slootman actually disagrees with Drucker on the management by objectives framework, “Another source of misalignment is management by objectives, which I have eliminated at every company i’ve joined in the last twenty years. MBOs cause employees to act as if they are running their own show, because they get compensated on their personal metrics, it is next to impossible to pull them off projects. They will be negotiating with you for relief. That is not alignment, that is every man for himself. If you need MBOs to get people to do their jobs, you may have the wrong people, the wrong managers, or both.” In Slootman’s eyes, management by objectives, which sets objectives for an entire organization that are translated into individual goals, ends up being abused by managers. Managers may rely on the objectives solely, and discount the leadership and creative thought necessary to succeed beyond an objective. “A person can do an excellent job according to objective measurement standards, but can fail miserably as a partner, subordinate, superior, or colleague. It is common for people not to be promoted for personal reasons than because of technical inadequacies.” For Slootman, superior execution comes from good judgment, and good judgment comes from bad judgment. Bad judgment is only made clear through experience, which can be the best teacher in his eyes. “New managers have to learn from and through their management chain. Organizations cannot scale and mature around inexperienced management staff.” At Data Domain, Slootman’s team finally started seeing success when they found the right leader for their contract manufacturing organization; at ServiceNow, when they found the right leader for cloud infrastructure; at Snowflake, when they found the right leader for scaling. “The organization needs innovation and discipline, or else the place will simply implode on itself. The common mistake is to rely on our innovators for discipline.” 5 dysfunctions of a team. Why execution is harder than strategy. But need to Prepare your next strategy early so you are ready when you get there.

  3. Recruiting Talent. Slootman urges leaders to recruit drivers, not passengers. “Passengers are people who don't mind simply being carried along by the company's momentum, offering little or no input, seemingly not caring much about the direction chosen by management. They are often pleasant, get along with everyone, attend meetings promptly, and generally do not stand out as troublemakers. They are often accepted into the fabric of the organization and stay there for many years. The problem is that while passengers can often diagnose and articulate a problem quite well, they have no investment in solving it. They don't do the heavy lifting. Drivers, on the other hand, get their satisfaction from making things happen, not blending in with the furniture. They feel a strong sense of ownership for their projects and teams and demand high standards from both themselves and others. They exude energy, urgency, ambition, even boldness. Faced with a challenge, they usually say, ‘Why not’ rather than ‘That’s impossible.’ These qualities make drivers massively valuable. Finding, recruiting, rewarding, and retaining them should be among your top priorities.” What I find most interesting about this philosophy is that most jobs train people to be passengers. Most CEOs prefer the calm and non-trouble making attitude of passengers over the outspokenness and aggression that sometimes comes with drivers. So what do you do when you find passengers? Its simple - get them off the bus. Although it can be intense, you need to execute by removing people first, getting the right people in, and then getting the right people in the right spots. We talked about this analogy in the Jim Collins book Good to Great. “At a struggling company, you need to change things fast by switching out people whose skills no longer fit the mission or never really did in the first place. The other advantage of moving fast is that everyone who stays on the bus will know that you are dead serious about high standards. The good ones will be energized by those standards.” The challenge with moving quickly is finding the right balance for what the organization can absorb at any given time. Moving too quickly when the organization is not ready, or moving too quickly when the plan hasn’t been set can lead to drastic consequences.

Business Themes

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  1. Turnarounds as a Training Ground. Famous football coach Bill Walsh joined the San Francisco 49ers after they were the last placed team in the NFL with a 2-14 record. The next season, Walsh’s first, the 49ers repeated the performance - 2-14 again. Walsh at one point broke down on a flight home from a crushing defeat against Miami. 16 months later, he was Super Bowl champion. Turnarounds provide an unbelievably difficult training ground for young executives. It is sink or swim, it is kill or be killed. As discussed in our last book, Bill McDermott took over the struggling SAP North America division before righting the ship and accelerating SAP to growth. Frank Slootman began his managerial career in similar situations. After stints at Burroughs Corporation in corporate planning and Comshare in product management, Frank joined Compuware as head of non-mainframe Product Management. While there, Compuware acquired the dutch company, uniface, as we touched on in the Tape Sucks book. “I jumped at the opportunity return to Amsterdam to take on the entire operation, which seemed in disarray. Colleagues warned me not to go because the place could not be saved, and they worried I’d go down with the ship. Compuware had bought uniface toward the end of its viable product software. But by now, my career had been about taking on what seemed like long odds, jobs nobody else would touch with a 10 foot pole. It was the only avenue open to me anyway and it didn’t matter how hairy these deals were. As a young person, you easily overestimate your capabilities, this is when I started learning what happens when you step into the wrong elevators. We did manage to stabilize uniface. That became a formative career experience in my mid-30s. I’d never had multiple numerous large, mission-critical customers before and hundreds of employees in my charge. I also started to develop an eye for talent which became a cornerstone of my management focus going forward.” Next, Slootman jumped to Ecosystems, a Compuware subsidiary based in silicon valley. He stabilized the struggling company, but they kept losing talent because mid-western Compuware wasn’t able to retain silicon valley employees. He then joined Borland as SVP of product operations, which had also fallen on hard times. They resurrected the brand and the business. Even by 40 years old, he was taking on problem children, and he kept getting offered CEO jobs at companies that were elevators to nowhere. Slootman interviewed over and over for CEO roles but was passed on because “you’ve never run sales.” He later commented on being passed over: “I led from the front and sold shoulder to shoulder with sales. These rejections left me with an unfavorable opinion of many venture capitalists who couldn’t recognize talent if it smacked them in the face.” Turnarounds, especially those inside big companies offer management challenges that most people don’t get to experience until its too late. For Slootman and McDermott, these were the right opportunities for their personalities and approaches at the right time of their career.

  2. Frank doesn’t believe in a Customer Success department. At Snowflake, there is no customer success department. In Slootman’s eyes: “They were happy to follow the trend set up by other companies like ours. But not me. I pulled the plug on these customer success departments in both companies, reassigning the staff back to the departments where their expertise fit best. Here’s why I was so opposed - if you have a customer success department that gives everyone else an incentive to stop worrying about how well our customers are thriving with our products and services. That sets up a disconnect that can create major problems down the road. People can become more focused on hitting the narrow goals of their silo rather than the broader and more important goal of customer satisfaction, which ultimately drives customer retention, word of mouth, profitability, and the long-term survival of the whole company. For instance, at ServiceNow, some of the customer success people grew quite dominant in the interaction with the customer and coordinated all the resources of the company for the customer’s benefit, including technical support, professional services, and even engineering. This had the effect that other departments sat back, became more passive, and felt less ownership of customer success. Customer success is the business of the entire company, not merely one department.” While this approach may work for Snowflake, it is not the norm in the SaaS world. In fact, there are entire companies like Gainsight, Totango, and ChurnZero, that help companies accelerate their Customer Success motion. Openview Venture Partners views customer success as critical for an effective product-led growth sales motion. Sales and Customer Success are important ways of generating product feedback from customers, but organizations need to make sure not to overwhelm product and engineering priorities. Often product teams don’t invest enough time in understanding the sales organization and the sales team views the product team as simply delivering on features to close deals. Leadership is necessary to help set priorities and collaboration across these departments.

  3. 5 steps to Amp it Up. Slootman outlines a five-step process for business leaders to accelerate growth and transform their organizations. The first step is to raise your standards and set ambitious goals for your company. This is followed by aligning your people and culture to support your vision, which requires careful attention to hiring, training, and communication. The third step is to sharpen your focus and prioritize the most critical areas of your business for growth. Once you have a clear focus, the fourth step is to pick up the pace and execute with speed and urgency. Finally, the fifth step is to transform your strategy by continually adapting to changes in the market and taking bold actions to stay ahead of the competition. By following these five steps, Slootman believes that business leaders can create a culture of high performance and achieve extraordinary results. Underpinning everything, is a culture of trust. Ultimately high performance cultures can be challenging and Slootman had times where former founders like Fred Luddy disagreed with his decisions. But as Slootman puts it: “In the long run, success trumps popularity. In my early days at several companies, founders openly regretted my hiring and openly complained to the board behind my back. But when companies succeed massively, as all of our companies have, founders will eventually get over it. Yes, its nice if they love you, but you can’t let yourself get rattled if they don’t. Your mission is to win, not to achieve popularity.”

Dig Deeper

  • Original Amp It Up Blog Post from 2018

  • Snowflake CEO Frank Slootman: taking ownership, increasing velocity & cultivating talent

  • The CEO Behind Software's Biggest IPO Ever | Forbes

  • Frank Slootman Is a Malcontent—That’s How He Likes It

  • The ServiceNow Story by Fred Luddy and Doug Leone

  • Knowledge12 Report: The world according to Frank Slootman

tags: Frank Slootman, Snowflake, ServiceNow, Data Domain, Sequoia, Borland, Burroughs, Compushare, ITSM, Peter Drucker, MBO, Jim Collins, Bill Walsh, Bill McDermott, SAP, Openview, Gainsight
categories: Non-Fiction
 

February 2021 - Rise of the Data Cloud by Frank Slootman and Steve Hamm

This month we read a new book by the CEO of Snowflake and author of our November 2020 book, Tape Sucks. The book covers Snowflake’s founding, products, strategy, industry specific solutions and partnerships. Although the content is somewhat interesting, it reads more like a marketing book than an actually useful guide to cloud data warehousing. Nonetheless, its a solid quick read on the state of the data infrastructure ecosystem.

Tech Themes

  1. The Data Warehouse. A data warehouse is a type of database that is optimized for analytics. These optimizations mainly revolve around complex query performance, the ability to handle multiple data types, the ability to integrate data from different applications, and the ability to run fast queries across large data sets. In contrast to a normal database (like Postgres), a data warehouse is purpose-built for efficient retrieval of large data sets and not high performance read/write transactions like a typical relational database. The industry began in the late 1970s and early 80’s, driven by work done by the “Father of Data Warehousing” Bill Inmon and early competitor Ralph Kimball, who was a former Xerox PARC designer. In 1986, Kimball launched Redbrick Systems and Inmon launched Prism Solutions in 1991, with its leading product the Prism Warehouse Manager. Prism went public in 1995 and was acquired by Ardent Software in 1998 for $42M while Red Brick was acquired by Informix for ~$35M in 1998. In the background, a company called Teradata, which was formed in the late 1970s by researchers at Cal and employees from Citibank, was going through their own journey to the data warehouse. Teradata would IPO in 1987, get acquired by NCR in 1991; NCR itself would get acquired by AT&T in 1991; NCR would then spin out of AT&T in 1997, and Teradata would spin out of NCR through IPO in 2007. What a whirlwind of corporate acquisitions! Around that time, other new data warehouses were popping up on the scene including Netezza (launched in 1999) and Vertica (2005). Netezza, Vertica, and Teradata were great solutions but they were physical hardware that ran a highly efficient data warehouse on-premise. The issue was, as data began to grow on the hardware, it became really difficult to add more hardware boxes and to know how to manage queries optimally across the disparate hardware. Snowflake wanted to leverage the unlimited storage and computing power of the cloud to allow for infinitely scalable data warehouses. This was an absolute game-changer as early customer Accordant Media described, “In the first five minutes, I was sold. Cloud-based. Storage separate from compute. Virtual warehouses that can go up and down. I said, ‘That’s what we want!’”

  2. Storage + Compute. Snowflake was launched in 2012 by Benoit Dageville (Oracle), Thierry Cruanes (Oracle) and Marcin Żukowski (Vectorwise). Mike Speiser and Sutter Hill Ventures provided the initial capital to fund the formation of the company. After numerous whiteboarding sessions, the technical founders decided to try something crazy, separating data storage from compute (processing power). This allowed Snowflake’s product to scale the storage (i.e. add more boxes) and put tons of computing power behind very complex queries. What may have been limited by Vertica hardware, was now possible with Snowflake. At this point, the cloud had only been around for about 5 years and unlike today, there were only a few services offered by the main providers. The team took a huge risk to 1) bet on the long-term success of the public cloud providers and 2) try something that had never successfully been accomplished before. When they got it to work, it felt like magic. “One of the early customers was using a $20 million system to do behavioral analysis of online advertising results. Typically, one big analytics job would take about thirty days to complete. When they tried the same job on an early version of Snowflake;’s data warehouse, it took just six minutes. After Mike learned about this, he said to himself: ‘Holy shit, we need to hire a lot of sales people. This product will sell itself.’” This idea was so crazy that not even Amazon (where Snowflake runs) thought of unbundling storage and compute when they built their cloud-native data warehouse, Redshift, in 2013. Funny enough, Amazon also sought to attract people away from Oracle, hence the name Red-Shift. It would take Amazon almost seven years to re-design their data warehouse to separate storage and compute in Redshift RA3 which launched in 2019. On top of these functional benefits, there is a massive gap in the cost of storage and the cost of compute and separating the two made Snowflake a significantly more cost-competitive solution than traditional hardware systems.

  3. The Battle for Data Pipelines. A typical data pipeline (shown below) consists of pulling data from many sources, perform ETL/ELT (extract, load, transform and vice versa), centralizing it in a data warehouse or data lake, and connecting that data to visualization tools like Tableau or Looker. All parts of this data stack are facing intense competition. On the ETL/ELT side, you have companies like Fivetran and Matillion and on the data warehouse/data lake side you have Snowflake and Databricks. Fivetran focuses on the extract and load portion of ETL, providing a data integration tool that allows you to connect to all of your operational systems (salesforce, zendesk, workday, etc.) and pull them all together in Snowflake for comprehensive analysis. Matillion is similar, except it connects to your systems and imports raw data into Snowflake, and then transforms it (checking for NULL’s, ensuring matching records, removing blanks) in your Snowflake data warehouse. Matillion thus focuses on the load and transform steps in ETL while Fivetran focuses on the extract and load portions and leverages dbt (data build tool) to do transformations. The data warehouse vs. data lake debate is a complex and highly technical discussion but it mainly comes down to Databricks vs. Snowflake. Databricks is primarily a Machine Learning platform that allows you to run Apache Spark (an open-source ML framework) at scale. Databricks’s main product, Delta Lake allows you to store all data types - structured and unstructured for real-time and complex analytical processes. As Datagrom points out here, the platforms come down to three differences: data structure, data ownership, and use case versatility. Snowflake requires structured or semi-structured data prior to running a query while Databricks does not. Similarly, while Snowflake decouples data storage from compute, it does not decouple data ownership meaning Snowflake maintains all of your data, whereas you can run Databricks on top of any data source you have whether it be on-premise or in the cloud. Lastly, Databricks acts more as a processing layer (able to function in code like python as well as SQL) while Snowflake acts as a query and storage layer (mainly driven by SQL). Snowflake performs best with business intelligence querying while Databricks performs best with data science and machine learning. Both platforms can be used by the same organizations and I expect both to be massive companies (Databricks recently raised at a $28B valuation!). All of these tools are blending together and competing against each other - Databricks just launched a new LakeHouse (Data lake + data warehouse - I know the name is hilarious) and Snowflake is leaning heavily into its data lake. We will see who wins!

An interesting data platform battle is brewing that will play out over the next 5-10 years: The Data Warehouse vs the Data Lakehouse, and the race to create the data cloud

Who's the biggest threat to @snowflake? I think it's @databricks, not AWS Redshifthttps://t.co/R2b77XPXB7

— Jamin Ball (@jaminball) January 26, 2021

Business Themes

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  1. Marketing Customers. This book at its core, is a marketing document. Sure, it gives a nice story of how the company was built, the insights of its founding team, and some obstacles they overcame. But the majority of the book is just a “Imagine what you could do with data” exploration across a variety of industries and use cases. Its not good or bad, but its an interesting way of marketing - that’s for sure. Its annoying they spent so little on the technology and actual company building. Our May 2019 book, The Everything Store, about Jeff Bezos and Amazon was perfect because it covered all of the decision making and challenging moments to build a long-term company. This book just talks about customer and partner use cases over and over. Slootman’s section is only about 20 pages and five of them cover case studies from Square, Walmart, Capital One, Fair, and Blackboard. I suspect it may be due to the controversial ousting of their long-time CEO Bob Muglia for Frank Slootman, co-author of this book. As this Forbes article noted: “Just one problem: No one told Muglia until the day the company announced the coup. Speaking publicly about his departure for the first time, Muglia tells Forbes that it took him months to get over the shock.” One day we will hear the actual unfiltered story of Snowflake and it will make for an interesting comparison to this book.

  2. Timing & Building. We often forget how important timing is in startups. Being the right investor or company at the right time can do a lot to drive unbelievable returns. Consider Don Valentine at Sequoia in the early 1970’s. We know that venture capital fund performance persists, in part due to incredible branding at firms like Sequoia that has built up over years and years (obviously reinforced by top-notch talents like Mike Moritz and Doug Leone). Don is a great investor and took significant risks on unproven individuals like Steve Jobs (Apple), Nolan Bushnell (Atari), and Trip Hawkins (EA). But he also had unfettered access to the birth of an entirely new ecosystem and knowledge of how that ecosystem would change business, built up from his years at Fairchild Semiconductor. Don is a unique person and capitalized on that incredible knowledgebase, veritably creating the VC industry. Sequoia is a top firm because he was in the right place at the right time with the right knowledge. Now let’s cover some companies that weren’t: Cloudera, Hortonworks, and MapR. In 2005, Yahoo engineers Doug Cutting and Mike Cafarella, inspired by the Google File System paper, created Hadoop, a distributed file system for storing and accessing data like never before. Hadoop spawned many companies like Cloudera, Hortonworks, and MapR that were built to commercialize the open-source Hadoop project. All of the companies came out of the gate fast with big funding - Cloudera raised $1B at a $4B valuation prior to its 2017 IPO, Hortonworks raised $260M at a $1B valuation prior to its 2014 IPO, and MapR $300M before it was acquired by HPE in 2019. The companies all had one thing in problem however, they were on-premise and built prior to the cloud gaining traction. That meant it required significant internal expertise and resources to run Cloudera, Hortonworks, and MapR software. In 2018, Cloudera and Hortonworks merged (at a $5B valuation) because the competitive pressure from the cloud was eroding both of their businesses. MapR was quietly acquired for less than it raised. Today Cloudera trades at a $5B valuation meaning no shareholder return since the merger and the business is only recently slightly profitable at its current low growth rate. This cautionary case study shows how important timing is and how difficult it is to build a lasting company in the data infrastructure world. As the new analytics stack is built with Fivetran, Matillion, dbt, Snowflake, and Databricks, it will be interesting to see which companies exist 10 years from now. Its probable that some new technology will come along and hurt every company in the stack, but for now the coast is clear - the scariest time for any of these companies.

  3. Burn Baby Burn. Snowflake burns A LOT of money. In the Nine months ended October 31, 2020, Snowflake burned $343M, including $169M in their third quarter alone. Why would Snowflake burn so much money? Because they are growing efficiently! What does efficient growth mean? As we discussed in the last Frank Slootman book - sales and marketing efficiency is a key hallmark to understand the quality of growth a company is experiencing. According to their filings, Snowflake added ~$230M of revenue and spent $325M in sales and marketing. This is actually not terribly efficient - it supposes a dollar invested in sales and marketing yielded $0.70 of incremental revenue. While you would like this number to be closer to 1x (i.e. $1 in S&M yield $1 in revenue - hence a repeatable go-to-market motion), it is not terrible. ServiceNow (Slootman’s old company), actually operates less efficiently - for every dollar it invests in sales and marketing, it generates only $0.55 of subscription revenue. Crowdstrike, on the other hand, operates a partner-driven go-to-market, which enables it to generate more while spending less - created $0.90 for every dollar invested in sales and marketing over the last nine months. However, there is a key thing that distinguishes the data warehouse compared to these other companies and Ben Thompson at Stratechery nails it here: “Think about this in the context of Snowflake’s business: the entire concept of a data warehouse is that it contains nearly all of a company’s data, which (1) it has to be sold to the highest levels of the company, because you will only get the full benefit if everyone in the company is contributing their data and (2) once the data is in the data warehouse it will be exceptionally difficult and expensive to move it somewhere else. Both of these suggest that Snowflake should spend more on sales and marketing, not less. Selling to the executive suite is inherently more expensive than a bottoms-up approach. Data warehouses have inherently large lifetime values given the fact that the data, once imported, isn’t going anywhere.” I hope Snowflake burns more money in the future, and builds a sustainable long-term business.

Dig Deeper

  • Early Youtube Videos Describing Snowflake’s Architecture and Re-inventing the Data Warehouse

  • NCR’s spinoff of Teradata in 2007

  • Fraser Harris of Fivetran and Tristan Handy of dbt speak at the Modern Data Stack Conference

  • Don Valentine, Sequoia Capital: "Target Big Markets" - A discussion at Stanford

  • The Mike Speiser Incubation Playbook (an essay by Kevin Kwok)

tags: Snowflake, Data Warehouse, Oracle, Vertica, Netezza, IBM, Databricks, Apache Spark, Open Source, Fivetran, Matillion, dbt, Data Lake, Sequoia, ServiceNow, Crowdstrike, Cloudera, Hortonworks, MapR, BigQuery, Frank Slootman, Teradata, Xerox, Informix, NCR, AT&T, Benoit Dageville, Mike Speiser, Sutter Hill Ventures, Redshift, Amazon, ETL, Hadoop, SQL
categories: Non-Fiction
 

February 2020 - How the Internet Happened: From Netscape to the iPhone by Brian McCullough

Brian McCullough, host of the Internet History Podcast, does an excellent job of showing how the individuals adopted the internet and made it central to their lives. He follows not only the success stories but also the flame outs which provide an accurate history of a time of rapid technological change.

Tech Themes

  1. Form to Factor: Design in Mobile Devices. Apple has a long history with mobile computing, but a few hiccups in the early days are rarely addressed. These hiccups also telegraph something interesting about the technology industry as a whole - design and ease of use often trump features. In the early 90’s Apple created the Figaro, a tablet computer that weighed eight pounds and allowed for navigation through a stylus. The issue was it cost $8,000 to produce and was 3/4 of an inch thick, making it difficult to carry. In 1993, the Company launched the Newton MessagePad, which cost $699 and included a calendar, address book, to-do list and note pad. However, the form was incorrect again; the MessagePad was 7.24 in. x 4.5 in. and clunky. With this failure, Apple turned its attention away from mobile, allowing other players like RIM and Blackberry to gain leading market share. Blackberry pioneered the idea of a full keyboard on a small device and Marc Benioff, CEO of salesforce.com, even called it, “the heroin of mobile computing. I am serious. I had to stop.” IBM also tried its hand in mobile in 1992, creating the Simon Personal Communicator, which had the ability to send and receive calls, do email and fax, and sync with work files via an adapter. The issue was the design - 8 in. by 2.5 in. by 1.5 in. thick. It was a modern smartphone, but it was too big, clunky, and difficult to use. It wasn’t until the iPhone and then Android that someone really nailed the full smart phone experience. The lessons from this case study offer a unique insight into the future of VR. The company able to offer the correct form factor, at a reasonable price can gain market share quickly. Others who try to pioneer too much at a time (cough, magic leap), will struggle.

  2. How to know you’re onto something. Facebook didn’t know. On November 30, 2004, Facebook surpassed one million users after being live for only ten months. This incredible growth was truly remarkable, but Mark Zuckerberg still didn’t know facebook was a special company. Sean Parker, the founder of Napster, had been mentoring Zuckerberg the prior summer: “What was so bizarre about the way Facebook was unfolding at that point, is that Mark just didn’t totally believe in it and wanted to go and do all these other things.” Zuckerberg even showed up to a meeting at Sequoia Capital still dressed in his pajamas with a powerpoint entitled: “The Top Ten Reasons You Should Not Invest.” While this was partially a joke because Sequoia has spurned investing in Parker’s latest company, it represented how immature the whole facebook operation was, in the face of rapid growth. Facebook went on to release key features like groups, photos, and friending, but most importantly, they developed their revenue model: advertising. The quick user growth and increasing ad revenue growth got the attention of big corporations - Viacom offered $2B in cash and stock, and Yahoo offered $1B all cash. By this time, Zuckerberg realized what he had, and famously spurned several offers from Yahoo, even after users reacted negatively to the most important feature that facebook would ever release, the News Feed. In today’s world, we often see entrepreneur’s overhyping their companies, which is why Silicon Valley was in-love with dropout founders for a time, their naivite and creativity could be harnessed to create something huge in a short amount of time.

  3. Channel Partnerships: Why apple was reluctant to launch a phone. Channel partnerships often go un-discussed at startups, but they can be incredibly useful in growing distribution. Some industries, such as the Endpoint Detection and Response (EDR) market thrives on channel partnership arrangements. Companies like Crowdstrike engage partners (mostly IT services firms) to sell on their behalf, lowering Crowdstrike’s customer acquisition and sales spend. This can lead to attractive unit economics, but on the flip side, partners must get paid and educated on the selling motion which takes time and money. Other channel relationships are just overly complex. In the mid 2000’s, mobile computing was a complicated industry, and companies hated dealing with old, legacy carriers and simple clunky handset providers. Apple tried the approach of working with a handset provider, Motorola, but they produced the terrible ROKR which barely worked. The ROKR was built to run on the struggling Cingular (would become AT&T) network, who was eager to do a deal with Apple in hopes of boosting usage on their network. After the failure of the ROKR, Cingular executives begged Jobs to build a phone for the network. Normally, the carriers had specifications for how phones were built for their networks, but Jobs ironed out a contract which exchanged network exclusivity for complete design control, thus Apple entered into mobile phones. The most important computing device of the 2000’s and 2010’s was built on a channel relationship.

Business Themes

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  1. AOL-Time Warner: the merger destined to fail. To fully understand the AOL-Time Warner merger, you must first understand what AOL was, what it was becoming, and why it was operating on borrowed time. AOL started as an ISP, charging customers $9.95 for five hours of dial-up internet access, with each additional hour costing $2.95. McCullough describes AOL: “AOL has often been described as training wheels for the Internet. For millions of Americans, their aol.com address was their first experience with email, and thus their first introduction to the myriad ways that networked computing could change their lives.” AOL grew through one of the first viral marketing campaigns ever; AOL put CDs into newspapers which allowed users to download AOL software and get online. The Company went public in March of 1992 and by 1996 the Company had 2.1 million subscribers, however subscribers were starting to flee to cheaper internet access. It turned out that building an ISP was relatively cheap, and the high margin cash flow business that AOL had built was suddenly threatened by a number of competitors. AOL persisted with its viral marketing strategy, and luckily many americans still had not tried the internet yet and defaulted to AOL as being the most popular. AOL continued to add subscribers and its stock price started to balloon; in 1998 alone the stock went up 593%. AOL was also inking ridiculous, heavily VC funded deals with new internet startups. Newly public Drkoop, which raised $85M in an IPO, signed a four year $89M deal to be AOL’s default provider of health content. Barnes and Noble paid $40M to be AOL’s bookselling partner. Tel-save, a long distance phone provider signed a deal worth $100M. As the internet bubble continued to grow, AOL’s CEO, Steve Case realized that many of these new startups would be unable to fufill their contractual obligations. Early web traffic reporting systems could easily be gamed, and companies frequently had no business model other than attract a certain demographic of traffic. By 1999, AOL had a market cap of $149.8B and was added to the S&P 500 index; it was bigger than both Disney and IBM. At this time, the world was shifting away from dial-up internet to modern broadband connections provided by cable companies. One AOL executive lamented: “We all knew we were living on borrowed time and had to buy something of substance by using that huge currency [AOL’s stock].” Time Warner was a massive media company, with movie studios, TV channels, magazines and online properties. On Jan 10, 2000, AOL merged with Time Warner in one of the biggest mergers in history. AOL owned 56% of the combined company. Four days later, the Dow peaked and began a downturn which would decimate hundreds of internet businesses built on foggy fundamentals. Acquisitions happen for a number of reasons, but imminent death is not normally considered by analysts or pundits. When you see acquisitions, read the press release and understand why (at least from a marketing perspective), the two companies made a deal. Was the price just astronomical (i.e. Instagram) or was their something very strategic (i.e. Microsoft-Github)? When you read the press release years later, it should indicate whether the combination actually was proved out by the market.

  2. Acquisitions in the internet bubble: why acquisitions are really just guessing. AOL-Time Warner shows the interesting conundrum in acquisitions. HP founder David Packard coined this idea somewhat in Packard’s law: “No company can consistently grow revenues faster than its ability to get enough of the right people to implement that growth and still become a great company. If a company consistently grows revenue faster than its ability to get enough of the right people to implement that growth, it will not simply stagnate; it will fall.” Author of Good to Great, Jim Collins, clarified this idea: “Great companies are more likely to die of ingestion of too much opportunity, than starvation from too little.” Acquisitions can be a significant cause of this outpacing of growth. Look no further than Yahoo, who acquired twelve companies between September 1997 and June 1999 including Mark Cuban’s Broadcast.com for $5.7B (Kara Swisher at WSJ in 1999), GeoCities for $3.6B, and Y Combinator founder Paul Graham’s Viaweb for $48M. They spent billions in stock and cash to acquire these companies! Its only fitting that two internet darlings would eventually end up in the hands of big-telecom Verizon, who would acquire AOL for $4.4B in 2015, and Yahoo for $4.5B in 2017, only to write down the combined value by $4.6B in 2018. In 2013, Yahoo would acquire Tumblr for $1.1B, only to sell it off this past year for $3M. Acquisitions can really be overwhelming for companies, and frequently they don’t work out as planned. In essence, acquisitions are guesses about future value to customers and rarely are they as clean and smart as technology executives make them seem. Some large organizations have gotten good at acquisitions - Google, Microsoft, Cisco, and Salesforce have all made meaningful acquisitions (Android, Github, AppDynamics, ExactTarget, respectively).

  3. Google and Excite: the acquisition that never happened. McCullough has an incredible quote nestled into the start of chapter six: “Pioneers of new technologies are rarely the ones who survive long enough to dominate their categories; often it is the copycat or follow-on names that are still with us to this day: Google, not AltaVista, in search; Facebook, not Friendster, in social networks.” Amazon obviously bucked this trend (he mentions that), but in search he is absolutely right! In 1996, several internet search companies went public including Excite, Lycos, Infoseek, and Yahoo. As the internet bubble grew bigger, Yahoo was the darling of the day, and by 1998, it had amassed a $100B market cap. There were tons of companies in the market including the players mentioned above and AltaVista, AskJeeves, MSN, and others. The world did not need another search engine. However, in 1998, Google founders Larry Page and Sergey Brin found a better way to do search (the PageRank algorithm) and published their famous paper: “The Anatomy of a Large-Scale Hypertextual Web Search Engine.” They then went out to these massive search engines and tried to license their technology, but no one was interested. Imagine passing on Goolge’s search engine technology. In an over-ingestion of too much opportunity, all of the search engines were trying to be like AOL and become a portal to the internet, providing various services from their homepages. From an interview in 1998, “More than a "portal" (the term analysts employ to describe Yahoo! and its rivals, which are most users' gateway to the rest of the Internet), Yahoo! is looking increasingly like an online service--like America Online (AOL) or even CompuServe before the Web.” Small companies trying to do too much (cough, uber self-driving cars, cough). Excite showed the most interest in Google’s technology and Page offered it to the Company for $1.6M in cash and stock but Excite countered at $750,000. Excite had honest interest in the technology and a deal was still on the table until it became clear that Larry wanted Excite to rip out its search technology and use Google’s instead. Unfortunately that was too big of a risk for the mature Excite company. The two companies parted ways and Google eventually became the dominant player in the industry. Google’s focus was clear from the get-go, build a great search engine. Only when it was big enough did it plunge into acquisitions and development of adjacent technologies.

Dig Deeper

  • Raymond Smith, former CEO of Bell Atlantic, describing the technology behind the internet in 1994

  • Bill Gates’ famous memo: THE INTERNET TIDAL WAVE (May 26, 1995)

  • The rise and fall of Netscape and Mosaic in one chart

  • List of all the companies made famous and infamous in the dot-com bubble

  • Pets.com S-1 (filing for IPO) showin a $62M net loss on $6M in revenue

  • Detail on Microsoft’s antitrust lawsuit

tags: Apple, IBM, Facebook, AT&T, Blackberry, Sequoia, VC, Sean Parker, Yahoo, Excite, Netscape, AOL, Time Warner, Google, Viaweb, Mark Cuban, HP, Packard's Law, Disney, Steve Case, Steve Jobs, Amazon, Drkoop, Android, Mark Zuckerberg, Crowdstrike, Motorola, Viacom, Napster, Salesforce, Marc Benioff, Internet, Internet History, batch2
categories: Non-Fiction
 

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