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Being Wrong: Adventures in the Margin of Error by Kathryn Schulz
affirmative action, anti-communist, banking crisis, Bernie Madoff, car-free, Cass Sunstein, cognitive dissonance, colonial rule, conceptual framework, cosmological constant, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, desegregation, Johann Wolfgang von Goethe, lake wobegon effect, longitudinal study, mandatory minimum, Pierre-Simon Laplace, Ronald Reagan, six sigma, stem cell, Steven Pinker, Tenerife airport disaster, the scientific method, The Wisdom of Crowds, theory of mind, Thomas Kuhn: the structure of scientific revolutions, trade route
Another well-known example of corporate efforts to prevent error is the quality-control process known as Six Sigma. Six Sigma was pioneered at Motorola in 1986 and is now used by the majority of Fortune 500 companies, plus countless smaller businesses. The protocol’s name comes from statistics: the Greek letter sigma (s) indicates the amount of standard deviation from a given norm. In this case, all deviation is assumed to be undesirable—an error in a manufacturing process or in its end product. A company that has achieved Six Sigma experiences just 3.4 such errors per million opportunities to err, a laudably low failure rate (or, framed positively, a 99.9997 percent success rate). To get a sense of what this means, consider that a company that ships 300,000 packages per year with a 99 percent success rate sends 3,000 packages to the wrong place. If that same company achieved Six Sigma, only a single package would go astray.
A serious incident means that either there was one fatality without substantial damage to the aircraft, or there was at least one serious injury and substantial damage to the aircraft. In addition to the drop in overall accident rates in commercial passenger service between 1998 and 2007, none of the accidents in 2007 were classified as major. Six Sigma. Most of the background on Six Sigma is drawn from Peter S. Pande, Robert P. Neuman, Roland R. Cavanagh, The Six Sigma Way: How GE, Motorola, and Other Top Companies are Honing Their Performance (McGraw-Hill Professional, 2000). I borrowed (and tweaked) the 300,000 packages example from this book, where it appears on p. 12. My understanding of the “define, measure, analyze, improve, control” process was refined by Forrest W. Breyfogle’s Implementing Six Sigma: Smarter Solutions Using Statistical Methods (John Wiley and Sons, 2003). “tolerance for failure”…“safe failure.” Pande et al., 17–18. “the enemy” and “evil” (FN).
If some of your brake pads are a half-inch thick and some are a quarter-inch thick, they might not fit with your other components, or they might not pass safety standards, or they might be rejected by the auto manufacturers you supply. With Six Sigma, then, the goal isn’t to improve the average per se, but to reduce the deviation from that average. To do this, Six Sigma analysts make use of a procedure that is usually encapsulated as “define, measure, analyze, improve, control.” In essence, that procedure involves isolating and assessing every single variable pertaining to a given process. Then analysts begin adjusting those variables to achieve and maintain the optimal outcome in terms of a company’s final product, customer satisfaction, and bottom line.* All of these error-prevention techniques—from Six Sigma to the innovations of the airline industry to the efforts at Beth Israel—have three key elements in common. The first, as I’ve indicated, is acceptance of the likelihood of error.
Execution: The Discipline of Getting Things Done by Larry Bossidy
Albert Einstein, business process, complexity theory, Iridium satellite, Long Term Capital Management, NetJets, old-boy network, shareholder value, six sigma, social software, Socratic dialogue, supply-chain management
I asked about e-auctions—and told the manager that he had to be buying some stuff that way these days; it was less expensive. He admitted they were behind the curve there. Finally, the company had a hodgepodge of systems (a common problem, by the way). I told him he had to make these systems talk to each other without spending a fortune. He told me he’d figure out how. Here’s the good news, though. I was trying to revive the company’s Six Sigma program, which had been let go in my absence. But this manager’s Six Sigma program was right on top of things. It needed a little work, but he had plenty of black belts—people with the highest expertise in the discipline. His people were working on the right projects, and they had all the right metrics for customers. His digitization effort was very nice too. And again, he did it all with no influence from headquarters. That was impressive.
Just as the leader has to be personally involved in execution, so must everyone else in the organization understand and practice the discipline. Execution has to be embedded in the reward systems and in the norms of behavior that everyone practices. Indeed, as we will show in chapter 4, focusing on execution is not only an essential part of a business’s culture, it is the one sure way to create meaningful cultural change. One way to get a handle on execution is to think of it as akin to the Six Sigma processes for continual improvement. People practicing this methodology look for deviations from desired tolerances. When they find them, they move quickly to correct the problem. They use the processes to constantly raise the bar, improving quality and throughput. They use them collaboratively across units to improve how processes work across the organization. It’s a relentless pursuit of reality, coupled with processes for constant improvement.
It’s a relentless pursuit of reality, coupled with processes for constant improvement. And it’s a huge change in behavior—a change, really, in culture. Leaders who execute look for deviations from desired managerial tolerances—the gap between the desired and actual outcome in everything from profit margins to the selection of people for promotion. Then they move to close the gap and raise the bar still higher across the whole organization. Like Six Sigma, the discipline of execution doesn’t work unless people are schooled in it and practice it constantly; it doesn’t work if only a few people in the system practice it. Execution has to be part of an organization’s culture, driving the behavior of all leaders at all levels. Execution should begin with the senior leaders, but if you are not a senior leader, you can still practice it in your own organization.
The Power of Moments: Why Certain Experiences Have Extraordinary Impact by Chip Heath, Dan Heath
Cal Newport, call centre, clean water, cloud computing, crowdsourcing, desegregation, fear of failure, Mahatma Gandhi, mental accounting, meta analysis, meta-analysis, school choice, six sigma, Steve Ballmer
In doing his work, Phelps relied heavily on the discipline of Six Sigma. If you manufacture products—let’s say rubber balls—naturally you want them to be free of defects. A “six sigma” process is one that produces only 3.4 defects per million attempts. So if you make a million rubber balls, only 3 or 4 of them will be warped or lopsided. To achieve that level of excellence, you must obsessively monitor the manufacturing process, gathering data to pinpoint problems and to reduce variability. The people who perform these feats of process improvement are practitioners of Six Sigma, and their voodoo can also be practiced on nonmanufacturing situations as well, such as reducing surgical errors or, in the case of Phelps, speeding up engine repair. The most talented practitioners seek out certification as a Six Sigma Black Belt, an honorific that has nothing to do with karate but rather reflects a noble and ultimately hopeless attempt to give the work some sex appeal.
The most talented practitioners seek out certification as a Six Sigma Black Belt, an honorific that has nothing to do with karate but rather reflects a noble and ultimately hopeless attempt to give the work some sex appeal. Back to the story: Phelps needed a Six Sigma Black Belt to assist him with his work in Albany, New York, and he hired Ranjani Sreenivasan for the role. Raised in India, Sreenivasan had been in the United States for only three years, having come to complete her master’s degree in mechanical engineering. Sreenivasan’s role was to use Six Sigma to help colleagues improve their processes, for instance by reorganizing the service shops so that more frequently used tools were closer at hand. But she struggled in the role. “She was kind of shy, a little withdrawn,” said Phelps. He worried that she wasn’t assertive enough to be taken seriously by the experienced hands at the firm.
He worried that she wasn’t assertive enough to be taken seriously by the experienced hands at the firm. Sreenivasan had a different perspective. She wasn’t introverted—her friends had nicknamed her “Thunder,” because they always knew when she was in the room. Rather, she was overwhelmed. She knew a lot about Six Sigma but almost nothing about servicing diesel engines. In meetings she felt as if her colleagues were “speaking in Greek and Latin.” She’d take notes of all the terms they used and ask someone later what they meant. At her first team meeting for a Six Sigma project, she sat silently, and afterward approached Phelps, distraught. “I was so upset,” she said. “I was seen as this new hire who knew nothing.” There was grumbling about her performance. Phelps knew she was the right person for the job, but she was in jeopardy. So he gave her a push. Phelps challenged her to get out in the field and spend some time learning the business.
The Startup Way: Making Entrepreneurship a Fundamental Discipline of Every Enterprise by Eric Ries
activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Airbnb, autonomous vehicles, barriers to entry, basic income, Ben Horowitz, Black-Scholes formula, call centre, centralized clearinghouse, Clayton Christensen, cognitive dissonance, connected car, corporate governance, DevOps, Elon Musk, en.wikipedia.org, fault tolerance, Frederick Winslow Taylor, global supply chain, index card, Jeff Bezos, Kickstarter, Lean Startup, loss aversion, Marc Andreessen, Mark Zuckerberg, means of production, minimum viable product, moral hazard, move fast and break things, move fast and break things, obamacare, peer-to-peer, place-making, rent-seeking, Richard Florida, Sam Altman, Sand Hill Road, secular stagnation, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Steve Jobs, the scientific method, time value of money, Toyota Production System, Uber for X, universal basic income, web of trust, Y Combinator
Welch introduced the process to GE with the goal of achieving Six Sigma Quality across the company within five years, stating, “Quality can truly change GE from one of the great companies to absolutely the greatest company in world business.”6 As I traveled around GE training executives, a lot of questions arose, from both fans and skeptics of Six Sigma, as to whether FastWorks was to be GE’s next “big thing.” Did it render past Six Sigma training obsolete? If FastWorks was meant to work alongside Six Sigma, how would you know when to use which? Were there certifications and levels to Lean Startup knowledge akin to the colored belts of Six Sigma? One day, as I was meeting with a Six Sigma black belt from one of GE’s industrial businesses—who was quite skeptical— I found myself distracted by the mug on his desk, which read: FAILURE IS NOT AN OPTION. Nobody in the startup world could have such a mug, I mused; it would be ridiculous. My experience is full of situations where reality proved too unpredictable to avoid failure.
But sometimes it means the forecast itself was a fantasy. How can we tell the difference? HOW DO WE DEAL WITH FAILURE? No doubt you’ve heard of Six Sigma, one of the most famous corporate transformations in management history. Introduced to GE in 1995 by CEO Jack Welch, Six Sigma is a process to develop and deliver near-perfect products. Sigma is a statistical term measuring how far a given process deviates from perfection. To achieve Six Sigma Quality, a process must produce no more than 3.4 defects per million opportunities, i.e., it must be defective less than 0.0000034 percent of the time. Welch introduced the process to GE with the goal of achieving Six Sigma Quality across the company within five years, stating, “Quality can truly change GE from one of the great companies to absolutely the greatest company in world business.”6 As I traveled around GE training executives, a lot of questions arose, from both fans and skeptics of Six Sigma, as to whether FastWorks was to be GE’s next “big thing.”
There was a time when producing high-quality products on time, on budget, and at scale was one of the preeminent problems of the age. Understanding how to build quality into products from the inside out required mastering the new statistical science of variation, and then devising tools, methodologies, and training programs that could make doing so practical. Standardization, mass production, lean manufacturing, and Six Sigma are all fruits of this hard-won conceptual victory. Baked into these methods is a presupposition that failure can be prevented through diligent preparation, planning, and execution. But the startup part of the management portfolio challenges this assumption. If some projects fail to meet their projections because the underlying uncertainty was extremely high, how do we hold those leaders accountable?
Winning Now, Winning Later by David M. Cote
activist fund / activist shareholder / activist investor, Asian financial crisis, business cycle, business process, hiring and firing, Internet of things, Parkinson's law, Paul Samuelson, Silicon Valley, six sigma, Steve Jobs, Toyota Production System, trickle-down economics
We had seen previous change efforts underperform precisely because we had failed to change mind-sets and galvanize our workforce. In 2002, we had begun to comprehensively train our workforce in the Six Sigma methodology for both design and manufacturing, hoping to improve the quality of our production processes. Previous Six Sigma training had touched only a small percentage of manufacturing people and products, and no engineers. But I rolled out the program too quickly and hadn’t refined how we presented it to workers and managers so that their mind-set would change, and they’d view it as more than just a training exercise. Plants that had trained in Six Sigma didn’t see appreciable improvements in quality because they hadn’t changed how they did their work. We were a mile wide, so to speak, in how much training we had delivered, but only an inch deep in terms of how people were using the tools.
The plant manager proudly showed me charts documenting how teams had improved producibility (the percentage of parts that emerge from production perfect the first time around) from 72 percent to 85 percent. That represented progress, but I couldn’t help but wonder why, after years of Six Sigma, we weren’t at 99-plus percent. Digging into it, I learned that the business had recently shifted production of a number of its poorly designed products to a new facility in Malaysia rather than fix the designs. In other words, they decided to manufacture poor designs in a lower-cost factory rather than fix the designs. Not very “Six Sigma” at all. We went back and implemented Six Sigma again more rigorously. Our Aerospace leader put in place quantifiable, trackable producibility metrics to govern every new design. The engineers protested, claiming this would slow down their design schedules, but we insisted that they do two seemingly conflicting things at the same time: deliver producible designs and do it on time.
During my second month at Honeywell, I came up with the five key strategic initiatives I wanted Honeywell to focus on: growth, productivity, cash, people, and operational enablers (like Six Sigma, and later, the Honeywell Operating System). I also generated a list of ten behaviors I wanted to define our culture and held a full-day meeting with my team to discuss them. We wound up adding two more behaviors—for twelve total—while modifying some of my original ones. As some of us joked, the Lord only needed ten commandments, but trying to end the color wars and get a large organization to become a performance machine required a couple more. The Five Initiatives * * * 1.Growth (via customer service, globalization, and technology) 2.Productivity (went hand-in-hand with growth) 3.Cash (improve working capital and have high-quality earnings) 4.People (keep the best talent, organized the right way and motivated) 5.Organizational enablers (including Six Sigma, Honeywell Operating System, and Functional Transformation) The Twelve Behaviors 1.Focus on customers and growth (serve customers well and aggressively pursue growth). 2.Lead impactfully (think like a leader and serve as a role model). 3.Get results (consistently meet any commitments that you make). 4.Make people better (encourage excellence in peers, subordinates, and/or managers). 5.Champion change (drive continuous improvement in our operations). 6.Foster teamwork and diversity (define success in terms of the entire team). 7.Adopt a global mind-set (view the business from all relevant perspectives, and see the world in terms of integrated value chains). 8.Take risks intelligently (recognize that we must take greater but smarter risks to generate better returns). 9.Be self-aware (recognize your behavior and how it affects those around you). 10.Communicate effectively (provide information to others in a timely, concise, and thoughtful way). 11.Think in an integrative fashion (make more holistic decisions beyond your own bailiwick by applying intuition, experience, and judgment to the available data). 12.Develop technical or functional excellence (be capable and effective in your particular area of expertise).
Design of Business: Why Design Thinking Is the Next Competitive Advantage by Roger L. Martin
asset allocation, Buckminster Fuller, business process, Frank Gehry, global supply chain, high net worth, Innovator's Dilemma, Isaac Newton, mobile money, QWERTY keyboard, Ralph Waldo Emerson, risk tolerance, six sigma, Steve Ballmer, Steve Jobs, supply-chain management, Wall-E, winner-take-all economy
The managerial skills that are built and rewarded are those of running heuristics or algorithms to produce reliable outcomes. Consider the cottage industry that has grown up around Six Sigma. Six Sigma relentlessly simplifies algorithms to the bare minimum, taking reliability to its logical extreme. Its statistical measures plane away from the algorithm any nuance that would sacrifice consistency of result. Many organizations—most famously, General Electric—promote Six Sigma techniques and reward managers who become Six Sigma “Black Belts.” These Black Belts are reliability masters. In even wider use than Six Sigma is a tool that was virtually unknown to corporate boardrooms just a generation ago: linear regression, a tool that is used for “proving” statistically the relationship between one factor (e.g., store hours) and another (e.g., sales per square foot).
Case in point: today’s complex, elaborate, firmwide software. Enterprise resource planning (ERP) systems keep track of all corporate data in a single database and spit out comprehensive reports on everything from inventory levels to sales by product to cost absorption by area. Customer relationship management (CRM) systems purport to ensure that a company knows exactly who its customers are, what each is buying, and what more it could sell to them. Six Sigma programs and total quality management (TQM) systems knock the waste out of an organization’s systems, and knowledge management (KM) systems (attempt to) organize all the knowledge in a corporation. Those and other tools enable the modern corporation to crunch data objectively and extrapolate from the past to make “scientific” predictions about the future, all part of the quest for reliability.
But they are no panacea. An ERP system can provide useful real-time data to track whether resources are being used efficiently, but it cannot generate a robust strategy. CRM systems put a wealth of data at the fingertips of customer-service reps, but data is no substitute for intimacy, as corporations discover when customers complain that the systems make them feel as if they are buying from Big Brother. Six Sigma and TQM systems drive out waste from the business as currently configured, but they will not generate innovative new business designs. KM systems will (sort of) organize all the knowledge in a corporation, but they cannot produce imaginative breakthroughs. Advances in knowledge emerge from the pursuit of valid results. That pursuit calls for a different set of tools and processes and, indeed, a different sort of organization.
Lessons from the Titans: What Companies in the New Economy Can Learn from the Great Industrial Giants to Drive Sustainable Success by Scott Davis, Carter Copeland, Rob Wertheimer
3D printing, activist fund / activist shareholder / activist investor, additive manufacturing, Airbnb, airport security, barriers to entry, business cycle, business process, clean water, commoditize, coronavirus, corporate governance, COVID-19, Covid-19, disruptive innovation, Elon Musk, factory automation, global pandemic, hydraulic fracturing, Internet of things, iterative process, low cost airline, low cost carrier, Marc Andreessen, megacity, Network effects, new economy, Ponzi scheme, profit maximization, random walk, RFID, ride hailing / ride sharing, risk tolerance, shareholder value, Silicon Valley, six sigma, skunkworks, software is eating the world, strikebreaker, Toyota Production System, Uber for X, winner-take-all economy
At the time, the press typically referred to GE as “the lumbering giant,” not exactly the reputation that Welch wanted to sustain. Welch was a young (mid-forties) and aggressive leader who saw much bigger potential. His first five years were spent cutting layers of management and pushing decision-making down through the organization. He also invested heavily in factory automation and pushed productivity onto the factory floor, a campaign that culminated in the 1990s with the aggressive adoption of Six Sigma (a system for extreme quality control). (See Figure 1.2.) Figure 1.2: The Jack Welch years (1981–2001). Source: General Electric filings, press reports; Bloomberg Meanwhile he pushed his executives to boost market share and find new areas of growth. Divisions had to be number one or number two in key markets to be kept in the mix. Welch exited slower-growth, more competitive businesses like mining and replaced them with higher-growth, often higher-tech areas such as specialty plastics.
It could lend where banks typically didn’t like to go in those days, areas like store-branded credit cards, project and equipment financing, aircraft leasing, railcar leasing, medical equipment leasing, and private equity financing. Anything niche or unique fit the vision. Insurance products were later added to the mix. It wasn’t all perfect, of course. In fact, GE Capital stumbled early on due to the bad decision to purchase Kidder Peabody in 1986—a humbling deal that taught Welch that some businesses just can’t be “Six Sigma’d.” The world of investment banking was just too far afield for GE. In hindsight, the expansion into insurance proved a bad move too, a big setback for GE after Welch retired. Hindsight will also show that GE Capital may not have been the most ethically managed asset that Welch oversaw. The quarter-to-quarter earnings performance eventually revealed a pattern of abuse, notably one-time gains that juiced earnings.
His playbook also included a heavy emphasis on global expansion and, in his later years, a hyperfocus on the internet as a productivity tool. His initiatives were never optional, but he sold the merits hard. He took little for granted. In his early years, he endured the extreme unpopularity that comes along with laying off a whopping 100,000 employees, but it’s clear he knew he had no chance unless he fixed the bloated corporate structure. His investments in automation and adoption of Six Sigma kept employees focused for north of a decade, and GE became a world-class manufacturer. The reputation of the company rose steadily, and the results for a broader stakeholder group were largely outstanding. The deals themselves took GE to a different level, but the equal hero here was the operational and management discipline. People forget at times, but Welch was a roll-up-your-sleeves operating guy.
Model Thinker: What You Need to Know to Make Data Work for You by Scott E. Page
"Robert Solow", Airbnb, Albert Einstein, Alfred Russel Wallace, algorithmic trading, Alvin Roth, assortative mating, Bernie Madoff, bitcoin, Black Swan, blockchain, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Checklist Manifesto, computer age, corporate governance, correlation does not imply causation, cuban missile crisis, deliberate practice, discrete time, distributed ledger, en.wikipedia.org, Estimating the Reproducibility of Psychological Science, Everything should be made as simple as possible, experimental economics, first-price auction, Flash crash, Geoffrey West, Santa Fe Institute, germ theory of disease, Gini coefficient, High speed trading, impulse control, income inequality, Isaac Newton, John von Neumann, Kenneth Rogoff, knowledge economy, knowledge worker, Long Term Capital Management, loss aversion, low skilled workers, Mark Zuckerberg, market design, meta analysis, meta-analysis, money market fund, Nash equilibrium, natural language processing, Network effects, p-value, Pareto efficiency, pattern recognition, Paul Erdős, Paul Samuelson, phenotype, pre–internet, prisoner's dilemma, race to the bottom, random walk, randomized controlled trial, Richard Feynman, Richard Thaler, school choice, sealed-bid auction, second-price auction, selection bias, six sigma, social graph, spectrum auction, statistical model, Stephen Hawking, Supply of New York City Cabdrivers, The Bell Curve by Richard Herrnstein and Charles Murray, The Great Moderation, The Rise and Fall of American Growth, the rule of 72, the scientific method, The Spirit Level, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, urban sprawl, value at risk, web application, winner-take-all economy, zero-sum game
The statistical bar will be lower for a drug that cures a fatal disease and exhibits only minor side effects than for a drug that cures toenail fungus but has a higher-than-expected incidence of bone cancer associated with its usage. The FDA also cares about the power of the statistical test—the probability that the test shows that the drug works. Six Sigma Method As our final application, we show how normal distributions inform quality control through the Six Sigma method. Developed in the mid-1980s by Motorola, the Six Sigma method reduces errors. The method models product attributes as drawn from a normal distribution. Imagine a company that produces bolts for door handles that must fit snugly into knobs made by another manufacturer. Specifications call for the bolts to be 14 millimeters in diameter, though any bolt between 13 and 15 millimeters in diameter will function properly.
Two-standard-deviation events occur 5% of the time—far too high a rate for manufacturers. The Six Sigma method involves working to reduce the size of a standard deviation to lower the probability of a failure. Companies can reduce error rates by tightening quality control. On February 26, 2008, Starbucks closed down over seven thousand shops for over three hours to retrain employees. Similarly, checklists used by airlines and now hospitals reduce variation.7 Six Sigma reduces the standard deviation so that even a six-standard-deviation error avoids a malfunction. In our bolt example, that would require reducing the standard deviation of a bolt’s diameter to one-sixth of a millimeter. Six standard deviations implies an error rate of 2 per billion cases. The actual threshold used assumes an unavoidable rate of one and a half standard deviations. Thus, a six-sigma event actually corresponds to a four-and-a-half sigma event, and an allowable error rate of about 1 per 3 million.
As we learn later, preventing riots depends less on reducing average levels of discontent than on appeasing people at the extreme. In this chapter, we adopt a structure-logic-function organization. We define normal distributions, describe how they arise, and then ask why they matter. We apply our knowledge of distributions to explain why good things come in small samples, to test for significance of effects, and to explain Six Sigma process management. We then go back to the logic question and ask what happens if we multiply rather than add random variables. We learn that we obtain a lognormal distribution. Lognormal distributions include larger events and are not symmetric about their means. It follows that multiples of effects lead to more inequality, an insight that has implications for how policies for increasing salaries affect income distributions.
A Mathematician Plays the Stock Market by John Allen Paulos
Benoit Mandelbrot, Black-Scholes formula, Brownian motion, business climate, business cycle, butter production in bangladesh, butterfly effect, capital asset pricing model, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, diversified portfolio, dogs of the Dow, Donald Trump, double entry bookkeeping, Elliott wave, endowment effect, Erdős number, Eugene Fama: efficient market hypothesis, four colour theorem, George Gilder, global village, greed is good, index fund, intangible asset, invisible hand, Isaac Newton, John Nash: game theory, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, mental accounting, Myron Scholes, Nash equilibrium, Network effects, passive investing, Paul Erdős, Paul Samuelson, Ponzi scheme, price anchoring, Ralph Nelson Elliott, random walk, Richard Thaler, Robert Shiller, Robert Shiller, short selling, six sigma, Stephen Hawking, stocks for the long run, survivorship bias, transaction costs, ultimatum game, Vanguard fund, Yogi Berra
About two-thirds of the time, the rate of return of this more volatile stock will be between -14.8 percent and 25.6 percent, and 95 percent of the time it will be between -35 percent and 45.8 percent. In all cases, the more standard deviations from the expected value, the more unusual the result. This fact helps account for the many popular books on management and quality control having the words “six sigma” in their titles. The covers of many of these books suggest that by following their precepts, you can attain results that are six standard deviations above the norm, leading, for example, to a minuscule number of product defects. A six-sigma performance is, in fact, so unlikely that the tables in most statistics texts don’t even include values for it. If you look into the books on management, however, you learn that Sigma is usually capitalized and means something other than sigma, the standard deviation of a chance-dependent quantity.
Chapter 4 - Chance and Efficient Markets Geniuses, Idiots, or Neither Efficiency and Random Walks Pennies and the Perception of Pattern A Stock-Newsletter Scam Decimals and Other Changes Benford’s Law and Looking Out for Number One The Numbers Man—A Screen Treatment Chapter 5 - Value Investing and Fundamental Analysis e is the Root of All Money The Fundamentalists’ Creed: You Get What You Pay For Ponzi and the Irrational Discounting of the Future Average Riches, Likely Poverty Fat Stocks, Fat People, and P/E Contrarian Investing and the Sports Illustrated Cover Jinx Accounting Practices, WorldCom’s Problems Chapter 6 - Options, Risk, and Volatility Options and the Calls of the Wild The Lure of Illegal Leverage Short-Selling, Margin Buying, and Familial Finances Are Insider Trading and Stock Manipulation So Bad? Expected Value, Not Value Expected What’s Normal? Not Six Sigma Chapter 7 - Diversifying Stock Portfolios A Reminiscence and a Parable Are Stocks Less Risky Than Bonds? The St. Petersburg Paradox and Utility Portfolios: Benefiting from the Hatfields and McCoys Diversification and Politically Incorrect Funds Beta—Is It Better? Chapter 8 - Connectedness and Chaotic Price Movements Insider Trading and Subterranean Information Processing Trading Strategies, Whim, and Ant Behavior Chaos and Unpredictability Extreme Price Movements, Power Laws, and the Web Economic Disparities and Media Disproportions Chapter 9 - From Paradox to Complexity The Paradoxical Efficient Market Hypothesis The Prisoner’s Dilemma and the Market Pushing the Complexity Horizon Game Theory and Supernatural Investor/Psychologists Absurd Emails and the WorldCom Denouement Bibliography Index Copyright Page Also by John Allen Paulos Mathematics and Humor (1980) I Think Therefore I Laugh (1985) Innumeracy: Mathematical Illiteracy and its Consequences (1988) Beyond Numeracy: Ruminations of a Numbers Man (1991) A Mathematician Reads the Newspaper (1995) Once Upon a Number: The Hidden Mathematical Logic of Stories (1998) To my father, who never played the market and knew little about probability, yet understood one of the prime lessons of both.
For those to whom this is not already Greek, we might say that µL, the mean costs of parking in the lot, and µS, the mean cost of parking on the street, are $13 and $11, respectively. Even though parking in the street is cheaper on average (assuming money was your only consideration), the variability of what you’ll have to pay there is much greater than it is with the lot. This brings us to the notion of standard deviation and stock risk. What’s Normal? Not Six Sigma Risk in general is frightening, and the fear it engenders explains part of the appeal of quantifying it. Naming bogeymen tends to tame them, and chance is one of the most terrifying bogeyman around, at least for adults. So how might one get at the notion of risk mathematically? Let’s start with “variance,” one of several mathematical terms for variability. Any chance-dependent quantity varies and deviates from its mean or average; it’s sometimes more than the average, sometimes less.
Statistics in a Nutshell by Sarah Boslaugh
Antoine Gombaud: Chevalier de Méré, Bayesian statistics, business climate, computer age, correlation coefficient, experimental subject, Florence Nightingale: pie chart, income per capita, iterative process, job satisfaction, labor-force participation, linear programming, longitudinal study, meta analysis, meta-analysis, p-value, pattern recognition, placebo effect, probability theory / Blaise Pascal / Pierre de Fermat, publication bias, purchasing power parity, randomized controlled trial, selection bias, six sigma, statistical model, The Design of Experiments, the scientific method, Thomas Bayes, Vilfredo Pareto
Centers for Disease Control and Prevention (CDC); definitions are drawn from Principles of Epidemiology in Public Health Practice, 3rd edition, a self-study course developed by the CDC for health care professionals. Pocket Dictionary of Statistics A glossary of terms used in business statistics, written by Hardeo Sahai and Anwer Khurshid and maintained on the website of the Higher Education division of the publisher, McGraw-Hill. Six Sigma Glossary A glossary of terms used in the Six Sigma quality control program, maintained on the website of MiC Quality, a company that provides Six Sigma training courses and educational materials. A Glossary for Multilevel Analysis A glossary of terms relevant to multilevel analysis, written by Dr. Ana V. Diez Roux, a Columbia University professor, and maintained on the website of the Pan American Health Organization. Probability Tables Tables for Probability Distributions Public domain tables for the standard normal distribution, t-distribution, F-distribution, and chi-square distribution, from the National Institute of Standards and Technology.
Figure 14-25. Control chart with increasing variability Figure 14-26. Control chart with a shock or outlier (single extreme value) Figure 14-27. Control chart with a change of level (upward shift of mean) Use of the standard deviation to define acceptable ranges of values for the outputs from a process is the source of the name for the Six Sigma program because sigma (σ) is the symbol for standard deviation. The idea behind the Six Sigma program is to reduce variability sufficiently that output in the range of ±3σ will still be acceptable to the customer. As discussed in Chapter 3, with normally distributed data, the probability of data points within particular ranges is known. The percentage of data from a normal distribution contained in different ranges, defined by standard deviations from the mean, is displayed in Figure 14-28.
Ironically, Deming’s approach was initially rejected in his native country (the United States) but enthusiastically embraced in Japan, where QI techniques were applied to manufacturing so successfully that Japanese companies were able to challenge and in some cases surpass the American supremacy in manufacturing. In response, American companies began adopting QI approaches in the 1980s; Motorola and General Electric are among the best-known early adopters. There are multiple approaches to QI, including a popular program known as Six Sigma (6σ), which is part of a general approach known as Total Quality Management (TQM). This section concentrates on the basics of QI, which are common to many such programs, and avoids getting into the specifics of jargon and acronyms of any particular program. It also concentrates on the statistical methodology used in QI, although the reader should bear in mind that most QI programs are multifaceted and include psychological and organizational strategies as well as statistical measurement and analytic techniques.
CIOs at Work by Ed Yourdon
8-hour work day, Apple's 1984 Super Bowl advert, business intelligence, business process, call centre, cloud computing, crowdsourcing, distributed generation, Donald Knuth, Flash crash, Googley, Grace Hopper, Infrastructure as a Service, Innovator's Dilemma, inventory management, Julian Assange, knowledge worker, Mark Zuckerberg, Nicholas Carr, rolodex, shareholder value, Silicon Valley, six sigma, Skype, smart grid, smart meter, software as a service, Steve Ballmer, Steve Jobs, Steven Levy, the new new thing, the scientific method, WikiLeaks, Y2K, Zipcar
Yourdon: Some of the numbers you gave me when I was here last time were staggering in terms of the millions of tests that you process. Wakeman: We have to do them all, they have to be done perfectly. So our objectives are 100 percent on-time, 100 percent accurate score reports. And the only way you can get there is to continually improve by learning from mistakes and making use of great quality programs such as Six Sigma. Great process plays a critical role as well, thus the reason we are implementing the ITIL v3 process framework. We continue to train staff in quality methods, defect detection, and continual improvement techniques. And it’s paying off. Defects continue to decrease and our customers are noticing. Yourdon: Interesting. Wakeman: We also embraced standardization in an effort to reduce complexity and reduce variation.
Wakeman: I’ll send you a copy of the scorecard, and an article that was written by Gartner about it. They actually did a best practice research note on our scorecard. Yourdon: You know, it’s interesting you mentioned this now. None of the other CIOs I’ve spoken to so far have mentioned scorecards. Wakeman: We worked really hard on getting a simple, one-page scorecard that defines what’s most important from a business perspective of what we do. And we track it. We use Six Sigma techniques to ensure our processes are in control. There is a control chart for each process metric. Yourdon: Interesting. Wakeman: Being a CIO of a big organization like mine, I’m always open to competition. There are many excellent firms out there that would like to run the IT department for ETS. It is my desire to be in a position where even if such a firm gains a sympathetic ear with ETS management I can say, “Compare us to anyone.
Ken Bohlen Vice President and CIO, Arizona Public Service Company (APS) Ken Bohlen is Vice President and Chief Information Officer for Arizona Public Service Company (APS), Arizona’s largest electric company. Based in Phoenix, APS serves more than 1.1 million customers and is one of the fastest-growing investor-owned electric utilities in the United States. Bohlen heads APS’s Information Technology department where he oversees the company’s vital electronic infrastructure and manages the digital challenges faced by a major electric utility. Bohlen also leads the Lean Six Sigma improvement process for APS. Before joining APS, Bohlen spent 10 years at Textron, Inc. where he served as Executive Vice President and Chief Innovation Officer. Prior to joining Textron, he served 25 years as an information/supply chain executive at both AlliedSignal Inc. and John Deere. Bohlen is a member of the American Production Inventory Control Society and a senior member of the Society of Manufacturing Engineers, Computer and Automated Systems Association.
The Outsiders: Eight Unconventional CEOs and Their Radically Rational Blueprint for Success by William Thorndike
Albert Einstein, Atul Gawande, Berlin Wall, Checklist Manifesto, choice architecture, Claude Shannon: information theory, collapse of Lehman Brothers, compound rate of return, corporate governance, discounted cash flows, diversified portfolio, Donald Trump, Fall of the Berlin Wall, Gordon Gekko, intangible asset, Isaac Newton, Louis Pasteur, Mark Zuckerberg, NetJets, Norman Mailer, oil shock, pattern recognition, Ralph Waldo Emerson, Richard Feynman, shared worldview, shareholder value, six sigma, Steve Jobs, Thomas Kuhn: the structure of scientific revolutions
If you had invested a dollar in GE stock when Welch became CEO, that dollar would have been worth an extraordinary $48 when he turned the reins over to his successor, Jeff Immelt. Welch was both an active manager and a master corporate ambassador. He was legendarily peripatetic, traveling constantly to visit GE’s far-flung operations, tirelessly grading managers and shuffling them between business units, and developing companywide strategic initiatives with exotic-sounding names like “Six Sigma” and “TQM.” Welch had a lively, pugnacious personality and enjoyed his interactions with Wall Street and the business press. He was very comfortable in the limelight, and during his tenure at GE, he frequently appeared on the cover of Fortune magazine. Since his retirement, he has remained in the headlines with occasional controversial pronouncements on a variety of business topics including the performance of his successor.
Over the last ten years, Berkshire has grown earnings per share significantly, and despite its size and diversity, the company operates with extraordinary efficiency—consistently ranking in the top quartile of the Fortune 500 for return on tangible assets. So, how does Buffett achieve these operating results? Beneath his avuncular exterior, Buffett is a deeply unconventional CEO, which is perhaps best seen by comparing his approach with that of Jack Welch (see table 8-3), who thrived at GE with a system that emphasized centralized strategic initiatives (Six Sigma, and so on), rotating CEOs, and a frenetic pace of travel and meetings. The contrast in management styles could hardly be more dramatic (although Buffett has deep admiration for Welch’s abilities). Buffett came to the CEO role without any relevant operating experience and consciously designed Berkshire to allow him to focus his time on capital allocation, while spending as little time as possible managing operations, where he felt he could add little value.
See stock performance Sias, John, 26, 32–33 Sie, John, 92, 93 Simmons, Dick, 114–115, 116, 117, 118, 124–125 Singleton, Henry, 1, 37–58, 107 —acquisitions by, 11, 39–41, 42 —background and education of, x–xi, 39, 41 —board members and, 54 —Buffett compared with, 56–58 —Buffett on, 37 —capital allocation by, xii, xiv, 38, 42, 55, 57, 207 —cash flow and, 11, 44–45 —closing of underperforming business unit by, 45 —decentralized approach of, 43–44, 57 —diversification by, 40–41, 151 —dividend policy of, 37–38, 46, 51, 57 —early career of, 39 —intelligent iconoclasm of, 4, 10–11 —investment philosophy of, 48–49, 50f, 57 —investor relations and, 53, 54, 57 —negotiating style of, 51–52 —nuts and bolts of approach of, 53–56 —spin-offs used by, 50–51, 96 —stock performance under, xi–xii, 38–39, 42, 42t, 47, 52–53, 52f —stock repurchase programs of, xi, 10, 45–48, 48t, 54–56, 142 —stock splits and, xi, 57 Sirius Broadcasting, 212 Six Sigma, viii, 190 Smith, Dick, 149–166 —acquisitions by, 8, 150–151, 165, 203 —asset sales by, 162, 164 —background and education of, 149–150, 151 —capital allocation by, 161, 162–163, 164, 165–166 —cash flow under, 150, 152, 157, 162–163, 165–166 —debt used by, 156, 162, 163, 164, 165 —diversification by, 150–151, 152, 154–155, 157 —divestitures by, 151 —investment with involvement strategy of, 154–155 —lease financing used by, 151–152 —nuts and bolts of approach of, 159–166 —office of, xvii, 161 —stock performance under, 150, 159, 160f —stock repurchase program of, 165 —tax minimization and, 163–164 —top executives and management of, 159–161, 166 Smith, Frank, 16–18, 24, 27 Smith, Phillip, 149–150, 151 Smith Barney, 157 Smits, Marcel, 147 Sokol, David, 188 Southeastern Asset Management, 121 Southwest Airlines, xviii Sparkman, J.
I Love Capitalism!: An American Story by Ken Langone
activist fund / activist shareholder / activist investor, Berlin Wall, Bernie Madoff, Bernie Sanders, business climate, corporate governance, East Village, fixed income, glass ceiling, income inequality, Paul Samuelson, Ronald Reagan, short selling, Silicon Valley, single-payer health, six sigma, VA Linux, Y2K, zero-sum game
Bob was all about the numbers, and his numbers were amazing. He slashed costs across the whole organization. He consolidated division executives’ responsibilities, which allowed him to cut a number of managers loose. He had a computerized inventory system installed at our Atlanta headquarters. There was a management method at GE called Six Sigma, a set of statistical tools for maximizing output and minimizing variability; to Jack Welch it was gospel, and Nardelli (whom some people used to call Little Jack) was Jack’s most passionate disciple. Nardelli brought Six Sigma to Home Depot. He also brought along his own general counsel, Frank Fernandez: I thought that was an unusual move, maybe a little worrying. He also brought in a former HR guy from General Electric, Dennis Donovan, a guy who lived on charts and percentages. Donovan was maniacal about these percentages: he always had a statistic to back up every conclusion.
See also Palm Beach, Florida Ford, Gerald, 226 Fort Bragg, 47, 49–52 Fortune, 27, 77, 99, 102, 220–21 front running, 108–10 fund managers, 67 G. H. Walker, 92, 95–96 Garden City, Michigan, 257–58 garment business, 64–67 Gault, Stanley, 183 General Electric (GE), 223, 256–57 board of, 181–82, 190, 205–10 CEO of, 181–82, 190, 205–10, 220–22 and Frank Blake, 226, 230, 232 imaging equipment of, 181–82 pension fund of, 67–69 Power Systems division of, 209, 213, 226 Six Sigma method of, 214 stock of, 208, 210, 255 General Motors, 56, 143, 147, 183–84 Georgia-Pacific, 82–83 Gillespie, Bob, 166–67 Giuliani, Rudy, 201 Glaspie, April, 172 Glassman, Jerry, 148 Glenn, Duke, 91–92 Glickman, Bob, 177–78, 182, 196 Goldman Sachs, 32, 41, 65, 71, 91–92, 97, 172–73, 187–88 Goodes, Mel, 116 Gould, Gordon, 164–66 Grace, Peter, 150 Grasso, Dick, 182–92, 195, 198–99, 201–3, 217, 261 Great Depression, 4, 52–53, 56, 244 Green, Roger, 91–92 Greenberg, Hank, 198 Greenville, South Carolina, 208 Grossman, Bob, 181–82, 196–97, 203, 265 Grossman, Maura, 194 Gruenstein, David, 193–94 Guggenheim Partners, 115 Handy Dan, 130–42, 145–56, 158 Harbison-Walker Refractories, 67–69, 89 Harlem Children’s Zone, 243 Hart, Maurice, 32 Hart, Mitch, 155–56 on Home Depot board, 211, 223, 227 works for Perot, 94, 96, 104, 107, 123 Hausman, Jack, 116 Headley, Russell, 13–15, 265 health-care field, 121–22, 124, 130, 135, 178.
Patrick’s Cathedral (New York City), 239, 243 Salem Leasing, 241, 252–53 salesmen, 54–64, 75–79, 105, 111, 125, 180, 250–51 Salomon Brothers, 90, 92, 112, 175, 247 Samuelson, Paul, 13 San Diego, California, 117–19, 121, 137, 144–45, 222 San Jose, California, 147–48 Sanders, Bernie, 249 Sands Point, Long Island, 117, 197 Sato, Steve, 121, 144, 235 Schapiro, Mary, 194–95, 200 Schenectady, New York, 209–10, 213 Schwartz, Alan, 114–15 Scott, Blaine, 98–99 Scruggs, Leonard Coe, 125 Sealy, 124, 139 Sears, 64, 254, 258 Seaver, Harry, 73 securities, 33, 41, 45, 50, 55, 57, 81, 117, 183, 192, 248 Securities and Exchange Commission (SEC), 59, 102–7, 119–21, 183 Security Pacific Bank (Los Angeles), 158–59 September 11, 2001, 185 Sexton, John, 197 Shearson, 163 Shearson, Hammill, 26–27, 69 Showalter, Paul, 17 Shroyer, Bruce, 78 Siemens, 181, 196–98 Sigma Chi fraternity, 13, 15–17, 24–25 Sigoloff, Sanford “Sandy,” 132, 138, 140–43, 145–52, 155 Silverman, Henry, 176–77 Singer, Paul, 223 Six Sigma management, 214 Skadden, Arps, 141 Sleeper, Matt, 24–26 Smilow, Joel, 179 Smith, Austin, 124 Smith, Bryan, 153 Smith, Derek, 168 Smutny, Rudy, 90, 108–10, 112, 122 Snowden, Herb, 124 socialism, 249–50 Somerville Lumber, 130 Southeast Bank (Miami), 155 Soviet Union, 46 Specter, Arlen, 171 Spector, Joe, 40–41 Spencer, Frank, 178–79 spirituality, 237–39, 242 Spitzer, Eliot, 187–88, 190–93, 195–96, 198–203, 217 Sporkin, Stanley, 105–7 stabilization rule, 103, 106–7 Standard Oil of New Jersey, 69–74 Standel, Paul, 124 statistics, 36–38 steel industry, 18–19, 56, 68–69, 184 Stein, Howard, 169 Steiner, Al and Phil, 58–63, 65 Steinhaus, Al, 166 Stern, Leonard, 175 Stirling Homex, 111–12 stock market, 161 analysts of, 71–75 “bear,” 124–25 “bull,” 192 computerization of, 183–84 downturns in, 52, 56–57, 59, 112, 188 rises in, 56, 192 See also New York Stock Exchange (NYSE) stocks common, 128–29, 155, 161 and “cram down,” 141 dividends for, 123, 144 inflating prices of, 187 large-cap, 255–56 nonqualified owners of, 119–21 options, 208, 210, 217, 219–20, 231, 245–46 preferred, 129, 155, 160–61 and proxy dispute, 119, 121, 223–25 publicly held, 131, 133–34, 139–40 secondary offerings of, 103 short selling of, 112–13 small float for, 112 strike price of, 208, 219–20, 246 value of, 93, 95, 98, 112–13, 131, 139–40, 144, 217 See also initial public offerings (IPOs); New York Stock Exchange (NYSE); specific companies subprime finance companies, 166 Summers, Bill, 189 Suozzi, Tom, 199 supply and demand, 14, 22–24, 57 Taft Stettinius & Hollister, 62–63 takeovers, unfriendly, 101–2, 150–51 Taussig, Andy, 224–25 taxes, 2, 86, 96–97, 138, 185, 200, 220, 252 Teague, Tommy, 241, 252–53 technology companies, 101, 118, 164, 167–68, 181, 185, 196–98, 244, 255–57.
The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing by Michael J. Mauboussin
Amazon Mechanical Turk, Atul Gawande, Benoit Mandelbrot, Black Swan, Checklist Manifesto, Clayton Christensen, cognitive bias, commoditize, Daniel Kahneman / Amos Tversky, David Brooks, deliberate practice, disruptive innovation, Emanuel Derman, fundamental attribution error, Gini coefficient, hindsight bias, hiring and firing, income inequality, Innovator's Dilemma, Long Term Capital Management, loss aversion, Menlo Park, mental accounting, moral hazard, Network effects, prisoner's dilemma, random walk, Richard Thaler, risk-adjusted returns, shareholder value, Simon Singh, six sigma, Steven Pinker, transaction costs, winner-take-all economy, zero-sum game, Zipf's Law
Consider two elements of a manufacturing business. The first is the actual manufacturing process. World-class manufacturers develop very clear processes that are highly repeatable and have very low error rates. There is a rich literature that applies statistical methods to manufacturing, with a goal of reducing costs.5 One well-known case in point is the Six Sigma method, designed to reduce variation in production. A company that achieves Six Sigma ability will have fewer than 3.4 defects for every million units of goods or services. General Electric and Honeywell, among others, have saved billions of dollars by implementing the method. Manufacturing is an activity that falls near the all-skill side of the continuum. A proper process using statistical control yields a favorable outcome a very high percentage of the time.6 The second element of a manufacturing business is simply deciding which products to manufacture.
This is also essential to understanding when intuition applies. See Eric Bonabeau, “Don't Trust Your Gut,” Harvard Business Review, May 2003, 116–123; David G. Myers, Intuition: Its Powers and Perils (New Haven, CT: Yale University Press, 2002). 5. Walter A. Shewhart, Statistical Method from the Viewpoint of Quality Control (1939; rept. New York: Dover, 1985). 6. Young Hoon Kwak and Frank T. Anbari, “Benefits, Obstacles, and Future of Six Sigma Approach,” Technovation 26, nos. 5–6 (May–June 2006): 708–715. 7. Christopher Chabris and Daniel Simons, The Invisible Gorilla: And Other Ways Our Intuition Deceives Us (New York: Crown, 2010), 83. 8. Philip E. Tetlock, Expert Political Judgment: How Good Is It? How Can We Know? (Princeton, NJ: Princeton University Press, 2005); Dan Gardner, Future Babble: Why Expert Predictions Are Next to Worthless, and You Can Do Better (New York: Dutton, 2011); and Dan Gardner and Philip Tetlock, “Overcoming Our Aversion to Acknowledging Our Ignorance,” Cato Unbound, July 2011. 9.
Korniotis, George M., and Alok Kumar. “Do Older Investors Make Better Investment Decisions?” Review of Economics and Statistics 93, no. 1 (February 2011): 244–265. Kovenock, Dan, Michael J. Mauboussin, and Brian Roberson. “Asymmetric Conflicts with Endogenous Dimensionality.” Korean Economic Review 26, no. 2 (Winter 2010): 287–305. Kwak, Young Hoon, and Frank T. Anbari. “Benefits, Obstacles, and Future of Six Sigma Approach.” Technovation 26, nos. 5–6 (May–June 2006): 708–715. Langer, Ellen J., and Jane Roth. “Heads I Win, Tails It's Chance: The Illusion of Control as a Function of the Sequence of Outcomes in a Purely Chance Task.” Journal of Personality and Social Psychology 32, no. 6 (December 1975): 951–955. Lee, Jennifer 8. “Who Needs Giacomo? Bet on a Fortune Cookie.” New York Times, May 11, 2005.
Money Mavericks: Confessions of a Hedge Fund Manager by Lars Kroijer
activist fund / activist shareholder / activist investor, Bernie Madoff, capital asset pricing model, corporate raider, diversification, diversified portfolio, family office, fixed income, forensic accounting, Gordon Gekko, hiring and firing, implied volatility, index fund, intangible asset, Jeff Bezos, Just-in-time delivery, Long Term Capital Management, merger arbitrage, NetJets, new economy, Ponzi scheme, post-work, risk-adjusted returns, risk/return, shareholder value, Silicon Valley, six sigma, statistical arbitrage, Vanguard fund, zero-coupon bond
It is particularly laughable how many people put themselves in the category of: ‘Can you believe it? XYZ happened – that is a one-in-a-million event.’ Equally self-deluding are those who insist rather more pretentiously that they were the victims of a ‘six-sigma event’. The only advantage of this expression is that it may scare away the follow-up question. Who wants to sound stupid by admitting that they don’t know what ‘six sigma’ means even if the guy in front of them has just cost them a fortune? Sigma (standard deviation) is a measure of how frequent various outlying events (or numbers) are relative to an average occurrence. A six-sigma event is something that should happen so infrequently that you might have heard about a guy who had heard about a guy who knows someone that it happened to; and that should happen about every 100 years. Yet it seems to happen to every other hedge fund that loses a lot of money.
The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone
airport security, Amazon Mechanical Turk, Amazon Web Services, bank run, Bernie Madoff, big-box store, Black Swan, book scanning, Brewster Kahle, buy and hold, call centre, centre right, Chuck Templeton: OpenTable:, Clayton Christensen, cloud computing, collapse of Lehman Brothers, crowdsourcing, cuban missile crisis, Danny Hillis, Douglas Hofstadter, Elon Musk, facts on the ground, game design, housing crisis, invention of movable type, inventory management, James Dyson, Jeff Bezos, John Markoff, Kevin Kelly, Kodak vs Instagram, late fees, loose coupling, low skilled workers, Maui Hawaii, Menlo Park, Network effects, new economy, optical character recognition, pets.com, Ponzi scheme, quantitative hedge fund, recommendation engine, Renaissance Technologies, RFID, Rodney Brooks, search inside the book, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Skype, statistical arbitrage, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Thomas L Friedman, Tony Hsieh, Whole Earth Catalog, why are manhole covers round?, zero-sum game
Wilke began his career at Andersen Consulting and then joined AlliedSignal, the manufacturing giant, which was later acquired by Honeywell. He quickly climbed the ranks to vice president, reporting directly to CEO Larry Bossidy and running the company’s $200-million-a-year pharmaceutical business. In AlliedSignal’s headquarters in Morristown, New Jersey, Wilke was immersed in the corporate dogma of Six Sigma, a manufacturing and management philosophy that seeks to increase efficiency by identifying and eliminating defects. Back in 1999, Scott Pitasky, an Amazon recruiter who later became the head of human resources at Microsoft, was put in charge of finding a replacement for Jimmy Wright. Pitasky had previously worked with Wilke at AlliedSignal, so he thought of his former colleague after concluding that Amazon needed someone who was smart enough to go toe to toe with Jeff Bezos, who delighted in questioning how everything was done.
Before Wilke joined Amazon, the general managers of the fulfillment centers often improvised their strategies, talking on the telephone each morning and gauging which facility was fully operational or had excess capacity, then passing off orders to one another based on those snap judgments. Wilke’s algorithms seamlessly matched demand to the correct FC, leveling out backlogs and obviating the need for the morning phone call. He then applied the process-driven doctrine of Six Sigma that he’d learned at AlliedSignal and mixed it with Toyota’s lean manufacturing philosophy, which requires a company to rationalize every expense in terms of the value it creates for customers and allows workers (now called associates) to pull a red cord and stop all production on the floor if they find a defect (the manufacturing term for the system is andon). In his first two years, Wilke and his team devised dozens of metrics, and he ordered his general managers to track them carefully, including how many shipments each FC received, how many orders were shipped out, and the per-unit cost of packing and shipping each item.
So when Bezos pulled Wilke out of an operating review in late 2006, Wilke wasn’t expecting to hear that that holiday season would be his last in the world of logistics. Bezos wanted Wilke to take over the entire North American retail division, and Wilke was charged with finding his own replacement. Wilke thought that Amazon’s progress in its FCs had plateaued, so instead of promoting from within the ranks of Amazon’s logistics executives, all of them molded, as he was, by the dogma of Six Sigma, Wilke went looking for someone with a fresh approach and additional international experience. The search led him to Marc Onetto, a former General Electric executive with a thick French accent and a gift for animated storytelling. Under Onetto’s watch, engineers once again rewrote elements of Amazon’s logistics software and devised a computer system, called Mechanical Sensei, that simulated all the orders coursing through Amazon’s fulfillment centers and predicted where new FCs would most productively be located.
Loonshots: How to Nurture the Crazy Ideas That Win Wars, Cure Diseases, and Transform Industries by Safi Bahcall
accounting loophole / creative accounting, Albert Einstein, Apple II, Apple's 1984 Super Bowl advert, Astronomia nova, British Empire, Cass Sunstein, Charles Lindbergh, Clayton Christensen, cognitive bias, creative destruction, disruptive innovation, diversified portfolio, double helix, Douglas Engelbart, Douglas Engelbart, Edmond Halley, Gary Taubes, hypertext link, invisible hand, Isaac Newton, Johannes Kepler, Jony Ive, knowledge economy, lone genius, Louis Pasteur, Mark Zuckerberg, Menlo Park, Mother of all demos, Murray Gell-Mann, PageRank, Peter Thiel, Philip Mirowski, Pierre-Simon Laplace, prediction markets, pre–internet, Ralph Waldo Emerson, RAND corporation, random walk, Richard Feynman, Richard Thaler, side project, Silicon Valley, six sigma, Solar eclipse in 1919, stem cell, Steve Jobs, Steve Wozniak, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tim Cook: Apple, tulip mania, Wall-E, wikimedia commons, yield management
Vail quarantined the team working on the technology for long-distance telephony in an office building in lower Manhattan. Like Bush, he tailored the systems. He “moved away from the rigid task allocation” of telephone operations and toward a similar loose-touch style. Both Bush and Vail understood intuitively decades ago what is repeatedly being rediscovered today. Efficiency systems such as Six Sigma or Total Quality Management might help franchise projects, but they will suffocate artists. When 3M, for example, inventor of Post-it Notes and Scotch Tape, brought in a high priest of Six Sigma as a new CEO in 2000, innovation plunged. It didn’t recover until well after he left and a new CEO dialed back the system. The new CEO described the efficiency system as a mistake: “You can’t say … well, I’m getting behind on invention, so I’m going to schedule myself for three good ideas on Wednesday and two on Friday.”
See also Endo, Akira Schure, Alex Science: The Endless Frontier (Bush report) scientific method as the mother of all loonshots path to, mirroring path to heliocentrism scientific revolution pan-European symphony as precursor to industrial reliance on Chinese technology, Islamic astronomy, Indian mathematics role of Kepler vs. others why England; why Western Europe, see world history (comparative) Sculley, John serendipity, role of Shen Kuo Tycho compared with Sikorsky, Igor (S-38, S-42) “simple, but not simplistic” models Sir Isaac Newton’s Philosophy Explain’d for the Use of the Ladies Six Degrees of Separation Six Sigma Slumdog Millionaire small-world networks Smith, Adam preference for work on ethics use of alliteration Smith, Alvy Smith, Joseph Soft equity definition of example at DARPA and Napoleon’s ribbon and open innovation solar eclipse, as natural experiment Song emperor, Song dynasty Sprat, Thomas SRT (spirit, relationships, time). See also rules for loonshot champions Sputnik 1 Stalin, Joseph Star Trek II: The Wrath of Khan Star Wars statins first patient to receive first (Endo): mevastatin second (Merck): lovastatin subsequent: Crestor, Lipitor, Zocor See also Endo; heart disease; Merck steam engine Stimson, Henry streaming video (Netflix, Amazon) Strogatz, Steven structure (in contrast with culture) need for both in world history (vs. race, culture, climate, or geography)n Susskind, Leonard Sutherland, Ivan symmetry-breaking transitions system mindset and chess definition of encouraged by external partnerships and open innovation in organizations See also Bush-Vail rule #3; rules for loonshot champions Taylor, Bob Taylor, Hoyt Taylor, John tea-temperature question Teller, Edward Tesla, Nikola Thaler, Richard Thiel, Peter the Three Deaths of the loonshot definition of and incentives See also angiogenesis; beta-blockers; Land (instant-print); statins 3D photography, movies 3M Time tournament theory Toy Story traffic flow and phase transitions transistor Trippe, Juan and Boeing 747 and dangerous, virtuous franchise cycle, see cycle, franchise and Lindbergh as master P-type innovator and saving China from communism, request from Chiang Kai-shek See also Pan Am; Moses Trap Truman, Harry Tubby the Tuba (animated film) tug-of-war (two opposing forces) at the heart of phase transitions inside companies two-tier employment two types of loonshots definition of see also P-type loonshots; S-type loonshots; blind side Tycho Brahe Shen compared with U-2 spy plane Uber U-boats (submarines) Churchill and FDR on the threat of See also Battle of the Atlantic “ugly babies and the Beast” compared with loonshots and franchises V-1 and V-2 rockets (German) Vagelos, Roy Vail, Theodore and equal-opportunity respect and rescue operations See also Bell Labs; Bush-Vail rules Vkontakte (Russian social network) Walmart Walton, Sam Warhol, Andy Watson, James Watson-Watt, Robert Watts, Duncan Watts-Strogatz paper (1998) Wegman, William (dogs) Welles, Orson (The Third Man) Wickert, Doug wisdom of crowds world history (comparative) first-appearance vs. adoption question global (Europe) vs. local (England) question natural experiment, Haiti and Dominican Republic Needham question (why not China) structure vs. race, culture, climate, or geographyn World War II, see Battle of the Atlantic; radar; Nazi Germany; U-boats Wozniak, Steve Xerox PARC.
Business Lessons From a Radical Industrialist by Ray C. Anderson
addicted to oil, Albert Einstein, banking crisis, business cycle, carbon footprint, centralized clearinghouse, clean water, cleantech, corporate social responsibility, Credit Default Swap, dematerialisation, distributed generation, energy security, Exxon Valdez, fear of failure, Gordon Gekko, greed is good, Indoor air pollution, Intergovernmental Panel on Climate Change (IPCC), intermodal, invisible hand, late fees, Mahatma Gandhi, market bubble, music of the spheres, Negawatt, new economy, oil shale / tar sands, oil shock, old-boy network, peak oil, renewable energy credits, shareholder value, Silicon Valley, six sigma, supply-chain management, urban renewal, Y2K
They find it to be chaotic—no two sticks, no two stones, no two leaves, no two square feet are the same. Yet there is a pleasant harmony in the disorder. They return to their studios and design a carpet tile in which no two tile faces are alike. All are similar, but none are identical, contrary to the prevailing industrial paradigm that demands cookie-cutter perfection from every mass-produced item—Six Sigma uniformity. Nature, the inspiration, is anything but uniform. She doesn’t know Six Sigma, but she is very effective. This new product is given a name, Entropy,® and in a year and a half it rises to the top of the bestseller list, faster than any other product ever has before. I have seen another design team dream up and address a weird challenge: How does a gecko cling upside down to a ceiling? The question arises in a session intended to figure out how to completely eliminate glue from the installation of carpet tiles.
Boone Pike, Judy Pinchot, Gifford and Libba Play to Win team-building exercises pollutants in manufacturing list of, from the old Interface substitutes for polylactic acid (PLA) population, environmental impact of population crash positive trends potato chips, environmentally sound production of poverty, global, challenge of power purchasing agreement (PPA) precautionary principle president actions that can be taken without congressional approval to mitigate climate change executive powers of leadership from new, advice for Presidential Climate Action Project (PCAP) President’s Council on Sustainable Development (PCSD) Price-Anderson Act problems, interconnected problem-solving, Einstein on Procter & Gamble public-private partnerships PVCs PZEV vehicles QUEST: Quality Utilizing Employees’ Suggestions and Teamwork Quinn, Daniel Ishmael rail, transportation by rainfall, run off from eroded land raw materials, reducing the amount and weight of RecycleBank RecycleBank Dollars recycled materials contaminated, expense of using price of replacing virgin raw materials recycling advantages of closed-loop by consumers incentives for nature’s way 100 percent goal ReEntry 2.0 regulations accused of shackling the free market effect of slowing environmental harm lag behind science regulators, keeping them at bay, with sustainability promise regulatory compliance reindeer, population crash of religion failure of institutions to solve environmental problems and science, conflict renewable energy goal of 100 percent renewable energy credits (REC) Re:Source Americas resources assumption that they are unlimited efficient use of peaking and decline of running out of respect, vs. autocratic management Riordan, Tim Rittenhouse, William Riverkeeper Robèrt, Karl-Henrik The Natural Step Rockland React-Rite Interface facility Rogers, Jim Roosevelt, Franklin Roosevelt, Theodore Roper, Anita Ruben, Andy St. Matthew Island (off Alaska) sales associates/employees, car travel by Sam’s Club SARA 313 chemicals Saudi Arabia Scherpenzeel (Holland) Interface facility science, and religion SC Johnson Scott, Graham Scott, Lee scrubbing sea, transportation by Seiko Epson self-interest sequestering of carbon Serreze, Mark Shaw Industries sick building syndrome Six Sigma Small Business Administration SmartWay Transport program (EPA) Smith and Hawken smokestacks cutting emissions from inventory of (Interface) inventory of emissions from (Interface) social equity, measuring social sustainability Sociometrics solar cells solar concentrators solar energy cost of not a bubble, but a revolution Solar-Made carpet solar photovoltaics, growth of industry solar units, on customers’ roofs solid waste, volume, from Interface factories “Someday they’ll send people like me to jail” South Bronx Southern California Gas Company species extinction Speth, Gus spirituality, and sustainability stack scrubbers Stahel, Walter stakeholders sensitizing them Staples state governments, environmentalism of stewardship of the earth (Biblical) Stigson, Björn STMicroelectronics Stonyfield Farm stuff, infatuation with Subaru of America subprime mortgage crisis suggestions from employees, rewards for sun, terawattage of Superfund Amendment and Reauthorization Act (SARA) supersaturated solutions sustainability competitive edge and goodwill from definition of framework for pursuing how to start planning for ignoring the laws of and profit seven paths to skepticism about and survival training course in university courses in sustainability programs, so-called, of some companies “Sustainable America: A New Consensus” sustainable society Sustainable South Bronx Sustainable Strategies Group SUVs TacTiles take-make-waste economy Tandera, Giulio Tau Beta Pi team-building exercises TEAM-UP program (DOE) technology environmental impact of improvements in, from market stimulus over-reliance on technophiles vs. technophobes technosphere TerraChoice Environmental Marketing textile industry thinking in the round third parties, damage to Thomas, Glenn, poem by, “Tomorrow’s Child” Thoreau, Henry David three crises (environmental, financial, and security) TI:GER program Toxic Chemical Elimination Team (Interface) toxic emissions, five principles for eliminating toxic minerals, that never should have been extracted Toyota traditional-craft skills transportation cost of GHG cost of transportation system, need to reengineer trash pickup trees nature’s technology of planted for environmental restoration planted to offset CO2 emissions Trees for Travel(tm) triple bottom line trucks efficiency of GHG emissions loading of transportation by trust, need for, in banking tyrants, in oil-producing states, American tolerance of unemployed people Unilever United Kingdom, Interface facilities in United States balance of trade economy, importance of oil to United States Green Building Council (USGBC) University of California University of Pennsylvania, Wharton School, Institute for Global Environmental Leadership University of Texas at Houston unsustainability, examples of UPS Ground vs.
Data-Ism: The Revolution Transforming Decision Making, Consumer Behavior, and Almost Everything Else by Steve Lohr
"Robert Solow", 23andMe, Affordable Care Act / Obamacare, Albert Einstein, big data - Walmart - Pop Tarts, bioinformatics, business cycle, business intelligence, call centre, cloud computing, computer age, conceptual framework, Credit Default Swap, crowdsourcing, Daniel Kahneman / Amos Tversky, Danny Hillis, data is the new oil, David Brooks, East Village, Edward Snowden, Emanuel Derman, Erik Brynjolfsson, everywhere but in the productivity statistics, Frederick Winslow Taylor, Google Glasses, impulse control, income inequality, indoor plumbing, industrial robot, informal economy, Internet of things, invention of writing, Johannes Kepler, John Markoff, John von Neumann, lifelogging, Mark Zuckerberg, market bubble, meta analysis, meta-analysis, money market fund, natural language processing, obamacare, pattern recognition, payday loans, personalized medicine, precision agriculture, pre–internet, Productivity paradox, RAND corporation, rising living standards, Robert Gordon, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, speech recognition, statistical model, Steve Jobs, Steven Levy, The Design of Experiments, the scientific method, Thomas Kuhn: the structure of scientific revolutions, unbanked and underbanked, underbanked, Von Neumann architecture, Watson beat the top human players on Jeopardy!
But it soon became clear to the McKesson executives that the larger opportunity was being able to capture a “big picture” view of their business. In consultant circles, it is called the “end-to-end” view. It is instructive to explain why McKesson was a promising test bed. McKesson is not just any company. It is, Katircioglu observes, “a well-oiled machine,” efficient and focused. McKesson was early to embrace Six Sigma, a system of statistical measurement and methods for eliminating product defects and streamlining business operations. It invested heavily in scanning, sensor, and software technology. Starting in the 1990s, McKesson invested heavily in foundational information technology. First came the migration from paper to digital records and tracking, with the adoption of bar-code scanning and radio tags on products.
Gallo’s use of, 123–33 Predix, 136 PricewaterhouseCoopers, 44 Principles of Scientific Management, The (Taylor), 208 Privacy Act (1974), 185 privacy concerns, 183–206 balancing privacy and data collection, 202–6 big data and personally identifying information, 187–92 cameras and, 183–86 data correlation and, 113 discrimination by statistical inference, 192–95 early computers and, 185–87 marketing and use of data, 195–97 social network data collection and, 197–202 productivity paradox, of computers, 72–75 Profiles in Performance: Business Intelligence Journeys and the Roadmap for Change (Dresner), 76 psycholinguistics, used for studying tweets, 199 Pulleyblank, William, 45–46, 47–48, 49 quantitative-to-qualitative transformation, data and, 7–8 “reality mining,” 206 Reisman, David, 155 Richardson, Tara, 106–7 Riedl, Paul, 156 Rock Health, 16 Rogers, Matt, 144 romantic relationships, social network research and, 87–88 Rometty, Virginia Haydock and, 156 IBM’s big data strategy and, 9, 42–45, 46, 47, 53–56 Rosenn, Itamar, 89–90, 94 Rotenberg, Marc, 204–5 Rothschild, Jeff, 86, 91–92, 98 Rubinsteyn, Alex, 180 Ruh, William, 134, 135–36 Sabre (Semi-Automated Business Research Environment), 46 Sage Bionetworks, 101–2, 170–71 SAS Institute, 52 satellite imagery, precision agriculture and, 129–32 Schadt, Eric background, 172–73 at Mount Sinai, 171–72, 173–74, 175 Sage Bionetworks and, 102 Schrage, Michael, 197 Science, 108 scientific management (Taylorism), 207–8 Seay, Mike, 188–89 Second Machine Age, The (Brynjolfsson and McAfee), 119–20 Shah, Rachana. See Fischer, Rachana Shah Singapore, traffic management in, 47–48 Singer, Natasha, 190 “six degrees of separation,” 87 Six Sigma system, 62 Sloan School of Management, at MIT, 71 “slow” thinking, 66–67 Smarr, Larry, 134, 214, 215 Smarter Planet campaign, of IBM, 48–53, 62, 128 smartphone cameras, privacy concerns and, 186 Smeall, Andrew, 26 Snow, C. P., 5–6 Snyder, Steven, 165–67, 170 social networks, research using human behavior and, 86–94 retail use, 153–62 spread of information and, 73–74 Twitter posts and, 197–202 see also privacy concerns Social Security numbers, data used to predict person’s, 187–88 software, origin of term, 96 Solow, Robert, 72 Speakeasy programming language, 160 Spee (Harvard club), 28–30 Spohrer, Jim, 25 Stanford University, 211–12 Starbucks, 157 Stockholm, rush-hour pricing in, 47 storytelling, computer algorithms and, 120–21, 149, 165–66, 205, 214 structural racism, in big data racial profiling, 194–95 Structure of Scientific Revolutions, The (Kuhn), 175 Sweeney, Latanya, 193–95 System S, at IBM, 40 Tarbell, Ida, 208 Taylor, Frederick Winslow, 207–8 Tecco, Halle, 16, 25, 28, 168–69 Tetlock, Philip, 67–68 thermostats, learning by, 143–45, 147–53 Thinking, Fast and Slow (Kahneman), 66–67 toggling, 84 Truth in Lending Act (1968), 185 T-shaped people, 25 Tukey, John, 96–97 Turing, Alan, 178–79 Tversky, Amos, 66 Twitter, 85 posts studied for personal information, 197–202 “Two Cultures, The” (Snow), 5–6 “universal machine” (Turing’s theoretical computer), 179 universities, data science and, 15–16, 97–98, 211–12 Unlocking the Value of Personal Data: From Collection to Usage (World Economic Forum), 203 “Unreasonable Effectiveness of Data, The” (Norvig), 116 use-only restrictions, on data, 203 Uttamchandani, Menka, 77–78, 80, 212 VALS (Values, Attitudes, and Lifestyles), 155 Van Alstyne, Marshall, 74 Vance, Ashlee, 85 Vargas, Veronica, 159–60 Varma, Anil, 136–37 Veritas, 91 vineyards, data used for precision agriculture in, 123–33, 212 Vivero, David, 29 Vladeck, David, 203, 204 von Neumann, John, 54 Von Neumann architecture, 54 Walker, Donald, 2, 63, 212 Walmart, 104, 154 Watson, Thomas Jr., 49 Watson technology, of IBM, 45, 66–67, 120, 205 as cloud service, 9, 54 Jeopardy and, 7, 40, 111, 114 medical diagnoses and, 69–70, 109 Watts, Duncan J., 86 weather analysis, with big data, 129–32 Weitzner, Daniel, 184 “Why ask Why?”
Eat People: And Other Unapologetic Rules for Game-Changing Entrepreneurs by Andy Kessler
23andMe, Andy Kessler, bank run, barriers to entry, Berlin Wall, Bob Noyce, British Empire, business cycle, business process, California gold rush, carbon footprint, Cass Sunstein, cloud computing, collateralized debt obligation, collective bargaining, commoditize, computer age, creative destruction, disintermediation, Douglas Engelbart, Eugene Fama: efficient market hypothesis, fiat currency, Firefox, Fractional reserve banking, George Gilder, Gordon Gekko, greed is good, income inequality, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, Joseph Schumpeter, Kickstarter, knowledge economy, knowledge worker, libertarian paternalism, low skilled workers, Mark Zuckerberg, McMansion, Netflix Prize, packet switching, personalized medicine, pets.com, prediction markets, pre–internet, profit motive, race to the bottom, Richard Thaler, risk tolerance, risk-adjusted returns, Silicon Valley, six sigma, Skype, social graph, Steve Jobs, The Wealth of Nations by Adam Smith, transcontinental railway, transfer pricing, wealth creators, Yogi Berra
In a world where all we do is wash each other’s cars, no wealth would be created. Fair enough. The economic measure of productivity is output per worker hour. Economists use fancy terms like “capital stock,” which are just tools to augment workers to increase their output. Fishing net. An ox and plow. Or an assembly line. And, I don’t know, even robots, I guess. More output from fewer hours produces wealth. Companies spent millions on factory gurus, Six-Sigma-smoking consultants from the 1950s all the way through the 1970s to help them squeeze gains out of workers. That’s what drove the stock market and wealth creation for several decades. That’s all fine in an Industrial Age when you can actually measure worker output in the form of widgets per day, cars off the line per hour, and the like. But in a service economy filled with knowledge workers flitting around trying to produce more, uh, banking or more insurance or more satisfaction at McDonald’s, the productivity game isn’t so easy.
Roosevelt, Teddy Rosendahl, Carl Rowes, Jeff Rules for Free Radicals abundance versus scarcity application of edge of network, intelligence at exceptionalism, embracing horizontal integration humans, adapting technology to jobs, eliminating with technology market entrepreneur, being markets versus managers money/highest returns connection productivity and wealth scale, importance of scarcity, creating with virtual pipe zero marginal costs, use of Rules for Radicals (Alinsky) Rupert, Johann SAT (Scholastic Aptitude Test) Say, Jean-Baptiste Say’s law Scale elements of historical examples of lack of recognizing tech examples of Scarcity. See Abundance and scarcity, and ad sales Schmidt, Eric Schumpter, Joseph Self-actualization Servers types of Services, and Creators Shaw, George Bernard Shutterfly Siemens, Karl Wilhelm Six-Sigma Skype Slackers Sloppers Smith, Adam Social networking Facebook, building virtual pipe of Software, open-source Soviet Union collapse former, stock exchanges of Spangler, James Spencer, Percy L. Spoerl, Joseph S. Sponges Standard of living and economy and wealth Stanford, Leland Stevens, Ted Stock markets benefits of as decision mechanism efficiency of of former Soviet Union investors, listening to operation of peak and crashes price discovery by role in capitalist system Stroud, John M.
Competing on Analytics: The New Science of Winning by Thomas H. Davenport, Jeanne G. Harris
always be closing, big data - Walmart - Pop Tarts, business intelligence, business process, call centre, commoditize, data acquisition, digital map, en.wikipedia.org, global supply chain, high net worth, if you build it, they will come, intangible asset, inventory management, iterative process, Jeff Bezos, job satisfaction, knapsack problem, late fees, linear programming, Moneyball by Michael Lewis explains big data, Netflix Prize, new economy, performance metric, personalized medicine, quantitative hedge fund, quantitative trading / quantitative ﬁnance, recommendation engine, RFID, search inside the book, shareholder value, six sigma, statistical model, supply-chain management, text mining, the scientific method, traveling salesman, yield management
Similarly, CEMEX, the global cement company, uses analytics to quantify expected benefits from increased market share and improved profitability by enforcing its processes and systems on the takeover target. Manufacturing, Operations, and Quality Analytics One analytical domain that has long existed in companies is operations, especially manufacturing and quality. This was the original home, for example, of Total Quality Management and Six Sigma, which, when done seriously, involve detailed statistical analysis of process variations, defect rates, and sources of problems. Manufacturing and quality analytics have had an enormous impact on the global manufacturing industries, but their impact has been less revolutionary for service industries and nonmanufacturing functions within manufacturing companies. For the great majority of organizations, it seems difficult to summon the required levels of discipline and rigor to apply statistical quality control or even a strong process orientation outside of manufacturing.
For years, operations management specialists have created algorithms to help companies keep minimal levels of inventory on hand while preventing stock-outs—among other supply chain challenges. And manufacturing firms have long relied on sophisticated mathematical models to forecast demand, manage inventory, and optimize manufacturing processes. They also pursued quality-focused initiatives such as Six Sigma and kaizen, tools for which data analysis is an integral part of the methodology. Customer relationship management, however, seems less amenable to analytical intervention—at least, that might be the common perception. The traditional focus in sales has been on the personal skills of salespeople—their ability to form long-term relationships and to put skeptical potential customers at ease. And marketing has long been viewed as a creative function whose challenge has been to understand customer behavior and convert that insight into inducements that will increase sales.
The Future of Technology by Tom Standage
air freight, barriers to entry, business process, business process outsourcing, call centre, Clayton Christensen, computer vision, connected car, corporate governance, creative destruction, disintermediation, disruptive innovation, distributed generation, double helix, experimental economics, full employment, hydrogen economy, industrial robot, informal economy, information asymmetry, interchangeable parts, job satisfaction, labour market flexibility, Marc Andreessen, market design, Menlo Park, millennium bug, moral hazard, natural language processing, Network effects, new economy, Nicholas Carr, optical character recognition, railway mania, rent-seeking, RFID, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, six sigma, Skype, smart grid, software as a service, spectrum auction, speech recognition, stem cell, Steve Ballmer, technology bubble, telemarketer, transcontinental railway, Y2K
Tasks are broken into modules, examined and reworked to reduce errors, improve consistency and speed things up. In both industries, the influence in India of ge, which has applied the “six sigma” method of quality improvements to its industrial businesses for years, is pervasive. Mr Roy used to run gecis, which was then ge’s bpo captive but is now being sold. It had become “too fat and happy”, according to one Indian competitor. One of the founding investors in Mr Talwar’s company is Gary Wendt, the former head of ge’s financial businesses. Wipro’s chairman, Azim Premji, has introduced so many of ge’s techniques to his company that the firm is known as India’s “baby ge”. Certainly, “Wiproites” seem to share the intensity of ge’s employees. Six-sigma “black belts” hurtle about Wipro’s 100-acre technology campus in Bangalore, improving everything from software coding to the way the company cleans its toilets.
O’Neil, David 73 O’Neil, John 28, 30 OneSaf 197 online banks 37 online shopping viii, 37 open standards 7, 10, 22–7, 31, 38, 43, 85–7, 115, 118–19, 152 operating systems 9, 10, 23–5, 31, 38, 85, 101, 109 operators, mobile phones 157–61, 162–9 Opsware 8, 15 optical-character recognition 121 Oracle 5, 20–2, 33, 38, 39–40, 46, 56, 62, 86, 243 Orange 157–8 organic IT 13–16, 88 original design manufacturers (ODMs), mobile phones 156–7 O’Roarke, Brian 192 O’Roarke, John 96 Orr, Scott 187 orthogonal frequency-division multiplexing (OFDM) 212–13, 215–17 INDEX Otellini, Paul 11, 95 outshored developments, software 38, 115, 138–9 outsourcing viii, 9, 19–20, 22, 38, 68–9, 71, 72, 88–92, 112–46, 158–60 see also globalisation barriers 121–2, 143 concepts 112–46 costs 112–24, 131–5, 140–3 cultural issues 122, 142 Europe 140–6 historical background 119–20, 125–6, 133 India 38, 109, 112–15, 119–22, 125–35, 137–8, 140–6 legal agreements 121–4 mobile phones 155–6, 158–60 opportunities 144–6 protectionists 140–6 reasons 123–4, 143 services 113–30 social outsourcing 143 “overshoot” stage, industries 9, 10–11, 109 overview vii–x, 6–7 Ovi, Alessandro 275–6 Oxford GlycoSciences 243 P Pacific Cycle 140 Page, Larry 9 Pait, Rob 207 Palladium 74, 76 Palm Pilot 150 Palmisano, Samuel 22 Paltrow, Gwyneth 173 Panasonic 156 Papadopoulos, Greg 14, 78–9, 83–4, 91 Papadopoulos, Stelios 237 Parker, Andrew 143 Parks Associates 96, 203 Parr, Doug 319 particulate filters 296–7 passwords 53, 58–61, 67, 96–7 patents, nanotechnology 321–6, 329 Patriot Act, America 35 PCs 9–16, 78–81, 82–110, 151, 171–3, 202–18 see also digital homes; hardware commoditisation issues 9–16, 132–5, 203 complexity issues 78–81, 82–110 screen sizes 100–1 UWB 214–18 Wi-Fi 209–18 PDAs see personal digital assistants Peck, Art 203 PentaSafe Security 60 Pentium chips 199–200 PeopleSoft 39, 86, 119, 126, 132 Perez, Carlota 5–6, 134 performance issues see also processing power; returns cars 291–8 Cell chips 198–200 cost links 29–30 Perlegen 244 personal digital assistants (PDAs) 151, 277, 279 see also handheld computers personal video recorders (PVRs) 203, 205–6 perverse incentives, security issues 61–2 Pescatore, John 55 Pfizer 69, 240, 247, 312, 315 pharmaceutical companies 239–40, 241–50, 312 PHAs 260 Philippines 130 Philips 120, 217 “phishing” 76, 89 phonograph 82, 84 photo-voltaic cells 280 photos ix, 78, 95, 101, 179–83 Physiome 248 Picardi, Tony 79 Pick, Adam 156 Pink Floyd 225 Piper, H. 292 Pittsburgh convention centre 304 Pivotal 187 plasma screens 230–2 plastics 238–9, 259–64 PlayStation 191–2, 199–200, 206–7 plug-and-play devices 78 plug-in hybrid cars 295–6 Poland 120 police involvement, security breaches 72 polio 265 politics 32–5 see also governments Pollard, John 157 pollution 275, 296–7, 299–304, 319 Pop Idol (TV show) 225 Pope, Alexander 267 Porsche 292 “post-technology” period, IT industry vii, 5–7 Powell, Michael 98, 206 power grids 233, 285–90 PowerPoint presentations 4–5, 107 Predictive Networks 337 Presley, Elvis 225 prices, downward trends viii, 4–7 PricewaterhouseCoopers 38 printers 78, 96 privacy issues 27, 34, 42–8, 179–83 see also security... mobile phones 179–83 processing power see also computer chips 353 THE FUTURE OF TECHNOLOGY exponential growth 4–7, 8–14 Proctor, Donald 106 Prodi, Romano 274–5 profits, future prospects 7, 17–18, 37–40 proprietary technology 24, 26, 80, 86 protectionists, outsourcing 140–6 proteins, biotechnology 241–64 protocols, complexity issues 86 Proxim 210 Prozac 315 PSA Peugeot Citroën 293, 296–7 PSP, Sony 191–3 public accounts 44 Pullin, Graham 177–8 PVRs see personal video recorders Q Qualcomm 164 quantum dots 312, 317, 322, 325 R radiation fears, mobile phones 176 radio 34–5, 36, 39, 94–5, 108, 155–61, 164, 209–18, 223 see also wireless... chips 155–61, 164 “garbage bands” 209–10, 215 music industry 223 spectrum 34–5, 94–5, 209–18 UWB 96–7, 214–19 Radjou, Navi 333–4 railway age vii, 5, 7, 23, 36, 39, 134 Raleigh, Greg 211 RAND 195 rationalisation exercises 31 RCA 108–9, 206, 208, 220, 315 real-world skills, gaming comparisons 194–7 RealNetworks 203 rechargeable batteries 280–4 Recourse Technologies 62–3 Reed, Philip 177 regulations 35, 44, 209–10, 326–9 see also legal issues relational databases 101–2 reliability needs viii, 42–8 religion 19 renewable energy 275–6, 286, 289, 300, 310, 315 ReplayTV 205 Research in Motion (RIM) 152–3 resistance problems, employees 31 return on investment (ROI) 30–1 returns 20, 29–31, 329 see also performance issues risk 20, 30, 329 revenue streams biotechnology 237–8, 241–2 354 gaming 189–90, 191 GM 251–2 mobile phones 151, 154–5, 157, 162–3, 165–6, 174 nanotechnology 321–6 revolutionary ideas vii–viii, 5–7, 13–14, 36–40, 80–4, 107–10, 116, 134, 151–3, 198–200, 236–40, 326–9 RFID radio tags 39, 94–5 Rhapsody 203 Ricardo 296–7 Riley, James, Lieutenant-Colonel 195–7 RIM see Research in Motion ringtones 165–6 RISC chips 200 risk assessments 70–4, 76 attitudes 18 handling methods 71 insurance policies 71–3 management 70–4 mitigation 71–3 outsourced risk 71, 72, 88–92 returns 20, 30, 329 security issues 42–8, 49–69, 70–4 RNA molecules 241–2, 249–50, 265 Robinson, Shane 15–16 robotics x, 233, 316, 332–5 Roco, Mihail 309 Rodgers, T.J. 32 Rofheart, Martin 216–17 Rogers, Richard 300 ROI see return on investment Rolls, Steve 121 Romm, Joseph 298 Roomba 332, 334–5 “root kit” software 51 Rose, John 226 Roslin Institute 256 Roy, Raman 125–8 Russia 115, 130, 140, 142, 145, 319 Ryan, John 312 S S700 mobile phone 171 Saffo, Paul 83–4, 103, 182 Salesforce.com 19, 20, 84, 91–2, 109 Samsung 158–60, 181, 208, 217, 231, 277 Santa Fe Institute 39 SAP 22, 38, 86, 119, 126, 132 satellite television 205 Saudi Arabia 180 scandals 28 scanning tunnelling microscope (STM) 306 SCC see Sustainable Computing Consortium Schadler, Ted 95, 97 Schainker, Robert 285, 289 INDEX Scherf, Kurt 96–7 Schmelzer, Robert 91 Schmidt, Eric 9, 35, 36–8 Schmidt, Nathan 66 Schneider National 29–31 Schneier, Bruce 43, 58, 61–2, 65, 70, 73–4 schools, surveillance technology 181 Schwartz, John 46 Schwinn 140, 143 Scott, Tony 43, 68–9 screen sizes 100–1 screws 23–4 Seagate Technology 207 seamless computing 96–7 Sears, Roebuck & Co 36 Securities and Exchange Commission 321 security issues viii, 25–7, 32–5, 42–8, 49–74, 86–7 see also privacy... airport approach 68–9 anti-virus software 50–1, 60, 67–8 biometric systems 60, 64–5, 71, 74 breaches 43–4, 46, 49–52, 62, 72–3 civil liberties 74 concepts 42–74, 86–7 costs 45–6, 50–1, 62, 70–4 employees 58–63, 69 encryption 53–4 firewalls 51–3, 58, 60, 62, 66–8, 71, 86–7 hackers 4, 43, 47, 49, 51–3, 58–63 handheld computers 67–8 honeypot decoys 62–3 human factors 57–63, 69 identity management 69 IDSs 51, 53–4, 62, 87 impact assessments 70–1, 76 insider attacks 62–3 insurance policies 71–3 internet 35, 42–8, 49–57, 61–2, 66, 66–7, 71, 73–6, 179–83 job vacancies 46 joint ventures 67 major threats 35, 42, 43, 47, 49–63, 66–9 management approaches 60–3, 69 Microsoft 54–6, 72, 74, 76 misconceptions 46–8 networks 42–8, 49–65, 66–9 passwords 53, 58–61, 67, 96–7 patches 56–7, 76 perverse incentives 61–2 police involvement 72 risk assessments 70–4, 76 standards 71–3 terrorism 35, 42, 43, 50, 65, 74, 75–6, 265–6 tools 49–63, 86–7 viruses 45, 47, 49–56, 59–60, 67–8, 74, 86, 89 Wi-Fi 66–7, 93 sedimentation factors 8–9, 84 segmentation issues, mobile phones 167–9 self-configuration concepts 88–9 Sellers, William 23 Seminis 254 Sendo 160 Senegal 182 September 11th 2001 terrorist attacks 35, 42, 43, 50, 65, 75 servers 9–16, 37–8, 62–3, 85–7, 132–3, 203 services industry 14, 17–22, 25–7, 31, 36–40, 80, 88–92, 109, 113–35, 203 see also web services outsourcing 113–46 session initiation protocol (SIP) 104–6 sewing machines 82, 84 SG Cowen 237 shapes, mobile phones 170–6 Shapiro, Carl 24 Sharp 156, 231, 326 shelfware phenomenon 20 Shelley, Mary 267, 269 shipping costs 121 sick building syndrome 302 Siebel 86 Siemens 120, 130, 142, 156, 159, 170, 172, 174 SightSpeed 84, 98, 103 SilentRunner 62 Silicon Valley 9, 32–40, 45–6, 54, 69, 79, 96, 98, 101, 103, 152, 313–14, 321 silk 263, 269 Simon, Herbert 336 simplicity needs 78–81, 84, 87, 88–92, 98–110 SIP see session initiation protocol Sircam virus 45, 49 Sirkin, Hal 120, 140 “six sigma” methods 128 SK 169 Skidmore, Owings & Merrill 302 Sky 205 Skype 103–4, 110 Sloan School of Management, MIT 30 Slovakia 120 small screens 100 Smalley, Richard 311 smallpox 265–6 smart power grids 233, 285–90 smartcards 64, 69 smartphones 150–3, 157–61 see also mobile phones SMES devices 289 Smith Barney 37 Smith, George 307–8 Smith, Lamar 75 Smith, Vernon 17 SNP 243–4 SOAP 25–7 355 THE FUTURE OF TECHNOLOGY social issues mobile phones 177–8, 182–3 music players 220–1 social outsourcing 143 software see also information technology ASPs 19–20, 91–2, 109 bugs 20–1, 54–6 Cell chips 198–200 commoditisation issues 10–16, 25, 132–5, 159, 203 complexity issues 14–15, 78–81, 82–110, 117–22 firewalls 52–3, 58, 86–7 hackers 51–3, 58–63 Java programming language 21–2, 25, 86 management software 13–16, 21–2, 88, 117–18 mobile phones 158–9 natural-language search software 339–40 operating systems 9, 10, 23–5, 31, 38, 85, 101, 109 outsourcing 38, 115, 138–9 patches 56–7, 76 premature releases 20–1 shelfware phenomenon 20 viruses 45, 47, 49–56, 59–60, 67, 74, 89 solar power 275–6, 286, 289, 301–2, 310, 315, 325 Solectron 112–13, 119 solid-state storage media 204, 207, 219 SOMO... project, mobile phones 177–8 Sony 95, 108, 156, 191–3, 198–200, 203, 206–7, 217, 228, 231, 282–4, 332, 334, 338 Sony Ericsson 156, 158, 159–60, 171 Sony/BMG 222–3, 227, 229 Sood, Rahul 38 Sorrent 187 South Africa 309, 319, 334 South Korea 156, 158, 163–5, 167–9, 170–1, 181, 319 soyabean crops 252–4 spam 76, 89, 118 Spar, Debora 32–3 speculation vii speech recognition 102, 121, 336 SPH-V5400 mobile phone 208 Spider-Man 189–90 Spinks, David 60–1, 63 Spitzer, Eliot 223 Sprint 167–8, 180–1 SQL 53 @Stake 54 Standage, Ella 316 standards green buildings 300–4 open standards 7, 10, 22–7, 31, 38, 43, 85–7, 115, 118–19, 152 356 security issues 71–3 W-CDMA standard 163–4, 168 web services 90–1 Wi-Fi 210–13 Stanford University 82, 137 Star Wars (movie) 186 steam power ix, 5, 134 steel industry 134 steering committees 31 stem cells 268–9 Steven Winter Associates 302 Stewart, Martha 249 STM see scanning tunnelling microscope stop-start hybrid cars 293–4 storage problems, electricity 275–6, 289–90 StorageTek 85 strategy 30 stress-resistance, biotechnology 254 Studio Daniel Libeskind 302 Sturiale, Nick 45 Sun Microsystems 9, 13–15, 21–2, 25, 27, 37–8, 43, 56, 58, 78–9, 83, 85, 87, 91, 102 supercomputers 199–200 Superdome machines 21 supply chains 8, 37–40, 155 surveillance technology 35, 74, 179–83, 309 Sussex University 5, 220, 310 Sustainable Computing Consortium (SCC) 27 Sweden 109 Swiss Army-knife design, mobile phones 171–2 Swiss Re Tower, 30 St Mary Axe 299, 301–2, 304 swivel design, mobile phones 171 Symantec 39, 46, 50, 62–3, 67 Symbian 158 Symbol 210 synthetic materials 258–64, 317 systems analysts 137 T T-Mobile 167–8 Taiwan 156–7, 160 Talwar, Vikram 144 Taylor, Andy 226 Taylor, Carson 287 TCP/IP 25 TCS 132–5, 145–6 Teague, Clayton 314 TechNet 33 techniques, technology 17–18 techno-jewellery design, mobile phones 172–4 technology see also individual technologies concepts vii–x, 4–7, 17–18, 23–7, 32–3, 82–4, 134, 326–9 cultural issues 93–4, 142 INDEX geekiness problems 83–4 government links 7, 18, 27, 31–5, 43–8, 123–4, 179–83, 209–10 Luddites 327 surveillance technology 35, 74, 179–83, 309 Tehrani, Rich 105 telecommunications viii, 23, 26, 103–6, 134, 164–5 telegraph 32–3, 108 telephone systems 84, 103–6, 109–10, 212–13, 214 Telia 109 terrorism 35, 42, 43, 50, 65, 74, 75–6, 265–6 Tesco 168 Tetris 12 Texas Energy Centre 287 Texas Instruments 125–6, 217 text-messaging facilities 165, 167 Thelands, Mike 164 therapeutic antibodies 249–50, 256–7 Thiercy, Max 339–40 thin clients 102 third-generation mobile phone networks (3G) 151, 162–9, 212 Thomas, Jim 318 Thomson, Ken 59 Thornley, Tony 164 3G networks see third-generation mobile phone networks TIA see Total Information Awareness TiVo 203, 205–6 Tomb Raider (game/movie) 187–8 Toshiba 156, 198–200, 203 Total Information Awareness (TIA) 35 toxicity issues, nanotechnology 316–17, 319, 328–9 Toyota 291–5, 297, 300–1, 334 toys see also gaming robotics 334 transatlantic cable 36, 39 transistors 4–7, 8–12, 85–7, 109 see also computer chips Transmeta 313 Treat, Brad 84, 98 Tredennick, Nick 10–11 Treo 150, 153 “Trojan horse” software 51–2 True Crime (game) 187 TruSecure 52, 60, 63 TTPCom 155–6 Tuch, Bruce 210 TVs see also video recorders flat-panel displays ix, 94, 147, 202–3, 230–2, 311 hard disks 204–8 screens 202–3, 230–2 set-top boxes 203, 205–6 UWB 214–18 Wi-Fi 212–18 U UBS Warburg 31, 45, 80–1, 89, 170, 174 UDDI 25–7 ultrawideband (UWB) 96–7, 214–19 UMTS see W-CDMA standard “undershoot” stage, industries 9, 109 UNECE 332–4 Ungerman, Jerry 52 Unimate 332–3 United Airlines 27 Universal Music 222–3, 226–7 Unix 9, 25, 85, 108 USB ports 78 usernames 59 USGBC 300–2 utility companies, cyber-terrorism threats 75–6 utility factors 7, 16, 17, 19–22, 42–8 UWB see ultrawideband V V500 mobile phone 157 vaccines 265–6 Vadasz, Les 33 Vail, Tim 290 value added 5–7, 37–40, 133, 138–9 value transistors 11 van Nee, Richard 211 Varian, Hal 24 VC see venture capital Veeco Instruments 324 vendors complexity issues 84–110 consumer needs 94–7 Venter, Craig 262–3, 271 venture capital (VC) 12, 31, 45, 79, 92, 107, 126–7, 238, 308, 321–6 Verdia 254–5, 261 Veritas 39, 85 Vertex 247 vertical integration, mobile phones 156–61 Vertu brand 173–4 Viacom 224 video phone calls 84, 103–6, 164–5, 167–8 video recorders see also TVs DVRs 205–6 handheld video players 206 hard disks 204–8 PVRs 203, 205–6 Wi-Fi 212–13 video searches, Google 11 357 THE FUTURE OF TECHNOLOGY Video Voyeurism Prevention Act, America 180 video-game consoles see gaming Virgin 95, 160, 167–8 Virgin Mobile 160, 167–8 virtual private networks (VPNs) 54, 68, 86–7 virtual tissue, biotechnology 248 virtualisation concepts 15–16, 88–92 viruses 45, 47, 49–56, 59–60, 67–8, 74, 86, 89 anti-virus software 50–1, 60, 67–8 concepts 49–56, 59–60, 74 costs 50–1 double-clicking dangers 59–60 Vista Research 46, 62, 67 Vodafone 164–5 voice conversations internet 103–6 mobile phones 165–9, 171 voice mail 104–6 voice-over-internet protocol (VOIP) 103–6, 167 Vonage 104, 110 VPNs see virtual private networks W W3C see World Wide Web Consortium W-CDMA standard 163–4, 168 Waksal, Sam 249 Wal-Mart 95, 114–15, 131–2, 140, 224, 228 Walkman 192 warfare AI 338 biotechnology 265–6 gaming comparisons 195–7, 339 nanotechnology 319 Warner Music 222–3, 226–7 Watson, James 236, 247, 271 web services 21–2, 25–7, 31, 80, 88–92, 109, 203 see also internet; services... complexity issues 88–92, 109 standards 90–1 Webster, Mark 211 WECA see Wireless Ethernet Compatibility Alliance Weill, Peter 30 Welland, Mark 318 Western Union 33, 108 Westinghouse Electric 332 wheat 253 white page 99–100 Wi-Fi 34–5, 66–7, 93, 95–7, 153, 203, 209–18 concepts 209–18 forecasts 209, 212–13 historical background 209–13 hotspots 211–12 mobile phones 212 standards 210–13 358 threats 212–13 UWB 214–18 Wilkerson, John 237 Williams, Robbie 222, 226 Wilsdon, James 318 WiMax 212–13 WiMedia 213 Wimmer, Eckard 265 wind power 275–6, 286, 289–90, 302 Windows 15, 24–5, 55–6, 96, 101, 108, 152, 203 Windows Media Center 203 WinFS 101 Wipro 112, 115, 120–1, 125–9, 131–5, 138, 145–6 Wireless Ethernet Compatibility Alliance (WECA) 211 wireless technology ix, 11, 34–5, 39, 66–7, 93, 95–7, 109–10, 147, 150–3, 167, 168–9, 171–3, 203, 209–13, 334 see also Wi-Fi Bluetooth wireless links 171–2, 173, 214–15, 218 concepts 209–13, 334 historical background 209–13 Wladawsky-Berger, Irving vii, 5, 19, 22, 25, 38–9 Wolfe, Josh 323 Wong, Leonard 195 Wood, Ben 156–7, 160, 174 Woodcock, Steven 338–9 Word 84, 107 work-life balance 80–1, 94 see also employees World Wide Web Consortium (W3C) 25 worm viruses 49–50, 59, 86, 89 Wright, Myles 118 “ws splat” 90–1 WSDL 25–7 X x-ray crystallography 247–8 Xbox 189, 206–7 Xelibri mobile phones 170, 172, 174 Xerox 108–9 XML see extensible markup language XtremeSpectrum 216 Y Y2K crisis 76, 126, 128 Yagan, Sam 229 Yanagi, Soetsu 84 Yurek, Greg 288 Z ZapThink 91
Extreme Money: Masters of the Universe and the Cult of Risk by Satyajit Das
affirmative action, Albert Einstein, algorithmic trading, Andy Kessler, Asian financial crisis, asset allocation, asset-backed security, bank run, banking crisis, banks create money, Basel III, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Black Swan, Bonfire of the Vanities, bonus culture, Bretton Woods, BRICs, British Empire, business cycle, capital asset pricing model, Carmen Reinhart, carried interest, Celtic Tiger, clean water, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, corporate raider, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, Daniel Kahneman / Amos Tversky, debt deflation, Deng Xiaoping, deskilling, discrete time, diversification, diversified portfolio, Doomsday Clock, Edward Thorp, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, eurozone crisis, Everybody Ought to Be Rich, Fall of the Berlin Wall, financial independence, financial innovation, financial thriller, fixed income, full employment, global reserve currency, Goldman Sachs: Vampire Squid, Gordon Gekko, greed is good, happiness index / gross national happiness, haute cuisine, high net worth, Hyman Minsky, index fund, information asymmetry, interest rate swap, invention of the wheel, invisible hand, Isaac Newton, job automation, Johann Wolfgang von Goethe, John Meriwether, joint-stock company, Jones Act, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, laissez-faire capitalism, load shedding, locking in a profit, Long Term Capital Management, Louis Bachelier, margin call, market bubble, market fundamentalism, Marshall McLuhan, Martin Wolf, mega-rich, merger arbitrage, Mikhail Gorbachev, Milgram experiment, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, mutually assured destruction, Myron Scholes, Naomi Klein, negative equity, NetJets, Network effects, new economy, Nick Leeson, Nixon shock, Northern Rock, nuclear winter, oil shock, Own Your Own Home, Paul Samuelson, pets.com, Philip Mirowski, plutocrats, Plutocrats, Ponzi scheme, price anchoring, price stability, profit maximization, quantitative easing, quantitative trading / quantitative ﬁnance, Ralph Nader, RAND corporation, random walk, Ray Kurzweil, regulatory arbitrage, rent control, rent-seeking, reserve currency, Richard Feynman, Richard Thaler, Right to Buy, risk-adjusted returns, risk/return, road to serfdom, Robert Shiller, Robert Shiller, Rod Stewart played at Stephen Schwarzman birthday party, rolodex, Ronald Reagan, Ronald Reagan: Tear down this wall, Satyajit Das, savings glut, shareholder value, Sharpe ratio, short selling, Silicon Valley, six sigma, Slavoj Žižek, South Sea Bubble, special economic zone, statistical model, Stephen Hawking, Steve Jobs, survivorship bias, The Chicago School, The Great Moderation, the market place, the medium is the message, The Myth of the Rational Market, The Nature of the Firm, the new new thing, The Predators' Ball, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, trickle-down economics, Turing test, Upton Sinclair, value at risk, Yogi Berra, zero-coupon bond, zero-sum game
But investors and shareholders liked the focus on market leadership. Sales of noncore assets, savage cost cutting, and reduction in employee numbers pleased investors even more. Welch came up with a succession of other big ideas, introducing management controls and planning tools that focused on allocating capital to businesses, suspiciously similar to those of Alfred Chandler from the 1960s. To improve product quality and reduce costs, Welch introduced six sigma, based on statistical tools for process and production control, originally developed by Allied Signal, Motorola, and the Japanese. Welch was not beyond naked opportunism, creating www.DestroyYourBusiness.com during the Internet boom, promoting digital technology to improve productivity. GE managers, trained at the firm’s Crotonville facilities (dubbed cretinville by sceptics), celebrated its integrated diversity, as well as its silo-less, boundary-less, and learning organization.
See also options profits, 121 risk, 124 intellectual property rights, securitization of, 168 interest rates cutting of, 340-341 lowering of, 348 International Accounting Standards Board, 289 International Grain Council, 334 International Institute of Finance (IIF), 289 International Monetary Fund (IMF), 96 international reply coupons (IRCs), 33 Internet bubble (1990s), 54 stocks, 58 InterNorth, 55 interviews on financial TV shows, 94 invention of money, 24-25 investment banks, 57, 309 leveraged buyouts (LBOs), 147-148 percentage of jobs in, 313 separation from commercial banks, 66 investments alternative, 252 exotic products, 73-74 hedge funds Amaranth, 250-252 clientele, 247-250 fees, 245 Hedgestock, 252 markets, 241 returns, 243-244 Sharpe ratios, 246-247 strategies, 241-243 incentives, 348 IO (interest only) bonds, 178 Ireland, 83, 344 Irish Times, The, 356 Iron Chef, The, 168 Irving, John, 29 Ising model, 204 It’s A Wonderful Life, 65, 180 Italy, derivatives, 215-216 ITT Corporation, 60 J Jackson, Marjorie, 156 Jackson, Michael, 21 Jackson, Tony, 363 James, Oliver, 274 Japan debt, 357 financialization, 38-39 housewife traders, 40-41 lost decades, 357 retirement, 49-50 six sigma, 60 Jefferson County, Alabama, 211-214 Jefferson, Thomas, 91 Jenkins, Simon, 302 Jenson, Michael, 120, 138-141 Jiabao, Wen, 86-87 Jian, Ma, 295 Jintao, Hu, 363 jobbers, 53 jobs certifications, 309-310 finance, 307-308 Jobs, Steve, 164 John F. Kennedy Profiles in Courage Award, 301 Johnson, Lyndon, 30, 129 Johnson, Samuel, 352 Johnson, Simon, 96, 294 Joint Economic Committee, 203 Jonas, Adam, 259 Jones, Alfred Winslow, 240 Jones, Norah, 157 Jones, Paul Tudor, 256 Jong, Erica, 73 Jorgenson, Andrew, 64 Joseph, Fred, 146 JP Morgan, 191, 272, 280, 283, 337, 360 jumbo loans, 182 Jünger, Ernst, 233 junk bonds, 143 leveraged buyouts (LBOs), 145-146 JWM Partners LLC, 257 K Kadlec, Charles W., 97 Kahn, Herman, 35 Kahneman, Daniel, 126 Kaltwasser, Pablo Rovira, 126 Kapur, Ajay, 41 Karinthy, Frigyes, 269 Kasouf, Sheen, 121 Katainen, Jyrki, 356 Kaufman, Henry, 292 Kaupthing Bank, 275, 288, 345 Kazakhstan, 72 keiretsu, 139 Kell, Kevin, 99 Keller, Marianne, 64 Kelly, Don, 141 Kennedy, Robert, 359 Kennedy, John F., 81, 364 Kerkorian, Kirk, 137 Kerviel, Jerome, 226-230 Kessler, Andy, 316 ketchup economics, 116 Keynes, John Maynard, 25-29, 33, 77, 100, 303, 347, 362-364 China’s use of philosophy, 87 diversification, 123 Great Depression, 103 risk, 127 uncertainty, 366 warnings about speculation, 88 Kierkegaard, Søren, 130, 179 Kim, Dow, 315 Kimberly-Clark, 92 kimono traders, 40 King Kullen, 208 King’s College, 29, 123 King, Mervyn, 195, 342 KISS, 327 kiwis (New Zealand dollars), 21 KKR (Kohlberg, Kravis, and Roberts), 135, 137 Klein, Naomi, 342 Klempere, Otto, 157 Kluge, John, 149 Knebworth House, 262 Knight, Frank, 128 knock-ins, 211, 217 knock-outs, 211, 217-219 Kogan, Valery, purchases of, 322 Kohn, Donald, 270, 301 Koppel, Ted, 90 Kotov, Alexander, 252 Kravis, Henry, 162 Krawcheck, Salli, 316 kronas (Iceland), 275 Krug Grande Cuvée champagne, 304 Kübler-Ross, Elizabeth, 329 Kubrick, Stanley, 35 Kuhn, Thomas, 273 Kuwati dinars, 21 Kwak, James, 294 kwatcha, 21 Kynikos Associates, 161 L L’engrenage, Mémoires d’un trader, 229 La Défense, 227 LA Galaxy, 339 LaBelle, Patti, 164 Ladies’ Home Journal, 97 Laffer Curve, 65, 110 Lahde, Andrew, 256, 330 Lamont, Thomas, 337 Last Chronicle of Barset, 173 Laurence J.
See also municipal bonds shadow banking system, 192, 195 Shakes, Ronnie, 43 Shakespeare, William, 36, 117 Shang Kong, 82 Sharpe ratios, hedge funds, 246-247 Sharpe, William, 117 Shaw, George Bernard, 30, 42 Shearer, Tony, 275, 288 Shearson Lehman Hutton, 149 shell games, 293 shift of assets, 288 Shin, Hyun Song, 273 Shiva, 339 ShockGen, 229 shopping after September 11, 2001, 44 A Short History of Financial Euphoria, 77 Short, Martin, 164 shorting of credit risk, 176 Sigur Ros, 345 silver, 58 Silver State Mortgage, 185 Simmel, Georg, 36, 328 Simmon, Gene, 327 Simon, David, 333 Simon, William, 135 Sinatra, Frank, 157 Sinclair, Upton, 305 Singapore as a financial center, 78, 82 Singer & Friedlander, 275, 288 single premium deferred annuity (SPDA), 145 SIVA (stated income verified assets) loans, 182 SIVs (structured investment vehicles), 190 Six Degrees of Separation, 269 six sigma, 60 Skeel, David, 206 Skilling, Jeffrey, 55-56, 288, 307, 313, 328 Skinner, B.F., 274 Skull and Bones, 148 Sloan School of Management at MIT, 96 slowness movements, 364 Slutsky, Eugene, 128 small-firm effect, 126 Smith, Adam, 23, 102, 129, 252, 320, 361 paper money, 27 Snail House, 351 snuff movies, 335 Social Insurance and Allied Services, 47 social security, 48 Société Générale (SG or Soc-Gen), 29, 226-228, 349 solid forms of money, 25 Solomon, David, 145 solutions, global financial crisis, 352-354 Sons of Gwalia (SoG), 216 Soros, George, 240, 242, 302, 326-327, 341 Sosin, Howard, 230 Sotheby’s, 323 South African rands, 21 South Sea Company, 53 Southern District of New York, 150 sovereign debt, 236-238 Soviet Union, 30 special economic zones (SEZ), 85 special purpose entity rules (SPE), 57 Spectator ab Extra, 326 speculation, 311 bubble economies, 54 debt and, 274-275 economy, 52 speculators, 88 Spencer, Herbert, 281 spontaneous symmetry breaking, 204 spreads, 169 Square Mile, the (London), 79 Squawk Box, 94 stabilization funds, 354 of global trade, 349 Stadler, Robert, 302 stagflation, 138 stagnation, 357 Stamford, Connecticut, 80 Standard & Poor’s (S&P), 141, 282 Standard Oil of Ohio (Sohio), 57 standards accounting, 289 gold, 29-31.
Reinventing Capitalism in the Age of Big Data by Viktor Mayer-Schönberger, Thomas Ramge
accounting loophole / creative accounting, Air France Flight 447, Airbnb, Alvin Roth, Atul Gawande, augmented reality, banking crisis, basic income, Bayesian statistics, bitcoin, blockchain, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, Cass Sunstein, centralized clearinghouse, Checklist Manifesto, cloud computing, cognitive bias, conceptual framework, creative destruction, Daniel Kahneman / Amos Tversky, disruptive innovation, Donald Trump, double entry bookkeeping, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ford paid five dollars a day, Frederick Winslow Taylor, fundamental attribution error, George Akerlof, gig economy, Google Glasses, information asymmetry, interchangeable parts, invention of the telegraph, inventory management, invisible hand, James Watt: steam engine, Jeff Bezos, job automation, job satisfaction, joint-stock company, Joseph Schumpeter, Kickstarter, knowledge worker, labor-force participation, land reform, lone genius, low cost airline, low cost carrier, Marc Andreessen, market bubble, market design, market fundamentalism, means of production, meta analysis, meta-analysis, Moneyball by Michael Lewis explains big data, multi-sided market, natural language processing, Network effects, Norbert Wiener, offshore financial centre, Parag Khanna, payday loans, peer-to-peer lending, Peter Thiel, Ponzi scheme, prediction markets, price anchoring, price mechanism, purchasing power parity, random walk, recommendation engine, Richard Thaler, ride hailing / ride sharing, Sam Altman, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, smart grid, smart meter, Snapchat, statistical model, Steve Jobs, technoutopianism, The Future of Employment, The Market for Lemons, The Nature of the Firm, transaction costs, universal basic income, William Langewiesche, Y Combinator
They required considerable institutional support (such as appropriate laws, financial instruments, and the like), but improvements over time (including organizational changes) increased their efficiency by leaps and bounds, and they ultimately became indispensable in virtually all sectors. Similar efficiency gains were realized through the optimization of every process within a firm, whether it was called Taylorism, Six Sigma, or lean management. Whether a focus on efficiency is a suitable strategy largely depends on two factors. First, are there existing inefficiencies within an industry that can be eliminated? The traditional network airline business model, for example, was wasteful enough that more efficient, low-cost airlines could take over a substantial share of the air-travel market. By contrast, modern large supermarket chains are so comparatively efficient in their operations that new entrants (including digital start-ups—remember Webvan?)
See automation/machine learning Mainichi Shimbun, 109 Malone, Thomas, 7 MAN, 182 market failure, reducing, 6 markets, 35–57 Amazon as, 87–88 chaotic, unplanned nature of, 160 choice limitations in, 13–14 communicative coordination and, 26–28, 30–33 comparison of firms and, 28, 111 competition between firms and, 30, 107 concentrated, 161–169, 171, 217 data-rich (see data-rich markets) decentralization in (see decentralization) feedback effects and, 160–175 fintechs and, 153 historical improvements in, 51–52 irrational decision-making in, 42–44 key difference between firms and, 32–33, 90 limitations of, 63 network effects and, 162–166 for noneconomic activities, 49–50 physical design of, 160–161 prediction, 50–51 resilience of, 39 scale effects and, 162–166 shift from firms to, 10–11, 30–32, 125–126 success of, 4, 49–50, 222 thick, 2, 82–83, 164, 213 Martin, Walt, 181–182 Marx, Karl, 143, 162 Mason, Vicki, 42 Massachusetts Institute of Technology (MIT), 7, 142, 159, 184, 195, 220 matching, 8–9, 11, 64, 66, 71–85, 212 algorithms for (see algorithms) centralized, 74 complexity of task, 43–44 in conventional vs. data-rich markets, 70–71 decentralized, 74, 127 fintechs and, 151–152 firms and, 127–129 nonmarket providers of, 75–76 variety of contexts for, 74–75 Max Planck Institute for Human Development, 105 McAfee, Andrew, 184 McDonald’s, 215 McGovern, George, 190 McNamara, Robert, 99–100 Medici, Cosimo de’ the Elder, 92, 93 Medici family, 91, 93 Mercedes-Benz, 110 Merrill, Douglas, 151 Merrill Lynch, 155 metadata, 66 Micro Ventures, 152–153 Microsoft, 165, 166, 169 Microsoft Imagine Cup, 75 Minyons club, 17–20 mobile phones iPhone, 136, 164 Kerala fishermen and, 36–37 payment business and, 147 Model T Ford, 29, 98, 162 money, 4, 45–57, 63, 64, 143–144, 212 advantages of using, 45–49 banks’ decreased use of, 136–137 data as a substitute for, 148–149 future role of, 5, 149 historical forms of currency, 47–48 importance of linked to utility, 45 informational function of, 48–49 intrinsic value not required for, 48 market efficiency improved by, 47–49 move from physical to virtual, 48 role of capital affected by demise of, 141 signaling with, 142 work unbundled from, 203–206, 218 See also capital; price monopolies, 30, 203 moon landing, 22, 159 Mosaic, 189 motorcycle manufacturing, 30–32, 33 Musk, Elon, 78, 189 My Years with General Motors (Sloan), 99 MySpace, 166 NASDAQ Composite Index, 196 National Aeronautics and Space Administration (NASA), 22 national champions, 30 National Oceanic and Atmospheric Administration, 133 negative income tax, 190 Netflix, 74, 75, 161, 196, 209 Netherlands, 191 network effects, 162–166 New York Central Railroad, 96 New York Times, 88–89, 208–209 Nixon, Richard, 190 Nobel Prize winners, 39, 74, 190 nominal tax rate, 198 Nordstrom, 211 Northwestern University, 83, 194 oligopolies, 30 Omidyar, Pierre, 1 ontology, 67–70, 81, 84, 136 defined, 67 firms and, 128 labor market and, 204 Organization for Economic Cooperation and Development (OECD) countries, 28 organized labor, 205 Orwell, George, 179 Otto, 181–183 Paine, Thomas, 190 Parthenon Group, 207 participatory policy measures, 186, 188–189, 190, 193, 200–202 patent system, 199 payment solutions businesses, 146–147, 149 PayPal, 135–136, 146, 189 Pearson, 69 Peep Trade, 76, 152 peer-to-peer lending, 152–153 Pentland, Sandy, 142 Peruzzi family, 91 Piketty, Thomas, 186 Pinterest, 210 poker, 59–62 populism, 13, 186 post-price retailers, 209 prediction markets, 50–51 preferences complexity of processing, 43–44 fintech extraction of, 151–152 improved means of capturing, 8, 64, 71–72, 76–81 standard language for comparing, 64 See also matching price, 7, 45–57 data-rich markets’ advantages over, 70–71, 72, 136–137 deemphasis on, 3, 122, 129, 136–137, 138, 212 detailed information lacking in, 4, 52–56 future role of, 5 information condensed by, 4, 46–47, 48–49, 63, 65 internal talent management and, 128 markets and, 36 volatility of, 36 PriceBlink, 52 PriceGrabber, 52 PriOS, 115 privacy issues, 145, 174 Procter & Gamble, 128 profits, 195–197 progressive consumption tax (PCT), 198 progressive data-sharing mandate, 12, 171, 199, 203 choice expanded by, 217 explained, 167–169 Prüfer, Jens, 167 punch-card tabulator, 96 Qin, Emperor, 24 Rack Habit, 207–208 Rawls, John, 223 regulatory measures for banks and financial institutions, 139–140 for feedback problems, 171–175 research and development, 196 resource scarcity, overcoming, 220–221 retail sector, 138, 207–212 retirement savings, 143–144, 195 returns on investments, 195 Robinhood Markets, 146 robo tax, 186–187 Rognlie, Matthew, 194 Ron, Lior, 182–183 Roth, Alvin, 74 Ryanair, 112 Saberr, 75 salary bands, 128, 129 salt (as currency), 47 Samsung, 196 Sandholm, Tuomas, 60, 62 SAP, 100 scale effects, 162–166 Scania, 182 Schottmüller, Christoph, 167 Schumpeter, Joseph, 120 scientific management, 96 Second Payment Service Directive (European Union), 140 Seedcamp, 75 self-employment, 185–186 Shapley, Lloyd, 74 Shepherd, Alistair, 75 shipping industry, 213 SigFig, 3, 151–152, 153, 156 silver standard, 48 Simon, Herbert, 104 Simon, Julian, 220 Siri, 79, 164 Six Sigma, 112 Sloan, Alfred P., 98–99, 101 Sloan School of Business, 220 Smith, Adam, 27, 143, 223 Snapchat, 166 Social Security, 192 SoFi, 150, 151 Soll, Jacob, 91 Solomon, Madi, 69–70 SOP. See standard operating procedure South Korea, 196 Soviet Union, 177 Spotify, 74, 75, 121–125, 196, 215 squadification, 123–125 St. Peter’s Basilica, 21 Stalin, Joseph, 177 standard operating procedure (SOP), 100–101, 106 start-ups, 141, 146, 199 increased capital available for, 142–143 network effects and, 165–166 See also fintechs Stash, 151, 215 steam engine, 111, 113 steel industry, 161 Stitch Fix, 208–212, 215 stock markets, 146 decreased investment options in, 143 share prices in, 2–3, 6, 196 Stripe and Square, 147 Stucke, Maurice, 166 subprime mortgage crisis, 6, 41, 55–56, 134, 155, 173 Suez Canal, 21 superstar firms, 195–197 Suzuki, 30 Switzerland, 136 Synco.
Where Good Ideas Come from: The Natural History of Innovation by Steven Johnson
Ada Lovelace, Albert Einstein, Alfred Russel Wallace, carbon-based life, Cass Sunstein, cleantech, complexity theory, conceptual framework, cosmic microwave background, creative destruction, crowdsourcing, data acquisition, digital Maoism, digital map, discovery of DNA, Dmitri Mendeleev, double entry bookkeeping, double helix, Douglas Engelbart, Douglas Engelbart, Drosophila, Edmond Halley, Edward Lloyd's coffeehouse, Ernest Rutherford, Geoffrey West, Santa Fe Institute, greed is good, Hans Lippershey, Henri Poincaré, hive mind, Howard Rheingold, hypertext link, invention of air conditioning, invention of movable type, invention of the printing press, invention of the telephone, Isaac Newton, Islamic Golden Age, James Hargreaves, James Watt: steam engine, Jane Jacobs, Jaron Lanier, Johannes Kepler, John Snow's cholera map, Joseph Schumpeter, Joseph-Marie Jacquard, Kevin Kelly, lone genius, Louis Daguerre, Louis Pasteur, Mason jar, mass immigration, Mercator projection, On the Revolutions of the Heavenly Spheres, online collectivism, packet switching, PageRank, patent troll, pattern recognition, price mechanism, profit motive, Ray Oldenburg, Richard Florida, Richard Thaler, Ronald Reagan, side project, Silicon Valley, silicon-based life, six sigma, Solar eclipse in 1919, spinning jenny, Steve Jobs, Steve Wozniak, Stewart Brand, The Death and Life of Great American Cities, The Great Good Place, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, transaction costs, urban planning
We need the phase-lock state for the same reason we need truth: a world of complete error and chaos would be unmanageable, on a social and a neurochemical level. (Not to mention genetic.) But leaving some room for generative error is important, too. Innovative environments thrive on useful mistakes, and suffer when the demands of quality control overwhelm them. Big organizations like to follow perfectionist regimes like Six Sigma and Total Quality Management, entire systems devoted to eliminating error from the conference room or the assembly line, but it’s no accident that one of the mantras of the Web startup world is fail faster. It’s not that mistakes are the goal—they’re still mistakes, after all, which is why you want to get through them quickly. But those mistakes are an inevitable step on the path to true innovation.
Scheele, Carl Wilhelm Scheutz, Per Georg Schickard, Wilhelm Schmidt, Brian Schumpeter, Joseph Scleractinia Seismographs Senebier, Jean Senefelder, Alois September 11, 2001, terrorist attacks (9/11) Serendipity chaos and in dreams hunches and Web and Servetus, Michael Sewing machines Sexual reproduction SGML Sharp, Philip A. Shibh, Ramzi bin al- Shocklee, Hank Shockley, Bill Sholes, Christopher Latham Shore, John Singer, Isaac Six Sigma Sketchpad Slide rules Smallpox vaccine Smith, H. O. SMS mobile communications platform Snow, John Sobrero, Ascanio Solar system, heliocentric theory of Sony Corporation Soubeiran, Eugène Soubra, Zakaria Mustapha Soviet Union space program of Spectroscopes Speed of light Spencer, Percy Spillover, information Spinning jenny Sputnik Stanford University Business School Woods Institute for the Environment Staphylococcus Starling, Ernest Henry Steamboats Steam engines Steam locomotives Steelmaking Stocking frames Stone, Biz Strasburger, Eduard Stratosphere StumbleSafely Subcultures Sunlight Foundation Sunspots Sunstein, Cass Superconductivity Superlinear scaling Supernovas Suspension bridges Sutherland, Ivan Swan, Joseph Switzerland Syntex Szilard, Leo Talking Heads Tangled bank, metaphor of Darwin’s use of Tansley, Arthur Tape recorders Tarnier, Stéphane Tartaglia, Niccolò Taxonomy TBWA/Chiat/Day advertising agency TCP/IP Teisserenc de Bort, Léon Telegraphy Telephone Telescopes Television 10/10 rule Terrestrial globes Tesla, Nikola Textile industry Thatcher, Robert Thermodynamics Thermometers Thomas, Dorothy Thomson, J.
Lab Rats: How Silicon Valley Made Work Miserable for the Rest of Us by Dan Lyons
Airbnb, Amazon Web Services, Apple II, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, business process, call centre, Clayton Christensen, clean water, collective bargaining, corporate governance, corporate social responsibility, creative destruction, cryptocurrency, David Heinemeier Hansson, Donald Trump, Elon Musk, Ethereum, ethereum blockchain, full employment, future of work, gig economy, Gordon Gekko, greed is good, hiring and firing, housing crisis, income inequality, informal economy, Jeff Bezos, job automation, job satisfaction, job-hopping, John Gruber, Joseph Schumpeter, Kevin Kelly, knowledge worker, Lean Startup, loose coupling, Lyft, Marc Andreessen, Mark Zuckerberg, McMansion, Menlo Park, Milgram experiment, minimum viable product, Mitch Kapor, move fast and break things, move fast and break things, new economy, Panopticon Jeremy Bentham, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, precariat, RAND corporation, remote working, RFID, ride hailing / ride sharing, Ronald Reagan, Rubik’s Cube, Ruby on Rails, Sam Altman, Sand Hill Road, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, Skype, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, Stanford prison experiment, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, TaskRabbit, telemarketer, Tesla Model S, Thomas Davenport, Tony Hsieh, Toyota Production System, traveling salesman, Travis Kalanick, tulip mania, Uber and Lyft, Uber for X, uber lyft, universal basic income, web application, Whole Earth Catalog, Y Combinator, young professional
After the war, Japanese companies refined Training Within Industry into what came to be known as the Toyota Production System, which then evolved into Lean Manufacturing and just-in-time manufacturing. In the 1980s, two engineers at Motorola, the American consumer electronics giant, dreamed up a manufacturing system called Six Sigma, which big companies around the world spent the next two decades adopting. And so it goes. For the past hundred years, since the days of Frederick Taylor, companies have been latching on to new management fads, and each new fad runs its course, and then everyone leaps onto the next one, believing—like Charlie Brown running for the football in Lucy’s hands—that this time things will be different. Management Science Meets the Information Age Twentieth-century Taylorite methodologies like Six Sigma, Lean Manufacturing, and the Toyota Production System were developed for manufacturing physical things—cars, airplanes, lawn furniture, whatever.
Endless Money: The Moral Hazards of Socialism by William Baker, Addison Wiggin
Andy Kessler, asset allocation, backtesting, bank run, banking crisis, Berlin Wall, Bernie Madoff, Black Swan, Branko Milanovic, break the buck, Bretton Woods, BRICs, business climate, business cycle, capital asset pricing model, commoditize, corporate governance, correlation does not imply causation, credit crunch, Credit Default Swap, crony capitalism, cuban missile crisis, currency manipulation / currency intervention, debt deflation, Elliott wave, en.wikipedia.org, Fall of the Berlin Wall, feminist movement, fiat currency, fixed income, floating exchange rates, Fractional reserve banking, full employment, German hyperinflation, housing crisis, income inequality, index fund, inflation targeting, Joseph Schumpeter, Kickstarter, laissez-faire capitalism, land reform, liquidity trap, Long Term Capital Management, McMansion, mega-rich, money market fund, moral hazard, mortgage tax deduction, naked short selling, negative equity, offshore financial centre, Ponzi scheme, price stability, pushing on a string, quantitative easing, RAND corporation, rent control, reserve currency, riskless arbitrage, Ronald Reagan, school vouchers, seigniorage, short selling, Silicon Valley, six sigma, statistical arbitrage, statistical model, Steve Jobs, stocks for the long run, The Great Moderation, the scientific method, time value of money, too big to fail, upwardly mobile, War on Poverty, Yogi Berra, young professional
And it is especially suspect now that in a world of freely floating currencies the freezing up of credit markets caused the stock market to crash in a mere subset of months within 2008. The assumptions of linearity and normally distributed outcomes are perhaps the most worrisome and limiting of thought, particularly because in the discipline of finance it has been almost unquestionably shown that six sigma events are happening with all too much regularity to be assumed random. (Two sigmas denote that in 95 percent of outcomes results will be within a stated boundary. A six sigma event is extremely rare; normally it would occur just 3.4 times in a million instances). The principals of Long-Term Capital Management, who had PhDs in economics, assumed away the possibility of rare outcomes with ruinous results for their investors. Nassim Nicholas Taleb has gained notoriety for reminding the investment community of this uncomfortable point.
See National Association of Securities Dealers Financial Missionaries to the World:The Politics and Culture of Dollar Diplomacy (Rosenberg), 279 412 Fisher, Irving, 94, 112–113, 114, 116, 131. See also Flat-Earth economics, debt inflation theory Fitzgerald, F. Scott, 165, 175 Flat-Earth economics: overview, 70–75 inflation targeting, 75–84 and the Great Depression, 84–94 debt inflation theory, 94–105 debt among nations, 105–115 and six sigma events, 111 Flower, Shawn, 295–296 Forbes, Steve, 203 Ford Foundation, 176–178 Ford, Henry, 177 Forecasting, 6–17 Foreclosure Act of 2008 (HR 3221), 142 Foster, Dean, 21 Foundations of Betrayal: How the Liberal Super Rich Undermine America (Kent), 175 Fox, Justin, 217 Frank, Barney, 139, 141, 186–187 Franklin, Benjamin, 42, 43, 44 Freddie Mac, 127, 139, 143, 149, 186, 190. See also Housing industry “Free banking,” 50, 158 “Free metallism,” 54–55, 110, 158 Friedman, Milton, 74, 85, 91–92, 112, 120 Friendly, Fred, 177 The Fundamental Problem with Fannie Mae and Freddie Mac (Wallison), 212 Fund, John, 185 Gaither, Rowan, 177 Geithner, Timothy, 32, 58, 72, 133, 211 General Electric, 317–318 General Motors, 318 Gibbon, Edward, 260 INDEX Gilbert, Seymour Parker, 62–63 Gingrich, Newt, 339 Gladwell, Malcom, 23 GMFS Limited, 352 Goble, Richard, 323, 325 Gold: as currency, 351–357 fiat currency system, 342–345 flexibility, 345–351 overview, 341–342 See also Fiat currency; Hard money; Socialism, and “I.O.U.S.A.”
Capitalism Without Capital: The Rise of the Intangible Economy by Jonathan Haskel, Stian Westlake
"Robert Solow", 23andMe, activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, Andrei Shleifer, bank run, banking crisis, Bernie Sanders, business climate, business process, buy and hold, Capital in the Twenty-First Century by Thomas Piketty, cloud computing, cognitive bias, computer age, corporate governance, corporate raider, correlation does not imply causation, creative destruction, dark matter, Diane Coyle, Donald Trump, Douglas Engelbart, Douglas Engelbart, Edward Glaeser, Elon Musk, endogenous growth, Erik Brynjolfsson, everywhere but in the productivity statistics, Fellow of the Royal Society, financial innovation, full employment, fundamental attribution error, future of work, Gini coefficient, Hernando de Soto, hiring and firing, income inequality, index card, indoor plumbing, intangible asset, Internet of things, Jane Jacobs, Jaron Lanier, job automation, Kenneth Arrow, Kickstarter, knowledge economy, knowledge worker, laissez-faire capitalism, liquidity trap, low skilled workers, Marc Andreessen, Mother of all demos, Network effects, new economy, open economy, patent troll, paypal mafia, Peter Thiel, pets.com, place-making, post-industrial society, Productivity paradox, quantitative hedge fund, rent-seeking, revision control, Richard Florida, ride hailing / ride sharing, Robert Gordon, Ronald Coase, Sand Hill Road, Second Machine Age, secular stagnation, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, software patent, sovereign wealth fund, spinning jenny, Steve Jobs, survivorship bias, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Tim Cook: Apple, total factor productivity, Tyler Cowen: Great Stagnation, urban planning, Vanguard fund, walkable city, X Prize, zero-sum game
But it would be going too far to say that no organizational investment is lasting and valuable. It seems obvious that there are businesses with strong cultures of good management and high performance, that creating and maintaining these cultures takes investment (both of time and of money), and that these companies are more likely to succeed than ones with worse cultures: think, for example, of kaizen in Toyota, or Six Sigma in General Electric (GE). Further examples are discussed in chapter 8. We know that innovation often involves investing in organizational change, such as creating a new business unit to sell a new product line. And it’s also possible to think of examples of companies that have invested to create valuable organizational assets outside their own firms. The remarkable Apple supply chain that Tim Cook was responsible for developing is clearly a long-term source of value for Apple, allowing it to bring products to market extraordinarily quickly.
., 131 rules and norms, 211–14 Sadun, Rafaella, 53, 82 Salter, Ammon, 197 Sampson, Rachelle, 168 Samsung, 73, 112 Sanders, Bernie, 223 Santa Fe Institute, 80 scalability, 9–10, 58, 60, 87, 101–2; definition of, 246n2; importance of, 67–68; income inequality and, 133–34; and increased investment, 110; and intangibles, 65–67; secular stagnation and, 103–5 Schreyer, Paul, 40 Schwarzenegger, Arnold, 16 Science: The Endless Frontier (Bush), 232 Second Machine Age, 30 secular stagnation, 91, 116; explanation for, 101–16; and intangibles investment, 102–3; profits and productivity differences and, 103–7; relationship of scalability and spillovers to, 109–16; symptoms of, 92–96 Shankar, Ravi, 61 Shi, Yuan, 168 Shih, Willy, 85 Shinoda, Yukio, 42 short-termism, 161, 168–69 Sichel, Dan, 4, 5, 39, 42, 43, 45 Siemens, 60–61, 204 single-factor productivity, 98–101 Six Sigma, 51 Skype, 217 Slack, 152, 217 smartphones, 72–73, 81 Smil, Vaclav, 146 Smith, Adam, 36, 188 social capital, 156, 236 soft infrastructure, 156 solar energy, 85 Solow, Robert, 39, 125 Song, Jae, 129, 131, 135 South Wales Institution of Engineers, 83 speculation, 249n1 spending, 46–47, 54; on assets, 20; rent-seeking, 113 Spenser, Percy, 80 spillovers, 9, 58, 61, 87, 102; contestedness and, 87; importance of, 77–79; and intangibles, 72–77, 109–16; Jacobs, 138; Marshall-Arrow-Romer, 62, 138; physical infrastructure and, 147–51; secular stagnation and, 103–4; slowing TFP growth and, 107–9; venture capital and, 178 Spotify, 18 Stack Overflow, 29 Stansted Airport, 1–2, 3–4 Starbucks, 34, 52, 65, 140, 183, 195, 197; scalability of, 67 start-up ecosystems, 222 Statute of Anne (1709), 76 stock markets, 167–68, 205–6; IPOs and, 171–72 stock of intangible assets, 56–57 Summers, Larry, 93 sunkenness, 8–9, 58, 60, 87, 246n5; as characteristic of intangibles, 68–70; importance of, 70–72; venture capital and, 175–76 sustained advantage, 250n2 Sutton, John, 67 symbolic analysis, 132–34 synergies, 10, 58, 61, 87–88, 213; and intangible assets, 80–83, 83–86; among investments, 110; maximizing the benefits of, 214–18; physical infrastructure and, 147–51; venture capital and, 176 System of National Accounts, 20, 43, 51 systems innovation, 198 tacit knowledge, 65 tangible investments, differences between intangible and, 7–10, 58 taxes, 139–40, 235; and financing, 166, 219 technology: and cost of intangible investment, 28; inequality as result of improvements in, 123–24, 126–27; and productivity of intangibles, 28–30; and spillovers, 151–52 Tesla Motors, 24, 111, 209 Thatcher, Margaret, 127 Theory of Moral Sentiments, The (Smith), 188 Thiel, Peter, 78, 175, 184–85, 187, 223 3M, 194 Toffler, Alvin, 4 Tonogi, Konomi, 42 total factor productivity (TFP), 96, 98, 102; poor performance of, 109–9, 114 Toyota, 29, 51 trade and inequality, 124 trademarks, 76 training and education, 51–52, 170, 228–30 Trajtenberg, Manuel, 106 Trump, Donald, 122, 141–42, 143 trust, 156 23andMe, 152 Twitter, 185, 187 Uber, 24, 28, 51; building of driver network by, 112–13; contestedness and, 115; legal travails of, 187; scalability of, 67, 101–2, 105; and synergies, 82; venture capital and, 174, 175 uncertainty, 87 Ure, Andrew, 126 Ur-Nammu, 75 US Federal Reserve, 4, 40, 41, 42, 165 US Food and Drug Administration, 154 Van Reenen, John, 82, 136, 173, 195 venture capital (VC) funding, 154–55, 161, 166, 174–75; problems with, 177–79; and intangibles, 175–77 Vlachos, Jonas, 131 Volcker, Paul, 165 von Mises, Ludwig, 38 von Wachter, Till, 129 Wallis, Gavin, 42, 223–24 Walmart, 81, 187 Warsh, David, 62 Wasmer, Etienne, 128 Watt, James, 78 wealth, 119–20, 121; housing and, 122, 128–29, 136–39; inequality of, 139–40; intangibles’ effects on, 129–40 Wealth of Nations, The (Smith), 36 Weightless World, The (Coyle), 4 Weitzman, Martin L., 195 Welch, Jack, 184 Whalley, Alexander, 224 “What Is the U.S.
Frugal Innovation: How to Do Better With Less by Jaideep Prabhu Navi Radjou
3D printing, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, barriers to entry, Baxter: Rethink Robotics, Bretton Woods, business climate, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, cloud computing, collaborative consumption, collaborative economy, Computer Numeric Control, connected car, corporate social responsibility, creative destruction, crowdsourcing, disruptive innovation, Elon Musk, financial exclusion, financial innovation, global supply chain, IKEA effect, income inequality, industrial robot, intangible asset, Internet of things, job satisfaction, Khan Academy, Kickstarter, late fees, Lean Startup, low cost airline, low cost carrier, M-Pesa, Mahatma Gandhi, megacity, minimum viable product, more computing power than Apollo, new economy, payday loans, peer-to-peer lending, Peter H. Diamandis: Planetary Resources, precision agriculture, race to the bottom, reshoring, risk tolerance, Ronald Coase, self-driving car, shareholder value, sharing economy, Silicon Valley, Silicon Valley startup, six sigma, smart grid, smart meter, software as a service, standardized shipping container, Steve Jobs, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, transaction costs, Travis Kalanick, unbanked and underbanked, underbanked, women in the workforce, X Prize, yield management, Zipcar
Polman believes that Unilever’s frugal innovation initiatives, many of which are described in this book, are not altruistic but simply common sense. Meanwhile, frugal innovation seeks to reduce not just the financial cost of doing business but also its environmental cost. Frugal innovation also seeks to minimise time, especially important in such situations as bringing a promising new drug to market. Frugal innovation is not a management technique like Six Sigma and total quality management (TQM), which aim to reduce cost and waste. Rather, cost efficiency is a means to achieve the larger goal of greater customer value, as is manifest in $30 computers, $40 tablets, $800 electrocardiogram (ECG) machines and $6,000 cars. It is also possible for firms to be frugal in how they develop and market new products and services, while exercising discretion over whether or not they pass these savings on to consumers.
MacArthur Foundation 14 John Deere 67 John Lewis 195 Johnson & Johnson 100, 111 Johnson, Warren 98 Jones, Don 112 jugaad (frugal ingenuity) 199, 202 Jugaad Innovation (Radjou, Prabhu and Ahuja, 2012) xvii, 17 just-in-time design 33–4 K Kaeser, Joe 217 Kalanick, Travis 163 Kalundborg (Denmark) 160 kanju 201 Karkal, Shamir 124 Kaufman, Ben 50–1, 126 Kawai, Daisuke 29–30 Kelly, John 199–200 Kennedy, President John 138 Kenya 57, 200–1 key performance indicators see KPIs Khan Academy 16–17, 113–14, 164 Khan, Salman (Sal) 16–17, 113–14 Kickstarter 17, 48, 137, 138 KieranTimberlake 196 Kimberly-Clark 25, 145 Kingfisher 86–7, 91, 97, 157, 158–9, 185–6, 192–3, 208 KissKissBankBank 17, 137 Knox, Steve 145 Knudstorp, Jørgen Vig 37, 68, 69 Kobori, Michael 83, 100 KPIs (key performance indicators) 38–9, 67, 91–2, 185–6, 208 Kuhndt, Michael 194 Kurniawan, Arie 151–2 L La Chose 108 La Poste 92–3, 157 La Ruche qui dit Oui 137 “labs on a chip” 52 Lacheret, Yves 173–5 Lada 1 laser cutters 134, 166 Laskey, Alex 119 last-mile challenge 57, 146, 156 L’Atelier 168–9 Latin America 161 lattice organisation 63–4 Laury, Véronique 208 Laville, Elisabeth 91 Lawrence, Jamie 185, 192–3, 208 LCA (life-cycle assessment) 196–7 leaders 179, 203–5, 214, 217 lean manufacturing 192 leanness 33–4, 41, 42, 170, 192 Learnbox 114 learning by doing 173, 179 learning organisations 179 leasing 123 Lee, Deishin 159 Lego 51, 126 Lego Group 37, 68, 69, 144 Legrand 157 Lenovo 56 Leroy, Adolphe 127 Leroy Merlin 127–8 Leslie, Garthen 150–1 Lever, William Hesketh 96 Levi Strauss & Co 60, 82–4, 100, 122–3 Lewis, Dijuana 212 life cycle of buildings 196 see also product life cycle life-cycle assessment (LCA) 196–7 life-cycle costs 12, 24, 196 Lifebuoy soap 95, 97 lifespan of companies 154 lighting 32, 56, 123, 201 “lightweighting” 47 linear development cycles 21, 23 linear model of production 80–1 Link 131 littleBits 51 Livi, Daniele 88 Livi, Vittorio 88 local communities 52, 57, 146, 206–7 local markets 183–4 Local Motors 52, 129, 152 local solutions 188, 201–2 local sourcing 51–2, 56, 137, 174, 181 localisation 56, 137 Locavesting (Cortese, 2011) 138 Logan car 2–3, 12, 179, 198–9 logistics 46, 57–8, 161, 191, 207 longevity 121, 124 Lopez, Maribel 65–6 Lopez Research 65–6 L’Oréal 174 Los Alamos National Laboratory 170 low-cost airlines 60, 121 low-cost innovation 11 low-income markets 12–13, 161, 203, 207 Lowry, Adam 81–2 M m-health 109, 111–12 M-KOPA 201 M-Pesa 57, 201 M3D 48, 132 McDonough Braungart Design Chemistry (MBDC) 84 McDonough, William 82 McGregor, Douglas 63 MacGyvers 17–18, 130, 134, 167 McKelvey, Jim 135 McKinsey & Company 81, 87, 209 mainstream, frugal products in 216 maintenance 66, 75, 76, 124, 187 costs 48–9, 66 Mainwaring, Simon 8 Maistre, Christophe de 187–8, 216 Maker Faire 18, 133–4 Maker platform 70 makers 18, 133–4, 145 manufacturing 20th-century model 46, 55, 80–1 additive 47–9 continuous 44–5 costs 47, 48, 52 decentralised 9, 44, 51–2 frugal 44–54 integration with logistics 57–8 new approaches 50–4 social 50–1 subtractive method 48 tools for 47, 47–50 Margarine Unie 96 market 15, 28, 38, 64, 186, 189, 192 R&D and 21, 26, 33, 34 market research 25, 61, 139, 141 market share 100 marketing 21–2, 24, 36, 61–3, 91, 116–20, 131, 139 and R&D 34, 37, 37–8 marketing teams 143, 150 markets 12–13, 42, 62, 215 see also emerging markets Marks & Spencer (M&S) 97, 215 Plan A 90, 156, 179–81, 183–4, 186–7, 214 Marriott 140 Mars 57, 158–9, 161 Martin Marietta 159 Martin, Tod 154 mass customisation 9, 46, 47, 48, 57–8 mass market 189 mass marketing 21–2 mass production 9, 46, 57, 58, 74, 129, 196 Massachusetts Institute of Technology see MIT massive open online courses see MOOCs materials 3, 47, 48, 73, 92, 161 costs 153, 161, 190 recyclable 74, 81, 196 recycled 77, 81–2, 83, 86, 89, 183, 193 renewable 77, 86 repurposing 93 see also C2C; reuse Mayhew, Stephen 35, 36 Mazoyer, Eric 90 Mazzella, Frédéric 163 MBDC (McDonough Braungart Design Chemistry) 84 MDI 16 measurable goals 185–6 Mechanical Engineer Laboratory (MEL) 52 “MEcosystems” 154–5, 156–8 Medicare 110 medication 111–12 Medicity 211 MedStartr 17 MEL (Mechanical Engineer Laboratory) 52 mental models 2, 193–203, 206, 216 Mercure 173 Merlin, Rose 127 Mestrallet, Gérard 53, 54 method (company) 81–2 Mexico 38, 56 Michelin 160 micro-factories 51–2, 52, 66, 129, 152 micro-robots 52 Microsoft 38 Microsoft Kinect 130 Microsoft Word 24 middle classes 197–8, 216 Migicovsky, Eric 137–8 Mikkiche, Karim 199 millennials 7, 14, 17, 131–2, 137, 141, 142 MindCET 165 miniaturisation 52, 53–4 Mint.com 125 MIT (Massachusetts Institute of Technology) 44–5, 107, 130, 134, 202 mobile health see m-health mobile phones 24, 32, 61, 129–30, 130, 168, 174 emerging market use 198 infrastructure 56, 198 see also smartphones mobile production units 66–7 mobile technologies 16, 17, 103, 133, 174, 200–1, 207 Mocana 151 Mochon, Daniel 132 modular design 67, 90 modular production units 66–7 Modularer Querbaukasten see MQB “mompreneurs” 145 Mondelez 158–9 Money Dashboard 125 Moneythink 162 monitoring 65–6, 106, 131 Monopoly 144 MOOCs (massive open online courses) 60, 61, 112, 113, 114, 164 Morieux, Yves 64 Morocco 207 Morris, Robert 199–200 motivation, employees 178, 180, 186, 192, 205–8 motivational approaches to shaping consumer behaviour 105–6 Motorola 56 MQB (Modularer Querbaukasten) 44, 45–6 Mulally, Alan 70, 166 Mulcahy, Simon 157 Mulliez family 126–7 Mulliez, Vianney 13, 126 multi-nodal innovation 202–3 Munari, Bruno 93 Murray, Mike 48–9 Musk, Elon 172 N Nano car 119, 156 National Geographic 102 natural capital, loss of 158–9 Natural Capital Leaders Platform 158–9 natural resources 45, 86 depletion 7, 72, 105, 153, 158–9 see also resources NCR 55–6 near-shoring 55 Nelson, Simon 113 Nemo, Sophie-Noëlle 93 Nest Labs 98–100, 103 Nestlé 31, 44, 68, 78, 94, 158–9, 194, 195 NetPositive plan 86, 208 networking 152–3, 153 new materials 47, 92 New Matter 132 new technologies 21, 27 Newtopia 32 next-generation customers 121–2 next-generation manufacturing techniques 44–6, 46–7 see also frugal manufacturing Nigeria 152, 197–8 Nike 84 NineSigma 151 Nissan 4, 4–5, 44, 199 see also Renault-Nissan non-governmental organisations 167 non-profit organisations 161, 162, 202 Nooyi, Indra 217 Norman, Donald 120 Norris, Greg 196 North American companies 216–17 North American market 22 Northrup Grumman 68 Norton, Michael 132 Norway 103 Novartis 44–5, 215 Novotel 173, 174 nudging 100, 108, 111, 117, 162 Nussbaum, Bruce 140 O O2 147 Obama, President Barack 6, 8, 13, 134, 138, 208 obsolescence, planned 24, 121 offshoring 55 Oh, Amy 145 Ohayon, Elie 71–2 Oliver Wyman 22 Olocco, Gregory 206 O’Marah, Kevin 58 on-demand services 39, 124 online communities 31, 50, 61, 134 online marketing 143 online retailing 60, 132 onshoring 55 Opel 4 open innovation 104, 151, 152, 153, 154 open-source approach 48, 129, 134, 135, 172 open-source hardware 51, 52, 89, 130, 135, 139 open-source software 48, 130, 132, 144–5, 167 OpenIDEO 142 operating costs 45, 215 Opower 103, 109, 119 Orange 157 Orbitz 173 organisational change 36–7, 90–1, 176, 177–90, 203–8, 213–14, 216 business models 190–3 mental models 193–203 organisational culture 36–7, 170, 176, 177–9, 213–14, 217 efficacy focus 181–3 entrepreneurial 76, 173 see also organisational change organisational structure 63–5, 69 outsourcing 59, 143, 146 over-engineering 27, 42, 170 Overby, Christine 25 ownership 9 Oxylane Group 127 P P&G (Procter & Gamble) 19, 31, 58, 94, 117, 123, 145, 195 packaging 57, 96, 195 Page, Larry 63 “pain points” 29, 30, 31 Palmer, Michael 212 Palo Alto Junior League 20 ParkatmyHouse 17, 63, 85 Parker, Philip 61 participation, customers 128–9 partner ecosystems 153, 154, 200 partners 65, 72, 148, 153, 156–8 sharing data with 59–60 see also distributors; hyper-collaboration; suppliers Partners in Care Foundation 202 partnerships 41, 42, 152–3, 156–7, 171–2, 174, 191 with SMBs 173, 174, 175 with start-ups 20, 164–5, 175 with suppliers 192–3 see also hyper-collaboration patents 171–2 Payne, Alex 124 PE International 196 Pearson 164–5, 167, 181–3, 186, 215 Pebble 137–8 peer-to-peer economic model 10 peer-to-peer lending 10 peer-to-peer sales 60 peer-to-peer sharing 136–7 Pélisson, Gérard 172–3 PepsiCo 38, 40, 179, 190, 194, 215 performance 47, 73, 77, 80, 95 of employees 69 Pernod Ricard 157 personalisation 9, 45, 46, 48, 62, 129–30, 132, 149 Peters, Tom 21 pharmaceutical industry 13, 22, 23, 33, 58, 171, 181 continuous manufacturing 44–6 see also GSK Philippines 191 Philips 56, 84, 100, 123 Philips Lighting 32 Picaud, Philippe 122 Piggy Mojo 119 piggybacking 57 Piketty, Thomas 6 Plan A (M&S) 90, 156, 179–81, 183–4, 186–7, 214 Planet 21 (Accor) 174–5 planned obsolescence 24, 121 Plastyc 17 Plumridge, Rupert 18 point-of-sale data 58 Poland 103 pollution 74, 78, 87, 116, 187, 200 Polman, Paul 11, 72, 77, 94, 203–5, 217 portfolio management tools 27, 33 Portugal 55, 103 postponement 57–8 Potočnik, Janez 8, 79 Prabhu, Arun 25 Prahalad, C.K. 12 predictive analytics 32–3 predictive maintenance 66, 67–8 Priceline 173 pricing 81, 117 processes digitising 65–6 entrenched 14–16 re-engineering 74 simplifying 169, 173 Procter & Gamble see P&G procurement priorities 67–8 product life cycle 21, 75, 92, 186 costs 12, 24, 196 sustainability 73–5 product-sharing initiatives 87 production costs 9, 83 productivity 49, 59, 65, 79–80, 153 staff 14 profit 14, 105 Progressive 100, 116 Project Ara 130 promotion 61–3 Propeller Health 111 prosumers xix–xx, 17–18, 125, 126–33, 136–7, 148, 154 empowering and engaging 139–46 see also horizontal economy Protomax 159 prototypes 31–2, 50, 144, 152 prototyping 42, 52, 65, 152, 167, 192, 206 public 50–1, 215 public sector, working with 161–2 publishers 17, 61 Pullman 173 Puma 194 purchasing power 5–6, 216 pyramidal model of production 51 pyramidal organisations 69 Q Qarnot Computing 89 Qualcomm 84 Qualcomm Life 112 quality 3, 11–12, 15, 24, 45, 49, 82, 206, 216 high 1, 9, 93, 198, 216 measure of 105 versus quantity 8, 23 quality of life 8, 204 Quicken 19–21 Quirky 50–1, 126, 150–1, 152 R R&D 35, 67, 92, 151 big-ticket programmes 35–6 and business development 37–8 China 40, 188, 206 customer focus 27, 39, 43 frugal approach 12, 26–33, 82 global networks 39–40 incentives 38–9 industrial model 2, 21–6, 33, 36, 42 market-focused, agile model 26–33 and marketing 34, 37, 37–8 recommendations for managers 34–41 speed 23, 27, 34, 149 spending 15, 22, 23, 28, 141, 149, 152, 171, 187 technology culture 14–15, 38–9 see also Air Liquide; Ford; GSK; IBM; immersion; Renault; SNCF; Tarkett; Unilever R&D labs 9, 21–6, 70, 149, 218 in emerging markets 40, 188, 200 R&D teams 26, 34, 38–9, 65, 127, 150, 194–5 hackers as 142 innovation brokering 168 shaping customer behaviour 120–2 Raspberry Pi 135–6, 164 Ratti, Carlo 107 raw materials see materials real-time demand signals 58, 59 Rebours, Christophe 157–8 recession 5–6, 6, 46, 131, 180 Reckitt Benckiser 102 recommendations for managers flexing assets 65–71 R&D 34–41 shaping consumer behaviour 116–24 sustainability 90–3 recruiting 70–1 recyclable materials 74, 81, 196 recyclable products 3, 73, 159, 195–6 recycled materials 77, 81–2, 83, 86, 89, 183, 193 recycling 8, 9, 87, 93, 142, 159 e-waste 87–8 electronic and electrical goods (EU) 8, 79 by Tarkett 73–7 water 83, 175 see also C2C; circular economy Recy’Go 92–3 regional champions 182 regulation 7–8, 13, 78–9, 103, 216 Reich, Joshua 124 RelayRides 17 Renault 1–5, 12, 117, 156–7, 179 Renault-Nissan 4–5, 40, 198–9, 215 renewable energy 8, 53, 74, 86, 91, 136, 142, 196 renewable materials 77, 86 Replicator 132 repurposing 93 Requardt, Hermann 189 reshoring 55–6 resource constraints 4–5, 217 resource efficiency 7–8, 46, 47–9, 79, 190 Resource Revolution (Heck, Rogers and Carroll, 2014) 87–8 resources 40, 42, 73, 86, 197, 199 consumption 9, 26, 73–7, 101–2 costs 78, 203 depletion 7, 72, 105, 153, 158–9 reducing use 45, 52, 65, 73–7, 104, 199, 203 saving 72, 77, 200 scarcity 22, 46, 72, 73, 77–8, 80, 158–9, 190, 203 sharing 56–7, 159–61, 167 substitution 92 wasting 169–70 retailers 56, 129, 214 “big-box” 9, 18, 137 Rethink Robotics 49 return on investment 22, 197 reuse 9, 73, 76–7, 81, 84–5, 92–3, 200 see also C2C revenues, generating 77, 167, 180 reverse innovation 202–3 rewards 37, 178, 208 Riboud, Franck 66, 184, 217 Rifkin, Jeremy 9–10 robots 47, 49–50, 70, 144–5, 150 Rock Health 151 Rogers, Jay 129 Rogers, Matt 87–8 Romania 2–3, 103 rookie mindset 164, 168 Rose, Stuart 179–80, 180 Roulin, Anne 195 Ryan, Eric 81–2 Ryanair 60 S S-Oil 106 SaaS (software as a service) 60 Saatchi & Saatchi 70–1 Saatchi & Saatchi + Duke 71–2, 143 sales function 15, 21, 25–6, 36, 116–18, 146 Salesforce.com 157 Santi, Paolo 108 SAP 59, 186 Saunders, Charles 211 savings 115 Sawa Orchards 29–31 Scandinavian countries 6–7 see also Norway Schmidt, Eric 136 Schneider Electric 150 Schulman, Dan 161–2 Schumacher, E.F. 104–5, 105 Schweitzer, Louis 1, 2, 3, 4, 179 SCM (supply chain management) systems 59 SCOR (supply chain operations reference) model 67 Seattle 107 SEB 157 self-sufficiency 8 selling less 123–4 senior managers 122–4, 199 see also CEOs; organisational change sensors 65–6, 106, 118, 135, 201 services 9, 41–3, 67–8, 124, 149 frugal 60–3, 216 value-added 62–3, 76, 150, 206, 209 Shapeways 51, 132 shareholders 14, 15, 76, 123–4, 180, 204–5 sharing 9–10, 193 assets 159–61, 167 customers 156–8 ideas 63–4 intellectual assets 171–2 knowledge 153 peer-to-peer 136–9 resources 56–7, 159–61, 167 sharing economy 9–10, 17, 57, 77, 80, 84–7, 108, 124 peer-to-peer sharing 136–9 sharing between companies 159–60 shipping costs 55, 59 shopping experience 121–2 SIEH hotel group 172–3 Siemens 117–18, 150, 187–9, 215, 216 Sigismondi, Pier Luigi 100 Silicon Valley 42, 98, 109, 150, 151, 162, 175 silos, breaking out of 36–7 Simple Bank 124–5 simplicity 8, 41, 64–5, 170, 194 Singapore 175 Six Sigma 11 Skillshare 85 SkyPlus 62 Small is Beautiful (Schumacher, 1973) 104–5 “small is beautiful” values 8 small and medium-sized businesses see SMBs Smart + Connected Communities 29 SMART car 119–20 SMART strategy (Siemens) 188–9 smartphones 17, 100, 106, 118, 130, 131, 135, 198 in health care 110, 111 see also apps SmartScan 29 SMBs (small and medium-sized businesses) 173, 174, 175, 176 SMS-based systems 42–3 SnapShot 116 SNCF 41–3, 156–7, 167 SoapBox 28–9 social business model 206–7 social comparison 109 social development 14 social goals 94 social learning 113 social manufacturing 47, 50–1 social media 16, 71, 85, 106, 108, 168, 174 for marketing 61, 62, 143 mining 29, 58 social pressure of 119 tools 109, 141 and transaction costs 133 see also Facebook; social networks; Twitter social networks 29, 71, 72, 132–3, 145, 146 see also Facebook; Twitter social pressure 119 social problems 82, 101–2, 141, 142, 153, 161–2, 204 social responsibility 7, 10, 14, 141, 142, 197, 204 corporate 77, 82, 94, 161 social sector, working with 161–2 “social tinkerers” 134–5 socialising education 112–14 Sofitel 173 software 72 software as a service (SaaS) 60 solar power 136, 201 sourcing, local 51–2, 56 Southwest Airlines 60 Spain 5, 6, 103 Spark 48 speed dating 175, 176 spending, on R&D 15, 22, 23, 28, 141, 149, 152, 171, 187 spiral economy 77, 87–90 SRI International 49, 52 staff see employees Stampanato, Gary 55 standards 78, 196 Starbucks 7, 140 start-ups 16–17, 40–1, 61, 89, 110, 145, 148, 150, 169, 216 investing in 137–8, 157 as partners 42, 72, 153, 175, 191, 206 see also Nest Labs; Silicon Valley Statoil 160 Steelcase 142 Stem 151 Stepner, Diana 165 Stewart, Emma 196–7 Stewart, Osamuyimen 201–2 Sto Corp 84 Stora Enso 195 storytelling 112, 113 Strategy& see Booz & Company Subramanian, Prabhu 114 substitution of resources 92 subtractive manufacturing 48 Sun Tzu 158 suppliers 67–8, 83, 148, 153, 167, 176, 192–3 collaboration with 76, 155–6 sharing with 59–60, 91 visibility 59–60 supply chain management see SCM supply chain operations reference (SCOR) model 67 supply chains 34, 36, 54, 65, 107, 137, 192–3 carbon footprint 156 costs 58, 84 decentralisation 66–7 frugal 54–60 integrating 161 small-circuit 137 sustainability 137 visibility 34, 59–60 support 135, 152 sustainability xix, 9, 12, 72, 77–80, 82, 97, 186 certification 84 as competitive advantage 80 consumers and 95, 97, 101–4 core design principle 82–4, 93, 195–6 and growth 76, 80, 104–5 perceptions of 15–16, 80, 91 recommendations for managers 90–3 regulatory demand for 78–9, 216 standard bearers of 80, 97, 215 see also Accor; circular economy; Kingfisher; Marks & Spencer; Tarkett; Unilever sustainable design 82–4 see also C2C sustainable distribution 57, 161 sustainable growth 72, 76–7 sustainable lifestyles 107–8 Sustainable Living Plan (Unilever) 94–7, 179, 203–4 sustainable manufacturing 9, 52 T “T-shaped” employees 70–1 take-back programmes 9, 75, 77, 78 Tally 196–7 Tarkett 73–7, 80, 84 TaskRabbit 85 Tata Motors 16, 119 Taylor, Frederick 71 technical design 37–8 technical support, by customers 146 technology 2, 14–15, 21–2, 26, 27 TechShop 9, 70, 134–5, 152, 166–7 telecoms sector 53, 56 Telefónica 147 telematic monitoring 116 Ternois, Laurence 42 Tesco 102 Tesla Motors 92, 172 testing 28, 42, 141, 170, 192 Texas Industries 159 Textoris, Vincent 127 TGV Lab 42–3 thermostats 98–100 thinking, entrenched 14–16 Thompson, Gav 147 Timberland 90 time 4, 7, 11, 41, 72, 129, 170, 200 constraints 36, 42 see also development cycle tinkerers 17–18, 133–5, 144, 150, 152, 153, 165–7, 168 TiVo 62 Tohamy, Noha 59–60 top-down change 177–8 top-down management 69 Total 157 total quality management (TQM) 11 total volatile organic compounds see TVOC Toyota 44, 100 Toyota Sweden 106–7 TQM (total quality management) 11 traffic 108, 116, 201 training 76, 93, 152, 167, 170, 189 transaction costs 133 transparency 178, 185 transport 46, 57, 96, 156–7 Transport for London 195 TrashTrack 107 Travelocity 174 trial and error 173, 179 Trout, Bernhardt 45 trust 7, 37, 143 TVOC (total volatile organic compounds) 74, 77 Twitter 29, 62, 135, 143, 147 U Uber 136, 163 Ubuntu 202 Uchiyama, Shunichi 50 UCLA Health 202–3 Udacity 61, 112 UK 194 budget cuts 6 consumer empowerment 103 industrial symbiosis 160 savings 115 sharing 85, 138 “un-management” 63–4, 64 Unboundary 154 Unilever 11, 31, 57, 97, 100, 142, 203–5, 215 and sustainability 94–7, 104, 179, 203–4 University of Cambridge Engineering Design Centre (EDC) 194–5 Inclusive Design team 31 Institute for Sustainability Leadership (CISL) 158–9 upcycling 77, 88–9, 93, 159 upselling 189 Upton, Eben 135–6 US 8, 38, 44, 87, 115, 133, 188 access to financial services 13, 17, 161–2 ageing population 194 ageing workforce 13 commuting 131 consumer spending 5, 6, 103 crowdfunding 137–8, 138 economic pressures 5, 6 energy use 103, 119, 196 environmental awareness 7, 102 frugal innovation in 215–16, 218 health care 13, 110, 208–13, 213 intellectual property 171 onshoring 55 regulation 8, 78, 216 sharing 85, 138–9 shifting production from China to 55, 56 tinkering culture 18, 133–4 user communities 62, 89 user interfaces 98, 99 user-friendliness 194 Utopies 91 V validators 144 value 11, 132, 177, 186, 189–90 aspirational 88–9 to customers 6–7, 21, 77, 87, 131, 203 from employees 217 shareholder value 14 value chains 9, 80, 128–9, 143, 159–60, 190, 215 value engineering 192 “value gap” 54–5 value-added services 62–3, 76, 150, 206, 209 values 6–7, 14, 178, 205 Vandebroek, Sophie 169 Vasanthakumar, Vaithegi 182–3 Vats, Tanmaya 190, 192 vehicle fleets, sharing 57, 161 Verbaken, Joop 118 vertical integration 133, 154 virtual prototyping 65 virtuous cycle 212–13 visibility 34, 59–60 visible learning 112–13 visioning sessions 193–4 visualisation 106–8 Vitality 111 Volac 158–9 Volkswagen 4, 44, 45–6, 129, 144 Volvo 62 W wage costs 48 wages, in emerging markets 55 Waitrose, local suppliers 56 Walker, James 87 walking the walk 122–3 Waller, Sam 195 Walmart 9, 18, 56, 162, 216 Walton, Sam 9 Wan Jia 144 Washington DC 123 waste 24, 87–9, 107, 159–60, 175, 192, 196 beautifying 88–9, 93 e-waste 24, 79, 87–8, 121 of energy 119 post-consumer 9, 75, 77, 78, 83 reducing 47, 74, 85, 96, 180, 209 of resources 169–70 in US health-care system 209 see also C2C; recycling; reuse water 78, 83, 104, 106, 158, 175, 188, 206 water consumption 79, 82–3, 100, 196 reducing 74, 75, 79, 104, 122–3, 174, 183 wealth 105, 218 Wear It Share It (Wishi) 85 Weijmarshausen, Peter 51 well-being 104–5 Wham-O 56 Whirlpool 36 “wicked” problems 153 wireless technologies 65–6 Wiseman, Liz 164 Wishi (Wear It Share It) 85 Witty, Andrew 35, 35–6, 37, 39, 217 W.L.
Big Blues: The Unmaking of IBM by Paul Carroll
accounting loophole / creative accounting, full employment, John Markoff, Mitch Kapor, popular electronics, Robert Metcalfe, Ronald Reagan, Silicon Valley, six sigma, software patent, Steve Ballmer, Steve Jobs, Steven Levy, thinkpad, traveling salesman
“This has captured the imagination of IBM people m uch more than I ever thought it would,” he said. “Now people are w andering around thinking about how to conduct their business perfectly. It’s astonishing. It’s the best thing to ever happen to us.” 1 But the heavy-handed approach gave the troops mixed feelings at best about Quality— known at IBM as M arket-Driven Quality, or, given the need for an acronym, M D Q — and its obsession with the Six Sigma m easurem ent. “Six Sigma Equals Heil H itler,” one person wrote on a form requesting anonymous feedback on the Quality program. Another BIG BLUES 245 employee com plained about how IBM was continuing to cut back on its num ber of employees and wrote that M DQ really stood for “Move, Die or Q uit.” An underground employee newsletter stated that M DQ must mean “M anagem ent-Driven Quest (for bigger bonuses).”
IBM had to win on its own merits, and it would find itself besting its little com petitors only some of the time. Besides pushing on the OEM front, Akers also decided to begin a Quality program, joining a host of American companies adopting Japa nese ideas about the need for measurable results in all business pro cesses and for constant im provem ent in those results. The eventual aim was to reach a nirvanalike state called Six Sigma, in which a company would be making fewer than 3.4 mistakes p er million products made, calls answered, and so on. Akers started out with the best of intentions. He had someone calculate that IBM spent $2.4 billion a year fixing problems with products; had those problems never occurred, that $2.4 billion would have dropped right down into IBM ’s profits. Akers also said, correctly, that IBM was frustrating customers with, for instance, bills so confusing that the customers sometimes paid IBM to help them decipher the bills.
Only Humans Need Apply: Winners and Losers in the Age of Smart Machines by Thomas H. Davenport, Julia Kirby
AI winter, Andy Kessler, artificial general intelligence, asset allocation, Automated Insights, autonomous vehicles, basic income, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, commoditize, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, digital map, disruptive innovation, Douglas Engelbart, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, fixed income, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, global pandemic, Google Glasses, Hans Lippershey, haute cuisine, income inequality, index fund, industrial robot, information retrieval, intermodal, Internet of things, inventory management, Isaac Newton, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joi Ito, Khan Academy, knowledge worker, labor-force participation, lifelogging, longitudinal study, loss aversion, Mark Zuckerberg, Narrative Science, natural language processing, Norbert Wiener, nuclear winter, pattern recognition, performance metric, Peter Thiel, precariat, quantitative trading / quantitative ﬁnance, Ray Kurzweil, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, social intelligence, speech recognition, spinning jenny, statistical model, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, superintelligent machines, supply-chain management, transaction costs, Tyler Cowen: Great Stagnation, Watson beat the top human players on Jeopardy!, Works Progress Administration, Zipcar
A study of process automation at Telefónica’s O2—the second-largest mobile carrier in the United Kingdom—found that as of April 2015, the company had automated more than 160 process areas involving between 400,000 and 500,000 transactions.9 Each of the process areas employed software “robots” from vendor Blue Prism. The overall ROI of this technology was between 650 and 800 percent. That’s a better payoff than most companies achieved from other approaches to process improvement, including reengineering and Six Sigma. There is certainly organizational and behavioral change involved with this form of technology, and it may eventually lead to layoffs. But most of the companies we’ve observed have redeployed workers to other roles. Human employees’ initial mistrust of automation tools gives way to relief that boring work is being done by a machine. At Xchanging, a process outsourcing company in the United Kingdom, the Blue Prism “robots” were given cute names like Poppy (after the poppies people wear in that country on Remembrance Day, when the machine went live) and Henry.10 The anthropomorphizing of these smart machines suggests that workers didn’t find this form of technology particularly threatening.
If you want an automation leader for your organization, you may have to find a similar “unicorn” with an unusual combination of backgrounds. Of course, different emphases in an organization’s automation or augmentation programs require different types of people. At Xchanging, the highly process-oriented nature of the work means that the head of “Robotic Automation,” Paul Donaldson (he has since moved to a similar job in a different company), needed a strong process focus. Fortunately, he’s a Six Sigma Black Belt. Donaldson says that his key responsibilities included directing the overall operation of robotic process automation, deciding which processes to apply it to, education, coordinating with IT, and setting the direction for where to go with the technology. He also worked closely with a systems manager in Xchanging’s IT organization who handles the technical aspects of the system and the interfaces with other systems.
The Butterfly Defect: How Globalization Creates Systemic Risks, and What to Do About It by Ian Goldin, Mike Mariathasan
"Robert Solow", air freight, Andrei Shleifer, Asian financial crisis, asset-backed security, bank run, barriers to entry, Basel III, Berlin Wall, Bretton Woods, BRICs, business cycle, butterfly effect, clean water, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, connected car, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, David Ricardo: comparative advantage, deglobalization, Deng Xiaoping, discovery of penicillin, diversification, diversified portfolio, Douglas Engelbart, Douglas Engelbart, Edward Lorenz: Chaos theory, energy security, eurozone crisis, failed state, Fellow of the Royal Society, financial deregulation, financial innovation, financial intermediation, fixed income, Gini coefficient, global pandemic, global supply chain, global value chain, global village, income inequality, information asymmetry, Jean Tirole, John Snow's cholera map, Kenneth Rogoff, light touch regulation, Long Term Capital Management, market bubble, mass immigration, megacity, moral hazard, Occupy movement, offshore financial centre, open economy, profit maximization, purchasing power parity, race to the bottom, RAND corporation, regulatory arbitrage, reshoring, Silicon Valley, six sigma, Stuxnet, supply-chain management, The Great Moderation, too big to fail, Toyota Production System, trade liberalization, transaction costs, uranium enrichment
Taiichi Ohno, 1988, Toyota Production System: Beyond Large-Scale Production (Portland, OR: Productivity Press). 18. Goldin, 2011, 30–31; see also David Magee, 2008, How Toyota Became #1: Leadership Lessons from the World’s Greatest Car Company (New York: Portfolio). 19. For a more detailed discussion of Toyota’s economic system, see Michael L. George, David T. Rowlands, and Bill Kastle, 2003, What Is Lean Six Sigma? (New York: McGraw-Hill Professional); Jeffrey Liker, 2004, The Toyota Way: 14 Management Principles from the World’s Greatest Manufacturer (New York: McGraw-Hill Professional); Magee, 2008; or Goldin, 2011, among others. 20. Markillie, 2006. 21. One estimate puts the total economic losses attributed to the floods by 1 December 2011 at US$45.7 billion and the damage to manufacturing at US$32 billion.
Georg, Co-Pierre, and Jenny Poschmann. 2010. “Systemic Risk in a Network Model of Interbank Markets with Central Bank Activity.” Jena Economic Research Paper 2010-33. Friedrich Schiller University and the Max Planck Institute of Economics, Jena, Germany. Accessed 1 February 2013. http://pubdb.wiwi.uni-jena.de/pdf/wp_2010_033.pdf. George, Michael L., David T. Rowlands, and Bill Kastle. 2003. What Is Lean Six Sigma? New York: McGraw-Hill Professional. Giddens, Anthony. 1991. The Consequences of Modernity. Stanford, CA: Stanford University Press. Gigerenzer, Gerd. 2010. Rationality for Mortals: How People Cope with Uncertainty. New York: Oxford University Press. Gigerenzer, Gerd, Ralph Hertwig, and Thorsten Pachur, eds. 2011. Heuristics: The Foundations of Adaptive Behavior. Oxford, UK: Oxford University Press.
Top Dog: The Science of Winning and Losing by Po Bronson, Ashley Merryman
Asperger Syndrome, Berlin Wall, Charles Lindbergh, conceptual framework, crowdsourcing, delayed gratification, deliberate practice, Edward Glaeser, experimental economics, Fall of the Berlin Wall, fear of failure, game design, industrial cluster, Jean Tirole, knowledge worker, longitudinal study, loss aversion, Mark Zuckerberg, meta analysis, meta-analysis, Mikhail Gorbachev, phenotype, Richard Feynman, risk tolerance, school choice, selection bias, shareholder value, Silicon Valley, six sigma, Steve Jobs, zero-sum game
Prevention-oriented individuals are most impacted by the latter—real-life examples of someone who made the mistake of not working hard enough. That message has a bigger impact. But in the long run, employees need to have gain-orientation to sustain growth. In the mid-2000s, Westinghouse Electric’s nuclear plant division realized it had a deep-seated culture problem. Their engineers had spent years absorbing a management strategy called Six Sigma, which has as its goal the eradication of errors from industrial processes. A Six Sigma process is one in which 99.99966% of the products manufactured are statistically expected to be free of defects. With this strategy firmly in place, Westinghouse had never bid on jobs unless its engineers already knew exactly what they’d be doing: they had to have proven, mistake-free expertise before even considering a new contract. And even when the engineers were willing to go to a potential new customer, they came in with a “Here’s what we can do for you,” and never asked, “What do you need?”
Big Data Analytics: Turning Big Data Into Big Money by Frank J. Ohlhorst
algorithmic trading, bioinformatics, business intelligence, business process, call centre, cloud computing, create, read, update, delete, data acquisition, DevOps, fault tolerance, linked data, natural language processing, Network effects, pattern recognition, performance metric, personalized medicine, RFID, sentiment analysis, six sigma, smart meter, statistical model, supply-chain management, Watson beat the top human players on Jeopardy!, web application
Miller, and Allan Russell Manufacturing Best Practices: Optimizing Productivity and Product Quality by Bobby Hull Marketing Automation: Practical Steps to More Effective Direct Marketing by Jeff LeSueur Mastering Organizational Knowledge Flow: How to Make Knowledge Sharing Work by Frank Leistner The New Know: Innovation Powered by Analytics by Thornton May Performance Management: Integrating Strategy Execution, Methodologies, Risk, and Analytics by Gary Cokins Retail Analytics: The Secret Weapon by Emmett Cox Social Network Analysis in Telecommunications by Carlos Andre Reis Pinheiro Statistical Thinking: Improving Business Performance, Second Edition by Roger W. Hoerl and Ronald D. Snee Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics by Bill Franks The Value of Business Analytics: Identifying the Path to Profitability by Evan Stubbs Visual Six Sigma: Making Data Analysis Lean by Ian Cox, Marie A. Gaudard, Philip J. Ramsey, Mia L. Stephens, and Leo Wright For more information on any of the above titles, please visit www.wiley.com. Cover image: @liangpv/iStockphoto Cover design: Michael Rutkowski Copyright © 2013 by John Wiley & Sons, Inc. All rights reserved. Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Published simultaneously in Canada.
Beautiful Testing: Leading Professionals Reveal How They Improve Software (Theory in Practice) by Adam Goucher, Tim Riley
Albert Einstein, barriers to entry, Black Swan, call centre, continuous integration, Debian, Donald Knuth, en.wikipedia.org, Firefox, Grace Hopper, index card, Isaac Newton, natural language processing, p-value, performance metric, revision control, six sigma, software as a service, software patent, the scientific method, Therac-25, Valgrind, web application
I wasn’t prepared to see a total parental nutrition product used to care for a family member. But I’m grateful that in this imperfect world, people do their best to create products that matter. And each of those products needs people who can test. 170 CHAPTER TWELVE CHAPTER THIRTEEN Software Development Is a Creative Process Chris McMahon OF THE WELL - KNOWN SOFTWARE DEVELOPMENT QUALITY PROCESSES come to us from the manufacturing industry. ISO9000, Six Sigma, and Lean all come from the assembly line, as does CMM to a certain extent. They are certainly all effective in the environments in which they were conceived. M OST And yet for every software business that succeeds in improving quality by these means, any number of others fail to get any benefit, regardless of how much they spend implementing the systems. At the same time, there are any number of highly successful software businesses and software products that succeed even though they follow no accepted quality processes at all.
A three-time college dropout and former professional musician, librarian, and waiter, Chris got his start as a software tester a little later than most, but his unique and varied background gives his work a sense of maturity that few others have. He lives in rural southwest Colorado, but contributes to a couple of magazines, several mailing lists, and is even a character in a book about software testing. M URALI N ANDIGAMA is a quality consultant and has more than 15 years of experience in various organizations, including TCS, Sun, Oracle, and Mozilla. Murali is a Certified Software Quality Analyst, Six Sigma lead, and senior member of IEEE. He has been awarded with multiple software patents in advanced software testing methodologies and has published in international journals and presented at many conferences. Murali holds a doctorate from the University of Hyderabad, India. B RIAN N ITZ has been a software engineer since 1988. He has spent time working on all aspects of the software life cycle, from design and development to QA and support.
The Investment Checklist: The Art of In-Depth Research by Michael Shearn
Asian financial crisis, barriers to entry, business cycle, call centre, Clayton Christensen, collective bargaining, commoditize, compound rate of return, Credit Default Swap, estate planning, intangible asset, Jeff Bezos, London Interbank Offered Rate, margin call, Mark Zuckerberg, money market fund, Network effects, pink-collar, risk tolerance, shareholder value, six sigma, Skype, Steve Jobs, supply-chain management, technology bubble, time value of money, transaction costs, urban planning, women in the workforce, young professional
For example, if a manager worked at General Electric (GE), take a look at any of several books and articles written about “the GE Way.” The GE Way is taught at GE’s management school: It involves rotating managers through many jobs, teaches them how to grow a business through acquisitions, and teaches productivity and quality-control tools such as Six Sigma. When Jim McNerney was passed over as CEO of GE, he was immediately recruited by 3M to be CEO (in 2001). Once he was CEO of 3M, he immediately began to look for acquisitions to make, and he instituted money-saving Six Sigma process-management systems companywide.16 By reading about the GE Way, you would have had a great insight into how McNerney would likely manage 3M. 37. How are senior managers compensated, and how did they gain their ownership interest? It is important to spend time reviewing the compensation and ownership interest of management by viewing the proxy statement.
Better Buses, Better Cities by Steven Higashide
Affordable Care Act / Obamacare, autonomous vehicles, business process, congestion charging, decarbonisation, Elon Musk, Hyperloop, income inequality, intermodal, jitney, Lyft, mass incarceration, Pareto efficiency, performance metric, place-making, self-driving car, Silicon Valley, six sigma, smart cities, transportation-network company, Uber and Lyft, Uber for X, uber lyft, urban planning, urban sprawl, walkable city, white flight, young professional
The lead driver might be told to start skipping stops to get ahead of the trailing bus; the operator of the second bus might be told to kick her passengers off, sending them to the leading bus, and drive further up the route to fill the service gap. Or the leader and follower might play a confusing game of bus stop leapfrog. It is best to design bus routes in ways that help avoid these problems to begin with. Industrial consultants have found that complex processes lead to product defects and manufacturing problems. Business improvement approaches such as Six Sigma and kaizen call for close audits of product assembly and business processes, in order to cut out unnecessary steps and iron out places where variability gets introduced into a product. Bus routes can be subjected to something similar. Transit planners and engineers have a full toolkit of technologies, techniques, and designs they can use to streamline a bus route, detailed in manuals such as the National Association of City Transportation Officials’ Transit Street Design Guide.
Company: A Short History of a Revolutionary Idea by John Micklethwait, Adrian Wooldridge
affirmative action, barriers to entry, Bonfire of the Vanities, borderless world, business process, Charles Lindbergh, Corn Laws, corporate governance, corporate raider, corporate social responsibility, creative destruction, credit crunch, crony capitalism, double entry bookkeeping, Etonian, hiring and firing, industrial cluster, invisible hand, James Watt: steam engine, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, knowledge economy, knowledge worker, laissez-faire capitalism, manufacturing employment, market bubble, mittelstand, new economy, North Sea oil, race to the bottom, railway mania, Ronald Coase, Silicon Valley, six sigma, South Sea Bubble, Steve Jobs, Steve Wozniak, strikebreaker, The Nature of the Firm, The Wealth of Nations by Adam Smith, Thorstein Veblen, trade route, transaction costs, tulip mania, wage slave, William Shockley: the traitorous eight
Big firms were much more likely than ever to go out of business: by 2000, roughly half the biggest one hundred industrial firms in 1974 had disappeared through takeovers or bankruptcy.5 The big firms that survived this maelstrom only did so by dint of bloody internal revolutions. In the first five years of the 1990s, IBM, a company once so stable that it refused to sack people during the Depression, laid off 122,000 of its workers, roughly a quarter of the total. Jack Welch’s two-decade reign at General Electric began in the 1980s with a period of shocking corporate brutality. A series of quasi-Maoist revolutions followed, complete with slogans (Work Out, Six Sigma, Destroyyourbusiness.com) and methods (getting thousands of managers to measure each other’s “boundarylessness,” and sacking the underperformers). By the time Welch retired in 2002, GE, which had repeatedly been voted the world’s most admired company, had become at its heart a services conglomerate. Despite this painful metamorphosis, the company still looked vulnerable, with analysts wondering whether Welch’s successor could keep the group together.
The Network Imperative: How to Survive and Grow in the Age of Digital Business Models by Barry Libert, Megan Beck
active measures, Airbnb, Amazon Web Services, asset allocation, autonomous vehicles, big data - Walmart - Pop Tarts, business intelligence, call centre, Clayton Christensen, cloud computing, commoditize, crowdsourcing, disintermediation, diversification, Douglas Engelbart, Douglas Engelbart, future of work, Google Glasses, Google X / Alphabet X, Infrastructure as a Service, intangible asset, Internet of things, invention of writing, inventory management, iterative process, Jeff Bezos, job satisfaction, Kevin Kelly, Kickstarter, late fees, Lyft, Mark Zuckerberg, Oculus Rift, pirate software, ride hailing / ride sharing, self-driving car, sharing economy, Silicon Valley, Silicon Valley startup, six sigma, software as a service, software patent, Steve Jobs, subscription business, TaskRabbit, Travis Kalanick, uber lyft, Wall-E, women in the workforce, Zipcar
We assert that the beliefs and skills that lead to success have changed dramatically in recent years and the most successful leaders will be those who can embrace new mental models. Thirty years ago, when essentially all assets were tangible, the best corporate leaders were those who could acquire and finance assets, manage a tight manufacturing process, hire and manage thousands of people, operate well, and grow their businesses to a competitive scale. In 1985, lean manufacturing and Six Sigma were the buzzwords, and Fortune’s most admired corporations were IBM, Coca-Cola, Dow Jones, 3M, and Hewlett-Packard. A lot has changed in thirty years, but two changes stand out clearly: the growth and ubiquity of digital technology, and the ongoing rapid, and exponentially increasing, pace and magnitude of change. In 2015, Fortune’s most admired companies were Apple, Google, Berkshire Hathaway, Amazon.com, and Starbucks, and a growing percentage of the Forbes wealthiest individuals are technologists or network leaders.
Keeping Up With the Quants: Your Guide to Understanding and Using Analytics by Thomas H. Davenport, Jinho Kim
Black-Scholes formula, business intelligence, business process, call centre, computer age, correlation coefficient, correlation does not imply causation, Credit Default Swap, en.wikipedia.org, feminist movement, Florence Nightingale: pie chart, forensic accounting, global supply chain, Hans Rosling, hypertext link, invention of the telescope, inventory management, Jeff Bezos, Johannes Kepler, longitudinal study, margin call, Moneyball by Michael Lewis explains big data, Myron Scholes, Netflix Prize, p-value, performance metric, publish or perish, quantitative hedge fund, random walk, Renaissance Technologies, Robert Shiller, Robert Shiller, self-driving car, sentiment analysis, six sigma, Skype, statistical model, supply-chain management, text mining, the scientific method, Thomas Davenport
As we noted in chapter 1, a quantitative analysis follows the following three stages and six steps: FRAMING THE PROBLEM Problem recognition Review of previous findings SOLVING THE PROBLEM Modeling and variable selection Data collection Data analysis COMMUNICATING AND ACTING ON RESULTS Results presentation and action In this chapter and chapters 3 and 4, we’ll describe each stage and step individually, and provide a couple of examples of quantitative analyses that cover all six steps, but feature the particular stage of analysis being discussed in the chapter. At the end of each of the three chapters we’ll lay out two examples—generally one from business and one involving society in general or personal experience—that illustrate how all six steps were employed in an analysis, but again focus in particular on one stage of the analysis. Our three-stage, six-step process isn’t the only way to do analytics (for example, there is a Six Sigma methodology for analyzing variation in product quality yielding no more than 3.4 defects per million products produced), but we expect that most analytical experts would agree with it, and it’s broad enough to encompass a lot of different types of business problems and analyses. The Problem Recognition Step 1. Problem recognition A quantitative analysis starts with recognizing a problem or decision and beginning to solve it.
Digital Accounting: The Effects of the Internet and Erp on Accounting by Ashutosh Deshmukh
accounting loophole / creative accounting, AltaVista, business continuity plan, business intelligence, business process, call centre, computer age, conceptual framework, corporate governance, data acquisition, dumpster diving, fixed income, hypertext link, interest rate swap, inventory management, iterative process, late fees, money market fund, new economy, New Journalism, optical character recognition, packet switching, performance metric, profit maximization, semantic web, shareholder value, six sigma, statistical model, supply-chain management, supply-chain management software, telemarketer, transaction costs, value at risk, web application, Y2K
The cost accounting system provides data useful for evaluating production function, determining product costs and generating information for inventory valuation for external reporting purposes. The twin objectives of quality and cost reduction have been a holy grail for manufacturing organizations. The last few decades have seen a number of methodologies, such as material requirements planning (MRP), manufacturing resource planning (MRP II), Just in Time (JIT), Robotics and Six Sigma, which strived to achieve these objectives. The conversion cycle is most visible in manufacturing organizations; however, the service industry has also benefited from conversion cycle concepts and theories. The conver- Copyright © 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. The Conversion Cycle 231 Exhibit 1.
Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. 368 Deshmukh performing tasks that may have been hyped in the initial phase. These tools, as they become widely available, will be definitely used by accountants and required to be evaluated by auditors. Exhibit 19. TransactionVision functionalities Transactionvision Business activity monitoring End-to-end transaction tracking Sales and marketing analytics • Managing service levels • Six sigma initiatives • Operational risk management • Straight through processing • Audit logging and fraud detection • Improving service levels • Resolving problems • Optimizing transaction performance • Planning system capacity • Assuring quality • Key performance indicators • Post promotion evaluation • Category management Exhibit 20. TransactionVision operations I. Electronic events captured II. Captured events stored III.
Think Like an Engineer: Use Systematic Thinking to Solve Everyday Challenges & Unlock the Inherent Values in Them by Mushtak Al-Atabi
3D printing, agricultural Revolution, Albert Einstein, Barry Marshall: ulcers, Black Swan, business climate, call centre, Clayton Christensen, clean water, cognitive bias, corporate social responsibility, dematerialisation, disruptive innovation, Elon Musk, follow your passion, global supply chain, happiness index / gross national happiness, invention of the wheel, iterative process, James Dyson, Kickstarter, knowledge economy, Lao Tzu, Lean Startup, On the Revolutions of the Heavenly Spheres, remote working, shareholder value, six sigma, Steve Jobs, Steven Pinker
For example, a project to address the gap in point 1 above can have the objective of improving satisfaction level of online customers (Specific customer segment) by 20% (Measurable) within 3 months (Time-bound). The Objective is Attainable and Realistic as well. The Scope of the project refers to the extent to which the project will go to achieve the objective(s). This can be, for example, “The project will focus on training the customer service staff” or “Implement a Six Sigma quality assurance programme to improve the quality of the products.” 6. What are the resources the project needs to succeed? 7. Who are the Stakeholders of the project? Stakeholders of a project are individuals, groups or entities that are affected or impacted by the project, and can affect or impact its successful completion. One of the key tasks and responsibilities of the project team is to identify, classify and engage the project stakeholders.
The Decline and Fall of IBM: End of an American Icon? by Robert X. Cringely
AltaVista, Bernie Madoff, business cycle, business process, cloud computing, commoditize, compound rate of return, corporate raider, full employment, if you build it, they will come, immigration reform, interchangeable parts, invention of the telephone, Khan Academy, knowledge worker, low skilled workers, Paul Graham, platform as a service, race to the bottom, remote working, Robert Metcalfe, Robert X Cringely, shareholder value, Silicon Valley, six sigma, software as a service, Steve Jobs, Toyota Production System, Watson beat the top human players on Jeopardy!, web application
Any evaluation of a technical requirement, which almost always results in something else for the better, especially in the software world, is considered scope change by these morons and for which you have to go through some ridiculous change management process to implement, and to which they object because they just don’t get it. bob / August 8, 2013 / 5:22 pm Beatles’ songs spoof IBM I’m just disappointed that I spent nearly three decades honing my denial of what the people at the helm were really about. I bought into the “corporate values” and the rest of the rah rah (e.g. “six sigma quality”, “transformation”), all the while bucking inner suspicions that nothing of lasting quality could come of the endless stream of clueless personnel and technical decisions, or of career promotion being proportional to obedience, while inversely proportional to hard work and innovating first in one’s approach and methods, and then in the products themselves. My 3 rating in January was a stunning display of what I want to call business mental illness.
Antifragile: Things That Gain From Disorder by Nassim Nicholas Taleb
Air France Flight 447, Andrei Shleifer, banking crisis, Benoit Mandelbrot, Berlin Wall, Black Swan, business cycle, Chuck Templeton: OpenTable:, commoditize, creative destruction, credit crunch, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, discrete time, double entry bookkeeping, Emanuel Derman, epigenetics, financial independence, Flash crash, Gary Taubes, George Santayana, Gini coefficient, Henri Poincaré, high net worth, hygiene hypothesis, Ignaz Semmelweis: hand washing, informal economy, invention of the wheel, invisible hand, Isaac Newton, James Hargreaves, Jane Jacobs, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, Kenneth Arrow, knowledge economy, Lao Tzu, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, Marc Andreessen, meta analysis, meta-analysis, microbiome, money market fund, moral hazard, mouse model, Myron Scholes, Norbert Wiener, pattern recognition, Paul Samuelson, placebo effect, Ponzi scheme, principal–agent problem, purchasing power parity, quantitative trading / quantitative ﬁnance, Ralph Nader, random walk, Ray Kurzweil, rent control, Republic of Letters, Ronald Reagan, Rory Sutherland, selection bias, Silicon Valley, six sigma, spinning jenny, statistical model, Steve Jobs, Steven Pinker, Stewart Brand, stochastic process, stochastic volatility, Thales and the olive presses, Thales of Miletus, The Great Moderation, the new new thing, The Wealth of Nations by Adam Smith, Thomas Bayes, Thomas Malthus, too big to fail, transaction costs, urban planning, Vilfredo Pareto, Yogi Berra, Zipf's Law
When, at Wharton, I discovered that I wanted to specialize in a profession linked to probability and rare events, a probability and randomness obsession took control of my mind. I also smelled some flaws with statistical stuff that the professor could not explain, brushing them away—it was what the professor was brushing away that had to be the meat. I realized that there was a fraud somewhere, that “six sigma” events (measures of very rare events) were grossly miscomputed and we had no basis for their computation, but I could not articulate my realization clearly, and was getting humiliated by people who started smoking me with complicated math. I saw the limits of probability in front of me, clear as crystal, but could not find the words to express the point. So I went to the bookstore and ordered (there was no Web at the time) almost every book with “probability” or “stochastic” in its title.
For instance, for a deviation that is called “three sigma,” events that should take place no more than one in 740 observations, the probability rises by 60% if one moves the standard deviation up by 5%, and drops by 40% if we move the standard deviation down by 5%. So if your error is on average a tiny 5%, the underestimation from a naive model is about 20%. Great asymmetry, but nothing yet. It gets worse as one looks for more deviations, the “six sigma” ones (alas, chronically frequent in economics): a rise of five times more. The rarer the event (i.e., the higher the “sigma”), the worse the effect from small uncertainty about what to put in the equation. With events such as ten sigma, the difference is more than a billion times. We can use the argument to show how smaller and smaller probabilities require more precision in computation. The smaller the probability, the more a small, very small rounding in the computation makes the asymmetry massively insignificant.
The Year Without Pants: Wordpress.com and the Future of Work by Scott Berkun
barriers to entry, blue-collar work, Broken windows theory, en.wikipedia.org, Firefox, future of work, Google Hangouts, Jane Jacobs, job satisfaction, Lean Startup, lone genius, Mark Zuckerberg, minimum viable product, post-work, remote working, Results Only Work Environment, Richard Stallman, Seaside, Florida, side project, Silicon Valley, six sigma, Skype, stealth mode startup, Steve Jobs, The Death and Life of Great American Cities, the map is not the territory, Tony Hsieh, trade route, zero-sum game
In anthropology terms, this superficial mimicry is called a cargo cult, a reference to the misguided worship of abandoned airplane landing strips among tribes hoping for the goods that airplanes had delivered to return. Every year new trends in work become popular in spite of their futility for most organizations that try them. These trends are often touted as revolutions and frequently are identified with a high-profile company of the day. Concepts like casual Fridays, brainstorming sessions, Lean, Six Sigma, Agile, matrixed organizations, or even 20 percent time (Google's policy of supporting pet projects) are management ideas that became popular in huge waves, heralded as silver bullets for workplaces. The promise of a trend is grand, but the result never is. Rarely do the consultants championing, and profiting from, these ideas disclose how superficial the results will be unless they're placed in a culture healthy enough to support them.
The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers by Ben Horowitz
Airbnb, Ben Horowitz, business intelligence, cloud computing, financial independence, Google Glasses, hiring and firing, Isaac Newton, Jeff Bezos, Marc Andreessen, Mark Zuckerberg, move fast and break things, move fast and break things, new economy, nuclear winter, Peter Thiel, Productivity paradox, random walk, Ronald Reagan, Silicon Valley, six sigma, Steve Ballmer, Steve Jobs
You can hand off tasks with a perfect understanding of what’s expected, you pass important information from one person to another, and you can maintain high-quality transactions with no bureaucratic overhead. With four thousand people, communication becomes more difficult. Ad hoc, point-to-point communication no longer works. You need something more robust—a communication bus or, to use the conventional term for human communication buses, a process. A process is a formal, well-structured communication vehicle. It can be a heavily engineered Six Sigma process or it can be a well-structured regular meeting. The size of the process should be scaled up or down to meet the needs of the communication challenge that it facilitates. When communication in an organization spans across organizational boundaries, processes will help ensure that the communication happens and that it happens with quality. If you are looking for the first process to implement in your company, consider the interview process.
The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses by Eric Ries
3D printing, barriers to entry, call centre, Clayton Christensen, clean water, cloud computing, commoditize, Computer Numeric Control, continuous integration, corporate governance, disruptive innovation, experimental subject, Frederick Winslow Taylor, Lean Startup, Marc Andreessen, Mark Zuckerberg, Metcalfe’s law, minimum viable product, Mitch Kapor, Network effects, payday loans, Peter Thiel, pets.com, Ponzi scheme, pull request, risk tolerance, selection bias, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, stealth mode startup, Steve Jobs, the scientific method, Toyota Production System, transaction costs
This means that we must focus our energies exclusively on producing outcomes that the customer perceives as valuable. Allowing sloppy work into our process inevitably leads to excessive variation. Variation in process yields products of varying quality in the eyes of the customer that at best require rework and at worst lead to a lost customer. Most modern business and engineering philosophies focus on producing high-quality experiences for customers as a primary principle; it is the foundation of Six Sigma, lean manufacturing, design thinking, extreme programming, and the software craftsmanship movement. These discussions of quality presuppose that the company already knows what attributes of the product the customer will perceive as worthwhile. In a startup, this is a risky assumption to make. Often we are not even sure who the customer is. Thus, for startups, I believe in the following quality principle: If we do not know who the customer is, we do not know what quality is.
Radicalized by Cory Doctorow
activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, Bernie Sanders, call centre, crowdsourcing, cryptocurrency, Edward Snowden, Flash crash, G4S, high net worth, information asymmetry, license plate recognition, obamacare, old-boy network, six sigma, TaskRabbit
Markets corrected them. If knowing a secret could make a stupid, unworthy person rich, then sooner or later, smart, superior people would find that secret out and clear out the misallocated wealth of all those dimbulbs. Markets were awesome at this. Back when everyone lived in shithole mud-street villages, the superior people had no choice but to breed with whoever was in the vicinity. Even a one-in-ten-million, six-sigma genius would end up hitched for life to some cow-eyed milkmaid, diluting the incredible genes he’d been handed by nature’s Powerball lotto. But little by little, humans got smarter, as the geniuses found smarter milkmaids, until they could build markets and then the information systems that markets thrived on, and then the information asymmetry started to collapse, slowly at first, then all at once, like a cliff that had been undermined by the inexorable tide of millions of human actions harnessed to the common goal of improving the species and its dominion over the earth.
Brave New Work: Are You Ready to Reinvent Your Organization? by Aaron Dignan
"side hustle", activist fund / activist shareholder / activist investor, Airbnb, Albert Einstein, autonomous vehicles, basic income, Bertrand Russell: In Praise of Idleness, bitcoin, Black Swan, blockchain, Buckminster Fuller, Burning Man, butterfly effect, cashless society, Clayton Christensen, clean water, cognitive bias, cognitive dissonance, corporate governance, corporate social responsibility, correlation does not imply causation, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, David Heinemeier Hansson, deliberate practice, DevOps, disruptive innovation, don't be evil, Elon Musk, endowment effect, Ethereum, ethereum blockchain, Frederick Winslow Taylor, future of work, gender pay gap, Geoffrey West, Santa Fe Institute, gig economy, Google X / Alphabet X, hiring and firing, hive mind, income inequality, information asymmetry, Internet of things, Jeff Bezos, job satisfaction, Kevin Kelly, Kickstarter, Lean Startup, loose coupling, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, minimum viable product, new economy, Paul Graham, race to the bottom, remote working, Richard Thaler, shareholder value, Silicon Valley, six sigma, smart contracts, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, source of truth, Stanford marshmallow experiment, Steve Jobs, TaskRabbit, the High Line, too big to fail, Toyota Production System, uber lyft, universal basic income, Y Combinator, zero-sum game
If you think certifying your project managers in Scrum is going to topple your bureaucracy, you’re in for some major disappointment. Agility is a mindset, not a tool set. It’s a piece of the puzzle, not the whole thing. It is necessary but not sufficient. It turns out agility isn’t an anomaly in this way. Many management innovations have emerged in the last half century, each promising to revolutionize work as we know it. Lean Manufacturing. Total Quality Management. ISO 9000. Six Sigma. Sociocracy. Holacracy. The Lean Startup. The list goes on and on. Each was, in its own way, a piece of an operating system. Some were misguided from the start. Others became perversions of themselves over time. And a few offered real wisdom that is yet to be fully realized. Thich Nhat Hanh wrote in Old Path White Clouds, “A finger pointing at the moon is not the moon.” When we focus too much on the method or the messenger, we lose sight of the deeper truth.
How to Speak Money: What the Money People Say--And What It Really Means by John Lanchester
asset allocation, Basel III, Bernie Madoff, Big bang: deregulation of the City of London, bitcoin, Black Swan, blood diamonds, Bretton Woods, BRICs, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Celtic Tiger, central bank independence, collapse of Lehman Brothers, collective bargaining, commoditize, creative destruction, credit crunch, Credit Default Swap, crony capitalism, Dava Sobel, David Graeber, disintermediation, double entry bookkeeping, en.wikipedia.org, estate planning, financial innovation, Flash crash, forward guidance, Gini coefficient, global reserve currency, high net worth, High speed trading, hindsight bias, income inequality, inflation targeting, interest rate swap, Isaac Newton, Jaron Lanier, joint-stock company, joint-stock limited liability company, Kodak vs Instagram, liquidity trap, London Interbank Offered Rate, London Whale, loss aversion, margin call, McJob, means of production, microcredit, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, negative equity, neoliberal agenda, New Urbanism, Nick Leeson, Nikolai Kondratiev, Nixon shock, Northern Rock, offshore financial centre, oil shock, open economy, paradox of thrift, plutocrats, Plutocrats, Ponzi scheme, purchasing power parity, pushing on a string, quantitative easing, random walk, rent-seeking, reserve currency, Richard Feynman, Right to Buy, road to serfdom, Ronald Reagan, Satoshi Nakamoto, security theater, shareholder value, Silicon Valley, six sigma, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, sovereign wealth fund, Steve Jobs, survivorship bias, The Chicago School, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, trickle-down economics, Washington Consensus, wealth creators, working poor, yield curve
Four sigma is starting to get seriously unlikely. That’s 99.993 percent unlikely, meaning 1 in 15,788. It’s about the chance that you will die in a fall this year. With five sigma, we’re going way past the edges of the humanly probable: it’s 1 in 1.74 million. In terms of the chance that an event will happen on a given day, a five-sigma event is supposed to happen one day in every 13,932 years. Six sigma is even bigger; it’s one day in every 4,039,906 years, and seven sigma is one day in every 3,105,395,365 years. In recent years, the mathematical models used by banks repeatedly calculated events as being at these levels of probability, despite the fact that the events kept happening. The obvious lesson was that the models were wrong, but the banks went on using them anyway. The overreliance on these models is one of the things that helped cause the credit crunch.
Nomadland: Surviving America in the Twenty-First Century by Jessica Bruder
Affordable Care Act / Obamacare, back-to-the-land, big-box store, Burning Man, cognitive dissonance, crowdsourcing, full employment, game design, gender pay gap, Gini coefficient, income inequality, Jeff Bezos, job automation, Mars Rover, new economy, off grid, payday loans, Pepto Bismol, precariat, Ronald Reagan, Saturday Night Live, sharing economy, six sigma, supply-chain management, union organizing, urban sprawl, white picket fence, Y2K
Truck accidents: Sarah Volpenhein, “Amid Sugar Beet Truck Accidents, Some Question Minnesota, North Dakota Regulations for Ag Drivers,” The Grand Forks Herald, October 7, 2015, http://www.grandforksherald.com/news/business/3856308-amid-sugar-beet-truck-accidents-some-question-minnesota-north-dakota. 194. Definition of “takt”: https://ocw.mit.edu/courses/engineering-systems-division/esd-60-lean-six-sigma-processes-summer-2004/lecture-notes/8_1assembly_op.pdf. CHAPTER TEN 202. LaVonne on feeling homeless: http://www.completeflake.com/what-vandwelling-is-really-like. 203. LaVonne on untouchables: http://www.completeflake.com/second-chances. 204. Bob’s definition of homeless: Bob Wells, How to Live in a Car, Van or RV: And Get Out of Debt, Travel, & Find True Freedom, CreateSpace Independent Publishing Platform, 2014, pp. 6–7. 205.
The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson, Andrew McAfee
"Robert Solow", 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, access to a mobile phone, additive manufacturing, Airbnb, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, American Society of Civil Engineers: Report Card, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, barriers to entry, basic income, Baxter: Rethink Robotics, British Empire, business cycle, business intelligence, business process, call centre, Charles Lindbergh, Chuck Templeton: OpenTable:, clean water, combinatorial explosion, computer age, computer vision, congestion charging, corporate governance, creative destruction, crowdsourcing, David Ricardo: comparative advantage, digital map, employer provided health coverage, en.wikipedia.org, Erik Brynjolfsson, factory automation, falling living standards, Filter Bubble, first square of the chessboard / second half of the chessboard, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, full employment, G4S, game design, global village, happiness index / gross national happiness, illegal immigration, immigration reform, income inequality, income per capita, indoor plumbing, industrial robot, informal economy, intangible asset, inventory management, James Watt: steam engine, Jeff Bezos, jimmy wales, job automation, John Markoff, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kevin Kelly, Khan Academy, knowledge worker, Kodak vs Instagram, law of one price, low skilled workers, Lyft, Mahatma Gandhi, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Mars Rover, mass immigration, means of production, Narrative Science, Nate Silver, natural language processing, Network effects, new economy, New Urbanism, Nicholas Carr, Occupy movement, oil shale / tar sands, oil shock, pattern recognition, Paul Samuelson, payday loans, post-work, price stability, Productivity paradox, profit maximization, Ralph Nader, Ray Kurzweil, recommendation engine, Report Card for America’s Infrastructure, Robert Gordon, Rodney Brooks, Ronald Reagan, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Simon Kuznets, six sigma, Skype, software patent, sovereign wealth fund, speech recognition, statistical model, Steve Jobs, Steven Pinker, Stuxnet, supply-chain management, TaskRabbit, technological singularity, telepresence, The Bell Curve by Richard Herrnstein and Charles Murray, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, total factor productivity, transaction costs, Tyler Cowen: Great Stagnation, Vernor Vinge, Watson beat the top human players on Jeopardy!, winner-take-all economy, Y2K
Instead of putting the machines needing the most power closest to the power source, the layout was based on a simple and powerful new principle: the natural workflow of materials. Productivity didn’t merely inch upward on the resulting assembly lines; it doubled or even tripled. What’s more, for most of the subsequent century, additional complementary innovations, from lean manufacturing and steel minimills to Total Quality Management and Six Sigma principles, continued to boost manufacturing productivity. As with earlier GPTs, significant organizational innovation is required to capture the full benefit of second machine age technologies. Tim Berners-Lee’s invention of the World Wide Web in 1989, to take an obvious example, initially benefited only a small group of particle physicists. But due in part to the power of digitization and networks to speed the diffusion of ideas, complementary innovations are happening faster than they did in the first machine age.
All Day Long: A Portrait of Britain at Work by Joanna Biggs
Anton Chekhov, bank run, banking crisis, call centre, Chelsea Manning, credit crunch, David Graeber, Desert Island Discs, Downton Abbey, Erik Brynjolfsson, financial independence, future of work, G4S, glass ceiling, industrial robot, job automation, land reform, low skilled workers, mittelstand, Northern Rock, payday loans, Right to Buy, Second Machine Age, six sigma, Steve Jobs, trickle-down economics, unpaid internship, wages for housework, Wall-E
The women, yeah, we’ve got the opportunity to go back to work but let’s face it, it’s at the cost of doing everything outside and inside.’ Men ‘just go to work and just expect meals to be cooked and kids to be fed, washed and watered. They think magic fairies exist! Because they don’t put a value on housework, they’re like what did you do with your day? So you have to find that worth yourself. I strongly believe in gender definition. It’s like the Six Sigma system of running a company in the sense that men and women have their own roles and contributions to make to the tranquility and efficiency of the home.’ In The Second Sex, Simone de Beauvoir saw cleaning the house as a way to hold away death but refuse life; Ann Oakley called housework ‘work directly opposed to the possibility of human self-actualisation’. In 1963, Betty Friedan documented the suffering of the seemingly perfect housewife in The Feminine Mystique.
Wait: The Art and Science of Delay by Frank Partnoy
algorithmic trading, Atul Gawande, Bernie Madoff, Black Swan, blood diamonds, Cass Sunstein, Checklist Manifesto, cognitive bias, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, Daniel Kahneman / Amos Tversky, delayed gratification, Flash crash, Frederick Winslow Taylor, George Akerlof, Google Earth, Hernando de Soto, High speed trading, impulse control, income inequality, information asymmetry, Isaac Newton, Long Term Capital Management, Menlo Park, mental accounting, meta analysis, meta-analysis, MITM: man-in-the-middle, Nick Leeson, paper trading, Paul Graham, payday loans, Ralph Nader, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, Ronald Reagan, Saturday Night Live, six sigma, Spread Networks laid a new fibre optics cable between New York and Chicago, Stanford marshmallow experiment, statistical model, Steve Jobs, The Market for Lemons, the scientific method, The Wealth of Nations by Adam Smith, upwardly mobile, Walter Mischel
Yet Minnesota Mining once had just that kind of visionary leadership. In 2001, in the aftermath of the collapse of Enron, Minnesota Mining hired as its new leader James McNerney, an executive at General Electric who had lost the competition to replace Jack Welch as GE’s CEO. McNerney was by all accounts an accomplished professional manager, but he was not a scientist. He was not a tinkerer. McNerney implemented the “six sigma” system of cutting costs and improving efficiency. During his first two years, Minnesota Mining cut nearly 10,000 jobs and closed a dozen plants. It changed its name to 3M. After two more years focused on efficiency, McNerney left to become CEO of Boeing. So much for Mother Mining. During his four years at the helm, the company’s culture became less patient. McNerney’s replacement, Sir George William Buckley, slashed another 6,000 jobs.
Peers Inc: How People and Platforms Are Inventing the Collaborative Economy and Reinventing Capitalism by Robin Chase
Airbnb, Amazon Web Services, Andy Kessler, banking crisis, barriers to entry, basic income, Benevolent Dictator For Life (BDFL), bitcoin, blockchain, Burning Man, business climate, call centre, car-free, cloud computing, collaborative consumption, collaborative economy, collective bargaining, commoditize, congestion charging, creative destruction, crowdsourcing, cryptocurrency, decarbonisation, different worldview, do-ocracy, don't be evil, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, Ferguson, Missouri, Firefox, frictionless, Gini coefficient, hive mind, income inequality, index fund, informal economy, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jane Jacobs, Jeff Bezos, jimmy wales, job satisfaction, Kickstarter, Lean Startup, Lyft, means of production, megacity, Minecraft, minimum viable product, Network effects, new economy, Oculus Rift, openstreetmap, optical character recognition, pattern recognition, peer-to-peer, peer-to-peer lending, peer-to-peer model, Richard Stallman, ride hailing / ride sharing, Ronald Coase, Ronald Reagan, Satoshi Nakamoto, Search for Extraterrestrial Intelligence, self-driving car, shareholder value, sharing economy, Silicon Valley, six sigma, Skype, smart cities, smart grid, Snapchat, sovereign wealth fund, Steve Crocker, Steve Jobs, Steven Levy, TaskRabbit, The Death and Life of Great American Cities, The Future of Employment, The Nature of the Firm, transaction costs, Turing test, turn-by-turn navigation, Uber and Lyft, uber lyft, Zipcar
Industrialization, followed by automation, has led us to value conformity and uniformity above all else and in every situation. The Peers Inc framework lets us apply that drive with more discretion. The industrial process taught us that tight control delivered the highest precision and quality (something we still want in the manufacturing of things such as smartphones, light bulbs, and refrigerators, and which can be achieved using tools such as Six Sigma). Managers sought to eradicate variation through this centralized control. The bigger the company, the greater the urge to centralize. I remember case studies from my business school strategy classes during the mid-1980s that encouraged an enlightened flexibility. If a centralized company was failing, then it should decentralize! If it was failing and decentralized, then of course it should centralize!
The Art of Scalability: Scalable Web Architecture, Processes, and Organizations for the Modern Enterprise by Martin L. Abbott, Michael T. Fisher
always be closing, anti-pattern, barriers to entry, Bernie Madoff, business climate, business continuity plan, business intelligence, business process, call centre, cloud computing, combinatorial explosion, commoditize, Computer Numeric Control, conceptual framework, database schema, discounted cash flows, en.wikipedia.org, fault tolerance, finite state, friendly fire, hiring and firing, Infrastructure as a Service, inventory management, new economy, packet switching, performance metric, platform as a service, Ponzi scheme, RFC: Request For Comment, risk tolerance, Rubik’s Cube, Search for Extraterrestrial Intelligence, SETI@home, shareholder value, Silicon Valley, six sigma, software as a service, the scientific method, transaction costs, Vilfredo Pareto, web application, Y2K
Prior to joining PayPal, Michael spent seven years at General Electric helping to develop the company’s technology strategy and processes. Michael has a B.S. in computer science from the United States Military Academy, an M.S. from Hawaii Pacific University, a Ph.D. in management information systems from Kennedy Western University, and an M.B.A. from Case Western Reserve University. Michael is a certified Six Sigma Master Black Belt and is pursuing a doctorate in management from Case Western Reserve University. xxv This page intentionally left blank Introduction This book is about the art of scale, scalability, and scaling of technology organizations, processes, and platforms. The information contained within has been carefully designed to be appropriate for any employee, manager, or executive of an organization or company that provides technology solutions.
Total = (9 × 5) + (1 × 4) + (9 × 3) + (−3 × 2) + (−3 × 1) Figure 19.4 Total Calculation 294 C HAPTER 19 F AST OR R IGHT ? Fast or Right Checklist • What does your gut tell you about the tradeoff? • What are the pros and cons of each alternative? • Is a more formal analysis required because of the risk or magnitude of the decision? • If a more formal analysis is required: What are the most important factors? In Six Sigma parlance, these are critical to quality indicators. How do these factors rank compared to each other—that is, what is the most important one of these factors? What are the actual tradeoffs being discussed? How do these tradeoffs affect the factors? • Would you feel comfortable standing in front of your board explaining your decision based on the information you have today? We have given you three methods of analyzing the tradeoffs from balancing the cost, quality, and speed constraints.
New Power: How Power Works in Our Hyperconnected World--And How to Make It Work for You by Jeremy Heimans, Henry Timms
"side hustle", 3D printing, 4chan, Affordable Care Act / Obamacare, Airbnb, augmented reality, autonomous vehicles, battle of ideas, Benjamin Mako Hill, bitcoin, blockchain, British Empire, Chris Wanstrath, Columbine, Corn Laws, crowdsourcing, David Attenborough, Donald Trump, Elon Musk, Ferguson, Missouri, future of work, game design, gig economy, hiring and firing, IKEA effect, income inequality, informal economy, job satisfaction, Jony Ive, Kibera, Kickstarter, Lean Startup, Lyft, Mark Zuckerberg, Minecraft, Network effects, new economy, Nicholas Carr, obamacare, Occupy movement, profit motive, race to the bottom, ride hailing / ride sharing, rolodex, Saturday Night Live, sharing economy, Silicon Valley, six sigma, Snapchat, social web, TaskRabbit, the scientific method, transaction costs, Travis Kalanick, Uber and Lyft, uber lyft, upwardly mobile, web application, WikiLeaks
Comstock herself had championed the Quirky relationship and had been closely tied to it when the company stumbled and then filed for bankruptcy. The signal she is trying to send, therefore, is clear: I failed at this and I’m still here. It’s not just OK to engage the crowd and fail spectacularly at GE; it is expected and embraced. Consider how different a philosophy this is from that of the legendary GE leader Jack Welch, who made his reputation through elimination of error and failure with his Six Sigma management process, and through elimination of staff with ruthless and regular culls. It was the layoffs that earned him the nickname “Neutron Jack,” because he’d explode and empty a building of people while leaving the structure standing. Comstock leads very differently. In GE nickname terms, we could think of her as Electron Beth, defined not by how she blows things up, but by how she binds people together.
Better, Stronger, Faster: The Myth of American Decline . . . And the Rise of a New Economy by Daniel Gross
2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, Affordable Care Act / Obamacare, Airbnb, American Society of Civil Engineers: Report Card, asset-backed security, Bakken shale, banking crisis, BRICs, British Empire, business cycle, business process, business process outsourcing, call centre, Carmen Reinhart, clean water, collapse of Lehman Brothers, collateralized debt obligation, commoditize, creative destruction, credit crunch, currency manipulation / currency intervention, demand response, Donald Trump, Frederick Winslow Taylor, high net worth, housing crisis, hydraulic fracturing, If something cannot go on forever, it will stop - Herbert Stein's Law, illegal immigration, index fund, intangible asset, intermodal, inventory management, Kenneth Rogoff, labor-force participation, LNG terminal, low skilled workers, Mark Zuckerberg, Martin Wolf, Maui Hawaii, McMansion, money market fund, mortgage debt, Network effects, new economy, obamacare, oil shale / tar sands, oil shock, peak oil, plutocrats, Plutocrats, price stability, quantitative easing, race to the bottom, reserve currency, reshoring, Richard Florida, rising living standards, risk tolerance, risk/return, Silicon Valley, Silicon Valley startup, six sigma, Skype, sovereign wealth fund, Steve Jobs, superstar cities, the High Line, transit-oriented development, Wall-E, Yogi Berra, zero-sum game, Zipcar
In services, Walmart’s insanely efficient supply chains relentlessly drove costs out of the system and set a global standard for rational logistics. McKinsey’s armies of whip-smart technocrats roamed the globe, peddling expensive advice on how to rationalize operations. In the happy expansion of the 2000s, efficiency and internal resources were easily overlooked. Manufacturers realized they could save more money simply by relocating production to Shenzhen, China, than they could by dispatching Six Sigma ninjas to improve operations. With debt flowing like a mighty stream and prices and asset values rising to the sky, what was the point of worrying about operational efficiencies? The discipline of business engineering was subordinated to financial engineering, as elite business schools created degrees and concentrations in the dark art. Productivity growth actually was quite weak during the credit boom, rising just 1.8 percent in 2007 and 2.1 percent in 2008.
Conscious Capitalism, With a New Preface by the Authors: Liberating the Heroic Spirit of Business by John Mackey, Rajendra Sisodia, Bill George
Berlin Wall, Buckminster Fuller, business process, carbon footprint, collective bargaining, corporate governance, corporate social responsibility, creative destruction, crony capitalism, cross-subsidies, en.wikipedia.org, Everything should be made as simple as possible, Fall of the Berlin Wall, fear of failure, Flynn Effect, income per capita, invisible hand, Jeff Bezos, job satisfaction, lone genius, Mahatma Gandhi, microcredit, Nelson Mandela, Occupy movement, profit maximization, Ralph Waldo Emerson, shareholder value, six sigma, social intelligence, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, Steven Pinker, The Fortune at the Bottom of the Pyramid, The Wealth of Nations by Adam Smith, too big to fail, union organizing, wealth creators, women in the workforce, zero-sum game
A Journey Worth Taking Building a conscious business is a challenging but wonderfully rewarding and meaningful undertaking, whether such a business is created from scratch or is the outcome of a transformation. We recognize that many leaders have become weary of change. It seems there is a new set of buzzwords to deal with every few years—from total quality management to the reengineering of business processes to Six Sigma and numerous others. But Conscious Capitalism is no flavor-of-the-month fad. The ideas we have articulated result in a more robust business model than the profit-maximization model it competes against, because they acknowledge and tap into more powerful motivations than self-interest alone. Unlike many other types of changes, the move toward becoming a conscious business feels natural, because it is aligned with the natural human qualities of all stakeholders.
Creative Intelligence: Harnessing the Power to Create, Connect, and Inspire by Bruce Nussbaum
3D printing, Airbnb, Albert Einstein, Berlin Wall, Black Swan, Chuck Templeton: OpenTable:, clean water, collapse of Lehman Brothers, creative destruction, Credit Default Swap, crony capitalism, crowdsourcing, Danny Hillis, declining real wages, demographic dividend, disruptive innovation, Elon Musk, en.wikipedia.org, Eugene Fama: efficient market hypothesis, Fall of the Berlin Wall, follow your passion, game design, housing crisis, Hyman Minsky, industrial robot, invisible hand, James Dyson, Jane Jacobs, Jeff Bezos, jimmy wales, John Gruber, John Markoff, Joseph Schumpeter, Kickstarter, lone genius, longitudinal study, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Martin Wolf, new economy, Paul Graham, Peter Thiel, QR code, race to the bottom, reshoring, Richard Florida, Ronald Reagan, shareholder value, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, six sigma, Skype, Steve Ballmer, Steve Jobs, Steve Wozniak, supply-chain management, Tesla Model S, The Chicago School, The Design of Experiments, the High Line, The Myth of the Rational Market, thinkpad, Tim Cook: Apple, too big to fail, tulip mania, We are the 99%, Y Combinator, young professional, Zipcar
How should we go about building a method to assess creativity on a national and global scale? Where do we start? As I discovered from my investigation into the history of creativity research, the attempt to find quantitative measures of creativity hasn’t been very fruitful in the past. But what’s the alternative? We do, after all, tend to associate assessment with mathematical measurement. From the incessant testing that goes on in K–12 classes thanks to No Child Left Behind, to Six Sigma management in business, we constantly test by the numbers. But creativity doesn’t appear to lend itself to metric measurement at this point in time. Perhaps in the future, we might be able to come up with an algorithm that works. But for now, we need qualitative measures. So I set about talking to the most creative people I know about what to do, asking them, “How do we assess creativity?” I first turned to what might appear an unlikely source, a business school dean.
Joel on Software by Joel Spolsky
AltaVista, barriers to entry, c2.com, commoditize, George Gilder, index card, Jeff Bezos, knowledge worker, Metcalfe's law, Mitch Kapor, Network effects, new economy, PageRank, Paul Graham, profit motive, Robert X Cringely, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, slashdot, Steve Ballmer, Steve Jobs, the scientific method, thinkpad, VA Linux, web application
My first real software job was at Microsoft, a company that is not exactly famous for its high-quality code, but which does nonetheless hire a large number of software testers. So I had sort of assumed that every software operation had testers. Many do. But a surprising number do not have testers. In fact, a lot of software teams don't even believe in testing. You would think that after all the quality mania of the '80s, with all kinds of meaningless international "quality" certifications like ISO-9000 and buzzwords like "six-sigma," managers today would understand that having high-quality products makes good business sense. In fact, they do. Most have managed to get this through their heads. But they still come up with lots of reasons not to have software testers, all of which are wrong. I hope I can explain to you why these ideas are wrong. If you're in a hurry, skip the rest of this chapter, and go out and hire one full-time tester for every two full-time programmers on your team.
The Digital Doctor: Hope, Hype, and Harm at the Dawn of Medicine’s Computer Age by Robert Wachter
"Robert Solow", activist fund / activist shareholder / activist investor, Affordable Care Act / Obamacare, AI winter, Airbnb, Atul Gawande, Captain Sullenberger Hudson, Checklist Manifesto, Chuck Templeton: OpenTable:, Clayton Christensen, collapse of Lehman Brothers, computer age, creative destruction, crowdsourcing, deskilling, disruptive innovation, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, Firefox, Frank Levy and Richard Murnane: The New Division of Labor, Google Glasses, Ignaz Semmelweis: hand washing, Internet of things, job satisfaction, Joseph Schumpeter, Kickstarter, knowledge worker, lifelogging, medical malpractice, medical residency, Menlo Park, minimum viable product, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, peer-to-peer, personalized medicine, pets.com, Productivity paradox, Ralph Nader, RAND corporation, Second Machine Age, self-driving car, Silicon Valley, Silicon Valley startup, six sigma, Skype, Snapchat, software as a service, Steve Jobs, Steven Levy, the payments system, The Wisdom of Crowds, Thomas Bayes, Toyota Production System, Uber for X, US Airways Flight 1549, Watson beat the top human players on Jeopardy!, Yogi Berra
Finally, as new factories were built and old managers retired or died off, businesses figured out how to make the most of the new technology. At that point, wrote Brynjolfsson and McAfee, “productivity didn’t merely inch upward on the resulting assembly lines; it doubled or even tripled. What’s more, for most of the subsequent century, additional complementary innovations, from lean manufacturing and steel mini-mills to Total Quality Management and Six Sigma principles, continued to boost manufacturing productivity.” This was a generational change—it took nearly 40 years for the productivity advantages of electric motors to be fully reflected in factory output statistics. Today as ever, changing the way that work is done often determines whether an organization will get its money’s worth from its IT investment. But the temptation to simply electronify the old process is powerful.
Black Box Thinking: Why Most People Never Learn From Their Mistakes--But Some Do by Matthew Syed
Airbus A320, Alfred Russel Wallace, Arthur Eddington, Atul Gawande, Black Swan, British Empire, call centre, Captain Sullenberger Hudson, Checklist Manifesto, cognitive bias, cognitive dissonance, conceptual framework, corporate governance, creative destruction, credit crunch, crew resource management, deliberate practice, double helix, epigenetics, fear of failure, fundamental attribution error, Henri Poincaré, hindsight bias, Isaac Newton, iterative process, James Dyson, James Hargreaves, James Watt: steam engine, Johannes Kepler, Joseph Schumpeter, Kickstarter, Lean Startup, mandatory minimum, meta analysis, meta-analysis, minimum viable product, publication bias, quantitative easing, randomized controlled trial, selection bias, Shai Danziger, Silicon Valley, six sigma, spinning jenny, Steve Jobs, the scientific method, Thomas Kuhn: the structure of scientific revolutions, too big to fail, Toyota Production System, US Airways Flight 1549, Wall-E, Yom Kippur War
As one author put it: Wallace, “admirably free from envy or jealousy,” was content to remain in Darwin’s shadow (Tori Reeve, Down House: The Home of Charles Darwin). *Getting the manufacturing process running seamlessly is often about ironing out unwanted deviations. It is about using process controls and the like to reduce variation. Creative change is often about experimentation; in other words, increasing variation. For more on this distinction, and how to reconcile it, see: http://www.forbes.com/sites/ricksmith/2014/06/11/is-six-sigma-killing -your-companys-future/. *One issue that was never fully resolved with Libyan Arab Airlines Flight 114 is why, according to the pilot of one of the Israeli Phantoms, all the window shades were down. It seems almost certain that, with pressure high and time limited, the pilot did not notice that some of the shades were, in fact, up. *As estimated by how often the nursing units were intercepting errors before they became consequential, and other key variables governing self-correction and learning.
Work Rules!: Insights From Inside Google That Will Transform How You Live and Lead by Laszlo Bock
Airbnb, Albert Einstein, AltaVista, Atul Gawande, Black Swan, book scanning, Burning Man, call centre, Cass Sunstein, Checklist Manifesto, choice architecture, citizen journalism, clean water, correlation coefficient, crowdsourcing, Daniel Kahneman / Amos Tversky, deliberate practice, en.wikipedia.org, experimental subject, Frederick Winslow Taylor, future of work, Google Earth, Google Glasses, Google Hangouts, Google X / Alphabet X, Googley, helicopter parent, immigration reform, Internet Archive, longitudinal study, Menlo Park, mental accounting, meta analysis, meta-analysis, Moneyball by Michael Lewis explains big data, nudge unit, PageRank, Paul Buchheit, Ralph Waldo Emerson, Rana Plaza, random walk, Richard Thaler, Rubik’s Cube, self-driving car, shareholder value, side project, Silicon Valley, six sigma, statistical model, Steve Ballmer, Steve Jobs, Steven Levy, Steven Pinker, survivorship bias, TaskRabbit, The Wisdom of Crowds, Tony Hsieh, Turing machine, winner-take-all economy, Y2K
Colleagues told me that the vaunted Session C process, a yearlong review of talent across the 300,000-person-strong company, had “lost its teeth” and “just wasn’t the same without Jack’s focus.”3 I didn’t have the benefit of having worked under both CEOs, but it dawned on me how deeply a CEO’s persona and focus can shape an institution. Most CEOs are very good at many things, but they become CEOs for being superbly distinctive at one or two, which tend to be matched to a company’s needs at that time. Even CEOs need to declare a major. Welch is best known for Six Sigma—a set of tools to improve quality and efficiency—and his focus on people. Immelt instead emphasized sales and marketing, most visibly through GE’s branded “ecomagination” efforts to make and be perceived as a maker of greener products. In 2006, after three years at GE, I was recruited to join Google as head of People Operations. I remember the recruiter, Martha Josephson, trying to convince me not to wear a suit to the interview.
Competition Demystified by Bruce C. Greenwald
additive manufacturing, airline deregulation, AltaVista, asset allocation, barriers to entry, business cycle, creative destruction, cross-subsidies, deindustrialization, discounted cash flows, diversified portfolio, Everything should be made as simple as possible, fault tolerance, intangible asset, John Nash: game theory, Nash equilibrium, Network effects, new economy, oil shock, packet switching, pets.com, price discrimination, price stability, selective serotonin reuptake inhibitor (SSRI), shareholder value, Silicon Valley, six sigma, Steve Jobs, transaction costs, yield management, zero-sum game
TABLE 18.3 Manufacturing productivity relative to the United States, 1970–80 and 1985–91 What had changed for the better was the attitude, training, and focus of American managers. Prior to 1980, management education in the United States had concentrated more on finance and marketing than on operations. But starting in the late 1970s, almost certainly induced by the intensity of overseas competition, that emphasis began to change. Techniques and goals like benchmarking, reengineering, quality circles and total quality management, just-in-time production systems, and six sigma standards helped to focus management attention on operational performance. The improvement in manufacturing productivity has been sustained well past the point at which firms were threatened with extinction if they did not reform their operations. The rate of growth has accelerated without significant increases in the rate of capital investment, without measurable improvements in the quality of the labor force, and without a ballooning of spending on research and development.
Gnuplot in Action: Understanding Data With Graphs by Philipp Janert
bioinformatics, business intelligence, Debian, general-purpose programming language, iterative process, mandelbrot fractal, pattern recognition, random walk, Richard Stallman, six sigma, survivorship bias
In many ways, my experience in the corporate world has been an influence while writing this book. I believe that graphical methods—which are accessible to anyone, regardless of mathematical or statistical training—are an excellent way to understand data and derive value from it (much better and more powerful than a five-day statistics class, and much more flexible and creative than a standard Six-Sigma program). And I believe that gnuplot is a very good tool to use for this purpose. Its learning curve is flat—you can pick up the basics in an hour. It requires no programming skills. It handles a variety of input formats. It’s fast and it’s interactive. It’s mature. It’s also free and open source. Gnuplot has always been popular with scientists all over—I hope to convince you that it can be useful to a much larger audience.
How I Became a Quant: Insights From 25 of Wall Street's Elite by Richard R. Lindsey, Barry Schachter
Albert Einstein, algorithmic trading, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, asset allocation, asset-backed security, backtesting, bank run, banking crisis, Black-Scholes formula, Bonfire of the Vanities, Bretton Woods, Brownian motion, business cycle, business process, butter production in bangladesh, buy and hold, buy low sell high, capital asset pricing model, centre right, collateralized debt obligation, commoditize, computerized markets, corporate governance, correlation coefficient, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, discounted cash flows, disintermediation, diversification, Donald Knuth, Edward Thorp, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, financial innovation, fixed income, full employment, George Akerlof, Gordon Gekko, hiring and firing, implied volatility, index fund, interest rate derivative, interest rate swap, John von Neumann, linear programming, Loma Prieta earthquake, Long Term Capital Management, margin call, market friction, market microstructure, martingale, merger arbitrage, Myron Scholes, Nick Leeson, P = NP, pattern recognition, Paul Samuelson, pensions crisis, performance metric, prediction markets, profit maximization, purchasing power parity, quantitative trading / quantitative ﬁnance, QWERTY keyboard, RAND corporation, random walk, Ray Kurzweil, Richard Feynman, Richard Stallman, risk-adjusted returns, risk/return, shareholder value, Sharpe ratio, short selling, Silicon Valley, six sigma, sorting algorithm, statistical arbitrage, statistical model, stem cell, Steven Levy, stochastic process, systematic trading, technology bubble, The Great Moderation, the scientific method, too big to fail, trade route, transaction costs, transfer pricing, value at risk, volatility smile, Wiener process, yield curve, young professional
Not only do I not believe quantum mechanics can be applied to financial markets, but I think most of the advanced statistical analyses financial folks perform today are ill-applied to the point of JWPR007-Lindsey April 30, 2007 16:46 Gregg E. Berman 63 absurdity. There is a big difference between astronomy and astrology, but not everyone realizes that. And that’s what made me very good at this first job. While spending many a long lab night staring at printouts from spectrum analyzers and traces from particle detectors, I routinely observed hundreds of six-sigma events appearing and disappearing right in front of my eyes. In order to succeed in experimental physics, you had to build up a real intuition about what types of results were real, and what was nothing more than data-mining, curve-fitting, or just plain statistical anomaly. By the end of my second year of research at the fund, I had gone about as far as I could go; but fortunately so had one of the fund’s general partners with whom I happened (not accidentally) to have developed a very good working relationship.
The Social Animal: The Hidden Sources of Love, Character, and Achievement by David Brooks
Albert Einstein, asset allocation, assortative mating, Atul Gawande, Bernie Madoff, business process, Cass Sunstein, choice architecture, clean water, creative destruction, Daniel Kahneman / Amos Tversky, David Brooks, delayed gratification, deliberate practice, disintermediation, Donald Trump, Douglas Hofstadter, Emanuel Derman, en.wikipedia.org, fear of failure, financial deregulation, financial independence, Flynn Effect, George Akerlof, Henri Poincaré, hiring and firing, impulse control, invisible hand, Joseph Schumpeter, labor-force participation, longitudinal study, loss aversion, medical residency, meta analysis, meta-analysis, Monroe Doctrine, Paul Samuelson, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, school vouchers, six sigma, social intelligence, Stanford marshmallow experiment, Steve Jobs, Steven Pinker, the scientific method, The Spirit Level, The Wealth of Nations by Adam Smith, Thorstein Veblen, transaction costs, Walter Mischel, young professional
All of her new colleagues had a different way of seeing, based on amassing huge piles of data and then devising formulas and building systems. The two modes seemed non-overlapping. Maybe it was in B-School, maybe it was somewhere else, but the team of assholes had been trained in certain methodologies. They had been trained to turn management into a science. They didn’t really grow up steeped in the features of a specific product. They were trained to study organizations. Some did Dynamic Systems Theory, some did Six Sigma Analysis, or the Taguchi Method or Su-Field Analysis (structural-substance field analysis). There was TRIZ, a Russian-made model-based technology for producing creativity. There was Business Process Reengineering. Erica looked this one up on Wikipedia. According to one of the management books quoted on the site, BPR “escalates the efforts of JIT [Just In Time] and TQM [Total Quality Management] to make process orientation a strategic tool and a core competence of the organization.
Connectography: Mapping the Future of Global Civilization by Parag Khanna
"Robert Solow", 1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 9 dash line, additive manufacturing, Admiral Zheng, affirmative action, agricultural Revolution, Airbnb, Albert Einstein, amateurs talk tactics, professionals talk logistics, Amazon Mechanical Turk, Asian financial crisis, asset allocation, autonomous vehicles, banking crisis, Basel III, Berlin Wall, bitcoin, Black Swan, blockchain, borderless world, Boycotts of Israel, Branko Milanovic, BRICs, British Empire, business intelligence, call centre, capital controls, charter city, clean water, cloud computing, collateralized debt obligation, commoditize, complexity theory, continuation of politics by other means, corporate governance, corporate social responsibility, credit crunch, crony capitalism, crowdsourcing, cryptocurrency, cuban missile crisis, data is the new oil, David Ricardo: comparative advantage, deglobalization, deindustrialization, dematerialisation, Deng Xiaoping, Detroit bankruptcy, digital map, disruptive innovation, diversification, Doha Development Round, edge city, Edward Snowden, Elon Musk, energy security, Ethereum, ethereum blockchain, European colonialism, eurozone crisis, failed state, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, fixed income, forward guidance, global supply chain, global value chain, global village, Google Earth, Hernando de Soto, high net worth, Hyperloop, ice-free Arctic, if you build it, they will come, illegal immigration, income inequality, income per capita, industrial cluster, industrial robot, informal economy, Infrastructure as a Service, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, LNG terminal, low cost airline, low cost carrier, low earth orbit, manufacturing employment, mass affluent, mass immigration, megacity, Mercator projection, Metcalfe’s law, microcredit, mittelstand, Monroe Doctrine, mutually assured destruction, New Economic Geography, new economy, New Urbanism, off grid, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Parag Khanna, Peace of Westphalia, peak oil, Pearl River Delta, Peter Thiel, Philip Mirowski, plutocrats, Plutocrats, post-oil, post-Panamax, private military company, purchasing power parity, QWERTY keyboard, race to the bottom, Rana Plaza, rent-seeking, reserve currency, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Coase, Scramble for Africa, Second Machine Age, sharing economy, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, six sigma, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, Stuxnet, supply-chain management, sustainable-tourism, TaskRabbit, telepresence, the built environment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, Tim Cook: Apple, trade route, transaction costs, UNCLOS, uranium enrichment, urban planning, urban sprawl, WikiLeaks, young professional, zero day
In the dense but influential treatise Empire (Harvard University Press, 2000), the American scholar Michael Hardt and the Italian dissident Antonio Negri posit globalization as an unregulated and all-consuming force that has no fixed locus. 13. Today’s complex global supply chains—hybrids of public and corporate actors—embody what the pioneering scholar James Rosenau called a “sphere of authority”: a trans-territorial, cross-jurisdiction entity that has low institutionalization, low visibility, multiple public and private operators and rule makers, and immense public relevance. 14. From the original Six Sigma manufacturing optimization process has grown a suite of tools such as electronic data interchange that leverage supplier and buyer data and market conditions to forecast volume and demand shifts, and sensor networks to track inventories, improve efficiency, and reduce waste. 15. Accenture’s Supply Chain Academy has managers from hundreds of Fortune 1000 companies enrolled in its thousands of online case study courses dedicated to achieving such business optimization. 16.
Crash of the Titans: Greed, Hubris, the Fall of Merrill Lynch, and the Near-Collapse of Bank of America by Greg Farrell
Airbus A320, Apple's 1984 Super Bowl advert, bank run, banking crisis, bonus culture, call centre, Captain Sullenberger Hudson, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, financial innovation, fixed income, glass ceiling, high net worth, Long Term Capital Management, mass affluent, Mexican peso crisis / tequila crisis, Nelson Mandela, plutocrats, Plutocrats, Ronald Reagan, six sigma, sovereign wealth fund, technology bubble, too big to fail, US Airways Flight 1549, yield curve
Merrill’s top internal accounting people—Chris Hayward and Dave Moser—routed every important document, including their daily updates, to Cotty. Meanwhile, BofA’s HR people spread out through Merrill Lynch’s headquarters to take the measure of the exotic creatures who would be joining their organization. At the executive level, BofA committed itself to various management trends popularized on business school campuses across the country. In recent years, the Charlotte bank had devoted its internal education programs to the “six-sigma” management program embraced by Jack Welch, the former CEO of General Electric who embarked on a new career as a management guru following his retirement. BofA executives put a lot of stock in psychological profiles and Myers-Briggs personality tests, which, among other things, purport to determine whether an individual is an introvert or an extrovert. Using the language of Myers-Briggs, Alphin judged Thain early on to be an introvert.
Site Reliability Engineering: How Google Runs Production Systems by Betsy Beyer, Chris Jones, Jennifer Petoff, Niall Richard Murphy
Air France Flight 447, anti-pattern, barriers to entry, business intelligence, business process, Checklist Manifesto, cloud computing, combinatorial explosion, continuous integration, correlation does not imply causation, crowdsourcing, database schema, defense in depth, DevOps, en.wikipedia.org, fault tolerance, Flash crash, George Santayana, Google Chrome, Google Earth, information asymmetry, job automation, job satisfaction, Kubernetes, linear programming, load shedding, loose coupling, meta analysis, meta-analysis, microservices, minimum viable product, MVC pattern, performance metric, platform as a service, revision control, risk tolerance, side project, six sigma, the scientific method, Toyota Production System, trickle-down economics, web application, zero day
Previously, he worked on UK and USA military aircraft, naval avionics and aircraft stores management systems, and UK railway signaling systems. Reliability is critical in this space because impact of incidents ranges from multimillion-dollar loss of equipment to injuries and fatalities. Eddie Kennedy is a project manager for the Global Customer Experience team at Google and a mechanical engineer by training. Eddie spent six years working as a Six Sigma Black Belt process engineer in a manufacturing facility that makes synthetic diamonds. This industry is characterized by a relentless focus on safety, because the extremes of temperature and pressure demands of the process pose a high level of danger to workers on a daily basis. John Li is currently a Site Reliability Engineer at Google. John previously worked as a systems administrator and software developer at a proprietary trading company in the finance industry.
Debunking Economics - Revised, Expanded and Integrated Edition: The Naked Emperor Dethroned? by Steve Keen
"Robert Solow", accounting loophole / creative accounting, banking crisis, banks create money, barriers to entry, Benoit Mandelbrot, Big bang: deregulation of the City of London, Black Swan, Bonfire of the Vanities, business cycle, butterfly effect, capital asset pricing model, cellular automata, central bank independence, citizen journalism, clockwork universe, collective bargaining, complexity theory, correlation coefficient, creative destruction, credit crunch, David Ricardo: comparative advantage, debt deflation, diversification, double entry bookkeeping, en.wikipedia.org, Eugene Fama: efficient market hypothesis, experimental subject, Financial Instability Hypothesis, fixed income, Fractional reserve banking, full employment, Henri Poincaré, housing crisis, Hyman Minsky, income inequality, information asymmetry, invisible hand, iterative process, John von Neumann, Kickstarter, laissez-faire capitalism, liquidity trap, Long Term Capital Management, mandelbrot fractal, margin call, market bubble, market clearing, market microstructure, means of production, minimum wage unemployment, money market fund, open economy, Pareto efficiency, Paul Samuelson, place-making, Ponzi scheme, profit maximization, quantitative easing, RAND corporation, random walk, risk tolerance, risk/return, Robert Shiller, Robert Shiller, Ronald Coase, Schrödinger's Cat, scientific mainstream, seigniorage, six sigma, South Sea Bubble, stochastic process, The Great Moderation, The Wealth of Nations by Adam Smith, Thorstein Veblen, time value of money, total factor productivity, tulip mania, wage slave, zero-sum game
However, an institutional investor – a pension fund, for example – with a weekly trading horizon, would probably consider that drop a buying opportunity because weekly returns over the past ten years have averaged 0.22 per cent with a standard deviation of 2.37 per cent. In addition, the technical drop has not changed the outlook of the weekly trader, who looks at either longer technical or fundamental information. Thus the day trader’s six-sigma [standard deviation] event is a 0.15-sigma event to the weekly trader, or no big deal. The weekly trader steps in, buys, and creates liquidity. This liquidity in turn stabilizes the market. (Peters 1994) The Fractal Markets Hypothesis thus explains the stability of the market by the realistic assumption that traders differ in their time horizons. It also alleges that instability is likely to occur if all investors suddenly switch to the same time horizon.
The Meritocracy Trap: How America's Foundational Myth Feeds Inequality, Dismantles the Middle Class, and Devours the Elite by Daniel Markovits
"Robert Solow", 8-hour work day, activist fund / activist shareholder / activist investor, affirmative action, Anton Chekhov, asset-backed security, assortative mating, basic income, Bernie Sanders, big-box store, business cycle, capital asset pricing model, Capital in the Twenty-First Century by Thomas Piketty, carried interest, collateralized debt obligation, collective bargaining, computer age, corporate governance, corporate raider, crony capitalism, David Brooks, deskilling, Detroit bankruptcy, disruptive innovation, Donald Trump, Edward Glaeser, Emanuel Derman, equity premium, European colonialism, everywhere but in the productivity statistics, fear of failure, financial innovation, financial intermediation, fixed income, Ford paid five dollars a day, Frederick Winslow Taylor, full employment, future of work, gender pay gap, George Akerlof, Gini coefficient, glass ceiling, helicopter parent, high net worth, hiring and firing, income inequality, industrial robot, interchangeable parts, invention of agriculture, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, knowledge economy, knowledge worker, Kodak vs Instagram, labor-force participation, longitudinal study, low skilled workers, manufacturing employment, Mark Zuckerberg, Martin Wolf, mass incarceration, medical residency, minimum wage unemployment, Myron Scholes, Nate Silver, New Economic Geography, new economy, offshore financial centre, Paul Samuelson, payday loans, plutocrats, Plutocrats, Plutonomy: Buying Luxury, Explaining Global Imbalances, precariat, purchasing power parity, rent-seeking, Richard Florida, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, savings glut, school choice, shareholder value, Silicon Valley, Simon Kuznets, six sigma, Skype, stakhanovite, stem cell, Steve Jobs, supply-chain management, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, Thomas Davenport, Thorstein Veblen, too big to fail, total factor productivity, transaction costs, traveling salesman, universal basic income, unpaid internship, Vanguard fund, War on Poverty, Winter of Discontent, women in the workforce, working poor, young professional, zero-sum game
., “Working with Machines: The Impact of Algorithmic and Data-Driven Management on Human Workers,” Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (April 2015): 1603, www.cs.cmu.edu/~mklee/materials/Publication/2015-CHI_algorithmic_management.pdf. every assembly line: For a broad overview of modern supply chain management, see generally Martin Christopher, Logistics and Supply Chain Management, 5th ed. (Harlow: Pearson, 2016), 35 (discussing how “just-in-time” strategy results in minimal inventory), 194 (the use of event management software to manage inventory levels), 225–26 (discussing the merits of Six Sigma management techniques), 289 (a change-embracing corporate culture). For in-depth case studies of Walmart’s and Amazon’s supply chains, see Colby Ronald Chiles and Marguarette Thi Dau, “An Analysis of Current Supply Chain Best Practices in the Retail Industry with Case Studies of Wal-Mart and Amazon.com” (master’s thesis, Georgia Institute of Technology, 2005), 66, 70, 103–4 (discussing both companies’ culture of innovation, including Walmart’s “Everyday Low Prices” mentality and its managers’ autonomy and incentives to keep costs low).
Valuation: Measuring and Managing the Value of Companies by Tim Koller, McKinsey, Company Inc., Marc Goedhart, David Wessels, Barbara Schwimmer, Franziska Manoury
activist fund / activist shareholder / activist investor, air freight, barriers to entry, Basel III, BRICs, business climate, business cycle, business process, capital asset pricing model, capital controls, Chuck Templeton: OpenTable:, cloud computing, commoditize, compound rate of return, conceptual framework, corporate governance, corporate social responsibility, creative destruction, credit crunch, Credit Default Swap, discounted cash flows, distributed generation, diversified portfolio, energy security, equity premium, fixed income, index fund, intangible asset, iterative process, Long Term Capital Management, market bubble, market friction, Myron Scholes, negative equity, new economy, p-value, performance metric, Ponzi scheme, price anchoring, purchasing power parity, quantitative easing, risk/return, Robert Shiller, Robert Shiller, shareholder value, six sigma, sovereign wealth fund, speech recognition, stocks for the long run, survivorship bias, technology bubble, time value of money, too big to fail, transaction costs, transfer pricing, value at risk, yield curve, zero-coupon bond
For a consumer electronics company, multiyear price trends for its individual products are an important indicator, as steadily declining prices often indicate lack of innovation compared with competitors. 2. Cost structure health metrics measure a company’s ability to manage its costs relative to competitors over three to five years. These metrics might include assessments of programs such as Six Sigma, a method made famous by General Electric and adopted by other companies to reduce CHOOSING THE RIGHT METRICS 585 costs continually and maintain a cost advantage relative to their competitors across most of their businesses. 3. Asset health measures how well a company maintains and develops its assets. For a hotel or restaurant chain, the average time between remodeling projects may be an important driver of asset health.