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May 2023 - Constellation Software Letters by Mark Leonard

We cover Canada’s biggest and quietest software company and their brilliant leader Mark Leonard.

Tech Themes

  1. Critics and Critiques. For a long time, Constellation heard the same critiques: Roll-ups never work, the businesses you are buying are old, the markets you are buying in are small, the delivery method of license/maintenance is phasing out. All of these are valid concerns. Constellation is a roll-up of many software businesses. Roll-ups, aka acquiring several businesses as the primary method of growth, do have tendency to blow up. The most frequent version for a blowup is leverage. Companies finance acquisitions with debt and eventually they make a couple of poor acquisition decisions and the debt load is too big, and they go bankrupt. A recent example of this is Thrashio, an Amazon third party sellers roll-up. RetailTouchPoints lays out the simple strategy: “Back in 2021, firms like Thrasio were able to buy these Amazon-based businesses for around 4X to 6X EBITDA and then turn that into a 15X to 25X valuation on the combined business.” However, demand for many of these products waned in the post-pandemic era, and Thrasio had too much debt to handle with the lower amount of sales. Bankruptcy isn’t all bad - several companies have emerged from bankruptcy with restructured debt, in a better position than before. To avoid the issue of leverage, Constellation has never taken on meaningful (> 1-2x EBITDA) leverage. This may change in the coming years, but for now it remains accurate. Concerns around market size and delivery method (SaaS vs. License/Maintenance) are also valid. Constellation has software businesses in very niche markets, like boating maintenance software that are inherently limited in size. They will never have a $1B revenue boat maintenance software business, the market just isn’t that big. However, the lack of enthusiasm over a small niche market tends to offer better business characteristics - fewer competitors, more likely adoption of de-facto technology, highly specialized software that is core to a business. Constellation’s insight to combine thousands of these niche markets was brilliant. Lastly, delivery methods have changed. Most customers now prefer to buy cloud software, where they can access technology through a browser on any device and benefit from continuous upgrades. Furthermore, SaaS businesses are subscriptions compared to license maintenance businesses where you pay a signficant sum for the license up-front and then a correspondingly smaller sum for maintenance. SaaS subscriptions tend to cost more over the long-term and have less volatile revenue spikes, but can be less profitable because of the need to continuously improve products and provide the service 24/7. Interestingly, Constellation continued to avoid SaaS even after it was the dominant method of buying software. From the 2014 letter: “The SaaS’y businesses also have higher organic growth rates in recurring revenues than do our traditional businesses. Unfortunately, our SaaS’y businesses have higher average attrition, lower profitability and require a far higher percentage of new name client acquisition per annum to maintain their revenues. We continue to buy and invest in SaaS businesses and products. We'll either learn to run them better, or they will prove to be less financially attractive than our traditional businesses - I expect the former, but suspect that the latter will also prove to be true.” While 2014 was certainly earlier in the cloud transformation, its not surprising that an organization built around the financial characteristics of license maintenance software struggled to make this transition. They are finally embarking on this journey, led their by their customers, and its causing license revenue to decline. License revenue has declined each of the last six quarters. The critiques are valid but Constellations assiduousness allowed them to side-step and even benefit from these critics as they scaled.

  2. Initiatives, Investing for Organic Growth, and Measurement. Although Leonard believes that organic growth is an important measure of success of a software company, he lays out in the Q1’07 letter the challenges of Constellation’s internal organic growth projects, dubbed Initiatives. “In 2003, we instituted a program to forecast and track many of the larger Initiatives that were embedded in our Core businesses (we define Initiatives as significant Research & Development and Sales and Marketing projects). Our Operating Groups responded by increasing the amount of investment that they categorized as Initiatives (e.g. a 3 fold increase in 2005, and almost another 50% increase during 2006). Initially, the associated Organic Revenue growth was strong. Several of the Initiatives became very successful. Others languished, and many of the worst Initiatives were terminated before they consumed significant amounts of capital.” The last sentence is the hardest one to stomach. Terminating initiatives before they had consumed lots of capital, is the smart thing to do. It is the rational thing to do. However, I believe this is at the heart of why Constellation has struggled with organic growth over time. Now I’ll be the first to admit that Constellation’s strategy has been incredible, and my criticism is in no way taking that away from them. Frankly, they won’t care what I say. But, as a very astute colleague pointed out to me, this position of measuring all internal R&D and S&M initiatives, is almost self-fulfilling. At the time Leonard wasn’t concerned with the potential for lack of internal investment and organic growth. He even remarked as so: “I’m not yet worried about our declining investment in Initiatives because I believe that it will be self-correcting. As we make fewer investments in new Initiatives, I’m confident that our remaining Initiatives will be the pick of the litter, and that they are likely to generate better returns. That will, in turn, encourage the Operating Groups to increase their investment in Initiatives. This cycle will take a while to play out, so I do not expect to see increased new Initiative investment for several quarters or even years.” By 2013, he had changed his tune: “Organic growth is, to my mind, the toughest management challenge in a software company, but potentially the most rewarding. The feedback cycle is very long, so experience and wisdom accrete at painfully slow rates. We tracked their progress every quarter, and pretty much every quarter the forecast IRR's eroded. Even the best Initiatives took more time and more investment than anticipated. As the data came in, two things happened at the business unit level: we started doing a better job of managing Initiatives, and our RDSM spending decreased. Some of the adaptations made were obvious: we worked hard to keep the early burn-rate of Initiatives down until we had a proof of concept and market acceptance, sometimes even getting clients to pay for the early development; we triaged Initiatives earlier if our key assumptions proved wrong; and we created dedicated Initiative Champion positions so an Initiative was less likely to drag on with a low but perpetual burn rate under a part-time leader who didn’t feel ultimately responsible. But the most surprising adaptation, was that the number of new Initiatives plummeted. By the time we stopped centrally collecting Initiative IRR data in Q4 2010, our RDSM spending as a percent of Net Revenue had hit an all-time low.” So how could the most calculating, strategic software company of maybe all time struggle to produce attractive organic growth prospects? I’d argue two things - 1) Incentives and 2) Rationality. First, on incentives, the Operating Group managers are compensated on ROIC and net revenue growth. If you are a BU manager and could invest in your business vs. buy another company that has declining organic growth but is priced appropriately (i.e. cheaply) requiring minimal capital outlay, you achieve both objectives by buying lower organic growers or even decliners. It is almost similar to buying ads to fill a hole in churned revenue. As long as you keep pressing the advertising button, you will keep gathering customers. But when you stop, it will be painful and growth will stall out. If I’m a BU manager buying meh software companies that achieve good ROIC and I’m growing revenues because of my acquisitions, it just means I need to keep finding more acquisitions to achieve my growth hurdles. Over time this is a challenge, but it may be multiple years before I have a bad acquisition growth year. Clearly, the incentives are not aligned for organic growth. Connected to the first point, the “buy growth for low cash outlays” strategy is perfectly rational based on the incentives. The key to its rationality is the known vs. the unknown. In buying a small, niche VMS business - way more is known about the range of outcomes. If you compare this to an organic growth initiative, it is clear why again, you choose the acquisition path. Organic growth investments are like venture capital. If sizeable, they can have an outsized impact on business potential. However, the returns are unknown. Simple probability illustrates that a 90% chance of a 20% ROIC and a 10% chance of a 10% ROIC, yields a 19% ROIC. I’d argue however, that with organic initiatives, particularly large, complex organic initiatives, there is an almost un-estimable return. If we use Amazon Web Services as perhaps the greatest organic growth initiative ever produced we can see why. Here is a reasonably capital-intensive business outside the core of Amazon’s online retailing applications. Sure, you can claim that they were already using AWS internally to run their operations, so the lift was not as strong. But it is still far afield from bookselling. AWS as an investment could never happen inside of Constellation (besides it being horizontal software). What manager is going to tank their ROIC via a capital-intensive initiative for several years to realize an astronomical gain down the line? What manager is going to send back to Constellation HQ, that they found a business that has the potential for $85B in revenue and $20B in operating profit 15 years out? You may say, “Vertical markets are small, they can’t produce large outcomes.” Constellation started after Veeva, a $30B public company, and Appfolio, a $7.5B company. The crux of the problem is that it is impossible to measure via a spreadsheet, the unknown and unknowable expected returns of the best organic growth initiatives. As Zeckhauser has discussed, the probabilities and associated gains/losses tend to be severely mispriced in these unknown and unknowable situations. Clayton Christensen identified this exact problem through his work on disruptive innovation. He urged companies to focus on ideas, failure, and learning, noting that strategic and financial planning must be discovery-based rather than execution based. Maybe there were great initiatives within Constellation that never got launched because incentives and rationality stopped them in their tracks. It’s not that you should burn the boats and put all your money into the hot new thing, it’s that product creation and organic growth are inherently risky ventures, and a certain amount of expected loss can be necessary to find the real money-makers.

  3. Larger deals. Leonard stopped writing annual letters, but broke the streak in 2021, when he penned a short note, outlining that the company would be pursuing more larger deals at lower IRRs and looking to develop a new circle of competence outside of VMS. I believe his words were chosen carefully to reflect Warren Buffett’s discussion of Circle of Competence and Thomas Watson Sr.’s (founder of IBM) quote: “I’m no genius. I’m smart in spots - but I stay around those spots.” While I appreciate the idea behind it, I’m less inclined to stay within my circle of competence. I’m young, curious, and foolish, and I think it would be a waste to pigeon-hole myself so early. After all, Warren had to learn about insurance, banking, beverages, etc and he didn’t let his not-knowing preclude him from studying. In justifying larger deals, Leonard cited Constellation’s scale and ability to invest more effectively than current shareholders. He also laid out the company’s edge: “Most of our competitors maximise financial leverage and flip their acquisitions within 3-7 years. CSI appreciates the nuances of the VMS sector. We allow tremendous autonomy to our business unit managers. We are permanent and supportive stakeholders in the businesses that we control, even if their ultimate objective is to eventually be a publicly listed company. CSI’s unique philosophy will not appeal to all sellers and management teams, but we hope it will resonate with some.” Since then Constellation has acquired Allscript’s hospital unit business in March 2022 for $700m in cash, completed a spin-merger of Lumine Group into larger company, WideOrbit, to create a publicly traded telecom advertising software provider, and is rumored to be looking at purchasing a subsidiary of Black Knight, which may have to be divested for its own transaction with ICE. These larger deals no doubt come with more complexity, but one large benefit is they sit within larger operating groups, and are shielded during what may be difficult transition periods for the businesses. It allows the businesses to operate more long-term and focus on providing value to end customers. As for deals outside of VMS, Mark Leonard commented on it during the 2022 earnings call: “I took a hard look at a thermal oil situation. I was looking at close to $1B investment, and it was tax advantaged. So it was a clever structure. It was a time when the sector could not get financing. And unfortunately, the oil prices ran away on me. So I was trying to be opportunistic in a sector that was incredibly beat up. So that is an example….So what are the characteristics there? Complexity. Where its a troubled situation with — circumstances and there’s a lot of complexity. I think we can compete better than the average investor, particularly when people are willing to take capital forever.” The remark on complexity reminded me of Baupost, the firm founded by legendary investor Seth Klarman, who famously bought claims on Lehman Brothers Europe following the 2008 bankruptcy. When you have hyper rational individuals, complexity is their friend.

Business Themes

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  1. Decentralized Operating Groups. Its safe to say that Mark Leonard is a BIG believer in decentralized operating groups. Constellation believes in pushing as much decision making authority as possible to the leaders of the various business units. The company operates six operating groups: Volaris, Harris, Topicus (now public), Jonas, Perseus, and Vela. Leonard mentioned the organizational structure in the context of organic growth: “When most of our current Operating Group Managers ran single BU’s, they had strong organic growth businesses. As those managers gave up their original BU management position to oversee a larger Group of BU’s (i.e. became Portfolio Managers), the organic growth of their original BU’s decreased and the profitability of those BU’s increased.” As an example of this dynamic, we can look at Vencora, a Fintech subsidiary of Volaris. Vencora is managed by a portfolio manager, itself a collection of Business Units (BUs) with their own leadership. The Operating Group leaders and Portfolio Managers are incentivized based on growth and ROIC. Furthermore, Constellation mandates that at least 25% (for some executives its 75%) of incentive compensation must be used to purchase shares in the company, on the open market. These shares cannot be sold for three years. This incentive system accomplishes three goals: It keeps broad alignment toward the success of Constellation as a whole, it avoids stock dilution, and it creates a system where employees continuously own more and more of the business. Acquisitions above $20M in revenue must be approved by the head office, who is constantly receiving cash from different subsidiaries and allocating to the highest value opportunities. At varying times, the company has instituted “Keep your capital” initiatives, particularly for the Volaris and Vela operating groups. As Leonard points out in the 2015 letter: “One of the nice side effects of the “keep your capital” restriction, is that while it usually drives down ROIC, it generates higher growth, which is the other factor in the bonus formula. Acquisitions also tend to create an attractive increase in base salaries as the team ends up managing more people, capital, BUs, etc. Currently, a couple of our Operating Groups are generating very high returns without deploying much capital and we are getting to the point that we’ll ask them to keep their capital if they don’t close acceptable acquisitions or pursue acceptable Initiatives shortly.” Because bonuses are paid on ROIC, if an operating group manager sends back a ton of cash to corporate and doesn’t do a lot of new acquisitions, then its ROIC is very high and bonuses will be high. However, because Volaris and Vela are so large, it does not benefit the Head Office to continuously receive these large dividend payments and then pay high bonuses. Head Office will have a mountain of cash with out a lot of easy opportunities to deploy it. Thus the Keep your Capital initiative tamps down bonuses (by tamping down ROIC) and forces the leaders of these businesses to search out productive ways to deploy capital. As a result, more internal growth initiatives are likely to be funded, when acquisitions remain scarce, thereby increasing organic growth. It also pushes BUs and Portfolio Managers to seek out acquisitions to use up some of the capital. Overall, the organizational structure gives extreme authority to individuals and operates with large and strong incentives toward M&A and ROIC.

  2. Selling Constellation. We all know about the epic “what would have happened” deals. A few that come to mind, Oracle buying TikTok US, Microsoft buying Yahoo for $55B, Yahoo acquiring Facebook, Facebook acquiring Snapchat, AT&T acquiring T-Mobile for $39B, JetBlue/Spirt, Ryanair/Aer Lingus. There are tons. Would you believe that Constellation was up for sale at one point? On April 4th 2011, the Constellation board announced that it was considering alternatives for the company. The company was $630m of revenue and $116m of Adj. EBITDA, growing revenue 44% year over year. Today, Constellation is $8.4B of revenue, with $1.16B of FCFA2S, growing revenue at 27% year over year. At the time, Leonard lamented: “I’m proud of the company that our employees and shareholders have built, and will be more than a little sad if it is sold.” To me, this is a critically important non-event to investigate. It goes to show that any company can prematurely cap its compounding. Today, Constellation is perhaps the most revered software company with the most beloved, mysterious genius leader. Imagine if Constellation had been bought by Oracle or another large software company? Where would Mark Leonard be today? Would we have the behemoth that exists today? After the process was concluded with no sale, Leonard discussed the importance of managing one’s own stock price. “I used to maintain that if we concentrated on fundamentals, then our stock price would take care of itself. The events of the last year have forced me to re-think that contention. I'm coming around to the belief that if our stock price strays too far (either high or low) from intrinsic value, then the business may suffer: Too low, and we may end up with the barbarians at the gate; too high, and we may lose previously loyal shareholders and shareholder-employees to more attractive opportunities.” Many technology CEOs could learn from Leonard, preserving an optimistic tone when the company is struggling or the market is punishing the company, and a pessimistic tone when the company is massively over-achieving, like COVID.

  3. Metrics. Leonard loves thinking about and building custom metrics. As he stated in the Q4’2007 letter, “Our favorite single metric for measuring our corporate performance is the sum of ROIC and Organic Net Revenue Growth (“ROIC+OGr”).” However, he is constantly tinkering and thinking about the best and most interesting measures. He generally focuses on three types of metrics: growth, profitability, and returns. For growth, his preferred measure is organic growth. He also believes net maintenance growth is correlated with the value of the business. “We believe that Net Maintenance Revenue is one of the best indicators of the intrinsic value of a software company and that the operating profitability of a low growth software business should correlate tightly to Net Maintenance Revenues.” I believe this correlation is driven by maintenance revenue’s high profitability and association with high EBITA levels (Operating income + amortization from intangibles). For profitability metrics, Leonard for a long time preferred Adj. Net Income (ANI) or EBITA. “ One of the areas where generally accepted accounting principles (“GAAP”) do a poor job of reflecting economic reality, is with goodwill and intangibles accounting. As managers we are at least partly to blame in that we tend to ignore these “expenses”, focusing on EBITA or EBITDA or “Adjusted” Net Income (which excludes Amortisation). The implicit assumption when you ignore Amortisation, is that the economic life of the asset is perpetual. In many instances (for our business) that assumption is correct.” He floated the idea of using free cash flow per share, but it suffers from volatility depending on working capital payments and doesn’t adjust for minority interest payments. Adj. Net Income does both of these things but doesn’t capture the actual cash into the business. In Q3’2019, Leonard adopted a new metric called Free Cash Flow Available to Shareholders (FCFA2S): “We calculate FCFA2S by taking net cash flow from operating activities per IFRS, subtracting the amounts that we spend on fixed assets and on servicing the capital we have sourced from other stakeholders (e.g. debt providers, lease providers, minority shareholders), and then adding interest and dividends earned on investments. The remaining FCFA2S is the uncommitted cashflow available to CSI's shareholders if we made no further acquisitions, nor repaid our other capital-providing stakeholders.” FCFA2S achieves a few happy mediums: 1) Similar to ANI, it is net of the cost of servicing capital (interest, dividends, lease payments) 2) It captures changes in working capital, while ANI does not 3) It reflects cash taxes as opposed to current taxes deducted from pre-tax income (this gets at a much more confusing discussion on deferred tax assets and the difference between book taxes and cash taxes) 4) When comparing FCFA2S to CFO, it tends to be closer than comparing ANI to reported net income. For return metrics, Leonard prefers ROIC (ANI/Average Invested Capital). In the 2015 letter, he laid out the challenge of this metric. First, ROIC can be infinity if a company grows large while reducing its working capital (common in software), effectively lowering the purchase price to zero. Infinity ROIC is a problem because bonuses are paid on ROIC. He contrasts ROIC with IRR but notes its drawbacks, that IRR does not indicate the hold period nor size of the investments. As is said at investing firms, “You can’t eat IRR.” In the 2017 letter, he discussed Incremental return on incremental invested capital ((ANI1 - ANI0)/(IC1-ICo)), but noted its volatility and challenge with handling share issuances / repurchases. Share issuances would increase IC, without an increase in ANI. When discussing high performance conglomerates (HPCs), he discusses EBITA Return (EBITA/Average Total Capital). He notes that: “ROIC is the return on the shareholders’ investment and EBITA Return is the return on all capital. In the former, financial leverage plays a role. In the latter only the operating efficiency with which all net assets are used is reflected, irrespective of whether those assets are financed with debt or shareholders’ investment.” This is similar to P/E vs. EV/EBITDA multiples, where P/E multiples should be used to value market capitalization (i.e. Price) while EV/EBITDA should be used to value the entirety of the business as it relates to debt and equityholders. Mark Leonard is a man of metrics, we will keep watching to see what he comes up with next! In this spirit, I will try to offer a metric for fast-growing software companies, where ROIC is effectively meaningless because negative working capital dynamics in software produce negative invested capital. Furthermore, faster growing companies generally spend ahead of growth and lose money so ANI, FCF, EBITA are all lower than they should be. If you believe the value of these businesses is closely related to revenue, you could use S&M efficiency, or net new ARR / S&M spend. While a helpful measure, many companies don’t disclose ARR. Furthermore, this doesn’t incorporate perhaps the most expensive investing cost, developing products. It also does not incorporate gross margins, which can vary between 50-90% for software companies. One metric you could use is incremental gross margin / (incremental S&M, R&D costs). Here the challenge would be the years it takes to develop products and GTM distribution. To get around this, you could use a cumulative number for R&D/S&M costs. You could also use future gross margin dollars and offset them, similar to the magic number. So our metric is 3 year + incremental gross margin / cumulative S&M and R&D costs. Not a great metric but it can’t hurt to try!

    Dig Deeper

  • Mark Leonard on the Harris Computer Group Podcast (2020)

  • Constellation Software Inc. -Annual General Meeting 2023

  • Mark Leonard: The Best Capital Allocator You’ve Never Heard Of

  • The Moments That Made Mark Miller

  • Topicus: Constellation Software 2.0

tags: Mark Leonard, Constellation Software, CSI, CSU, Harris, Topicus, Lumine, AppFolio, Thrasio, ROIC, FCF, EBITA, Mark Miller, Harris Computer, Volaris, SaaS, AWS, Zeckhauser, Clayton Christensen, IBM, Black Knight, ICE, Seth Klarman, Lehman, Jonas, Perseus, Vela, Vencora, FCFA2S, AT&T, T-Mobile
categories: Non-Fiction
 

March 2023 - Mindset: The New Psychology of Success

This month we check out Satya Nadella’s favorite book - Mindset, by Carol Dweck. The book has become an international sensation and we find out why!

Tech Themes

  1. Growth vs. Fixed Mindset. The book’s main argument is about the distinction between a growth mindset vs. a fixed mindset. A fixed mindset supposes that one’s abilities are fixed in nature - “I am smart because my parents were smart,” “I am good at sports without trying,” “I am good at tests because I just am.” People with fixed mindsets, who believe that people’s abilities largely can’t change, find themselves frequently feeling scared to make mistakes or be wrong. In contrast, a growth mindset supposes that people can drastically alter their abilities through challenge, hard work, perserverance, and the mental attitude that growth is attainable. Each person has some growth and some fixed mindset beliefs. Its important to understand that the fixed mindset is normally adopted because it benefits the person. As Dweck laments: “It told them who they were or who they wanted to be (a smart, talented child) and it told them how to be that (perform well). In this way it provided a formula for self-esteem and path to love and respect from others.” Often people can fall into the trap of results, whereby succeeding in something makes me good at it and failing makes me bad vs. praising and focusing on effort and improvement. For people that become hyperfocused on results, effort can be viewed as lowly. “If you are considered a genius, a talent, or a natural - then you have a lot to lose. Effort can reduce you. The idea of trying and still failing - of leaving yourself without any excuses - is the worst fear within the fixed mindset.” As someone who has put in significant effort into things like sports, only to lose in critical games, this sentence really resonated with me. Often you believe the effort should be rewarded with results, that is the dream described by coaches. But sometimes its not, and you have to wonder whether the effort is really worth it. However, this is a fixed mindset approach. The effort you put in is what establishes the long-term habit of success. Failures can occur from randomness. Failures could also signal that a change in approach is necessary, and often highlights an issue that had been papered over for one reason or another. The effort and the grind and the process are the fun part.

  2. Managing and Teaching. One of the craziest things about mindsets is how easily they can be primed. Several studies discussed in the book place participants into a growth or fixed mindset with simple prompts. “Joseph Martocchio conducted a study of employees who were taking a short computing training course. Half of the employees were put into a fixed mindset. He told them it was all a matter of how much ability they possessed. The other half were put in a growth mindset. He told them that computer skills could be developed through practice. Those in the growth mindset gained considerable confidence in their computer skills as they learned, despite the many mistakes they inevitably made. But because of those mistakes, those with the fixed mindset actually lost confidence in their computer skills as they learned!” All day, every day, we are slipping in and out of different mindsets, often at the prompting of others. And frequently, these mindsets are little conversations going on in the back of our heads! Its important to try to recognize when you are slipping into a fixed mindset, and reframe the thought as a growth mindset one! Changing one’s perception of their own abilities is difficult, but that didn’t stop Marva Collins. “Collins took inner-city Chicago kids who had failed in the public schools and treated them like geniuses. Many of them had been labled ‘learning disabled’ or ‘emotionally disturbed.’..By June, they reached the middle of the fifth grade reader, studying Aristotle, Aesop, Tolstoy, Shakespeare along the way.” Collins set a strong upfront contract with her students: “None of you has ever failed. School may have failed yhou. Well, goodbye to failure, children. Welcome to success. You will read hard books in here and understand what you read. You will write every day…But you must help me to help you. If you don’t give anyhting, don’t expect anything. Success is not coming to you, you must come to it.” Collins raised the kids’ standard, while maintaining a compassionate and nurturing environment. This combination of challenge and nurture can produce wonderful growth. Its important that people don’t feel judged, but rather like someone is pushing them and trying to help them improve.

  3. Motivation, Talent, and Mindset. Many people believe in naturals, indiviudals that simply rolled out of bed and became unbelievable athletes, leaders, business people, etc. They often miss the painstaking process of growth that led up to their eventual success. People often correlate talent with prior successes, forgetting the ways in which systems can produce mediocre talent from renowned systems. And frequently, society, parents, friends, and companions praise eachother for talent or success, rather than effort. In his book Malcolm Gladwell discusses the role that talent plays in an individual’s mindset. “Gladwell concludes that when people live in an environment that esteems them for their innate talent, they have grave difficult when their image is threatened. ‘They will not take the remedial course. They will not stand up to investors and the public and admit that they were wrong. They’d sooner lie.’” When we understand the basis of motivation, we can see why people feel threatened when they hold a fixed mindset about their “innate talent.” Self-determination theory speculates that motivation exists on a spectrum from amotivation (or complete lack of motivation) to extrinsic to intrinsic. There are several types of extrinsic motivation as you move along the spectrum to more internalized motivation: External regulation is motivation based on external rewards like compliance or money; Introjected motivation is based on approval from others and social acceptance; Identified motivation is based on consciously valuing the activity; and Integrated motivation is based on self-congruence, or I do this activity because this is the person I am. Lastly, we have full intrinsic motivation, where we pursue things solely because we enjoy doing that activity. For many high performing individuals, their passions seem to fluctuate between extrinsic motivators and intrinsic motivators. The reason we may feel threatened when we have a fixed mindset and our talent comes into question could stem from maintaining an identified or integrated motivation with an activity. For example, if you believe yourself to be a shrewd business person, and the motivation you feel to execute a business strategy comes from that belief that you are excellent, when you make a terrible decision you are faced with a view that sits in direct contrast to how you viewed yourself. This cognitive dissonance can cause severe depression. A growth mindset may reframe the terrible decision as a learning opportunity. Furthermore, a growth mindset may mean laughing at the decision, and getting excited about the challenge caused by it, placing more of the motivation on just executing the business strategy vs. the results of the strategy.

Business Themes

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  1. Lou Gerstner and IBM turnaround. IBM is currently facing challenges. Despite spinning off its services unit Kyndryl in November 2021, IBM’s stock remains at a negative return since June 2018. This isn’t the first time IBM’s business has gone off the rails. The 1970s and early 80s were so prosperous for IBM that their culture had gone sideways. A pervasive sense of entitlement filled the air. A 1990 Washington Post article discussed their challenges: “Since 1986, IBM has cut its work force three times. Its no-layoff policy (honored even in the Depression) seems vulnerable. So far all reductions have occurred through voluntary retirements. IBM has lagged in some new computer markets; workstations (souped-up personal computers) are an example. Profits have faltered. In 1988 they were nearly $800 million less than in 1984, despite a $13 billion rise in revenues. IBM's stock is trading around 100, down from the 1987 peak of 175 .” The company even came under antitrust investigation for monopolistic behavior (cough, sound familiar?). When all was lost, the board of directors turned to Lou Gerstner, who had successfully run the Travel Services division of American Express and led RJR Nabisco after KKR’s massive $25B buyout in 1989. Gerstner opened the channels of communication, disbanded the management committee, and tried to dismantle IBM’s hierarchical culture. He shifted bonus measures to broader measures like IBM’s overall performance, instead of narrow measures like a division’s EBITDA. The bonus structure change fostered teamwork across the company. By the time Gerstner stepped down in 2002, its market cap had risen from $29B to $168B. However, what’s excluded from the story is Gerstner’s tactics, he laid off 60,000 workers, including 35,000 in 1994. Gerstner was also handsomely rewarded for this turnaround, netting hundreds of millions in stock through option plans. Laying off workers and making money aren’t inherently bad, and Gerstner’s leadership is still commendable - but its important to note that it likely wasn’t just a mindset shift that led to his success at IBM.

  2. Jack Welch - the Best or the Worst. Jack Welch is another executive lauded throughout the book. Long praised for his aggressive management style and focus on performance, Welch was considered an unquestionable genius when he was CEO of GE. Welch became CEO of GE in 1981 and embarked on a 20 year run filled with cost-cutting, layoffs, and countless acquisitions. Under Welch, GE made 600 acquisitions and pushed the company into every aspect of business, including owning TV station NBC and investment bank Kidder Peabody at one point. Kidder Peabody went through two famous trading scandals. In 1987, it was involved in Ivan Boesky’s insider trading scheme, and several years later (under GE’s ownership) it was the subject of another, more egregious trading scandal, whereby a trader placed fake trades and was paid bonuses based on fake results. Dweck uses this as a way to show Welch’s growth mindset: “There is a whole chapter titled ‘Too Full of Myself’ about the time he was on an acquisition roll and felt he could do no wrong. ‘The Kidder experience never left me’ It taught him that ‘there’s only a razor’s edge between self-confidence and hubris. This time hubris won and taught me a lesson I would never forget.” GE’s market value increased from $12B in 1981 to $410B in 2001. In 1999, Fortune named him manager of the century. He launched GE Capital, which would peak around 40% of its business: “But blue-chip G.E. had none of those burdens, which meant that, when it came to making money, Welch’s non-bank bank could put real banks to shame. He then used the proceeds from G.E. Capital to acquire hundreds of companies. In the warm glow of G.E.’s riches, Welch articulated a series of principles that captivated his peers. Fire nonperformers without regret. Shed any business that isn’t first or second in its market category. Your duty is always to enrich your shareholders.” But let’s dig into the not so bright side of Jack Welch. When he became CEO, Welch laid off hundreds of thousands of employees, taking GE’s total from 411,000 in 1980 to 299,000 at the end of 1985. He championed an Enron like approach of ranking employees and firing the bottom 10% every year. He was married three times, and had an extra-marital affair with a Harvard Business Review reporter, who eventually became his third wife. After Welch left GE, its stock fell precipitously, as it tried to unwind GE Capital and all of the other 600 acquisitions it had made during the conglomerate era of the 1980s. Welch’s retirement package was absolutely egregious: “After Welch left G.E., the details of his retirement package were made public. It included a pension of $7.4 million a year and a mountain of perks. He got the use of a company Boeing 737, at an estimated cost of $3.5 million a year. He got an apartment in Donald Trump’s 1 Central Park West, plus deals at the restaurant Jean-Georges downstairs, courtside seats at Knicks games, a subsidy for a car and driver, box seats at the Metropolitan Opera, discounts on diamond and jewelry settings, and on and on—all this for someone worth an estimated nine hundred million dollars. And then, finally, G.E. agreed to pay the monthly dues at the four golf clubs where he played.” If we can learn anything from Jack Welch about growth mindset, its that you can be both a fixed mindset person and a growth mindset person, judging and communicating.

  3. Sports Mindset. Sports provide an excellent training ground to explore mindset. According to Dweck, growth mindset athletes tend to find success in doing their best, in learning and improving. They also find setbacks motivating and informative, digesting them as a wake-up call. Lastly, growth mindset athletes take more control of their process. Here Dweck discusses Tiger Wood’s Dad’s approach to toughening his son: “Tiger’s dad made sure to teach him how to manage his attention and his course strategy. Mr. Woods would make loud noises or throw things just as little Tiger was about to swing.” Woods would often envision a younger rival, pouring himself into learning shots” I have to give myself a reason to work so hard. He’s out there somewhere. He’s twelve.” While this psychological manipulation produced an amazing golfer, it also caused a lot of trauma. Tiger’s complicated relationship with his father and subsequent extra-marital affairs and DUIs have somewhat overshadowed his amazing golf achievements. Another reputationally poor example in the book is Lenny Dykstra. Dykstra, a man who has been charged with well over 25 misdemeanor and felony accounts and who personally filed for bankruptcy, is said to have had a growth mindset by Billy Beane, who claimed, “He had no concept of failure…And I was the opposite.” Beane eventually became GM of the Oakland Athletics, and focused their scouting and recruiting efforts on statistically sound and collegial players, rather than popular stars. Dykstra’s lack of failure concept was recently echoed by soccer star Kevin De Bruyne. “A lot of times when people make mistakes, they don't do it anymore. When I make a mistake, I try to do it twice more and if I make it twice more I'll do it again. I think in in one kind of way [its] learning where you go wrong and I think you understand more out of it if you make errors.” Kevin clearly displays a growth mindset and love for soccer.

    Dig Deeper

  • 60 Minutes: Marva Collins 1995 Part 1

  • From the archives: Jack Welch on 60 Minutes (2001)

  • KEVIN DE BRUYNE MASTERCLASS! | Learn from the assist king himself

  • Promoting Motivation, Health, and Excellence: Ed Deci at TEDxFlourCity

  • Developing a Growth Mindset with Carol Dweck

tags: Carol Dweck, Joe Martocchio, Marva Collins, Chicago, Malcolm Gladwell, Self-Determination Theory, Lou Gerstner, Kyndryl, IBM, RJR Nabisco, KKR, Jack Welch, GE, GE Capital, NBCU, Ivan Boesky, Tiger Woods, Billy Beane, Oakland Athletics, Kevin De Bruyne
categories: Non-Fiction
 

May 2022 - Play Nice, But Win by Michael Dell and James Kaplan

This month we dive into the history of Dell Computer Corporation, one of the biggest PC and server companies in the world! Michael Dell gives a first-hand perspective of all of Dell’s big successes and failures throughout the years and his intense battle with Carl Icahn, over the biggest management buyout in history.

Tech Themes

  1. Be a Tinkerer. When he was in seventh grade, Michael Dell begged his parents to buy an Apple II computer (which costs ~$5,000 in today's dollars). Immediately after the computer arrived, he took the entire thing apart to see exactly how the system worked. After diving deep into each component, Dell started attending Apple user groups. During one, he met a young and tattered Steve Jobs. Dell began tutoring people on the Apple II's components and how they could get the most out of it. When IBM entered the market in 1980 with the 5150 computer, he did the same thing - took it apart, and examined the components. He realized that almost everything IBM made came from other companies (not IBM) and that the total value of its components was well below the IBM price tag. From this simple insight, he had a business. He started fixing up a couple of computers for local business people in Austin. Dell's machines cost less and delivered more performance. The company got so big (50k - 80k revenue per month) that during his freshman year at UT Austin, Dell decided to drop out, much to his parent's dismay. On May 3rd, 1984, Dell incorporated his company and never returned to school.

  2. Lower Prices and Better Service - a Powerful Combination. Dell Computer Corporation was the original DTC business. Rather than selling in big box retail stores, Dell carried out orders via mail request. When the internet became prominent in the late 90s, Dell started taking orders online. After his insight that the cost of components was significantly lower than the selling price, he flew to the far east to meet his suppliers. He started placing big deals and getting better and better prices. This strategy is the classic low-end disruption pattern that we learned about in Clayton Christensen's, The Innovator's Dilemma – a lowered-priced competitor that offers better service, customizability starts to crush the competition. Christensen is important to note that the internet itself was a sustaining innovation to Dell, but very disruptive to the market as a whole: "Usually, the technology simply is an enabler of the disruptive business model. For example, is the Internet a disruptive technology? You can't say that. If you bring it to Dell, it's a sustaining technology to what Dell's business model was in 1996. It made their processes work better; it helped them meet Dell's customers' needs at lower cost. But when you bring the very same Internet to Compaq, it is very disruptive [to the company's then dealer-only sales model]. So how do we treat that? We praise [CEO Michael] Dell, and we fire Eckhard Pfeiffer [Compaq's former CEO]. In reality, those two managers are probably equally competent." If competitors lowered prices, Dell could find better components and continually lower prices. Dell's strategy led to many departures from the personal PC market – IBM left, HP acquired Compaq in a disastrous deal for HP, and many others never made it back.

  3. Layoffs, Crises, and Opportunities. Dell IPO'd in 1988 and joined the Fortune 500 in 1991 as they hit $800m in sales for the year. So you would think the company would be humming when it hit $2B in sales in 1993, right? Wrong. Everything was breaking. When a company scales that quickly, it doesn't have time to create processes and systems. Personnel issues began to happen more frequently. As Dell recalls, the head of sales had a drinking problem, and the head of HR had a stripper girlfriend on the payroll. The company was late to market with notebooks, and it had to institute a recall on its notebooks which could catch fire in some instances. During that time, Dell hired Bain to do an internal report about how it should change its processes for its new scale – Kevin Rollins of the Bain team knew the business super well and thought incredibly strategically. After the Bain assignment, Rollins joined the company as Vice-chairman, ultimately becoming CEO for a brief period in 2004. One of his first recommendations was to cease its experiment selling through department stores and to stay DTC-focused. During the internet bubble, Dell faced another crisis – its stock had risen precipitously for many years, but once the bubble burst, in a matter of months, it fell from $50 to $17 a share. The company missed its earnings estimates for five quarters in a row and had to do two layoffs – one with 1,700 people and another with 4,000. During this time, an internal poll showed that 50% of Dell team members would leave if another company paid them the same rate. Dell realized that the values statement he had written in 1988 was no longer resonating and needed updating – he refreshed the value statement and focused the company on its role in the global IT economy. Dell understands that you should never waste a great crisis, and always find the opportunity for growth and improvement when things aren't going well.

Business Themes

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  1. Carl Icahn and Dell. No one in business represents a corporate nemesis quite like Carl Icahn. Icahn was born in Rockaway, NY, and earned his tuition money at Princeton playing poker against the rich kids. Icahn is an activist investor and popularized the field of activist investing with some big, bold battles against companies in the early 1980s. Icahn got his start in 1968 by purchasing a seat on the New York Stock Exchange. He completed his first major takeover attempt in 1978, and the rest was history. Icahn takes an intense stance against companies, typically around big mergers, acquisitions, or divestitures. He 1) buys up a lot of shares, like 5-10% of a company, 2) accuses the company and usually the management of incompetence or a lousy strategy 3) argues for some action - a sale of a division, a change in management, a special dividend 4) sues the company in a variety of ways around shareholder negligence 5) sends letters to shareholders and the company detailing his findings/claims 6) puts up a new slate of board members at the company 7) waits to profit or gets paid to go away (also called greenmail). Icahn used these exact tactics when he took on Michael Dell. Icahn issued several scathing letters about Dell, criticizing the company's poor performance, highlighting Michael Dell's obvious conflicts of interest as CEO, and demanding the special committee evaluate the deal fairly. Icahn normally makes money when he gets involved, and he is essentially a gnat that doesn't go away until he makes money one way or another. After the fight, Icahn still made a profit of 10s of millions, and his fight with Dell was just beginning.

  2. Take Privates and Transformation. Michael Dell had thought a couple of times about taking the company private when he was approached by Egon Durban of Silver Lake Partners, a large tech private equity firm. Dell and Zender went on a walk in Hawaii and worked out what a transaction might be. The issue with Dell at that time was that the PC market was under siege. People thought tablets were the future, and their questions found confirmation in the PC market's declining volumes. Dell had spent $14B on an acquisition spree, acquiring a string of enterprise software companies, including Quest Software, SonicWall, Boomi, Secureworks, and more, as it redirected its strategy. But these companies had yet to kick into gear, and most of Dell's business was still PCs and servers. The stock price had fallen about 45% since Michael Dell had rejoined as CEO in 2007. Dell had thought about taking the company private a couple of other times, but now seemed like a great time - they needed to transform, and fast. Enacting a transformation in the public markets is tough because wall street focuses on quarter-to-quarter metrics over long-term vision. He first considered the idea in June 2012 when talking with the then largest shareholder Southeastern Asset Management. After letting the idea percolate, Dell held discussions with Silver Lake and KKR. Silver Lake and Dell submitted a bid at $12.70, then $12.90, then $13.25, then $13.60, then $13.65. On February 4th, 2013, the special committee accepted Silver Lake's offer. On March 5th, Carl Icahn entered the fray, saying he owned about $1b of shares. Icahn submitted a half proposal suggesting the company pay a one-time special dividend, he would acquire a substantial part of the stock and it would remain public, under different leadership. On July 18th, the special committee delayed a vote on the acquisition because it became clear that Dell couldn't get enough of the "majority of the minority" votes needed to close the acquisition. A few weeks later, Silver Lake and Dell raised their bid to $13.75 (the original asking price of the committee), and the committee agreed to remove the voting standard, allowing the SL/Dell combo to win the deal. After various lawsuits, Icahn gave up in September 2013, when it became clear he had no strategy to convince shareholders to his side. It was an absolute whirlwind of a deal process, and Dell escaped with his company.

  3. Big Deals. After Dell went private, Michael Dell and Egon Durban started scouring the world for enticing tech acquisitions. They closed on a small $1.4B storage acquisition, which reaffirmed Michael Dell's interest in the storage market. After the deal, Dell reconsidered something that almost happened in 2008/09 – a merger with EMC. EMC was the premier enterprise storage company with a dominant market share. On top of that, EMC owned VMware, a software company that had successfully virtualized the x86 architecture so servers could run multiple operating systems simultaneously. Throughout 2008 and 2009, Dell and EMC had deeply considered a merger – to the point that its boards held joint discussions about integration plans and deal price. The boards scrapped the deal during the financial crisis, and in the ensuing years, EMC grew and grew. By 2014 it was a $59B public company and the largest company in Massachusetts. In mid-2014, Dell started to consider the idea. He pondered the strategic and competitive implications of the deal everywhere he went. Little did he know that he was already late to the party – it later came out that both HP and Cisco had looked at acquiring EMC in 2013. HP got down to the wire, with the deal being championed by Meg Whitman, as a way to move past the Autonomy debacle and board room in-fighting. HP had a handshake agreement to merge with EMC in a 1:1 deal, but at the last minute, HP re-traded and demanded a more advantageous split (i.e. HP would own 55% of the combined company) and EMC said no. When EMC then turned to Dell, Whitman slammed the deal. While the only remaining competitor of size was Dell, there was still a question of how they could finance the deal, especially as a private company. Dell's ultimate package was a pretty crazy mix of considerations: Dell issued a tracking stock related specifically to Dell's business, it then took out some $40b in loans against its newly acquired VMWare equity and the cash flow of Dell's underlying business, Michael Dell and Silver lake also put in an additional $5B of equity capital. After Silver Lake and Dell determined the financing structure, Dell faced a grueling interrogation session in front of the EMC board as final approval for the deal. The deal was announced on October 12th, 2015, and it closed a year later. By all measures, it appears the deal was a success – the company has undergone a complete transformation – shedding some acquired assets, spinning off VMWare, and going public again by acquiring its own tracking stock. Michael Dell took some huge risks - taking his company private and completing the biggest tech merger in history. It seems to have paid off handsomely.

Dig Deeper

  • Michael Dell, Dell Technologies | Dell Technologies World 2022

  • Steve Jobs hammers Michael Dell (1997)

  • Michael Dell interview - 7/23/1991

  • Background of the Merger - the full SEC timeline of the EMC-Dell Merger

  • Carl Icahn's First Ever Interview | 1985

tags: Michael Dell, Dell, Carl Icahn, Apple, Steve Jobs, HP, Cisco, Meg Whitman, IBM, Austin, DTC, Clayton Christensen, Innovator's Dilemma, Compaq, Kevin Rollins, Bain, Internet History, Activist, Silver Lake, Quest Software, SonicWall, Secureworks, Egon Durban, KKR, Southeastern Asset Management, EMC, Joe Tucci, VMware
categories: Non-Fiction
 

October 2021 - Unapologetically Ambitious by Shellye Archambeau

This month we hear the story of famous technology CEO Shellye Archambeau, former leader of GRC software provider, Metricstream. Archambeau packs her memoir full of amazing stories and helpful career advice; the book is a must-read for any ambitious leader looking for how to break into Silicon Valley’s top ranks.

Tech Themes

  1. The Art of the Pivot. When Archambeau joined Zaplet in 2003 as its new CEO, she had a frank conversation with the chairman of the board Vinod Khosla. She asked him one question: “You have a great reputation for supporting your companies, but you also have a reputation of being strong-willed and sometimes dominating. I just need to know before I answer [where I will take the job], are you hiring me to implement your strategy, or are you hiring me to be the CEO?” Vinod responded: “I would be hiring you to be the CEO, to run the company, fully responsible and accountable.” With that answer, Archambeau accepted the job and achieved her life-long goal of becoming a CEO before age forty. Archambeau had just inherited a struggling former silicon-valley darling that had raised over $100M but had failed to translate that money into meaningful sales. Zaplet’s highly configurable technology was a vital asset, but the company had not locked on to a real problem. Struggling to set a direction for the company, Archambeau spoke with board member Roger McNamee, who suggested pivoting into compliance software. In early 2004, Zaplet merged with compliance software provider MetricStream (taking its name), with Archambeau at the helm of the combined company. She wasn’t out of the woods yet. The 2008/09 financial crisis pushed MetricStream to the brink. With less than $2M in the bank, Archambeau ditched her salary, executed a layoff, and rallied her executive through the financial crisis. As banks recapitalized, they sought new compliance and risk management platforms to avoid future issues, and MetricStream was well-positioned to serve this new set of highly engaged customers. Archambeau’s first and only CEO role lasted for 14 years, as she led Metricstream to $100M in revenue and 2,000+ employees.

  2. Taking Calculated Risks. Although Archambeau architected a successful turnaround, her career was not without challenges. After years of working her way up at IBM, Archambeau strategically chose to seek out a challenging international assignment, an essential staple of IBM’s CEOs. While working in Tokyo as VP and GM for Public Sector in Asia Pacific, Archambeau was not selected for a meeting with Lou Gerstner, IBM’s CEO. She put it bluntly: “I was ranked highly in terms of my performance - close to the top of the yearly ranking, not just in Japan, but globally. Yet I was pretty sure I wasn’t earning the salary many of my colleagues were getting.” It was then that Archambeau realized that she might need to leave IBM to achieve her goal of becoming CEO. She left IBM and became President of Blockbuster.com, as they were beginning to compete with Netflix. Blockbuster was staunch in its dismissal of Netflix, refusing to buy the streaming company when it had a chance for a measly $50M. Archambeau was unhappy with management’s flippant attitude toward a legitimate threat and left Blockbuster’s Dallas HQ after only 9 months. After this difficult work experience, Archambeau sought out work in Silicon Valley, moving to the nation’s tech hub without her family. She became Head of Sales and Marketing for Northpoint Communications. The company was fighting a losing DSL cable battle, and after a merger with Verizon fell through, the company went bankrupt. Then Archambeau became CMO of Loudcloud, Ben Horowitz’s early cloud product covered in our March 2020 book, The Hard Thing About Hard Things. But things were already blowing up at Loudcloud, and after a year, Archambeau was looking for another role following the sale of LoudCloud’s services business to EDS. At 40 years old, Archambeau had completed international assignments, managed companies across technology, internet, and telecom, and seen several mergers and bankruptcies. That experience laid the bedrock for her attitude: “After the dot-com bubble burst, I would need to double down and take greater risks, but-and this probably won’t surprise you-I had planned for this…It’s 2002, I’m almost forty, I’ve learned a great deal from Northpoint and Loudcloud, and I’m feeling ready for my chance to be a CEO.” Archambeau was always ready for the next challenge, unafraid of the risks posed - prepared to make her mark on the Tech industry.

  3. Find the Current. Trends drive the Tech industry, and finding and riding those trends can be hugely important to creating a career. As in Archambeau’s journey, she saw the growing role of technology as an intern at IBM in the 1980s and knew the industry would thrive over time. As the internet and telecom took hold, she jumped into new and emerging businesses, unafraid of roadblocks. As she puts it: “Ultimately, when it comes to reaching your goals, the real skill lies in spotting the strongest current - in an organization, in an industry, even in the larger economy - and then positioning yourself so it propels you forward. Sail past the opportunities that lead you into the weeds and take the opportunities that will move you toward your goals.”

Business Themes

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  1. The Power of Networking. One of Archambeau’s not-so-secret strategies toward career success was networking. She is a people person and radiates energy in every conversation. Beyond this natural disposition, Archambeau took a very concerted and intentional approach toward building her network, and it shows. Archambeau crosses paths with Silicon Valley legends like Bill Campbell and Ben Horowitz throughout the book. Beyond one-to-one mentorship relationships, Archambeau joined several organizations to grow her network, including Watermark, the Committee of 200, ITSM Form, Silicon Valley Leadership Group, and more. These groups offered a robust foundation and became a strong community, empowering and inspiring her to lead!

  2. Support and Tradeoffs. As a young college sophomore, Archambeau knew she wanted to be the breadwinner of the family. When she met her soon-to-be husband Scotty, a 38-year-old former NFL athlete, she was direct with him: “I would really like to be able to have someone stay home with the kids, especially when they are in school. But the thing is…I just don’t want it to be me.” Scotty thought patiently, “You know, Archambeau, I’ve had a lot of experiences in my life. I’ve had three different careers and you know I like working. But, I think I could see myself doing that, for you.” That was the icing on top of the cake. The two married and had two children while Archambeau worked up the ranks to become CEO. Scotty took care of the kids, Kethlyn and Kheaton, when Archambeau moved to Silicon Valley for work. She understood the tough tradeoff she was making and acknowledged that her relationship with her daughter felt more strained during Kethlyn’s teenage years. It begs the question, how comfortable are you with the tradeoffs you are making today? Moving to a new city to pursue a career that may strain family dynamics is never an easy decision. Family was always important to Archambeau, but it became front and center when Scotty was diagnosed with blood cancer in 2010. Although she was still CEO of MetricStream, things changed: “I had accumulated vacation days, I was putting off trips and experiences for ‘when the time was right’…We’re going to do things that we would have waited to do. We’re going to them now.” Family and friends became a priority - they always were!

  3. Earning Respect. As a Black woman in Technology, Archambeau had to overcome the odds repeatedly. She recounted: “As a young African American woman, I was accustomed to earning respect. Whenever I got a promotion or a new job, I walked into it understanding that people likely would assume I was not quite qualified or not equity ready. I presumed I need to establish relationships and credibility, to develop a reputation, to prove myself.” While incredibly sad that Archambeau had to deal with this questioning, she learned how to use it to her advantage. As her family moved around the country, Archambeau faced repeated challenges: getting denied from taking advanced classes in school, getting bullied and beaten walking home from school, and starting high school with leg braces in a new city. Through these difficulties, she developed a simple methodology for getting through tough times: “Accept the circumstances, fake it ‘til you make it, control what you can, and trust that things will get better.” Archambeau took that mentality with her and earned the respect of the entire IBM Japan when she presented her introduction slides entirely in Japanese to build trust with her new co-workers. It was the first time a foreign executive had done so. Archambeau’s ability to boldly take action in face of many obstacles is impressive.

Dig Deeper

  • Knowing Your Power | Shellye Archambeau | TEDxSonomaCounty

  • Spelman College Courageous Conversations - Shellye Archambeau

  • Shellye Archambeau: Becoming a CEO (A) - A Harvard Business School Case

  • MetricStream Raises $50M to Take on the GRC Market

tags: Metricstream, Zaplet, Shellye Archambeau, Vinod Khosla, Ben Horowitz, Loudcloud, Bill Campbell, GRC, Japan, Lou Gerstner, IBM, Blockbuster, Netflix, Silicon Valley, Silver Lake, Roger McNamee, Northpoint Communications, Verizon
categories: Non-Fiction
 

May 2021 - Crossing the Chasm by Geoffrey Moore

This month we take a look at a classic high-tech growth marketing book. Originally published in 1991, Crossing the Chasm became a beloved book within the tech industry although its glory seems to have faded over the years. While the book is often overly prescriptive in its suggestions, it provides several useful frameworks to address growth challenges primarily early on in a company’s history.

Tech Themes

  1. Technology Adoption Life Cycle. The core framework of the book discusses the evolution of new technology adoption. It was an interesting micro-view of the broader phenomena described in Carlota Perez’s Technological Revolutions. In Moore’s Chasm-crossing world, there are five personas that dominate adoption: innovators, early adopters, early majority, late majority, and laggards. Innovators are technologists, happy to accept more challenging user experiences to push the boundaries of their capabilities and knowledge. Early adopters are intuitive buyers that enjoy trying new technologies but want a slightly better experience. The early majority are “wait and see” folks that want others to battle test the technology before trying it out, but don’t typically wait too long before buying. The late majority want significant reference material and usage before buying a product. Laggards simply don’t want anything to do with new technology. It is interesting to think of this adoption pattern in concert with big technology migrations of the past twenty years including: mainframes to on-premise servers to cloud computing, home phones to cell phones to iphone/android, radio to CDs to downloadable music to Spotify, and cash to check to credit/debit to mobile payments. Each of these massive migration patterns feels very aligned with this adoption model. Everyone knows someone ready to apply the latest tech, and someone who doesn’t want anything to do with it (Warren Buffett!).

  2. Crossing the Chasm. If we accept the above as a general way products are adopted by society (obviously its much more of a mish/mash in reality), we can posit that the most important step is from the early adopters to the early majority - the spot where the bell curve (shown below) really opens up. This is what Geoffrey Moore calls Crossing the Chasm. This idea is highly reminiscent of Clay Christensen’s “not good enough” disruption pattern and Gartner’s technology hype cycle. The examples Moore uses (in 1991) are also striking: Neural networking software and desktop video conferencing. Moore lamented: “With each of these exciting, functional technologies it has been possible to establish a working system and to get innovators to adopt it. But it has not as yet been possible to carry that success over to the early adopters.” Both of these technologies have clearly crossed into the mainstream with Google’s TensorFlow machine learning library and video conferencing tools like Zoom that make it super easy to speak with anyone over video instantly. So what was the great unlock for these technologies, that made these commercially viable and successfully adopted products? Well since 1990 there have been major changes in several important underlying technologies - computer storage and data processing capabilities are almost limitless with cloud computing, network bandwidth has grown exponentially and costs have dropped, and software has greatly improved the ability to make great user experiences for customers. This is a version of not-good-enough technologies that have benefited substantially from changes in underlying inputs. The systems you could deploy in 1990 just could not have been comparable to what you can deploy today. The real question is - are there different types of adoption curves for differently technologies and do they really follow a normal distribution as Moore shows here?

  3. Making Markets & Product Alternatives. Moore positions the book as if you were a marketing executive at a high-tech company and offers several exercises to help you identify a target market, customer, and use case. Chapter six, “Define the Battle” covers the best way to position a product within a target market. For early markets, competition comes from non-consumption, and the company has to offer a “Whole Product” that enables the user to actually derive benefit from the product. Thus, Moore recommends targeting innovators and early adopters who are technologist visionaries able to see the benefit of the product. This also mirrors Clayton Christensen’s commoditization de-commoditization framework, where new market products must offer all of the core components to a system combined into one solution; over time the axis of commoditization shifts toward the underlying components as companies differentiate by using faster and better sub-components. Positioning in these market scenarios should be focused on the contrast between your product and legacy ways of performing the task (use our software instead of pen and paper as an example). In mainstream markets, companies should position their products within the established buying criteria developed by pragmatist buyers. A market alternative serves as the incumbent, well-known provider and a product alternative is a near upstart competitor that you are clearly beating. What’s odd here is that you are constantly referring to your competitors as alternatives to your product, which seems counter-intuitive but obviously, enterprise buyers have alternatives they are considering and you need to make the case that your solution is the best. Choosing a market alternative lets you procure a budget previously used for a similar solution, and the product alternative can help differentiate your technology relative to other upstarts. Moore’s simple positioning formula has helped hundreds of companies establish their go-to-market message: “For (target customers—beachhead segment only) • Who are dissatisfied with (the current market alternative) • Our product is a (new product category) • That provides (key problem-solving capability). • Unlike (the product alternative), • We have assembled (key whole product features for your specific application).”

Business Themes

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  1. What happened to these examples? Moore offers a number of examples of Crossing the Chasm, but what actually happened to these companies after this book was written? Clarify Software was bought in October 1999 by Nortel for $2.1B (a 16x revenue multiple) and then divested by Nortel to Amdocs in October 2001 for $200M - an epic disaster of capital allocation. Documentum was acquired by EMC in 2003 for $1.7B in stock and was later sold to OpenText in 2017 for $1.6B. 3Com Palm Pilot was a mess of acquisitions/divestitures. Palm was acquired by U.S Robotics which was acquired by 3COM in 1997 and then subsequently spun out in a 2000 IPO which saw a 94% drop. Palm stopped making PDA devices in 2008 and in 2010, HP acquired Palm for $1.2B in cash. Smartcard maker Gemplus merged with competitor Axalto in an 1.8Bn euro deal in 2005, creating Gemalto, which was later acquired by Thales in 2019 for $8.4Bn. So my three questions are: Did these companies really cross the chasm or were they just readily available success stories of their time? Do you need to be the company that leads the chasm crossing or can someone else do it to your benefit? What is the next step in the chasm journey after its crossed and why did so many of these companies fail after a time?

  2. Whole Products. Moore leans into an idea called the Whole Product Concept which was popularized by Theodore Levitt’s 1983 book The Marketing Imagination and Bill Davidow’s (of early VC Mohr Davidow) 1986 book Marketing High Technology. Moore explains the idea: “The concept is very straightforward: There is a gap between the marketing promise made to the customer—the compelling value proposition—and the ability of the shipped product to fulfill that promise. For that gap to be overcome, the product must be augmented by a variety of services and ancillary products to become the whole product.” There are four different perceptions of the product: “1. Generic product: This is what is shipped in the box and what is covered by the purchasing contract. 2.Expected product: This is the product that the consumer thought she was buying when she bought the generic product. It is the minimum configuration of products and services necessary to have any chance of achieving the buying objective. For example, people who are buying personal computers for the first time expect to get a monitor with their purchase-how else could you use the computer?—but in fact, in most cases, it is not part of the generic product. 3.Augmented product: This is the product fleshed out to provide the maximum chance of achieving the buying objective. In the case of a personal computer, this would include a variety of products, such as software, a hard disk drive, and a printer, as well as a variety of services, such as a customer hotline, advanced training, and readily accessible service centers. 4. Potential product: This represents the product’s room for growth as more and more ancillary products come on the market and as customer-specific enhancements to the system are made. These are the product features that have maybe expected or additional to drive adoption.” Moore makes a subtle point that after a while, investments in the generic/out-of-the-box product functionality drive less and less purchase behavior, in tandem with broader market adoption. Customers want to be wooed by the latest technology and as products become similar, customers care less about what’s in the product today, and more about what’s coming. Moore emphasizes Whole Product Planning where you can see how you get to those additional features into the product over time - but Moore was also operating in an era when product decisions and development processes were on two-year+ timelines and not in the DevOps era of today, where product updates are pushed daily in some cases. In the bottoms-up/DevOps era, its become clear that finding your niche users, driving strong adoption from them, and integrating feature ideas from them as soon as possible can yield a big success.

  3. Distribution Channels. Moore focuses on each of the potential ways a company can distribute its solutions: Direct Sales, two-tier retail, one-tier retail, internet retail, two-tier value-added reselling, national roll-ups, original equipment manufacturers (OEMs), and system integrators. As Moore puts it, “The number-one corporate objective, when crossing the chasm, is to secure a channel into the mainstream market with which the pragmatist customer will be comfortable.” These distribution types are clearly relics of technology distribution in the early 1990s. Great direct sales have produced some of the best and biggest technology companies of yesterday including IBM, Oracle, CA Technologies, SAP, and HP. What’s so fascinating about this framework is that you just need one channel to reach the pragmatist customer and in the last 10 years, that channel has become the internet for many technology products. Moore even recognizes that direct sales had produced poor customer alignment: “First, wherever vendors have been able to achieve lock-in with customers through proprietary technology, there has been the temptation to exploit the relationship through unfairly expensive maintenance agreements [Oracle did this big time] topped by charging for some new releases as if they were new products. This was one of the main forces behind the open systems rebellion that undermined so many vendors’ account control—which, in turn, decrease predictability of revenues, putting the system further in jeopardy.” So what is the strategy used by popular open-source bottoms up go-to-market motions at companies like Github, Hashicorp, Redis, Confluent and others? Its straightforward - the internet and simple APIs (normally on Github) provide the fastest channel to reach the developer end market while they are coding. When you look at Open Source scaling, it can take years and years to Cross the Chasm because most of these early open source adopters are technology innovators, however, eventually, solutions permeate into massive enterprises and make the jump. With these new go-to-market motions coming on board, driven by the internet, we’ve seen large companies grow from primarily inbound marketing tactics and less direct outbound sales. The companies named above as well as Shopify, Twilio, Monday.com and others have done a great job growing to a massive scale on the backs of their products (product-led growth) instead of a salesforce. What’s important to realize is that distribution is an abstract term and no single motion or strategy is right for every company. The next distribution channel will surprise everyone!

Dig Deeper

  • How the sales team behind Monday is changing the way workplaces collaborate

  • An Overview of the Technology Adoption Lifecycle

  • A Brief History of the Cloud at NDC Conference

  • Frank Slootman (Snowflake) and Geoffrey Moore Discuss Disruptive Innovations and the Future of Tech

  • Growth, Sales, and a New Era of B2B by Martin Casado (GP at Andreessen Horowitz)

  • Strata 2014: Geoffrey Moore, "Crossing the Chasm: What's New, What's Not"

tags: Crossing the Chasm, Github, Hashicorp, Redis, Monday.com, Confluent, Open Source, Snowflake, Shopify, Twilio, Geoffrey Moore, Gartner, TensorFlow, Google, Clayton Christensen, Zoom, nORTEL, Amdocs, OpenText, EMC, HP, CA, IBM, Oracle, SAP, Gemalto, DevOps
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
 

November 2020 - Tape Sucks: Inside Data Domain, A Silicon Valley Growth Story by Frank Slootman

This month we read a short, under-discussed book by current Snowflake and former ServiceNow and Data Domain CEO, Frank Slootman. The book is just like Frank - direct and unafraid. Frank has had success several times in the startup world and the story of Data Domain provides a great case study of entrepreneurship. Data Domain was a data deduplication company, offering a 20:1 reduction of data backed up to tape casettes by using new disk drive technology.

Tech Themes

Data Domain’s 2008 10-K prior to being acquired

Data Domain’s 2008 10-K prior to being acquired

  1. First time CEO at a Company with No Revenue. Frank is an immigrant to the US, coming from the Netherlands shortly after graduating from the University of Rotterdam. After being rejected by IBM 10+ times, he joined Burroughs corporation, an early mainframe provider which subsequently merged with its direct competitor Sperry for $4.8B in 1986. Frank then spent some time at Compuware and moved back to the Netherlands to help it integrate the acquisition of Uniface, an early customizable report building software. After spending time there, he went to Borland software in 1997, working his way up the product management ranks but all the while being angered by time spent lobbying internally, rather than building. Frank joined Data Domain in the Spring of 2003 - when it had no customers, no revenue, and was burning cash. The initial team and VC’s were impressive - Kai Li, a computer science professor on sabbatical from Princeton, Ben Zhu, an EIR at USVP, and Brian Biles, a product leader with experience at VA Linux and Sun Microsystems. The company was financed by top-tier VC’s New Enterprise Associates and Greylock Partners, with Aneel Bhusri (Founder and current CEO of Workday) serving as initial CEO and then board chairman. This was a stacked team and Slootman knew it: “I’d bring down the average IQ of the company by joining, which felt right to me.” The Company had been around for 18 months and already burned through a significant amount of money when Frank joined. He knew he needed to raise money relatively soon after joining and put the Company’s chances bluntly: “Would this idea really come together and captivate customers? Nobody knew. We, the people on the ground floor, were perhaps, the most surprised by the extraordinary success we enjoyed.”

  2. Playing to his Strengths: Capital Efficiency. One of the big takeaways from the Innovators by Walter Issacson was that individuals or teams at the nexus of disciplines - primarily where the sciences meet the humanities, often achieved breakthrough success. The classic case study for this is Apple - Steve Jobs had an intense love of art, music, and design and Steve Wozniak was an amazing technologist. Frank has cultivated a cross-discipline strength at the intersection of Sales and Technology. This might be driven by Slootman’s background is in economics. The book has several references to economic terms, which clearly have had an impact on Frank’s thinking. Data Domain espoused capital efficiency: “We traveled alone, made few many-legged sales calls, and booked cheap flights and hotels: everybody tried to save a dime for the company.” The results showed - the business went from $800K of revenue in 2004 to $275 million by 2008, generating $75M in cash flow from operations. Frank’s capital efficiency was interesting and broke from traditional thinking - most people think to raise a round and build something. Frank took a different approach: “When you are not yet generating revenue, conservation of resource is the dominant theme.” Over time, “when your sales activity is solidly paying for itself,” the spending should shift from conservative to aggressive (like Snowflake is doing this now). The concept of sales efficiency is somewhat talked about, but given the recent fundraising environment, is often dismissed. Sales efficiency can be thought of as: “How much revenue do I generate for every $1 spent in sales and marketing?” Looking at the P&L below, we see Data Domain was highly efficient in its sales and marketing activity - the company increased revenue $150M in 2008, despite spending $115M in sales and marketing (a ratio of 1.3x). Contrast this with a company like Slack which spent $403M to acquire $230M of new revenue (a ratio of 0.6x). It gets harder to acquire customers at scale, so this efficiency is supposed to come down over time but best in class is hopefully above 1x. Frank clearly understands when to step on the gas with investing, as both ServiceNow and Snowflake have remained fairly efficient (from a sales perspective at least) while growing to a significant scale.

  3. Technology for Technology’s Sake. “Many technologies are conceived without a clear, precise notion of the intended use.” Slootman hits on a key point and one that the tech industry has struggled to grasp throughout its history. So many products and companies are established around budding technology with no use case. We’ve discussed Magic Leap’s fundraising money-pit (still might find its way), and Iridium Communications, the massive satellite telephone that required people to carry a suitcase around to use it. Gartner, the leading IT research publication (which is heavily influenced by marketing spend from companies) established the Technology Hype Cycle, complete with the “Peak of inflated expectations,” and the “Trough of Disillusionment” for categorizing technologies that fail to live up to their promise. There have been several waves that have come and gone: AR/VR, Blockchain, and most recently, Serverless. Its not so much that these technologies were wrong or not useful, its rather that they were initially described as a panacea to several or all known technology hindrances and few technologies ever live up to that hype. Its common that new innovations spur tons of development but also lots of failure, and this is Slootman’s caution to entrepreneurs. Data Domain was attacking a problem that existed already (tape storage) and the company provided what Clayton Christensen would call a sustaining innovation (something that Slootman points out). Whenever things go into “winter state”, like the internet after the dot-com bubble, or the recent Crpyto Winter which is unthawing as I write; it is time to pay attention and understand the relevance of the innovation.

Business Themes

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  1. Importance of Owning Sales. Slootman spends a considerable amount of this small book discussing sales tactics and decision making, particularly with respect to direct sales and OEM relationships. OEM deals are partnerships with other companies whereby one company will re-sell the software, hardware, or service of another company. Crowdstrike is a popular product with many OEM relationships. The Company drives a significant amount of its sales through its partner model, who re-sell on behalf of Crowdstrike. OEM partnerships with big companies present many challenges: “First of all, you get divorced from your customer because the OEM is now between you and them, making customer intimacy challenging. Plus, as the OEM becomes a large part of your business, for all intents and purposes they basically own you without paying for the privilege…Never forget that nobody wants to sell your product more than you do.” The challenges don’t end there. Slootman points out that EMC discarded their previous OEM vendor in the data deduplication space, right after acquiring Data Domain. On top of that, the typical reseller relationship happens at a 10-20% margin, degrading gross margins and hurting ability to invest. It is somewhat similar to the challenges open-source companies like MongoDB and Elastic have run into with their core software being…free. Amazon can just OEM their offering and cut them out as a partner, something they do frequently. Partner models can be sustainable, but the give and take from the big company is a tough balance to strike. Investors like organic adoption, especially recently with the rise of freemium SaaS models percolating in startups. Slootman’s point is that at some point in enterprise focused businesses, the Company must own direct sales (and relationships) with its customers to drive real efficiency. After the low cost to acquire freemium adopters buy the product, the executive team must pivot to traditional top down enterprise sales to drive a successful and enduring relationship with the customer.

  2. In the Thick of Things. Slootman has some very concise advice for CEOs: be a fighter, show some humanity, and check your ego at the door. “Running a startup reduces you to your most elementary instincts, and survival is on your mind most of the time…The CEO is the ‘Chief Combatant,’ warrior number one.” Slootman views the role of CEO as a fighter, ready to be the first to jump into the action, at all times. And this can be incredibly productive for business as well. Tony Xu, the founder and CEO of Doordash, takes time out every month to do delivery for his own company, in order to remain close to the customer and the problems of the company. Jeff Bezos famously still responds and views emails from customers at jeff@amazon.com. Being CEO also requires a willingness to put yourself out there and show your true personality. As Slootman puts it: “People can instantly finger a phony. Let them know who you really are, warts and all.” As CEO you are tasked with managing so many people and being involved in all aspects of the business, it is easy to become rigid and unemotional in everyday interactions. Harvard Business School professor and former leader at Uber distills it down to a simple phrase: “Begin With Trust.” All CEO’s have some amount of ego, driving them to want to be at the top of their organization. Slootman encourages CEO’s to be introspective, and try to recognize blind spots, so ego doesn’t drive day-to-day interactions with employees. One way to do that is simple: use the pronoun “we” when discussing the company you are leading. Though Slootman doesn’t explicitly call it out - all of these suggestions (fighting, showing empathy, getting rid of ego) are meant to build trust with employees.

  3. R-E-C-I-P-E for a Great Culture. The last fifth of the book is all focused on building culture at companies. It is the only topic Slootman stays on for more than a few chapters, so you know its important! RECIPE was an acronym created by the employees at Data Domain to describe the company’s values: Respect, Excellence, Customer, Integrity, Performance, Execution. Its interesting how simple and focused these values are. Technology has pushed its cultural delusion’s of grandeur to an extreme in recent years. The WeWork S-1 hilariously started with: “We are a community company committed to maximum global impact. Our mission is to elevate the world’s consciousness.” But none of Data Domain’s values were about changing the world to be a better place - they were about doing excellent, honest work for customers. Slootman is lasered focused on culture, and specifically views culture as an asset - calling it: “The only enduring, sustainable form of differentiation. These days, we don’t have a monopoly for very long on talent, technology, capital, or any other asset; the one thing that is unique to us is how we choose to come together as a group of people, day in and day out. How many organizations are there that make more than a halfhearted attempt at this?” Technology companies have taken different routes in establishing culture: Google and Facebook have tried to create culture by showering employees with unbelievable benefits, Netflix has focused on pure execution and transparency, and Microsoft has re-vamped its culture by adopting a Growth Mindset (has it really though?). Google originally promoted “Don’t be evil,” as part of its Code of Conduct but dropped the motto in 2018. Employees want to work for mission-driven organizations, but not all companies are really changing the world with their products, and Frank did not try to sugarcoat Data Domain’s data-duplication technology as a way to “elevate the world’s consciousness.” He created a culture driven by performance and execution - providing a useful product to businesses that needed it. The culture was so revered that post-acquisition, EMC instituted Data Domain’s performance management system. Data Domain employees were looked at strangely by longtime EMC executives, who had spent years in a big and stale company. Culture is a hard thing to replicate and a hard thing to change as we saw with the Innovator’s Dilemma. Might as well use it to help the company succeed!

Dig Deeper

  • How Data Domain Evolved in the Cloud World

  • Former Data Domain CEO Frank Slootman Gets His Old Band Back Together at ServiceNow

  • The Contentious Take-over Battle for Data Domain: Netapp vs. EMC

  • 2009 Interview with Frank Slootman After the Acquisition of Data Domain

tags: Snowflake, DoorDash, ServiceNow, WeWork, Data Domain, EMC, Netapp, Frank Slootman, Borland, IBM, Burroughs, Sperry, NEA, Greylock, Workday, Aneel Bhusri, Sun Microsystems, USVP, Uber, Netflix, Facebook, Google, Microsoft, Amazon, Jeff Bezos, Tony Xu, MongoDB, Elastic, Crowdstrike, Crypto, Gartner, Hype Cycle, Slack, Apple, Steve Jobs, Steve Wozniak, Magic Leap, batch2
categories: Non-Fiction
 

October 2020 - Working in Public: The Making and Maintenance of Open Source Software by Nadia Eghbal

This month we covered Nadia Eghbal’s instant classic about open-source software. Open-source software has been around since the late seventies but only recently it has gained significant public and business attention.

Tech Themes

The four types of open source communities described in Working in Public

The four types of open source communities described in Working in Public

  1. Misunderstood Communities. Open source is frequently viewed as an overwhelmingly positive force for good - taking software and making it free for everyone to use. Many think of open source as community-driven, where everyone participates and contributes to making the software better. The theory is that so many eyeballs and contributors to the software improves security, improves reliability, and increases distribution. In reality, open-source communities take the shape of the “90-9-1” rule and act more like social media than you could think. According to Wikipedia, the "90–9–1” rule states that for websites where users can both create and edit content, 1% of people create content, 9% edit or modify that content, and 90% view the content without contributing. To show how this applies to open source communities, Eghbal cites a study by North Carolina State Researchers: “One study found that in more than 85% of open source projects the research examined on Github, less than 5% of developers were responsible for 95% of code and social interactions.” These creators, contributors, and maintainers are developer influencers: “Each of these developers commands a large audience of people who follow them personally; they have the attention of thousands of developers.” Unlike Instagram and Twitch influencers, who often actively try to build their audiences, open-source developer influencers sometimes find the attention off-putting - they simply published something to help others and suddenly found themselves with actual influence. The challenging truth of open source is that core contributors and maintainers give significant amounts of their time and attention to their communities - often spending hours at a time responding to pull requests (requests for changes / new features) on Github. Evan Czaplicki’s insightful talk entitled “The Hard Parts of Open Source,” speaks to this challenging dynamic. Evan created the open-source project, Elm, a functional programming language that compiles Javascript, because he wanted to make functional programming more accessible to developers. As one of its core maintainers, he has repeatedly been hit with requests of “Why don’t you just…” from non-contributing developers angrily asking why a feature wasn’t included in the latest release. As fastlane creator, Felix Krause put it, “The bigger your project becomes, the harder it is to keep the innovation you had in the beginning of your project. Suddenly you have to consider hundreds of different use cases…Once you pass a few thousand active users, you’ll notice that helping your users takes more time than actually working on your project. People submit all kinds of issues, most of them aren’t actually issues, but feature requests or questions.” When you use open-source software, remember who is contributing and maintaining it - and the days and years poured into the project for the sole goal of increasing its utility for the masses.

  2. Git it? Git was created by Linus Torvalds in 2005. We talked about Torvalds last month, who also created the most famous open-source operating system, Linux. Git was born in response to a skirmish with Larry McAvoy, the head of proprietary tool BitKeeper, over the potential misuse of his product. Torvalds went on vacation for a week and hammered out the most dominant version control system today - git. Version control systems allow developers to work simultaneously on projects, committing any changes to a centralized branch of code. It also allows for any changes to be rolled back to earlier versions which can be enormously helpful if a bug is found in the main branch. Git ushered in a new wave of version control, but the open-source version was somewhat difficult to use for the untrained developer. Enter Github and GitLab - two companies built around the idea of making the git version control system easier for developers to use. Github came first, in 2007, offering a platform to host and share projects. The Github platform was free, but not open source - developers couldn’t build onto their hosting platform - only use it. GitLab started in 2014 to offer an alternative, fully-open sourced platform that allowed individuals to self-host a Github-like tracking program, providing improved security and control. Because of Github’s first mover advantage, however, it has become the dominant platform upon which developers build: “Github is still by far the dominant market player: while it’s hard to find public numbers on GitLab’s adoption, its website claims more than 100,000 organizations use its product, whereas GitHub claims more than 2.9 million organizations.” Developers find GitHub incredibly easy to use, creating an enormous wave of open source projects and code-sharing. The company added 10 million new users in 2019 alone - bringing the total to over 40 million worldwide. This growth prompted Microsoft to buy GitHub in 2018 for $7.5B. We are in the early stages of this development explosion, and it will be interesting to see how increased code accessibility changes the world over the next ten years.

  3. Developing and Maintaining an Ecosystem Forever. Open source communities are unique and complex - with different user and contributor dynamics. Eghbal tries to segment the different types of open source communities into four buckets - federations, clubs, stadiums, and toys - characterized below in the two by two matrix - based on contributor growth and user growth. Federations are the pinnacle of open source software development - many contributors and many users, creating a vibrant ecosystem of innovative development. Clubs represent more niche and focused communities, including vertical-specific tools like astronomy package, Astropy. Stadiums are highly centralized but large communities - this typically means only a few contributors but a significant user base. It is up to these core contributors to lead the ecosystem as opposed to decentralized federations that have so many contributors they can go in all directions. Lastly, there are toys, which have low user growth and low contributor growth but may actually be very useful projects. Interestingly, projects can shift in and out of these community types as they become more or less relevant. For example, developers from Yahoo open-sourced their Hadoop project based on Google’s File System and Map Reduce papers. The initial project slowly became huge, moving from a stadium to a federation, and formed subprojects around it, like Apache Spark. What’s interesting, is that projects mature and change, and code can remain in production for a number of years after the project’s day in the spotlight is gone. According to Eghbal, “Some of the oldest code ever written is still running in production today. Fortran, which was first developed in 1957 at IBM, is still widely used in aerospace, weather forecasting, and other computational industries.” These ecosystems can exist forever, but the costs of these ecosystems (creation, distribution, and maintenance) are often hidden, especially the maintenance aspect. The cost of creation and distribution has dropped significantly in the past ten years - with many of the world’s developers all working in the same ecosystem on GitHub - but it has also increased the total cost of maintenance, and that maintenance cost can be significant. Bootstrap co-creator Jacob Thornton likens maintenance costs to caring for an old dog: “I’ve created endlessly more and more projects that have now turned [from puppies] into dogs. Almost every project I release will get 2,000, 3,000 watchers, which is enough to have this guilt, which is essentially like ‘I need to maintain this, I need to take care of this dog.” Communities change from toys to clubs to stadiums to federations but they may also change back as new tools are developed. Old projects still need to be maintained and that code and maintenance comes down to committed developers.

Business Themes

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  1. Revenue Model Matching. One of the earliest code-hosting platforms was SourceForge, a company founded in 1999. The Company pioneered the idea of code-hosting - letting developers publish their code for easy download. It became famous for letting open-source developers use the platform free of charge. SourceForge was created by VA Software, an internet bubble darling that saw its stock price decimated when the bubble finally burst. The challenge with scaling SourceForge was a revenue model mismatch - VA Software made money with paid advertising, which allowed it to offer its tools to developers for free, but meant its revenue model was highly variable. When the company went public, it was still a small and unproven business, posting $17M in revenue and $31M in costs. The revenue model mismatch is starting to rear its head again, with traditional software as a service (SaaS) recurring subscription models catching some heat. Many cloud service and API companies are pricing by usage rather than a fixed, high margin subscription fee. This is the classic electric utility model - you only pay for what you use. Snowflake CEO Frank Slootman (who formerly ran SaaS pioneer ServiceNow) commented: “I also did not like SaaS that much as a business model, felt it not equitable for customers.” Snowflake instead charges based on credits which pay for usage. The issue with usage-based billing has traditionally been price transparency, which can be obfuscated with customer credit systems and incalculable pricing, like Amazon Web Services. This revenue model mismatch was just one problem for SourceForge. As git became the dominant version control system, SourceForge was reluctant to support it - opting for its traditional tools instead. Pricing norms change, and new technology comes out every day, it’s imperative that businesses have a strong grasp of the value they provide to their customers and align their revenue model with customers, so a fair trade-off is created.

  2. Open Core Model. There has been enormous growth in open source businesses in the past few years, which typically operate on an open core model. The open core model means the Company offers a free, normally feature limited, version of its software and also a proprietary, enterprise version with additional features. Developers might adopt the free version but hit usage limits or feature constraints, causing them to purchase the paid version. The open-source “core” is often just that - freely available for anyone to download and modify; the core's actual source code is normally published on GitHub, and developers can fork the project or do whatever they wish with that open core. The commercial product is normally closed source and not available for modification, providing the business a product. Joseph Jacks, who runs Open Source Software (OSS) Capital, an investment firm focused on open source, displays four types of open core business model (pictured above). The business models differ based on how much of the software is open source. Github, interestingly, employs the “thick” model of being mostly proprietary, with only 10% of its software truly open-sourced. Its funny that the site that hosts and facilitates the most open source development is proprietary. Jacks nails the most important question in the open core model: “How much stays open vs. How much stays closed?” The consequences can be dire to a business - open source too much and all of a sudden other companies can quickly recreate your tool. Many DevOps tools have experienced the perils of open source, with some companies losing control of the project it was supposed to facilitate. On the flip side, keeping more of the software closed source goes against the open-source ethos, which can be viewed as organizations selling out. The continuous delivery pipeline project Jenkins has struggled to satiate its growing user base, leading to the CEO of the Jenkins company, CloudBees, posting the blog post entitled, “Shifting Gears”: “But at the same time, the incremental, autonomous nature of our community made us demonstrably unable to solve certain kinds of problems. And after 10+ years, these unsolved problems are getting more pronounced, and they are taking a toll — segments of users correctly feel that the community doesn’t get them, because we have shown an inability to address some of their greatest difficulties in using Jenkins. And I know some of those problems, such as service instability, matter to all of us.” Striking this balance is incredibly tough, especially in a world of competing projects and finite development time and money in a commercial setting. Furthermore, large companies like AWS are taking open core tools like Elastic and MongoDB and recreating them in proprietary fashions (Elasticsearch Service and DocumentDB) prompting company CEO’s to appropriately lash out. Commercializing open source software is a never-ending battle against proprietary players and yourself.

  3. Compensation for Open Source. Eghabl characterizes two types of funders of open-source - institutions (companies, governments, universities) and individuals (usually developers who are direct users). Companies like to fund improved code quality, influence, and access to core projects. The largest groups of contributors to open source projects are mainly corporations like Microsoft, Google, Red Hat, IBM, and Intel. These corporations are big enough and profitable enough to hire individuals and allow them to strike a comfortable balance between time spent on commercial software and time spent on open source. This also functions as a marketing expense for the big corporations; big companies like having influencer developers on payroll to get the company’s name out into the ecosystem. Evan You, who authored Vue.js, a javascript framework described company backed open-source projects: “The thing about company-backed open-source projects is that in a lot of cases… they want to make it sort of an open standard for a certain industry, or sometimes they simply open-source it to serve as some sort of publicity improvement to help with recruiting… If this project no longer serves that purpose, then most companies will probably just cut it, or (in other terms) just give it to the community and let the community drive it.” In contrast to company-funded projects, developer-funded projects are often donation based. With the rise of online tools for encouraging payments like Stripe and Patreon, more and more funding is being directed to individual open source developers. Unfortunately though, it is still hard for many open source developers to pursue open source on individual contributions, especially if they work on multiple projects at the same time. Open source developer Sindre Sorhus explains: “It’s a lot harder to attract company sponsors when you maintain a lot of projects of varying sizes instead of just one large popular project like Babel, even if many of those projects are the backbone of the Node.js ecosystem.” Whether working in a company or as an individual developer, building and maintaining open source software takes significant time and effort and rarely leads to significant monetary compensation.

Dig Deeper

  • List of Commercial Open Source Software Businesses by OSS Capital

  • How to Build an Open Source Business by Peter Levine (General Partner at Andreessen Horowitz)

  • The Mind Behind Linux (a talk by Linus Torvalds)

  • What is open source - a blog post by Red Hat

  • Why Open Source is Hard by PHP Developer Jose Diaz Gonzalez

  • The Complicated Economy of Open Source

tags: Github, Gitlab, Google, Twitch, Instagram, E;, Elm, Javascript, Open Source, Git, Linus Torvalds, Linux, Microsoft, MapReduce, IBM, Fortran, Node, Vue, SourceForge, VA Software, Snowflake, Frank Slootman, ServiceNow, SaaS, AWS, DevOps, CloudBees, Jenkins, Intel, Red Hat, batch2
categories: Non-Fiction
 

September 2020 - Women of Color in Tech by Susanne Tedrick

This month we dove into Susanne Tedrick’s new book, Women of Color in Tech. Tedrick provides an excellent overview of the challenges many women of color face when trying to enter into and stay in the technology industry. The mix of real-world advice, personal experience, and industry stories combine to form a comprehensive resource for anyone in technology or looking to enter the field.

Tech Themes

  1. The Current State. Tedrick starts the book with uncomfortable statistics. Only 26% of computing roles are held by women; Black women hold 3% and Hispanic women hold 2% of computing roles. In addition, the trends aren’t positive - 26% is a 9% decrease since 1990. According to the Ascend Foundation, a Pan-Asian organization for business professionals, from 2007 to 2015, black women experienced a 13% decrease in professional roles in technology. While distressing, there are some green shoots, a 2012 paper by Heather Gonzalez and Jeffrey Kuenzi pointed out that science and engineering graduate program enrollments grew 65%, 55%, and 50% for Hispanic/Latino, American Indian/Alaska Native, and African American students, respectively. So why is this? Tedrick acknowledges that there is no one single answer, instead, its a combination of circumstances starting at early adolescence. Tedrick introduces the idea of “STEM Deserts” or areas where STEM education is not offered. These deserts disproportionally affect high poverty schools (schools where 75% or more of the students are eligible for free lunch and breakfast). Almost half of these schools contain large Black and Hispanic populations. Once women of color arrive at college it gets harder: “Coupling [student debt] with professor’s biases, a lack of meaningful support at home or within their community, and few to no peers with whom they can identify in their academic programs, many young women of color struggle to get through their programs.” For the few that conquer all of these challenges, the workplace introduces a whole new set of issues. Tedrick cites the Kapor Center’s Tech Leavers Study: “Thirty percent of women of color respondents claimed that they were passed over for promotions and 24% report being stereotyped.” According to a Harvard Business Review article written by feminist legal scholar Joan Williams, “77% of black women report having to prove themselves over and over; their success discounted and their expertise questioned.” When you compile all of these challenges throughout a lifetime, it becomes an incredibly difficult journey for black women in tech.

  2. Technical Roles and the Building Blocks of the Internet. Tedrick introduces many key organizational roles in technology including business analysis, consulting, data science, information security, product management, project management, software development, technical sales, technical support, user experience design, and web design. After introducing each one, she provides a prescriptive guide for individuals looking to learn more - hitting on key skills, educational requirements, and the latest trends. While I can’t cover every role here, one underappreciated position / sub-segment of technology Tedrick discusses is computer networking. Ultimately, networking was the benefit that unlocked the internet to the masses. Protocols like TCP/IP, VoIP, and HTTP are crucial to the functioning internet. These protocols offer ways for computers to communicate with one another in a consistent manner. The IP (Internet Protocol) provides basic addressing for computers and TCP provides the continual delivery of ordered and reliable bytes from one computer to another in what are called packets. A packet is a pre-defined standard for sending data. VoIP is an extension of this protocol specifically for transcoding audio and video voice signals into packets. HTTP is the way you request the data found at a location: http://techbookofthemonth.com tells the browser to fetch the website at that URL. A lot of basic networking features are typically baked into the operating system, which for most consumers today is Linux. Linux is an open-source operating system that handles all of the things that makes your computer run: memory, CPU, connected devices, graphics, desktop environment, and the ability to run applications. However, Linux programming is still not a commonly learned skill. Tedrick quotes Tameika Reed, a senior infrastructure engineer and founder of Women in Linux: “We have people who are getting degrees and PhDs and so on. . . . When it comes down to Linux, which runs in 90 percent of most companies, and it’s time to troubleshoot something, they don’t know how to troubleshoot the basics of the foundation. I look at Linux as the foundations of getting into tech.” Red Hat, which was acquired by IBM for $34 billion in 2019, offers an enterprise version of Linux which comes with support, guaranteed versioning, and additional security. While computer networking is not a flashy industry, it underpins so much that it remains very interesting.

  3. Technology Skills. Chapter six lays out a great way to assess your own skills and understand where you need improvement. These skills can require additional schooling via college, trade schools, or massive-open-online-courses (MOOCs) like Coursera but other ways to complement this learning include hackathons, conferences, networking, and volunteering. Tedrick wanted to improve her own skills so she volunteered to help set up a conference: “To improve my web design, WordPress, and conference organization skills, I volunteered my services for a leadership conference being held by IEEE Women in Engineering for four months in 2016. I helped to build and maintain the event website using WordPress, as well as helped people with registration and refunds. This experience greatly improved my understanding of web design, search engine optimization (SEO), event promotion, and collaborating with remote teams (I was based in Chicago, while much of the event team and registrants were based in and around Detroit, Michigan). In the process, I learned more about the different fields of engineering and broadened my network with incredible engineering students and professionals.” The book is incredibly helpful for skill-building - it gives you the exact things you need to learn to be successful in specific positions and it even clears up some myths of the technology industry. One common myth is that “Tech Careers Require Constant, Hands-On Programming.” As evidenced by the myriad of roles listed above, the technology industry involves so much more than programming. In addition, Tech careers exist outside of the top five big-name companies like Microsoft, Google, Facebook, Amazon, and Netflix and even exist at non-tech companies too. One critical skill that Tedrick highlights for a number of different technical roles is communication. Communication is not often mentioned when discussing software engineering, but Tedrick picks up on its huge importance, and the necessary ability to communicate to technical and non-technical audiences. On top of sharing with non-technical audiences, engineers need to know how to communicate accurate deadlines to managers and ask for help when unsure of how to implement a challenging new feature. Communication is not just speaking, its also listening and empathetically understanding where others are coming from, to establish common ground and grow mutual understanding.

Business Themes

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  1. Tedrick’s Story and Grit. Susanne’s personal stories appear throughout the book and perfectly complement the substantial amount of how-to information and advice. Chapter nine talks about the daily challenges of many women of color in tech and their lack of support to solve those challenges. Susanne’s own story is one of incredible determination and perseverance: “My mother had been diagnosed with a brain tumor when I was very young. This initial tumor led to more health issues for her over the years, including a decline into dementia, a loss of some of her short-term memory, and impacted mobility. The latter half of her life was spent in and out of hospitals, having numerous operations and medical incidents. My father was left to care for me and my sister, while also supporting several other family members in one house. Between work and caring for my mom, he couldn’t be around much, and fortunately, some nearby relatives and family friends helped to raise and care for us. As there was only one income (already too high to qualify for most public assistance programs) and my mother needed many medications, there were times where a choice had to be made between eating, having phone service, making critical house repairs, or having the lights stay on. This went on for nearly two decades, up until my mother’s death. It wasn’t until well into my adult life that I realized I was living in ‘survival mode’ and just trying to exist. I was spending most of my time trying to find happiness in my life; having a meaningful and engaging career was not an immediate goal or one I thought was achievable for me.” After working in administrative roles and taking on a couple of different jobs, she managed to attend Northwestern while continuing to work. “I used much of my vacation and holiday time from work not only to study but to attend conferences, interviews, boot camps, and the like. I did homework during lunch breaks or before the start of a full workday, only to go to class for several hours in the same evening.” Tedrick has risen to be an award-winning public speaker, author, and technologist at IBM (oh and she’s also run a couple of marathons). Her story is truly inspirational!

  2. Culture, Intersectionality, and Bias. We’ve discussed Clayton Christensen’s Resources-Processes-Values framework before and how they impact the discovery of emerging technologies. Often the processes create a culture and set of habitual routines that can be difficult to change. The culture of big technology has been anti-women for a long time. As Tedrick points out, women of color not only have to deal with this challenge but also repeated racial abuse, microaggressions, and tokenism. Kimberlé Crenshaw called this intersectionality, or the idea that a person's social identities (e.g., gender, caste, sex, race, class, sexuality, religion, disability, physical appearance, height, etc.) combine to create unique modes of discrimination and privilege. Tedrick points out an example of this with Sheryl Sandberg’s famous novel, Lean In. The book became a bestseller and made Sheryl Sandberg a household name (to those that didn’t already know her as COO of Facebook). However, as Tedrick points out: “The central problem with the book, which Sandberg herself later acknowledged, is that it assumed that the reader had certain privileges that many women of color do not have: completely supportive households that don’t require much of their time and attention, work cultures that allow expression of their thoughts without fear of being fired or held back, and access to career mentors to help them become stronger leaders. This lack of understanding of where the reader may be coming from and experiencing caused much of Sandberg’s advice to ring hollow for women of color.” The book ignores the structural challenges that many women of color face. Michelle Obama put it bluntly: “It’s not always enough to lean in, because that shit doesn’t work all the time.” When building culture at an organization, it’s super important to think about how that culture addresses each social identity at the company. Furthermore, it’s not the responsibility of diverse individuals to build that culture. Tedrick sums it up well: “Addressing tokenism, much like addressing bias, unfortunately, is not something that you alone can address. It is also not our responsibility to address this. It is up to organizations and their leaders to correct and address tokenism so that women of color are fully engaged.”

  3. Negotiating Compensation. Understanding pay and compensation are critical to understanding any job offer. Frequently job candidates are remiss to ask for additional compensation because they fear retribution like the offer is pulled and given to someone else and worry about sounding greedy before even joining a new company. As Susanne found out after receiving her first traditional job, this can lead to lower salaries, especially when adjusting for location. In addition, Susanne points out the enormous gender pay gap that occurs at organizations: “It’s no secret that women—and specifically, women of color—are underpaid in about every industry, not just tech. While it is on companies to fix their approaches to compensation, it is our right and duty to demand fair compensation for our work.” A study of the technology industry done by job search marketplace, Hired, shows that black women were paid $0.89 on the dollar compared to white males. This is the lowest across White, Asian, Black, and Hispanic men and women in the technology sector. For LGBTQI+ individuals, the wage gap is $0.90 to $1 of compensation for non-LGBTQI+. While pay gap detail for black LGBTQI+ community is under-studied, according to The National LGBTQ Task Force’s 2011, 48% of trans and gender non-conforming black individuals experienced discrimination in the hiring process. Outside of the technology industry, the pay gap is even more stark with Black women earning $0.62 for every dollar earned by a White male. To address many of these challenges, and ensure that candidates get as close to a fair offer as possible, Tedrick lays out a framework for considering a new job, from pay to benefits to location. Tedrick advises individuals to first research local salaries for the role they are taking on. Armed with data, Tedrick suggests candidates try to be confident, respectful, and flexible in all discussions and to emphasize the unique value they bring to the organization.

Dig Deeper

  • Work Smart & Start Smart: Salary Negotiation for Women of Color

  • Anita Borg and the history of one of the largest professional organizations for women in technology

  • How the World’s most prevalent operating system was built by a 21-year old in Finland

  • Black Girls Code: Empowering Young Black Women to Become Innovators

  • Tedrick’s Twitter, website, and talk with the Women’s National Book Association

tags: TCP/IP, VoIP, HTTP, Computer Networking, Linux, Red Hat, IBM, Susanne Tedrick, Coursera, IEEE Women in Engineering, Grit, Culture, Diversity, Women in Tech, Intersectionality, Facebook, Sheryl Sandberg, Michelle Obama, Gender Pay Gap, batch2
categories: Non-Fiction
 

April 2020 - Good To Great by Jim Collins

Collins’ book attempts to answer the question - Why do good companies continue to be good companies? His analysis across several different industries provides meaningful insights into strong management and strategic practices.

Tech Themes

  1. Packard’s Law. We’ve discussed Packard’s law before when analyzing the troubling acquisition history of AOL-Time Warner and Yahoo. As a reminder, Packard’s law states: “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. [And] 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.” Given Good To Great is a management focused book, I wanted to explore an example of this law manifesting itself in a recent management dilemma. Look no further than ride-sharing giant, Uber. Uber’s culture and management problems have been highly publicized. Susan Fowler’s famous blog post kicked off a series of blows that would ultimately lead to a board dispute, the departure of its CEO, and a full-on criminal investigation. Uber’s problems as a company, however, can be traced to its insistence to be the only ride-sharing service throughout the world. Uber launched several incredibly unprofitable ventures, not only a price-war with its local competitor Lyft, but also a concerted effort to get into China, India, and other locations that ultimately proved incredibly unprofitable. Uber tried to be all things transportation to every location in the world, an over-indulgence that led to the Company raising a casual $20B prior to going public. Dara Khosrowshahi, Uber’s replacement for Travis Kalanick, has concertedly sold off several business lines and shuttered other unprofitable ventures to regain financial control of this formerly money burning “logistics” pit. This unwinding has clearly benefited the business, but also limited growth, prompting the stock to drop significantly from IPO price. Dara is no stranger to facing travel challenges, he architected the spin-out of Expedia with Barry Diller, right before 9/11. Only time will tell if he can refocus the Company as it looks to run profitably. Uber pushed too far in unprofitable locations, and ran head on into Packard’s law, now having to pay the price for its brash push into unprofitable markets.

  2. Technology Accelerators. In Collins’ Good to Great framework (pictured below), technology accelerators act as a catalyst to momentum built up from disciplined people and disciplined thought. By adapting a “Pause, think, crawl, walk, run” approach to technology, meaning a slow and thoughtful transition to new technologies, companies can establish best practices for the long-term, instead of short term gains from technology faux-feature marketing. Technology faux-feature marketing, which is decoupled from actual technology has become increasingly popular in the past few years, whereby companies adopt a marketing position that is actually complete separate from their technological sophistication. Look no further than the blockchain / crypto faux-feature marketing around 2018, when Long Island iced-tea changed its name to Long Island Blockchain, which is reminiscent of companies adding “.com” to their name in the early 2000’s. Collins makes several important distinctions about technology accelerators: technology should only be a focus if it fits into a company’s hedgehog concept, technology accelerators cannot make up for poor people choices, and technology is never a primary root cause of either greatness or decline. The first two axioms make sense, just think of how many failed, custom software projects have begun and never finished; there is literally an entire wikipedia page dedicated to exactly that. The government has also reportedly been a famous dabbler in homegrown, highly customized technology. As Collins notes, technology accelerators cannot make up for bad people choices, an aspect of venture capital that is overlooked by so many. Enron is a great example of an interesting idea turned sour by terrible leadership. Beyond the accounting scandals that are discussed frequently, the culture was utterly toxic, with employees subjected to a “Performance Review Committee” whereby they were rated on a scale of 1-5 by their peers. Employees rated a 5 were fired, which meant roughly 15% of the workforce turned over every year. The New York Times reckoned Enron is still viewed as a trailblazer for the way it combined technology and energy services, but it clearly suffered from terrible leadership that even great technology couldn’t surmount. Collins’ most controversial point is arguably that technology cannot cause greatness or decline. Some would argue that technology is the primary cause of greatness for some companies like Amazon, Apple, Google, and Microsoft. The “it was just a better search engine” argument abounds discussions of early internet search engines. I think what Collins’ is getting at is that technology is malleable and can be built several different ways. Zoom and Cloudflare are great examples of this. As we’ve discussed, Zoom started over 100 years after the idea for video calling was first conceived, and several years after Cisco had purchased Webex, which begs the question, is technology the cause of greatness for Zoom? No! Zoom’s ultimate success the elegance of its simple video chat, something which had been locked up in corporate feature complexity for years. Cloudflare presents another great example. CDN businesses had existed for years when Cloudflare launched, and Cloudflare famously embedded security within the CDN, building on a trend which Akamai tried to address via M&A. Was technology the cause of greatness for Cloudflare? No! It’s way cheaper and easier to use than Akamai. Its cost structure enabled it to compete for customers that would be unprofitable to Akamai, a classic example of a sustaining technology innovation, Clayton Christensen’s Innovator’s Dilemma. This is not to say these are not technologically sophisticated companies, Zoom’s cloud ops team has kept an amazing service running 24/7 despite a massive increase in users, and Cloudflare’s Workers technology is probably the best bet to disrupt the traditional cloud providers today. But to place technology as the sole cause for greatness would be understating the companies achievements in several other areas.

  3. Build up, Breakthrough Flywheel. Jeff Bezos loves this book. Its listed in the continued reading section of prior TBOTM, The Everything Store. The build up, breakthrough flywheel is the culmination of disciplined people, disciplined thought and disciplined action. Collins’ points out that several great companies frequently appear like overnight successes; all of a sudden, the Company has created something great. But that’s rarely the case. Amazon is a great example of this; it had several detractors in the early days, and was dismissed as simply an online bookseller. Little did the world know that Jeff Bezos had ideas to pursue every product line and slowly launched one after the other in a concerted fashion. In addition, what is a better technology accelerator than AWS! AWS resulted from an internal problem of scaling compute fast enough to meet growing consumer demand for their online products. The company’s tech helped it scale so well that they thought, “Hey! Other companies would probably like this!” Apple is another classic example of a build-up, breakthrough flywheel. The Company had a massive success with the iPod, it was 40% of revenues in 2007. But what did it do? It cannablized itself and pursued the iPhone, with several different teams within the company pursuing it individually. Not only that, it created a terrible first version of an Apple phone with the Rokr, realizing that design was massively important to the phone’s success. The phone’s technology is taken for granted today, but at the time the touch screen was simply magical!

Business Themes

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  1. Level 5 Leader. The first part and probably the most important part of the buildup, breakthrough, flywheel is disciplined people. One aspect of Good to Great that inspired Collins’ other book Built to Last, is the idea that leadership, people, and culture determine the long-term future of a business, even after current leadership has moved on from the business. To set an organization up for long-term success, executives need to display level five leadership, which is a mix of personal humility and professional will. Collins’ leans in on Lee Iacocca as an example of a poor leader, who focused more on personal celebrity and left Chrysler to fail, when he departed. Level 5 leadership has something that you don’t frequently see in technology business leaders, humility. The technology industry seems littered with far more Larry Ellison and Elon Musk’s than any other industry, or maybe its just that tech CEOs tend to shout the loudest from their pedestals. One CEO that has done a great job of representing level five leadership is Shantanu Narayen, who took the reigns of Adobe in December 2007, right on the cusp of the financial crisis. Narayen, who’s been described as more of a doer than a talker, has dramatically changed Adobe’s revenue model, moving the business from a single sale license software business focused on lower ACV numbers, to an enterprise focused SaaS business. This march has been slow and pragmatic but the business has done incredibly well, 10xing since he took over. Adobe CFO, Mark Garrett, summarized it best in a 2015 McKinsey interview: “We instituted open dialogue with employees—here’s what we’re going through, here’s what it might look like—and we encouraged debate. Not everyone stayed, but those who did were committed to the cloud model.”

  2. Hedgehog Concept. The Hedgehog concept (in the picture wheel to the right) is the overlap of three questions: What are you passionate about?, What are you the best in the world at?, and What drives your economic engine? This overlap is the conclusion of Collins’ memo to Confront the Brutal Facts, something that Ben Horowitz emphasizes in March’s TBOTM. Once teams have dug into their business, they should come up with a simple way to center their focus. When companies reach outside their hedgehog concept, they get hurt. The first question, about organizational passion, manifests itself in mission and value statements. The best in the world question manifests itself through value network exercises, SWOT analyses and competitive analyses. The economic engine is typically shown as a single metric to define success in the organization. As an example, let’s walk through an example with a less well-known SaaS company: Avalara. Avalara is a provider of tax compliance software for SMBs and enterprises, allowing those businesses to outsource complex and changing tax rules to software that integrates with financial management systems to provide an accurate view of corporate taxes. Avalara’s hedgehog concept is right on their website: “We live and breathe tax compliance so you don't have to.” Its simple and effective. The also list a slightly different version in their 10-K, “Avalara’s motto is ‘Tax compliance done right.’” Avalara is the best at tax compliance software, and that is their passion; they “live and breath” tax compliance software. What drives Avalara’s economic engine? They list two metrics right at the top of their SEC filings, number of core customers and net revenue retention. Core customers are customers who have been billed more than $3,000 in the last twelve months. The growth in core customers allows Avalara to understand their base of revenue. Tax compliance software is likely low churn because filing taxes is such an onerous process, and most people don’t have the expertise to do it for their corporate taxes. They will however suffer from some tax seasonality and some customers may churn and come back after the tax period has ended for a given year. Total billings allows Avalara to account for this possibility. Avalara’s core customers have grown 32% in the last twelve months, meaning its revenue should be following a similar trajectory. Net retention allows the company to understand how customer purchasing behavior changes over time and at 113% net retention, Avalara’s overall base is buying more software from Avalara than is churning, which is a positive trend for the company. What is the company the best in the world at? Tax compliance software for SMBs. Avalara views their core customer as greater than $3,000 of trailing twelve months revenue, which means they are targeting small customers. The Company’s integrations also speak to this - Shopify, Magento, NetSuite, and Stripe are all focused on SMB and mid-market customers. Notice that neither SAP nor Oracle ERP is in that list of integrations, which are the financial management software providers that target large enterprises. This means Avalara has set up its product and cost structure to ensure long-term profitability in the SMB segment; the enterprise segment is on the horizon, but today they are focused on SMBs.

  3. Culture of Discipline. Collins describes a culture of discipline as an ability of managers to have open and honest, often confrontational conversation. The culture of discipline has to fit within a culture of freedom, allowing individuals to feel responsible for their division of the business. This culture of discipline is one of the first things to break down when a CEO leaves. Collins points on this issue with Lee Iaccoca, the former CEO of Chrysler. Lee built an intense culture of corporate favoritism, which completely unraveled after he left the business. This is also the focus of Collins’ other book, Built to Last. Companies don’t die overnight, yet it seems that way when problems begin to abound company-wide. We’ve analyzed HP’s 20 year downfall and a similar story can be shown with IBM. In 1993, IBM elected Lou Gerstner as CEO of the company. Gerstner was an outsider to technology businesses, having previously led the highly controversial RJR Nabisco, after KKR completed its buyout in 1989. He has also been credited with enacting wholesale changes to the company’s culture during his tenure. Despite the stock price increasing significantly over Gerstner’s tenure, the business lost significant market share to Microsoft, Apple and Dell. Gerstner was also the first IBM CEO to make significant income, having personally been paid hundreds of millions over his tenure. Following Gerstner, IBM elected insider Sam Palmisano to lead the Company. Sam pushed IBM into several new business lines, acquired 25 software companies, and famously sold off IBM’s PC division, which turned out to be an excellent strategic decision as PC sales and margins declined over the following ten years. Interestingly, Sam’s goal was to “leave [IBM] better than when I got there.” Sam presided over a strong run up in the stock, but yet again, severely missed the broad strategic shift toward public cloud. In 2012, Ginni Rometty was elected as new CEO. Ginni had championed IBM’s large purchase of PwC’s technology consulting business, turning IBM more into a full service organization than a technology company. Palmisano has an interesting quote in an interview with a wharton business school professor where he discusses IBM’s strategy: “The thing I learned about Lou is that other than his phenomenal analytical capability, which is almost unmatched, Lou always had the ability to put the market or the client first. So the analysis always started from the outside in. You could say that goes back to connecting with the marketplace or the customer, but the point of it was to get the company and the analysis focused on outside in, not inside out. I think when you miss these shifts, you’re inside out. If you’re outside in, you don’t miss the shifts. They’re going to hit you. Now acting on them is a different characteristic. But you can’t miss the shift if you’re outside in. If you’re inside out, it’s easy to delude yourself. So he taught me the importance of always taking the view of outside in.” Palmisano’s period of leadership introduced a myriad of organizational changes, 110+ acquisitions, and a centralization of IBM processes globally. Ginni learned from Sam that acquisitions were key toward growth, but IBM was buying into markets they didn’t fully understand, and when Ginni layered on 25 new acquisitions in her first two years, the Company had to shift from an outside-in perspective to an inside-out perspective. The way IBM had historically handled the outside-in perspective, to recognize shifts and get ahead of them, was through acquisition. But when the acquisitions occured at such a rapid pace, and in new markets, the organization got bogged down in a process of digestion. Furthermore, the centralization of processes and acquired businesses is the exact opposite of what Clayton Christensen recommends when pursuing disruptive technology. This makes it obvious why IBM was so late to the cloud game. This was a mainframe and services company, that had acquired hundreds of software businesses they didn’t really understand. Instead of building on these software platforms, they wasted years trying to put them all together into a digestible package for their customers. IBM launched their public cloud offering in June 2014, a full seven years after Microsoft, Amazon, and Google launched their services, despite providing the underlying databases and computing power for all of their enterprise customers. Gerstner established the high-pay, glamorous CEO role at IBM, which Palmisano and Ginni stepped into, with corporate jets and great expense policies. The company favored increasing revenues and profits (as a result of acquisitions) over the recognition and focus on a strategic market shift, which led to a downfall in the stock price and a declining mindshare in enterprises. Collins’ understands the importance of long term cultural leadership. “Does Palmisano think he could have done anything differently to set IBM up for success once he left? Not really. What has happened since falls to a new coach, a new team, he says.”

Dig Deeper

  • Level 5 Leadership from Darwin Smith at Kimberly Clark

  • From Good to Great … to Below Average by Steven Levitt - Unpacking underperformance from some of the companies Collins’ studied

  • The Challenges faced by new CEO Arvind Krishna

  • Overview of Cloudflare Workers

  • The Opposite of the Buildup, Breakthrough, Flywheel - the Doom Loop

tags: IBM, Apple, Microsoft, Packard's Law, HP, Uber, Barry Diller, Enron, Zoom, Cloudflare, Innovator's Dilemma, Clayton Christensen, Jeff Bezos, Amazon, Larry Ellison, Adobe, Shantanu Narayen, Avalara, Hedgehog Concept, batch2
categories: Non-Fiction
 

March 2020 - The Hard Thing About Hard Things by Ben Horowitz

Ben Horowitz, GP of the famous investment fund Andreessen Horowitz, addresses the not-so-pleasant aspects of being a founder/CEO during a crisis. This book provides an excellent framework for anyone going through the struggles of scaling a business and dealing with growing pains.

Tech Themes

  1. The importance of Netscape. Now that its been relegated to history by the rise of AOL and internet explorer, its hard to believe that Netscape was ever the best web browser. Founded by Marc Andreessen, who had founded the first web browser, Mosaic (as a teenager!), Netscape would go on to achieve amazing success only to blow up in the face of competition and changes to internet infrastructure. Netscape was an incredible technology company, and as Brian McCullough shows in last month’s TBOTM, Netscape was the posterchild for the internet bubble. But for all the fanfare around Netscape’s seminal IPO, little is discussed about its massive and longstanding technological contributions. In 1995, early engineer Brendan Eich created Javascript, which still stands as the dominant front end language for the web. In the same year, the Company developed Secure Socket Layer (SSL), the most dominant basic internet security protocol (and reason for HTTPS). On top of those two fundamental technologies, Netscape also developed the internet cookie, in 1994! Netscape is normally discussed as the amazing company that ushered many of the first internet users onto the web, but its rarely lauded for its longstanding technological contributions. Ben Horowitz, author of the Hard Thing About Hard Things was an early employee and head of the server business unit for Netscape when it went public.

  2. Executing a pivot. Famous pivots have become part of startup lore whether it be in product (Glitch (video game) —> Slack (chat)), business model (Netflix DVD rental —> Streaming), or some combo of both (Snowdevil (selling snowboards online) —> Shopify (ecommerce tech)). The pivot has been hailed as necessary tool in every entrepreneur’s toolbox. Though many are sensationalized, the pivot Ben Horowitz underwent at LoudCloud / Opsware is an underrated one. LoudCloud was a provider of web hosting services and managed services for enterprises. The Company raised a boatload ($346M) of money prior to going public in March 2001, after the internet bubble had already burst. The Company was losing a lot of money and Ben knew that the business was on its last legs. After executing a 400 person layoff, he sold the managed services part of the business to EDS, a large IT provider, for $63.5M. LoudCloud had a software tool called Opsware that it used to manage all of the complexities of the web hosting business, scaling infrastructure with demand and managing compliance in data centers. After the sale was executed, the company’s stock fell to $0.35 per share, even trading below cash, which meant the markets viewed the Company as already bankrupt. The acquisition did something very important for Ben and the Opsware team, it bought them time - the Company had enough cash on hand to execute until Q4 2001 when it had to be cash flow positive. To balance out these cash issues, Opsware purchased Tangram, Rendition Networks, and Creekpath, which were all software vendors that helped manage the software of data centers. This had two effects - slowing the burn (these were profitable companies), and building a substantial product offering for data center providers. Opsware started making sales and the stock price began to tick up, peaking the attention of strategic acquirers. Ultimately it came down to BMC Software and HP. BMC offered $13.25 per share, the Opsware board said $14, BMC countered with $13.50 and HP came in with a $14.25 offer, a 38% premium to the stock price and a total valuation of $1.6B, which the board could not refuse. The Company changed business model (services —> software), made acquisitions and successfully exited, amidst a terrible environment for tech companies post-internet bubble.

  3. The Demise of the Great HP. Hewlett-Packard was one of the first garage-borne, silicon valley technology companies. The company was founded in Palo Alto by Bill Hewlett and Dave Packard in 1939 as a provider of test and measurement instruments. Over the next 40 years, the company moved into producing some of the best printers, scanners, calculators, logic analyzers, and computers in the world. In the 90s, HP continued to grow its product lines in the computing space, and executed a spinout of its manufacturing / non-computing device business in 1999. 1999 marks the tragic beginning of the end for HP. The first massive mistake was the acquisition of Compaq, a flailing competitor in the personal computer market, who had acquired DEC (a losing microprocessor company), a few years earlier. The acquisition was heavily debated, with Walter Hewlett, son of the founder and board director at the time, engaging in a proxy battle with then current CEO, Carly Firorina. The new HP went on to lose half of its market value and incur heavy job losses that were highly publicized. This started a string of terrible acquisitions including EDS, 3COM, Palm Inc., and Autonomy for a combined $28.8B. The Company spun into two divisions - HP Inc. and HP Enterprise in 2015 and each had their own spinouts and mergers from there (Micro Focus and DXC Technology). Today, HP Inc. sells computers and printers, and HPE sells storage, networking and server technology. What can be made of this sad tale? HP suffered from a few things. First, poor long term direction - in hindsight their acquisitions look especially terrible as a repeat series of massive bets on technology that was already being phased out due to market pressures. Second, HP had horrible corporate governance during the late 90s and 2000s - board in-fighting over acquisitions, repeat CEO fiirings over cultural issues, chairman-CEO’s with no checks, and an inability to see the outright fraud in their Autonomy acquisition. Lastly, the Company saw acquisitions and divestitures as band-aids - new CEO entrants Carly Fiorina (from AT&T), Mark Hurd (from NCR), Leo Apotheker (from SAP), and Meg Whitman (from eBay) were focused on making an impact at HP which meant big acquisitions and strategic shifts. Almost none of these panned out, and the repeated ideal shifts took a toll on the organization as the best talent moved elswehere. Its sad to see what has happened at a once-great company.

Business Themes

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  1. Ill, not sick: going public at the end of the internet bubble. Going public is supposed to be the culmination of a long entrepreneurial journey for early company employees, but according to Ben Horowitz’s experience, going public during the internet bubble pop was terrible. Loudcloud had tried to raise money privately but struggled given the terrible conditions for raising money at the beginning of 2001. Its not included in the book but the reason the Company failed to raise money was its obscene valuation and loss. The Company was valued at $1.15B in its prior funding round and could only report $6M in Net Revenue on a $107M loss. The Company sought to go public at $10 per share ($700M valuation), but after an intense and brutal roadshow that left Horowitz physically sick, they settled for $6.00 per share, a massive write-down from the previous round. The fact that the banks were even able to find investors to take on this significant risk at this point in the business cycle was a marvel. Timing can be crucial in an IPO as we saw during the internet bubble; internet “businesses” could rise 4-5x on their first trading day because of the massive and silly web landgrab in the late 90s. On the flip side, going public when investors don’t want what you’re selling is almost a death sentence. Although they both have critical business and market issues, WeWork and Casper are clear examples of the importance of timing. WeWork and Casper were late arrivals on the unicorn IPO train. Let me be clear - both have huge issues (WeWork - fundamental business model, Casper - competition/differentiation) but I could imagine these types of companies going public during a favorable time period with a relatively strong IPO. Both companies had massive losses, and investors were especially wary of losses after the failed IPOs of Lyft and Uber, which were arguably the most famous unicorns to go public at the time. Its not to say that WeWork and Casper wouldn’t have had trouble in the public markets, but during the internet bubble these companies could’ve received massive valuations and raised tons of cash instead of seeking bailouts from Softbank and reticent public market investors.

  2. Peactime / Wartime CEO. The genesis of this book was a 2011 blog post written by Horowitz detailing Peacetime and Wartime CEO behavior. As the book and blog post describe, “Peacetime in business means those times when a company has a large advantage vs. the competition in its core market, and its market is growing. In times of peace, the company can focus on expanding the market and reinforcing the company’s strengths.” On the other hand, to describe Wartime, Horowitz uses the example of a previous TBOTM, Only the Paranoid Survive, by Andy Grove. In the early 1980’s, Grove realized his business was under serious threat as competition increased in Intel’s core business, computer memory. Grove shifted the entire organization whole-heartedly into chip manufacturing and saved the company. Horowitz outlines several opposing behaviors of Peacetime and Wartime CEOs: “Peacetime CEO knows that proper protocol leads to winning. Wartime CEO violates protocol in order to win; Peacetime CEO spends time defining the culture. Wartime CEO lets the war define the culture; Peacetime CEO strives for broad based buy in. Wartime CEO neither indulges consensus-building nor tolerates disagreements.” Horowitz concludes that executives can be a peacetime and wartime CEO after mastering each of the respective skill sets and knowing when to shift from peacetime to wartime and back. The theory is interesting to consider; at its best, it provides an excellent framework for managing times of stress (like right now with the Coronavirus). At its worst, it encourages poor CEO behavior and cut throat culture. While I do think its a helpful theory, I think its helpful to think of situations that may be an exception, as a way of testing the theory. For example, lets consider Google, as Horowitz does in his original article. He calls out that Google was likely entering in a period of wartime in 2011 and as a result transitioned CEOs away from peacetime Eric Schmidt to Google founder and wartime CEO, Larry Page. Looking back however, was it really clear that Google was entering wartime? The business continued to focus on what it was clearly best at, online search advertising, and rarely faced any competition. The Company was late to invest in cloud technology and many have criticized Google for pushing billions of dollars into incredibly unprofitable ventures because they are Larry and Sergey’s pet projects. In addition, its clear that control had been an issue for Larry all along - in 2011, it came out that Eric Schmidt’s ouster as CEO was due to a disagreement with Larry and Sergey over continuing to operate in China. On top of that, its argued that Larry and Sergey, who have controlling votes in Google, stayed on too long and hindered Sundar Pichai’s ability to effectively operate the now restructured Alphabet holding company. In short, was Google in a wartime from 2011-2019? I would argue no, it operated in its core market with virtually no competition and today most Google’s revenues come from its ad products. I think the peacetime / wartime designation is rarely so black and white, which is why it is so hard to recognize what period a Company may be in today.

  3. Firing people. The unfortunate reality of business is that not every hire works out, and that eventually people will be fired. The Hard Thing About Hard Things is all about making difficult decisions. It lays out a framework for thinking about and executing layoffs, which is something that’s rarely discussed in the startup ecosystem until it happens. Companies mess up layoffs all the time, just look at Bird who recently laid off staff via an impersonal Zoom call. Horowitz lays out a roughly six step process for enacting layoffs and gives the hard truths about executing the 400 person layoff at LoudCloud. Two of these steps stand out because they have been frequently violated at startups: Don’t Delay and Train Your Managers. Often times, the decision to fire someone can be a months long process, continually drawn out and interrupted by different excuses. Horowitz encourages CEOs to move thoughtfully and quickly to stem leaks of potential layoffs and to not let poor performers continue to hurt the organization. The book discusses the Law of Crappy People - any level of any organization will eventually converge to the worst person on that level; benchmarked against the crappiest person at the next level. Once a CEO has made her mind up about the decision to fire someone, she should go for it. As part of executing layoffs, CEOs should train their managers, and the managers should execute the layoffs. This gives employees the opportunity to seek direct feedback about what went well and what went poorly. This aspect of the book is incredibly important for all levels of entrepreneurs and provides a great starting place for CEOs.

Dig Deeper

  • Most drastic company pivots that worked out

  • Initial thoughts on the Opsware - HP Deal from 2007

  • A thorough history of HP’s ventures, spin-offs and acquisitions

  • Ben’s original blog post detailing the pivot from service provider to tech company

  • The First (1995-01) and Second Browser War (2004 - 2017)

tags: Apple, IBM, VC, Google, HP, Packard's Law, Amazon, Android, Internet History, Marc Andreessen, Andreessen Horowitz, Loudcloud, Opsware, BMC Software, Mark Hurd, Javascript, Shopify, Slack, Netflix, Compaq, DEC, Micro Focus, DXC Technology, Carly Firoina, Leo Apotheker, Meg Whitman, WeWork, Casper, Larry Page, Eric Schmidt, Sundar Pichai, batch2
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
 

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

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  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

tags: IBM, Microsoft, Moore's Law, Apple, Alan Turing, OpenAI, Cloud Computing, Bell Labs, Intel, MIT, Ada Lovelace, batch2
categories: Non-Fiction
 

December 2019 - The Moon is a Harsh Mistress by Robert A. Heinlein

This futuristic, anti-establishment thriller is one of Elon Musk’s favorite books. While Heinlein’s novel can drag on with little action, The Moon is a Harsh Mistress presents an interesting war story and predicts several technological revolutions.

Tech Themes

  1. Mike, the self-aware computer and IBM. Mycroft Holmes, Heinlein’s self-aware, artificially intelligent computer is a friendly, funny and focused companion to Manny, Wyoh and Prof throughout the novel. Mike’s massive hardware construction is analogous to the way companies are viewing Artificial Intelligence today. Mike’s AI is more closely related to Artificial General Intelligence, which imagines a machine that can go beyond the standard Turing Test, with further abilities to plan, learn, communicate in natural language and act on objects. The 1960s were filled with predictions of futuristic robots and machines. Ideas were popularized not only in books like The Moon is a Harsh Mistress but also in films like 2001: A Space Odyssey, where the intelligent computer, HAL 9000, attempts to overthrow the crew. In 1965, Herbert Simon, a noble prize winner, exclaimed: “machines will be capable, within twenty years, of doing any work a man can do.” As surprising as it may seem today, the dominant technology company of the 1960’s was IBM, known for its System/360 model. Heinlein even mentions Thomas Watson and IBM at Mike’s introduction: “Mike was not official name; I had nicknamed him for Mycroft Holmes, in a story written by Dr. Watson before he founded IBM. This story character would just sit and think--and that's what Mike did. Mike was a fair dinkum thinkum, sharpest computer you'll ever meet.” Mike’s construction is similar to that of present day IBM Watson, who’s computer was able to win Jeopardy, but has struggled to gain traction in the market. IBM and Heinlein approached the computer development in a similar way, Heinlein foresaw a massive computer with tons of hardware linked into it: “They kept hooking hardware into him--decision-action boxes to let him boss other computers, bank on bank of additional memories, more banks of associational neural nets, another tubful of twelve-digit random numbers, a greatly augmented temporary memory. Human brain has around ten-to-the tenth neurons. By third year Mike had better than one and a half times that number of neuristors.” This is the classic IBM approach – leverage all of the hardware possible and create a massive database of query-able information. This actually does work well for information retrieval like Jeopardy, but stumbles precariously on new information and lack of data, which is why IBM has struggled with Watson applications to date.

  2. Artificial General Intelligence. Mike is clearly equipped with artificial general intelligence (AGI); he has the ability to securely communicate in plain language, retrieve any of the world’s information, see via cameras and hear via microphones. As discussed above, Heinlein’s construction of Mike is clearly hardware focused, which makes sense considering the book was published in the sixties, before software was considered important. In contrast to the 1960s, today, AGI is primarily addressed from an algorithmic, software angle. One of the leading research institutions (excluding the massive tech companies) is OpenAI, an organization who’s mission is: “To ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity.” OpenAI was started by several people including Elon Musk and Sam Altman, founder of Y Combinator, a famous startup incubator based in Silicon Valley. OpenAI just raised $1 billion from Microsoft to pursue its artificial algorithms and is likely making the most progress when it comes to AGI. The organization has released numerous modules that allow developers to explore the wide-ranging capabilities of AI, from music creation, to color modulation. But software alone is not going to be enough to achieve full AGI. OpenAI has acknowledged that the largest machine learning training runs have been run on increasingly more hardware: “Of course, the use of massive compute sometimes just exposes the shortcomings of our current algorithms.” As we discussed before (companies are building their own hardware for this purpose, link to building their own hardware), and the degradation of Moore’s Law imposes a serious threat to achieving full Artificial General Intelligence.

  3. Deep Learning, Adam Selene, and Deep Fakes. Heinlein successfully predicted machine’s ability to create novel images. As the group plans to take the rebellion public, Mike is able to create a depiction of Adam Selene that can appear on television and be the face of the revolution: “We waited in silence. Then screen showed neutral gray with a hint of scan lines. Went black again, then a faint light filled middle and congealed into cloudy areas light and dark, ellipsoid. Not a face, but suggestion of face that one sees in cloud patterns covering Terra. It cleared a little and reminded me of pictures alleged to be ectoplasm. A ghost of a face. Suddenly firmed and we saw "Adam Selene." Was a still picture of a mature man. No background, just a face as if trimmed out of a print. Yet was, to me, "Adam Selene." Could not he anybody else.” Image generation and manipulation has long been a hot topic among AI researchers. The research frequently leverages a technique called Deep Learning, which is a play on classically used Artificial Neural Networks. A 2012 landmark paper from the University of Toronto student Ilya Sutskever, who went on to be a founder at OpenAI, applied deep learning to the problem of image classification with incredible success. Deep learning and computer vision have been inseparable ever since. One part of research focuses on a video focused image superimposition technique called Deep Fakes, which became popular earlier this year. As shown here, these videos are essentially merging existing images and footage with a changing facial structure, which is remarkable and scary at the same time. Deep fakes are gaining so much attention that even the government is focused on learning more about them. Heinlein was early to the game, imaging a computer could create a novel image. I can only imagine how he’d feel about Deep Fakes.

Business Themes

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  1. Video Conferencing. Manny and the rest of the members of the revolution communicate through encrypted phone conversations and video conferences. While this was certainly ahead of its time, video conferencing was first imagined in the late 1800s. Despite a clear demand for the technology, it took until the late 2000s arguably, to reach appoint where mass video communication was easily accessible for businesses (Zoom Video) and individuals (FaceTime, Skype, etc.) This industry has constantly evolved and there are platforms today that offer both secure chat and video such as Microsoft Teams and Cisco Webex. The entire industry is a lesson in execution. The idea was dreamed up so long ago, but it took hundreds of years and multiple product iterations to get to a de-facto standard in the market. Microsoft purchased Skype in 2011 for $8.5B, the same year that Eric Yuan founded Zoom. This wasn’t Microsoft’s first inroads into video either, in 2003, Microsoft bought Placeware and was supposed to overtake the market. But they didn’t and Webex continued to be a major industry player before getting acquired by Cisco. Over time Skype popularity has waned, and now, Microsoft Teams has a fully functioning video platform separate from Skype – something that Webex did years ago. Markets are constantly in a state of evolution, and its important to see what has worked well. Skype and Zoom both succeeded by appealing to free users, Skype initially focused on free consumers, and Zoom focused on free users within businesses. WebEx has always been enterprise focused but they had to be, because bandwidth costs were too high to support a video platform. Teams will go to market as a next-generation alternate/augmentation of Outlook; it will be interesting to see what happens going forward.

  2. Privacy and Secure Communication. As part of the revolution’s communication, a secure, isolated message system is created whereby not only are conversations fully encrypted and undetected by authorities but also individuals are unable to speak with more than two others in their revolution tree. Today, there are significant concerns about secure communication – people want it, but they also do not. Facebook has declared that they will implement end to end encryption despite warnings from the government not to do so. Other mobile applications like Telegram and Signal promote secure messaging and are frequently used by reporters for anonymous tips. While encryption is beneficial for those messaging, it does raise concerns about who has access to what information. Should a company have access to secure messages? Should the government have access to secure messages? Apple has always stayed strong in its privacy declaration, but has had its own missteps. This is a difficult question and the solution must be well thought out, taking into account unintended consequences of sweeping regulation in any direction.

  3. Conglomerates. LuNoHo Co is the conglomerate that the revolution utilized to build a massive catapult and embezzle funds. While Mike’s microtransaction financial fraud is interesting (“But bear in mind that an auditor must assume that machines are honest.”), the design of LuNoHo Co. which is described as part bank, part engineering firm, and part oil and gas exploitation firm, interestingly addresses the conventional business wisdom of the times. In the 1960s, coming out of World War II, conglomerates began to really take hold across many developing nations. The 1960s were a period of low interest rates, which allowed firms to perform leveraged buyouts of other companies (using low interest loans), sometimes in a completely unrelated set of industries. Activision was once part of Vivendi, a former waste management, energy, construction, water and property conglomerate. The rationale for these moves was often that a much bigger organization could centralize general costs like accounting, finance, legal and other costs that touched every aspect of the business. However, when interest rates rose in the late 70s and early 80s, several conglomerate profits fell, and the synergies promised at the outset of the deal turned out to be more difficult to realize than initially assumed. Conglomerates are incredibly popular in Asia, often times supported by the government. In 2013, McKinsey estimated: “Over the past decade, conglomerates in South Korea accounted for about 80 percent of the largest 50 companies by revenues. In India, the figure is a whopping 90 percent. Meanwhile, China’s conglomerates (excluding state-owned enterprises) represented about 40 percent of its largest 50 companies in 2010, up from less than 20 percent a decade before.” Softbank, the famous Japanese conglomerate and creator of the vision fund, was originally a shrink-wrap software distributor but now is part VC and part Telecommunications provider. We’ve discussed the current state of Chinese internet conglomerates, Alibaba and Tencent who each own several different business lines. Over the coming years, as internet access in Asia grows more pervasive and the potential for economic downturn increases, it will be interesting to see if these conglomerates break apart and focus on their core businesses.

Dig Deeper

  • The rise and fall of Toshiba

  • Using Artificial Intelligence to Create Talking Images

  • MIT Lecture on Image Classification via Deep Learning

  • 2019 Trends in the Video Conferencing Industry

  • The Moon is a Harsh Mistress may be a movie

tags: Facebook, IBM, Zoom, Artificial Intelligence, AI, AGI, Watson, OpenAI, Y Combinator, Microsoft, Moore's Law, Deep Fakes, Deep Learning, Elon Musk, Skype, WebEx, Cisco, Apple, Activision, Conglomerate, Softbank, Alibaba, Tencent, Vision Fund, China, Asia, batch2
categories: Fiction
 

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

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  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

tags: Investing, Yahoo, Cloud Computing, Google, Facebook, Sheryl Sandberg, Susan Wojcicki, Marissa Mayer, IBM, Trilogy Software, Paypal, Peter Thiel, Keith Rabois, Zero to One, Silver Lake, Sergey Brin, Larry Page, YouTube, AdWords, AdSense, Atari, Nolan Bushnell, Steve Jobs, WeWork, Uber, Zenefits, Slack, Flickr, Stewart Butterfield, batch2
categories: Non-Fiction
 

September 2019 - Ready Player One by Ernest Cline

Ernest Cline’s magical world of virtual reality is explores a potential new medium of communication through an excellent heroic tale.

Tech Themes

1. Wide-ranging applicability and use cases of Virtual Reality. Although the novel was written in 2011, Ernest Cline does an incredible job of detailing the complex and numerous use cases of VR throughout the novel. Cline’s 18 year old main character Wade Watts attends school via VR, where you can have a limitless number of students all learn from the same teacher. Beyond that, different worlds and galaxies are easily conjured up with different themes, time periods and technology taking learning and experience to another level: Wade spends time playing old video games in an effort to unlock certain clues about James Halliday, Wade re-enacts all of Matthew Broderick’s part in the movie War Games in an effort to unlock one of the keys, Aech and Wade frequently hang out in the Basement, a re-created 1980’s recreational room with vintage magazines and game consoles. All of these distinct use cases – education, gaming, social networking, and entertainment – are the promise of Virtual Reality. There is a long way to go before that promise is met.

2. The intersection of the online/offline world. As James Halliday writes in Anorak’s Almanac: “Going outside is highly overrated.” Ready Player One does a great job of exploring the conflation of the online and offline worlds. The book weaves together experiences from this intersection into critical moments of the book including Wade’s escape from the Stacks and his imprisonment by IOI. While there is a tangible feeling that online is the much preferred experience for all the reasons discussed above, it’s the offline in-person events that truly shape the heroic ending of the book. This serves as a reminder that the OASIS is very much a virtual reality and explores the need for in-person human connection. Ironically, this is something Halliday sorely missed out on as shown through his unrequited love for Ogden Morrow’s (co-creator of the OASIS) wife, Kira. As big companies move into our homes through Google Homepods, Amazon Echos, Facebook Portals, the human connection element needs to be maintained.

3. The ability to disguise your identity online. “In the OASIS, you could become whomever and whatever you wanted to be, without ever revealing your true identity, because your anonymity was guaranteed.” This quote about the OASIS is largely true of today’s Internet. Through private browsing, Virtual Private Networks, avoiding Google and ad-tagging websites, people are able to stay anonymous online already. But what the OASIS does in addition, is allow you to modify not only your back-story, but also how you appear to others, something that is very important in VR. While there is no question that Wade, Art3mis and Aech are able to avoid insecurities by masking their identities, eventually those insecurities are revealed, albeit with little consequence. Given the myriad of leaks and breaches in the last few years (Yahoo, Facebook, DoorDash, etc.), as the VR ecosystem continues to grow, increasing amounts of privacy will be needed to maintain anonymity.

Business themes

1. What is the dominant revenue model in VR? The evil villains at Innovative Online Industries (IOI) and their army of sixers have tried several hostile takeover attempts to acquire Halliday’s Gregarious Simulations Systems in order to convert it to a paid user model. IOI is the world’s largest internet service provider and just like other three letter named tech behemoths (cough, IBM, cough), fits the classic evil corporation vibe. Dismissing the potential business and technology conflicts (the world’s largest ISP is probably critical in delivering the OASIS throughout the world), its interesting to theorize what the dominant revenue model of VR may be. Facebook recently launched its VR world to complement its Oculus devices and there have been varied attempts to launch similar software worlds like Rec Room. The big discovery Google made early on was that advertising would be the business model of the web. Facebook copied this as it created social networking and as devices transitioned from desktop to mobile, and image to video, advertising continued to be the dominant mode of content monetization. Is there any reason to think VR will be any different? Potentially. The current dominant model for video gaming is subscriber based, freemium (paying for enhanced abilities, character changes, etc.) or single purchase. While there is no reason these ideas can’t be combined with advertising, the idea of a multi-world VR landscape may reduce some of the targeted ROI you receive from very specific ad-targeting on Instagram and Google today. In a limitless world, advertising to specific people will be difficult. Beyond that, porting the mish-mash of complex technologies used in today’s advertising landscape would add even more challenge.

2. The BIG, evil tech corporation. IOI is the quintessential evil technology company. As the world’s largest ISP, IOI could be a reference to Comcast, which is the United States’ largest ISP and often referenced as one of the most hated companies. Comcast, like other ISPs is always facing the challenge of serving millions of subscribers but unlike other companies, they are monopolistic in certain areas where they are the only viable provider for internet, allowing them to raise prices and treat customers poorly. The big, evil technology corporation cliché has been around for a long time and today’s largest tech companies have all spent sometime being that cliché. This dynamic can arise for many reasons. At Amazon, it’s the continued alienation of open source communities, the anti-competitive behavior around its search algorithm and the smothering of small vendors on its marketplace. Facebook and Google have both faced privacy concerns. Google has been sued for manipulating search on mobile devices. Microsoft was sued for anti-trust issues over browsers. As startups begin to dominate their core businesses, unless they continue innovating, they begin acting defensively to maintain their leading position. Facebook feature copied Snapchat stories almost immediately after they came out. IBM had a book written on them in the 1980s claiming they were anticompetitive. There is a reason corporate communications (WeWork lol) are so important and maintaining the image of a positive change for good. Every major technology company has spent time as the evil one, some have just spent more time than others.

3. Difficulty in creating VR applications. Ready Player One stoked a lot interest in the promise of VR, but the actual implementation is incredibly difficult with the hardware and software we have available as tools today. Moore’s law is slowing and some computer scientists have suggested specific chips to address the demands of newer technologies like Artificial Intelligence, Virtual Reality and Deep Learning. After Facebook acquired Oculus in 2014 for $2.4B, funding continued to flow into VR startups. Magic Leap, the highly secretive and most heavily funded VR startup has raised $2.3B on its own, and after years of development finally released its hardware for over $2,000 per device and its unclear if it makes a profit on any sales yet. More recently, several VR companies have gone bankrupt and laid off employees as product development didn’t reach application or end users before the funding ran out. While the software and hardware continues to improve, a lot still needs to be figured out before VR becomes mainstream.

Dig Deeper

  • VR Garden in Montreal

  • Oculus co-founder Palmer Lucky’s review of Magic Leap

  • Augmented Reality and Virtual Reality in Healthcare

  • Deep dive into the secretive Magic Leap

  • The real world easter egg hunt from Ready Player One

tags: Ernest Cline, VR, AR, Video Games, IBM, Facebook, Snap, Google, Amazon, Apple, War Games, VPN, DoorDash, Yahoo, Rec Room, Magic Leap, Oculus, Deep Learning, batch2
categories: Fiction
 

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