Sunday, October 21, 2018

D’Aveni, The Pan-Industrial Revolution

Richard D’Aveni, a professor at Dartmouth’s Tuck School of Business, has set forth a bold hypothesis. As 3-D printing or, more generally, additive manufacturing (AM) becomes increasingly sophisticated, manufacturing will be transformed and pan-industrial companies will come to dominate the world economy. At the moment, although investors certainly haven’t bought into this story, among the leading contenders for dominance are Jabil, GE, Siemens, and United Technologies.

In The Pan-Industrial Revolution: How New Manufacturing Titans Will Transform the World (Houghton Mifflin Harcourt, 2018) D’Aveni argues that, contrary to the popular myth, “the future of additive manufacturing does not lie in a world of ‘makers’—hobbylike small-scale craftspeople producing a few items at a time in little workshops scattered all over the world.” Instead, “the logic of the pan-industrial revolution—and the power of the virtuous cycle of growth that it will set in motion—will make the drive toward bigness practically irresistible.”

Pan-industrial firms are distinguished by their ability to “use industrial platforms to build flexible supply chains and powerful business ecosystems, enabling greater product diversification than practiced by any corporation of today.” In contrast to traditional manufacturing, which puts efficiency first, platform-managed AM puts agility first. Among the characteristics of platform-managed AM are: (1) products are built all at once, eliminating assembly and permitting internal complexity, (2) flexible equipment and workers are used to make a broad range of products at an affordable cost, (3)shallow learning curves facilitated by software, AI, and machine learning make innovation and entry to new markets relatively easy, and (4) short supply chains move production close to customers and minimize costs of transportation, warehousing, and inventory control.

AM has already made great strides in industries as diverse as medical devices, fashion, construction, and food. For instance, Dubai has partnered with the Chinese company Winsun to 3D print offices and homes, with a goal of having 30 percent of the city 3D printed by 2030.

Even though the future is unlikely to play out exactly as D’Aveni foresees it, he makes a strong case for an exciting new industrial revolution, the initial stages of which we are already beginning to see.

Wednesday, October 17, 2018

Siilasmaa, Transforming Nokia

Risto Siilasmaa, the chairman of Nokia, has written a real-life business thriller, one that he lived through and, along with Nokia, survived. Transforming Nokia: The Power of Paranoid Optimism to Lead Through Colossal Change (McGraw-Hill, 2018) takes the reader from the height of Nokia’s success in the global smartphone market in 2008, when it had a more than 50 percent share, to the company’s near bankruptcy in 2012, to the sale of its iconic smartphone business to Microsoft, up to today, where it is a top player in wireless infrastructure.

Siilasmaa had founded and served as CEO of F-Secure for 18 years before, at the age of 42, he was tapped to join the Nokia board of directors in 2008, a year after Apple introduced the iPhone. The timing couldn’t have been worse. Although Nokia tried to respond to the onslaught of competition in the smartphone market, it was plagued by technological, leadership, and cultural issues. It brought on a new CEO, an American from Microsoft, in the fall of 2010, who launched Project Sea Eagle, “a sweeping internal review of Nokia’s capabilities and competitiveness.” As a result of this review, Nokia decided to partner with Microsoft on the Windows Phone. In response to this decision, a Google senior vice president tweeted, “Two turkeys do not make an eagle.” Unfortunately for Nokia, he was right.

It was under this grim set of circumstances that, in May of 2012, Siilasmaa became chairman of Nokia. In the second part of his book he describes how he transformed the company. He attributes this in large measure to being a paranoid optimist, one who combines “vigilance and a healthy dose of realistic fear with a positive, forward-looking outlook.” In practice, he writes, “paranoid optimism calls upon leaders to explore a full spectrum of scenarios: the best case, the worst case, and the options in between. By imagining the unthinkable, you won’t be surprised and can generate strategies that will help you avoid it. As a result, you can radiate an unwavering certainty of eventual victory because you have already imagined the worst that could happen and have constructed a response.”

And many unthinkables did happen along the way. The negotiations with Microsoft to sell Nokia’s “crown jewels” were fraught with unexpected hurdles. Siemens wanted to get rid of its share of Nokia Siemens Networks, which over the course of six years had posted a cumulative operating loss in the billions. Could Nokia buy Siemens out even though it didn’t have the funds? Was it wise to do so? What should the company do with its digital map business, HERE, and its patent portfolio? Should NSN merge with Alcatel-Lucent—and in three weeks, as the executive chairman of NSN suggested? (The unrealistic time frame was scrapped.) “Merging with Alcatel-Lucent would increase NSN’s market share in the global wireless infrastructure market from 18 percent to more than 30 percent, leapfrogging over Huawei and closing in on market leader Ericsson.”

Nokia today is indeed “a company reborn.” “Out of some 100,000 employees, fewer than 1 percent held a Nokia badge in 2012.” The route to its rebirth makes for fascinating reading.

Sunday, October 14, 2018

Iqbal, Volatility

Adam S. Iqbal is the global head of FX Exotics and Correlation at Goldman Sachs and was formerly an FX options trader and portfolio manager at Barclays and Pimco. He holds a Ph.D. in financial mathematics and financial economics.

In Volatility: Practical Options Theory (Wiley, 2018) Iqbal sets himself the goal of providing “an intuitive, as well as technical, understanding of both the basic and advanced ideas in options theory, with the aim of encouraging translational work from theory into practical application by market makers, portfolio managers, investment managers, risk managers, traders, and other market practitioners.” Only peripherally is he writing for the retail options trader with a mathematical bent. He draws his examples from the FX market.

The ability to delta hedge, Iqbal explains, means that “options are fundamentally not bets on direction, but are bets on volatility.” Moreover, the spot FX rate is a martingale, so it exhibits no mean reversion or autocorrelation. Price-based predictability therefore has no place in probability distributions used to model FX rates for the purpose of option pricing.

What matters, and what professionals who use and price options should understand before they embark on building models or, under time constraints, in lieu of relying on models, are the major principles underlying options—first- and second-order greeks as well as implied volatility and term structure (along with smile and skewness). Only after all of these concepts are described in detail does Iqbal introduce the Black-Scholes-Merton model.

Iqbal provides examples of how the trader might make decisions without invoking a full-fledged mathematical model. In the case of a risk reversal, for instance, “one way that traders use to circumvent disagreements over volatility references is to trade a contract known as a risk reversal by smile vega. The idea here is that, since the seller of the risk reversal believes in lower volatility references, if she agrees to trade at the higher volatility references, she can sell a higher notional of the put than she purchases of the call.”

Or take the case in which a normal distribution is priced into options but market participants begin to realize that the actual distribution is leptokurtic, with a higher peak and fatter tales. The peak “means that spot is more likely to remain in the center of the distribution than is currently priced. This means that they sell ATM straddles to profit from the additional probability that we observe only very small moves. Second, they realize that spot is also more likely to exhibit a very large positive or negative return than is priced. They therefore look to purchase OTM strangles. That is, market participants buy the butterfly. … [T]he more kurtosis there is in the spot PDF, the higher the fair price should be for the butterfly.”

Wednesday, October 10, 2018

Hoffman & Yeh, Blitzscaling

In my wildest fantasies I never envisage creating the next Amazon or Facebook. But I’m intrigued by the people who set out to do just that, who they are and how they do it. Blitzscaling: The Lightning-Fast Path to Building Multibillion-Dollar Scaleups by Reid Hoffman and Chris Yeh (Currency / Crown, 2018) addresses the second question. And the answer is not for the faint of heart.

Blitzscaling is “prioritizing speed over efficiency in the face of uncertainty.” It can be compared to three other forms of rapid growth: classic start-up growth, classic scale-up growth, and fastscaling. Start-up growth prioritizes efficiency in the face of uncertainty (e.g., does your product satisfy a strong market demand?). Scale-up growth focuses on growing efficiently once the company has some certainty about the environment. Fastscaling, where you sacrifice efficiency for the sake of increasing growth, takes place in an environment of certainty and “is a good strategy for gaining market share or trying to achieve revenue milestones.”

And then there’s blitzscaling, which “combines the gut-wrenching uncertainty of start-up growth with the potential for a much bigger, more embarrassing, more consequential failure.” It’s hard to raise capital to blitzscale and, “to make matters worse, you usually need more money to blitzscale than to fastscale, because you have to keep enough capital in reserve to recover from the many mistakes you’re likely to make along the way.”

Blitzscaling is most applicable to high tech, but its techniques can benefit a range of industries. Two examples are the Spanish clothing retailer Zara and the shale oil company Chesapeake Energy.

This book grew out of a course that authors Reid Hoffman, the founder of LinkedIn and currently a partner at the venture capital firm Greylock Partners, and Chris Yeh, a writer and entrepreneur, co-taught at Stanford in the fall of 2015. Perhaps because of this, the authors not only explain the many intricacies and manifestations of blitzscaling but also address how to blitzscale responsibly and build companies that improve society.

Blitzscaling is about as fast-paced a book as its subject matter. It is packed with sophisticated business advice and useful examples of success and failure. Entrepreneurs and would-be entrepreneurs as well as investors in break-through companies will learn a tremendous amount from reading it. They may even decide to take up the book’s final challenge: “Race you to the future.”

Sunday, October 7, 2018

Tulchinsky, The UnRules

In some ways Igor Tulchinsky has written an “un-book,” and it’s undoubtedly the better for it. The UnRules: Man, Machines and the Quest to Master Markets (Wiley, 2018) is a short book, coming in at about 150 pages. As Tulchinsky explains in the preface, he is a man of few words. As it is, even to get to 150 pages, he blends memoir, the history of finance and mathematics, sometimes arcane examples, and quantitative analysis. But the result is a captivating personal account of what it takes for an immigrant to succeed in the world of quantitative finance and how data analytics are changing our future, and not only our financial future.

Tulchinsky is the founder, chairman, and CEO of WorldQuant, a global quantitative investment management firm. He is also the founder of WorldQuant Foundation and WorldQuant University, which offers a tuition-free two-year online master’s degree program in financial engineering and a free eight-week module on data science.

The UnRule, which Tulchinsky admits is loosely related to the liar’s paradox (loosely because it is an empirical rule), is that “All theories and all methods have flaws. Nothing can be proved with absolute certainty, but anything may be disproved, and nothing that can be articulated can be perfect.”

This UnRule informs his investing philosophy: create many competing points of view or, more precisely formulated in the case of his investment firm, alphas. In ten years WorldQuant went from 19 alphas to 10 million! “Today a typical portfolio may contain tens of thousands of alphas; the largest may contain 100,000. To our portfolio strategists, individual alphas, which may have vectors of hundreds or thousands of securities, remain black boxes. The algorithms, logic, and intellectual property remain with the researchers; the strategists know individual alphas only as mathematical expressions of a market signal. … [A] portfolio is all math.”

Readers who are looking for the mathematical secret sauce will be disappointed. But those in search of the qualities necessary for a person to thrive in today’s financial markets will be richly rewarded.

Wednesday, October 3, 2018

Belsky, The Messy Middle

We’ve all been there. We start a project with great enthusiasm. Then, as we proceed, the goal seems farther and farther away. We have self-doubts, we are mired in the mundane, we are on a roller coaster of successes and failures. The journey to make something great is definitely not linear.

In The Messy Middle: Finding your way through the hardest and most crucial part of any bold venture (Portfolio/Penguin, 2018) Scott Belsky, an entrepreneur and venture investor who is now chief product officer at Adobe, explores the ups and downs between a project launch and its (sometimes) successful conclusion.

“The middle,” he writes, “makes and breaks you, and ending up on the right side of this line depends on how you manage everything in between. It requires immense perseverance, self-awareness, craftsmanship, and strategy. It also requires luck, harvested whenever you encounter it.”



Belsky draws on his experience with Behance, his first company, which he founded in 2006 and sold to Adobe in 2012. He gives advice in two- or three-page bites. Among his words of wisdom: attempt a new perspective of it before you quit it; just stay alive long enough to become an expert; moving fast is great, so long as you slow down at every turn; too much scrutiny creates flaws; data is only as good as its source, and doesn’t replace intuition; the science of business is scaling, the art of business is the things that don’t.

There’s a lot of sound advice in this book. And since it’s laid out like a huge smorgasbord, you can read it that way as well, picking and choosing your way through it. And you can go back for seconds when you’re at a different stage of your endeavor.

Sunday, September 30, 2018

Marks, Mastering the Market Cycle

Howard Marks, cochairman and cofounder of Oaktree Capital Management and author of The Most Important Thing, expands on one of his twenty “most important things” in Mastering the Market Cycle: Getting the Odds on Your Side (Houghton Mifflin Harcourt, 2018). Marks paints in broad strokes, so the reader will not come away from this book with any concrete trade ideas. But, after reading Marks’s analysis, he should better understand how to sync his portfolio with the ebb and flow of the market, so as not to buy at the top and sell at the bottom, even though “the tendency of people to go to excess will never end.”

Marks discusses multiple cycles that feed into the market cycle: the economic cycle, the cycle in profits, the pendulum of investor psychology, the cycle in attitudes toward risk, the credit cycle, the distressed debt cycle, and the real estate cycle. He also looks at the cycle in success. Of these, the one he considers most important is the risk cycle. So let me summarize some of his points on this front.

It is often set forth as a truism that, since there seems to be a positive relationship between risk and return (the ubiquitous upper-sloping line), “riskier assets produce higher returns” and hence “if you want to make more money, the answer is to take more risk.” This formulation, Marks explains, “cannot be true, since if riskier assets could be counted on to produce higher returns, they by definition wouldn’t be riskier.”

In general, of course, the capital market line, or risk/return continuum, makes sense if viewed in terms of rational expectations. We expect to make a higher return on investments in small cap stocks than on investments in money market funds, and the former is perceived to be proportionally riskier than the latter. On this continuum “there won’t be particular points … where risk-bearing is rewarded much more or much less than at others (that is, investments whose promised risk-adjusted return is obviously superior to the rest).”

But fluctuations in attitudes toward risk can upset this continuum. As investors become increasingly optimistic, even euphoric, they are willing to settle for skimpy risk premiums on risky investments. “This reduced insistence on adequate risk premiums causes the slope of the capital market line to flatten.” And so, Marks writes, “risk is high when investors feel risk is low. And risk compensation is at a minimum just when risk is at a maximum.” At the other end of the spectrum, when markets sell off, investors become excessively risk averse, and the slope of the capital market line increases, offering “an exaggerated payoff for risk-bearing. Thus the reward for bearing incremental risk is greatest at just the moment when—no, rather, just because—people absolutely refuse to bear it.”

When should investors begin to buy as the market is cascading downward? Marks strongly rejects the idea of waiting for the bottom. First, there’s no way to know, except in hindsight, when the bottom has been reached. “And second, it’s usually during market slides that you can buy the largest quantities of the thing you want, from sellers who are throwing in the towel and while the non-knife-catchers are hugging the sidelines. But once the slide has culminated in a bottom, by definition there are few sellers left to sell, and during the ensuing rally it’s buyers who predominate.” So, to repeat, when should investors start to buy? For Marks, the answer’s simple: buy when price is below intrinsic value. And if price continues downward, buy more. “All you need for ultimate success in this regard is (a) an estimate of intrinsic value, (b) the emotional fortitude to persevere, and (c) eventually to have your estimate of value proved correct.”

Wednesday, September 26, 2018

Knapp & Zeratsky, Make Time

Another day, another self-help book that takes time away from things I should really be doing. Call it a form of distraction. But, oops, this is precisely what Jake Knapp and John Zeratsky in Make Time: How to Focus on What Matters Every Day (Currency/Crown, 2018) try to steer us away from.

They offer a four-step process for “making time.” First, highlight—that is, decide what you want to make time for. “Each day, you’ll choose a single activity to prioritize and protect in your calendar.” It can be anything—finishing a presentation, cooking dinner, playing with your kids, or (yes) reading a book. It can be something that’s urgent and/or something that gives you satisfaction and/or joy. It should take between 60 and 90 minutes. Second, beat distraction. Third, energize. And fourth, reflect. Steps two through four should be pretty self-evident, but the authors explain them in sometimes seemingly controversial detail. For instance, “if you live a little more like a prehistoric human, we predict you’ll enhance your mental and physical energy.” This does not mean to go on a paleo diet but merely to move, eat real food, go off the grid, socialize, and get enough good sleep.

Many of the principles behind this book were inspired by the Google design sprints, created by one of the co-authors (Jake). A design sprint was “a workweek redesigned from the ground up. For five days, a team would cancel all meetings and focus on solving a single problem, following a specific checklist of activities.” In 2012 the authors started working together to run these sprints with startups in the Google Ventures portfolio. Over the next few years they ran more than 150.

From the design sprint laboratory the authors learned that something magical happens when you start the day with one high-priority goal. The five-day Google Ventures schedule was: Monday—the team creates a map of the problem, Tuesday—each person sketches one solution, Wednesday—the group decides which solutions are best, Thursday—they build a prototype, and Friday—they test it.

I think one can combine features of the design sprints with the much less imposing “make time” highlights to come up with reasonable ways to innovate and accomplish projects. If I succeed at my own design sprint, Make Time will not have been a distraction but an unwitting highlight.

Sunday, September 23, 2018

Agrawal et al., Prediction Machines

Prediction Machines: The Simple Economics of Artificial Intelligence (Harvard Business Review Press, 2018) by Ajay Agrawal, Joshua Gans, and Avi Goldfarb, all chaired professors at the University of Toronto’s Rotman School of Management, is an excellent introduction to the opportunities and limitations of AI. Their thesis is that, as things now stand, AI is becoming an ever cheaper community that lowers the cost of prediction and will change how businesses operate. But it cannot replace judgment, so human beings will not be sitting around as unproductive idlers.

One of the goals of enhanced prediction is to replace satisficing with more optimal solutions. For instance, airport lounges are “imperfect solutions to uncertainty” and “will be undermined by better prediction.” With traffic apps and apps tracking flight delays, the traveler has new options such as “unless there is a traffic problem, leave later and go directly to the gate” or “if there is flight delay, leave later.”

The authors explore various ways in which artificial intelligence enhances decision-making, especially in the business context, but in the end (at least so far) it cannot replace human beings. We have data that machines don’t, from our senses to data that we opt to keep private. Moreover, prediction machines are often stymied by rare events that are difficult to predict because of a lack of data, “including presidential elections and earthquakes.” (Not that human beings and their statistical models did such a great job with the last presidential election.)

The authors speculate about which countries might have an advantage in developing AI. So far the United States is the world leader in terms of both research and commercial application. But “the trend lines are changing.” The future of AI may be “made in China,” as the New York Times suggested. First, China is spending billions on AI. Second, it has more people—and therefore more data (the new oil). Third, China doesn’t regulate privacy, so easy data access is another advantage. And, I would add, a trade war focused on twentieth-century manufacturing is unlikely to derail China’s efforts to gain an advantage in the twenty-first century.

Wednesday, September 12, 2018

McLean, Saudi America

Bethany McLean, the well-known financial journalist (she co-authored The Smartest Guys in the Room and All the Devils Are Here and wrote Shaky Ground), has turned her attention to shale oil and gas in Saudi America: The Truth About Fracking and How It’s Changing the World (Columbia Global Reports, 2018). In this 140-page piece she doesn’t address environmental concerns about fracking. Instead, her focus is on assessing the “breathless predictions about America’s future as an oil and gas colossus,” which, she argues, “has more to do with Wall Street than with geopolitics or geology.”

Central to her story is “America’s most reckless billionaire,” as Forbes once described the late Aubrey McClendon, the founder of Chesapeake Energy. He was a “flag waver for natural gas” and fracking, arguing that, with fracking, gas production was no longer wildcatting but manufacturing. He went all in, creating a vast web of debt for Chesapeake as well as himself personally. As gas prices dropped, so did Chesapeake’s stock , but he remained a true believer and doubled down, announcing deal after deal. “But the economics weren’t working anywhere,” and McClendon found himself in financial and legal hell. At the age of 56 he was killed when his car collided with a concrete wall at high speed. The state medical examiner ruled his death an accident.

As the economy has rebounded after the great recession, so has fracking, thanks in large measure to technology. Production at the Permian Basin increased from just shy of one million barrels of oil a day in 2010 to over 2.5 million barrels a day in 2017. The International Energy Agency predicts that, within a few years, output will be more than four million barrels a day. And the break-even cost has plunged from around $70 in 2008 to less than $50 today, some saying as low as $25, or even $15. But these break-even figures do not take into account the cyclical nature of service costs. As the price of oil rises and demand for services (such as renting rigs, hiring crews, purchasing sand) increases, so do the costs. One analysis claims that almost half of the reduction in break-even costs was due to a temporary plunge in service costs.

Wall Street has been supporting the comeback of shale, to the tune of about $70 billion in capital in 2015 and $60 billion in debt in 2017. “Wall Street’s willingness to fund money-losing shale operators is, in turn, a reflection of ultra-low interest rates.” Because, despite higher oil prices, most shale operators are still losing money; in the first quarter of 2018 only five companies generated more cash than they spent.

What is the future of the shale revolution? It’s hard to say. Shale wells deplete, global alliances shift, renewables are becoming less expensive. The administration’s push to allow drilling in previously prohibited areas might create an oversupply and crater prices. “If this comes about at a time of rising interest rates and the end of the era of cheap capital, we may soon begin talking about how the Trump Administration killed the shale revolution.” Or not. Basically, we don’t have a clue about what’s coming next.

Sunday, September 9, 2018

Zeng, Smart Business

Ming Zeng’s Smart Business: What Alibaba’s Success Reveals about the Future of Strategy (Harvard Business Review Press, 2018) is a thought-provoking book. Written by the chief strategy officer at the Alibaba Group, it challenges traditional business models and offers an alternative based on data intelligence and network coordination.

As with all books about China, I’m always stunned by the magnitude of the numbers. For instance, on Single’s Day on November 11, 2017, Alibaba processed 1.5 billion transactions, totaling about $25 billion. At its peak during that day, Alibaba’s technology platforms processed 325,000 orders and 256,000 payments every second. By comparison, Visa’s stated capacity at about that time was 65,000 payments per second globally.

Zeng dispels the common notion that Alibaba is the Amazon of China. “Unlike Amazon, Alibaba is not even a retailer in the traditional sense—we don’t source or keep stock, and logistics services are carried out by third-party service providers. Instead, Alibaba is what you get if you take every function associated with retail and coordinate them online into a sprawling, data-driven network of sellers, marketers, service providers, logistics companies, and manufacturers. … Alibaba’s mandate is to apply cutting-edge technologies—from machine learning to the mobile internet and cloud computing—to revolutionize how business is done.”

The business model that Zeng describes stands in sharp contrast to that of traditional business. It’s a C2B model that demands constant innovation. And a lot of work for all of its participants. But, as the title says, it’s “smart,” and the rewards are sometimes staggering.


As I pondered Zeng’s thesis, a couple of obvious questions came to mind. First, is this a model that, with modifications, can extend beyond the digital retail space? Second, is it essentially a monopolistic framework? My best guesses: yes, and probably. And so, I believe that everyone who wants to make a mark in the business world should read Zeng’s book. They might want government regulators to skip it.

Thursday, September 6, 2018

Hennessy, Leading Matters

John Hennessy, a computer scientist and one of the founders of MIPS Computer Systems, whom Marc Andreessen called “the godfather of Silicon Valley,” was president of Stanford University from 2000 to 2016. He is now, in his “retirement,” chairman of Alphabet, Google’s parent company, and director of the Knight-Hennessy Scholars Program. So when Hennessy reflects on his professional life, as he does in Leading Matters: Lessons from My Journey (Stanford University Press, 2018), people who are either already in or aspire to leadership roles would do well to pay attention.

Though an engineer, Hennessy looks at leadership through a “soft” lens. In fact, he writes that “as you climb to higher leadership positions, the role of facts and data decreases. Sure, facts form a set of boundaries that you must account for, but your task is to find solutions to complex problems, despite limitations imposed by facts and figures. … [Y]ou must develop your ability to bring people together, to inspire them, to mentor them, and to lead them into the direction of your vision.”

For him, what matters are humility, authenticity and trust, leadership as service, empathy, courage, collaboration and teamwork, innovation, intellectual curiosity, and storytelling. He describes, chapter by chapter, how he honed these character traits and skills through the many challenges he faced as the top academic administrator at a world-class university.

The book has a wonderful coda of books Hennessy has learned from: biographies of leaders and innovators, books on history, science, and leadership, and fiction.

Wednesday, September 5, 2018

Kocienda, Creative Selection

Ken Kocienda was the principal engineer of iPhone software at Apple, so he writes with authority in Creative Selection: Inside Apple’s Design Process During the Golden Age of Steve Jobs (St. Martin’s Press, 2018). I should say up front that I have never owned an Apple product and that I got my first smart phone only last year. I’m not normally a slow adopter, but I simply never felt the need for a mobile phone since (1) I’m rarely mobile and (2) I almost never use a phone of any sort. And so, that I found Kocienda’s book fascinating is a real tribute.

Kocienda had the unenviable job of creating a touchscreen keyboard for what became the iPhone. The BlackBerry, first released in 1999, had a physical keyboard with little chiclet keys beneath the screen, but this of necessity reduced the phone’s screen size. Apple was determined to have a software keyboard, where “plastic keys would give way to pixels.” But early efforts didn’t go well. Thumb-typing produced nothing intelligible, “not just wrong words but babble.” Engineers tried having bigger keys, “ganging up multiple letters on each key as they did on flip phone keypads and developing various means to choose the correct letters: sliding, double taps, long presses, and others.” But the user had to think about every letter, and even Apple engineers often got lost in the middle of typing a word.

Kocienda took another stab at this problem, using a big-key QWERTY keyboard with multiple letters per key “but that offloaded the decision of picking the letters to the computer.” This, of course, required the creation of a huge dictionary. But it didn’t do the job. It failed in ways both humorous and frustrating. And so, smaller, single-letter keys were reintroduced. With the assistance of touchscreen keyboard autocorrection (and a great deal more work on Kocienda’s part), “junky key presses produced perfect typing,” well, at least some of the time. Kocienda has an amusing article in Wired, published to coincide with his book’s publication date, “I Invented the iPhone’s Autocorrect. Sorry about That, and You’re Welcome.”

Although Kocienda structures his book in terms of seven elements of innovation (inspiration, collaboration, craft, diligence, decisiveness, taste, and empathy), what makes it a good read is nothing abstract. It’s his account of the actual process of creating a winning product.

Sunday, August 19, 2018

Faber, The Best Investment Writing, vol. 2

If you didn’t read the first volume of Meb Faber’s The Best Investment Writing (and you should have and of course still can), you’re got another crack at learning from a lot of smart folks who collectively manage hundreds of billions of dollars. The second volume of The Best Investment Writing (Harriman House, 2018) includes more than 40 articles, and, since the book runs about 350 pages, the articles are bite-sized. Most of them originally appeared online and were geared to a semi-distracted readership, which increasingly describes all of us.

The articles are organized under four headings: market conditions, risk and returns; investment portfolios, strategies and edges; pricing and valuation; and personal finance, behavioral biases and beyond.

Here I’ll recap two articles that appealed to me and that lent themselves to summary. The second criterion ruled out many excellent contributions. For instance, trying to summarize Barry Ritholtz’s “An Expert’s Guide to Calling a Market Top: The landscape is filled with pundits predicting the demise of the bull market. Here’s how to get in on the action” would be like trying to summarize a Letterman top-10 list. The task would simply produce a pale imitation of the original.

And so, to the two articles I chose. First, “10,000 Hours or 10 Minutes: What Does It Take to Be a ‘World-Class’ Investor?” by Charlie Bilello, originally published on the website of Pension Partners. From the title you can surmise that Bilello will debunk the applicability of the 10,000-hours rule to trading/investing. He argues that luck trumps skill in investment outcomes and that, in looking at the successes of the market wizards of years past, we can’t determine with certainty whether their performance was the result of skill or luck. More important, “even if we concluded that there was some skill involved, doing x, y, and z because a ‘market wizard’ did x, y, and z in the past is a guarantee of nothing. …the environment they operated in no longer exists. … If the wizards themselves were faced with the task of repeating their prior successes, they too would fail—Warren Buffett would not be the next Warren Buffett if he had to start over again today. Paul Tudor Jones would not be the next Paul Tudor Jones. Stanley Druckenmiller would not be the next Stanley Druckenmiller.” The average investor should simply spend ten minutes learning about controlling costs, diversification, and asset allocation. “In a field where the outcome is driven more by luck than by skill, being a master of nothing (diversifying and protecting yourself from the unknowable future) yields the highest probability of success.”

Second, Samuel Lee’s “Waiting for the Market to Crash Is a Terrible Strategy.” We hear over and over that we should be fearful when others are greedy and greedy when others are fearful. But is this really so? Lee shows that putting cash to work in the market only after a crash has been “an abysmal strategy, far worse than buying and holding in both absolute and risk-adjusted terms.” Using monthly U.S. stock market total returns from mid-1926 to the end of 2016, he simulated variations of the “buy after a crash” strategy, “changing both the drawdown thresholds [from -10% to -50% in increments of 5%] before buying and the holding periods [from 12 to 60 months] after a buy.” In all cases the strategy failed. The reasons? “First, the historical equity risk premium was high and decades could pass before a big-enough crash, making it very costly to sit in cash. Second, the market tended to exhibit momentum more than mean reversion over years-long horizons. As strange as it sounds, you would have been better off buying when the market was going up and selling when it was going down, using a trend-following rule.”

Wednesday, August 15, 2018

Bova, Growth IQ

In Growth IQ: Get Smarter about the Choices That Will Make or Break Your Business (Portfolio/Penguin, 2018) Tiffani Bova regales the reader with stories about 30 companies to demonstrate what she considers to be the only 10 paths to growth. Although this book is written for entrepreneurs and managers, it’s a worthwhile read for investors who want to assess the growth strategies of companies on their radar screen.

Without the stories, the paths to growth—customer experience, customer base penetration, acceleration, product expansion, customer and product diversification, sales optimization, churn, partnerships, co-opetition, and unconventional strategies—would seem either abstract or, in many cases, obvious. Moreover, taken in isolation, they probably wouldn’t even work. As Bova writes, “It isn’t enough to have the ‘right’ new growth strategy. You must fully understand what the current market context is prior to making any moves.” And then you need to select key actions that can positively influence outcomes and establish a priority, order, and timing to those actions. In sum, “Growth IQ is a holistic approach to finding the right path, in the right market context, in the right combination and sequence—creating a multiplier effect that is far more powerful than just focusing on one or two efforts in isolation.”

Almost all of the companies Bova writes about are publicly traded, though not all of them are stock market darlings. Some companies, such as Sears, Blockbuster, Wells Fargo, and Blue Apron, are fodder for cautionary tales. Even those that Bova selected to illustrate a particular path to growth may not have executed especially well in another domain, at another time.

Growing a company is not a mechanical exercise, as Bova points out again and again in her examples. But intelligently pursuing multiple paths to growth will pay off. “Amazon has pursued all ten possible growth paths in little more than two decades.” It is “the very embodiment of Growth IQ.”

Wednesday, August 8, 2018

Effron, 8 Steps to High Performance

We all start our careers with attributes (e.g., intelligence, personality, physical attractiveness) and socioeconomic backgrounds that are “largely unchangeable once we become adults.” These combined items “predict up to 50 percent of anyone’s individual performance” and give some people a clear advantage over others. But that leaves the other 50+ percent that people can control and shape at will.

In 8 Steps to High Performance: Focus on What You Can Change (Ignore the Rest) (Harvard Business Review Press, 2018) Marc Effron shares “scientifically proven” things you can do to help yourself be a high performer. They are, in a nutshell: (1) set big goals, (2) behave to perform, (3) grow yourself faster, (4) connect, (5) maximize your fit, (6) fake it, (7) commit your body, and (8) avoid distractions.

These behaviors have been shown to work within a corporate environment. They are not necessarily behaviors that propel people to be successful entrepreneurs, not even behaviors that top CEOs exhibit. For instance, top performing CEOs seem to be high on general ability (fast, aggressive, persistent, efficient, proactive, high standards) and low on interpersonal skills (respectful, open to criticism, good listening skills, teamwork). But, writes Effron, “if you’re not already at the top, I’d suggest that both great results and great interpersonal behaviors are essential ingredients for high performance.”

“Grow yourself faster” is a step worth pausing at. “[R]oughly 70 percent of your professional growth will come from the work experiences you have, 20 percent will come from your interactions with others, and 10 percent will come from formal education.” Formal education “that may seem critical to success often isn’t. Only thirty-nine Fortune 100 CEOs have an MBA, and many of those leaders didn’t earn them at top-ranked schools.” (And, yes, this book was published by a wholly-owned subsidiary of Harvard University that reports to the Harvard Business School.)

Growth, Effron contends, is “a cycle—perform, get feedback, perform again better…. The faster and more often you move through that cycle, the faster you’ll develop and get the next opportunity to learn a new skill, test a new behavior, and get more helpful feedback. Each cycle you move through should make you more competent and more competitive.”

Effron’s chapter on how you can prime your body to perform better at work is something of a myth buster. “Surprisingly little science,” he writes, “makes a direct link between our bodies and individual high performance at work. The science that does exist says that sleep matters most, exercise has some minor and specific effects, and diet has no direct effect. That doesn’t mean that exercise and diet don’t matter in your life, but neither has much power to boost your performance at work.” As for sleep, quality impacts performance more than quantity.

The final step, avoid distractions, is not about smart phones and email. Instead, Effron tells the reader to “avoid the fads that distract you from what’s scientifically proven to improve your performance. Many of these fads present advice that would seem to make your life easier (focus on your strengths), quickly increase your performance (adopt a growth mindset), or give you instant self-confidence (strike a power pose).” But this advice is misguided. For instance, focusing on your strengths “will help you be better at the exact same things you’re good at today, but won’t help you to be good at anything else.”

“If you want to accomplish more than you thought you could or break through a performance barrier,” the author concludes, don’t follow fads but follow the eight steps given in this book.

Wednesday, July 18, 2018

Rees, Principles of Financial Modelling

In the old days banks wanted applicants to be comfortable with Excel. Now they’re upping the ante. Citi, for instance, wants its incoming investment bank analysts to know Python. But Excel hasn’t gone the way of the dodo. It’s still incredibly useful for a range of financial tasks. The problem is that most Excel users have no idea how to go beyond basic formulas and engage the program as a high-level tool. In Principles of Financial Modelling: Model Design and Best Practices using Excel and VBA (Wiley, 2018) Michael Rees sets out to fill this void.

Rees’s more than 500-page book is divided into six parts: (1) introduction to modeling, core themes and best practices, (2) model design and planning, (3) model building, testing and auditing, (4) sensitivity and scenario analysis, simulation and optimization, (5) Excel functions and functionality, and (6) foundations of VBA and macros. As these part titles indicate, Rees first addresses financial modeling, from design to optimization, and then explains how to use Excel and VBA to implement the models. Complementary to this book is a website, which contains 237 Excel files.

Here, to give a sense of the book, I will summarize Rees’s distinction between database and formula-driven approaches to modeling.

Traditional models, for instance those used for cash flow valuation, are formula-focused. They “often have a small set of numerical assumptions, from which large tables of calculations are performed. Certainly, where a single value is used for an assumption across multiple time periods (such as a single growth rate in revenues that applies to all future time periods), arbitrarily large tables of calculations may be generated simply by extending the time axis sufficiently, even as the number of inputs remains fixed.”

Where a large volume of data is required, however, the appropriate model will use “database concepts, functionality or data-oriented architectures and modular structures. These include the structuring of data sets into (perhaps several) contiguous ranges, using a column (field)-based approach for the model’s variables (with well-structured field identifiers, disciplined naming conventions, and so on).”

Even though in practice these two approaches to modeling can sometimes overlap, with the modeler confronted with both large data sets and potentially many formulas, Rees contends that “at the design stage, the reflection on the appropriate approach is fundamental: an inappropriate choice can lead to a model that is inflexible, cumbersome and not fit for the purpose.”

Before they set out to build models in Excel, analysts would do well to read Rees’s book. With its help, they will avoid many pitfalls.

Friday, July 13, 2018

Hall, A Carnival of Losses

I’m getting to the age that I read things about getting old. Not the advice that AARP sends out but essays by writers who are comfortably ahead of me on the march to 100. Donald Hall, the former poet laureate, delivered two such volumes of late, Essays After Eighty and A Carnival of Losses (Houghton Mifflin Harcourt, 2018), the latter written as he was nearing 90. (Hall died last month, on June 23.)

Essays After Eighty addressed old age more expansively, and humorously, than A Carnival of Losses. The new book has qualities of leftover stew: warmed-up reminiscences and bits and pieces that were probably in the literary root cellar, such as his recollections of poets. It’s still a delightful read, but if I were to recommend only a single title, it would be Essays After Eighty.

Wednesday, July 11, 2018

Govindarajan & Ramamurti, Reverse Innovation in Health Care

I got an advance reader’s copy of Reverse Innovation in Health Care: How to Make Value-Based Delivery Work (Harvard Business Review Press, 2018) by Vijay Govindarajan and Ravi Ramamurti. I put it aside, thinking that it was not within the scope of this blog. But then came the tornadoes that struck Connecticut, one of which touched down far too close for comfort, on May 15. My property (fortunately not the house) was devastated, with large uprooted trees all around the house and the edges of the property and the top of one mighty oak pinning, and miraculously only denting, the car sitting in the driveway. Naturally, I had no power for days, and no Internet access for days more. And so, with my usual routine upended as well, I turned to this book.

The book’s premise is that U.S. healthcare providers can learn from models that have been successful in India. The authors are not, of course, touting Indian healthcare as a whole, which is sorely wanting. But one hospital system in particular, Narayana Health, could serve as an exemplar.

Founded by Dr. Devi Shetty in 2001 with a vision to treat all patients regardless of their ability to pay, Narayana Health is now a profitable company that offers, most notably, open-heart surgery (which would normally cost between $100,000 and $150,000 in the U.S.) to paying patients for $2,100 and to subsidized patients for $1,307. The hospital’s cost for each surgery is $1,100 to $1,200. Narayana is now doing about 14,700 cardiac surgeries a year. On average, in 2016-17 Narayana’s cardiac surgeons performed two to three times as many open-heart surgeries as their U.S. counterparts. And their outcome metrics rival those of the best hospitals in the world.

Shetty is a ruthless cost-cutter, as long as cutting costs doesn’t negatively impact quality of care. To construct Narayana’s no-frills hospitals, for example, costs about half that of its competitors. And when Shetty wanted to buy disposable surgery gowns and drapes from multinational suppliers who refused to budge on price, he had them stitched locally. Within four years, this firm became the largest manufacturer of disposable surgical gowns in India. The multinationals, unable to compete on price, left the market.

Narayana has innovated through task-shifting, allowing surgeons to do three operations in the time it takes other hospitals to do one. “[E]very motion in the operating cycle is choreographed to reduce turnaround time and optimize pay grades.” Senior surgeons do little or nothing that can be done by lower-paid, less-skilled staff.

In perhaps the most striking instance of task-shifting, in Narayana’s multispecialty hospital in Mysore, family members provide much of the post-ICU care. Since, in India, the entire family comes to the hospital with the patient and typically spends three days there, Narayana upgraded them from “underfoot” to caregivers. They get instruction from a four-hour video curriculum. “The practice of training families for in-hospital postoperative care not only frees up the nursing staff for other work but also eases the transition to reliable, high-quality home care, reducing readmissions by 30 percent.”

Narayana uses a hub-and-spoke model and, through farming cooperatives in Shetty’s home state, instituted an insurance plan to reach out to underserved villages. By 2017 the insurer had four million members who, for 22 cents a month, could get free treatment at 800 network hospitals across the state for any procedure whose cost did not exceed $2,200.

Shetty is also starting to pursue opportunities in telemedicine.

The authors highlight four new models in or near the United States that use some of the Indian tactics: Health City Cayman Islands (founded by Narayana Health), University of Mississippi Medical Center, Ascension, and Iora Health. All of these are making strides in trying to change the American healthcare system from the bottom up.

Reverse Innovation in Health Care offers ways for U.S. healthcare to save billions without compromising (indeed, perhaps with improving) quality. And it’s not simply on the back of low wages. The authors address a series of questions that skeptics raise to show that aspects of the model would be viable in the United States. As such, it’s an essential read for anyone who is prepared to tackle the change-resistant healthcare establishment.

Wednesday, June 27, 2018

McNally, The Promise of Failure

Why write? Especially when, in most cases, the writer faces rejection of one sort or another. This is the question John McNally raises in The Promise of Failure: One Writer’s Perspective on Not Succeeding (University of Iowa Press, 2018). Although McNally is addressing writers and would-be writers (of whom I am decidedly not one), his thoughts on failure can sometimes be generalized.

So, again, why write? “If no one out there cares if you put down your pen right now and never pick it up again, why keep doing this thing that you’re doing?” One reason is that “it’s the only thing [you’re] even remotely good at.”

So you keep writing and “putting [your] work out there,” even though you “ultimately have no control over whether something gets published or doesn’t…. It’s like letting go of a helium-filled balloon and hoping it touches an airplane. Once you let go of the string, it’s no longer in your control.” What a wonderful image for the disjunction between process and outcome. Once you hit the buy or sell button…. No, I don’t want to mash McNally’s language by forcing an analogy.

When, in the face of failure, should you just pack it in and quit doing what you’re doing? McNally says that he has “always been of the belief that as long as you’re not hurting anyone, it’s foolish not to pursue the thing you want to pursue, even if you pursue it badly.” Here it’s more difficult to analogize to trading. The writer piles up rejection slips; the trader piles up losses. Losses may not be psychologically more difficult to handle than rejection slips, but they do have a way of eroding any semblance of well-being. The losing trader either has to find some way to be profitable (and many highly successful traders have clawed their way back from nothingness) or should find something else to pursue.

But if you’re going to pursue trading, here’s McNally’s advice (and in this case it’s easy to analogize): “I measure my goals not by a typed page, not by a paragraph, not by a sentence. But by a word. One word. Because I know well enough now that one word will lead me to the next word and that this is how you get to where you’re going.”

Sunday, June 24, 2018

Portnoy, The Geometry of Wealth

Brian Portnoy, director of investment education at Virtus Investment Partners, has written a personal finance book that goes beyond mere finance. The Geometry of Wealth: How to Shape a Life of Money and Meaning (Harriman House, 2018) approaches the subject by way of three shapes: the circle, purpose; the triangle, priorities; and the square, tactics. The circle exemplifies how we navigate life’s ups and downs, through the back-and-forth of defining and then adapting. Portnoy imagines two triangles. The first one has risk management at its base, spending and saving decisions in the middle, and big dreams at the top. The second triangle is intended to be a bridge between planning priorities and investment decisions. At its base is behavior, then comes portfolio management, and finally individual parts of portfolios at the apex. As for tactics, the four corners of the square represent the growth we hope to achieve, the emotional pain of achieving those gains, fit (“how additional decisions improve or undermine what you already own”), and flexibility.

Portnoy addresses the sources of a joyful life because, as he writes, “if wealth is defined as funded contentment, then we need to know what we’re supposed to be funding.” He suggests four such sources: the need to belong, the need to direct one’s own destiny, the need to be good at something worthwhile, and the need for a purpose outside of one’s self.

But can we afford a meaningful life? “Purpose and prosperity,” he acknowledges, “aren’t necessarily a match for each other.” We need the wherewithal to “underwrite meaning and become truly wealthy.” And so we have to set priorities—priorities such as being less wrong rather than being more right, immunizing our liabilities before maximizing our assets, and addressing psychological vagaries.

Tactics is “the part where we strive for decent outcomes.” And where Portnoy looks at how to be a successful investor, with particular reference to returns, volatility, correlation, and liquidity.

In his final chapter, “Shapeless,” Portnoy turns to the tug-and-pull between now and later, between enough and more. “At any moment in life we have to decide whether we want, as Hunter S. Thompson once framed it, ‘to float with the tide, or to swim for a goal.’ We harbor an urge to do both, to appreciate the moment, to cherish where we are, but then also to push out for that next thing, to get to that next Great Place.”

Wednesday, June 20, 2018

Gannett, The Creative Curve

The thesis of Allen Gannett’s The Creative Curve (Currency / Crown, 2018) isn’t revolutionary. But I guess that’s the point. If it were, the book wouldn’t sell well. It would defy the science of what becomes a hit.

More interesting, however, at least to me, than how to identify the next big thing, whether it’s a new Ben & Jerry’s ice cream flavor or a blockbuster movie, is how people prepare to be creative. Because aha moments don’t happen in a vacuum. In the shower, perhaps; in a vacuum, never.

Gannett postulates four laws of the creative curve: consumption, imitation, creative communities, and iterations. Here I’ll look only at the first law.

How can some people be such successful serial entrepreneurs? In part, it’s due to pattern recognition, the ability to develop an uncanny instinct for opportunity. “Research shows that when entrepreneurs have significant prior knowledge, they no longer need to engage in slow, deliberate searches for new ideas. On the contrary, their prior experience gives them a rich library of exemplars they can access automatically.”

To build this mental library, would-be creators voraciously consume highly relevant material. In fact, in the case of already successful creative artists, it seems to be part and parcel of their daily routine. They spend about 20 percent of their waking hours expanding their knowledge of their field. Writers read, artists go to art shows, songwriters listen to music, old and new.

The 20 percent principle, the author contends, provides the building blocks necessary for aha moments to flourish. “This accumulation of prior knowledge fills up the brain with examples and concepts that artists then use to uncover non-obvious insights. … You can’t have insights about things you don’t know anything about.”

In brief, if you want to be a creative whatever, and that includes being a creative investor or trader, you need to accumulate a large repertoire of relevant material—and keep adding to it. Aha moments come only to the well prepared.

Sunday, June 17, 2018

Carreyrou, Bad Blood

On Friday Elizabeth Holmes, the founder of Theranos, and its former president Ramesh “Sunny” Balwani were criminally charged with wire fraud. These charges came three months after the SEC sued Holmes and Theranos for a “massive fraud” at the company.

John Carreyrou, a lauded investigative reporter at the Wall Street Journal who covered Theranos extensively from 2015 on, has written a spine-chilling book, Bad Blood: Secrets and Lies in a Silicon Valley Startup (Alfred A. Knopf, 2018).

It’s hard to imagine, amid all the suspicions, firings, and general upheaval, that Theranos got away with its alleged fraud for as long as it did. It was the persona of Elizabeth Holmes (along later on with some heavy legal fire power) that kept it going, that attracted big dollars from normally savvy investors and big names to the company board, that convinced companies such as Safeway and Walgreens to offer Theranos’s flawed finger-stick blood tests (although they later pulled back). People were bewitched by her “mixture of charm, intelligence, and charisma.” They didn’t see her much less flattering side.

Put Bad Blood at the top of your summer reading list. You won’t regret it

Wednesday, June 13, 2018

Yu, Leap

Legally or illegally, companies have for centuries copied the intellectual property of their competitors and encroached on their market share. One has only to think back to the commercial espionage of Francis Cabot Lowell, who in 1810-11, while strolling through dozens of British cotton mills, memorized critical details of mechanized textile manufacturing. Using this information, his Boston Manufacturing Company and eventually mills throughout New England took the growing American mass market away from British textile exporters.

Leap: How to Thrive in a World Where Everything Can Be Copied (PublicAffairs/Hachette, 2018) by Howard Yu is, in the best sense of the word, a story book. It tells tales of woe as well as tales of resilience. These case studies all have a point, but, even if they didn’t, they would be fascinating in and of themselves.

Wu, a professor at the International Institute for Management Development (IMD) in Lausanne, Switzerland, believes that the key to outlasting copycat competition is to leap. “Pioneers must move across knowledge disciplines, to leverage or create new knowledge on how a product is made or a service is delivered. Absent such efforts, latecomers will always catch up.”

Wu articulates five principles necessary for making a successful leap: (1) understand your firm’s foundational knowledge and its trajectory, (2) acquire and cultivate new knowledge disciplines, (3) leverage seismic shifts, (4) experiment to gain evidence, and (5) dive deep into execution. These principles, as stated, are somewhat telegraphic, but Wu develops them through compelling case studies from companies spanning the globe: for instance, Steinway (an example of what not to do in the face of competition, in its case, from Yamaha), Procter & Gamble, Novartis, WeChat, Recruit Holdings, and John Deere.

Leap is the kind of book that everyone with an interest in business can profit from. And here’s a lesson that everybody, active investors/traders in particular, can profit from. “Successful executives often exhibit a bias for action. But it’s even more important to separate the noise from the signal that actually pinpoints the glacial movement around us. Listening carefully to the right signals requires patience and discipline. Seizing a window of opportunity, which means not necessarily being the first mover but the first to get it right, takes courage and determination. To leap successfully is to master these two seemingly contradictory abilities. The discipline to wait and the determination to drive, in balanced combination, often pay off handsomely.”