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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, 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, 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.
A Mathematician Plays the Stock Market by John Allen Paulos
Benoit Mandelbrot, Black-Scholes formula, Brownian motion, business climate, butterfly effect, capital asset pricing model, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, diversified portfolio, 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, invisible hand, Isaac Newton, John Nash: game theory, Long Term Capital Management, loss aversion, Louis Bachelier, mandelbrot fractal, margin call, mental accounting, Nash equilibrium, Network effects, passive investing, Paul Erdős, Ponzi scheme, price anchoring, Ralph Nelson Elliott, random walk, Richard Thaler, Robert Shiller, Robert Shiller, short selling, six sigma, Stephen Hawking, 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.
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, 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 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.
Money Mavericks: Confessions of a Hedge Fund Manager by Lars Kroijer
Bernie Madoff, capital asset pricing model, diversification, diversified portfolio, family office, fixed income, forensic accounting, Gordon Gekko, hiring and firing, implied volatility, index fund, Jeff Bezos, Just-in-time delivery, Long Term Capital Management, merger arbitrage, new economy, Ponzi scheme, 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.
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, crowdsourcing, data acquisition, digital Maoism, discovery of DNA, Dmitri Mendeleev, double entry bookkeeping, double helix, 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, Jacquard loom, James Hargreaves, James Watt: steam engine, Jane Jacobs, Jaron Lanier, John Snow's cholera map, Joseph Schumpeter, Joseph-Marie Jacquard, Kevin Kelly, lone genius, Louis Daguerre, Louis Pasteur, Mason jar, 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.
23andMe, Andy Kessler, bank run, barriers to entry, Berlin Wall, British Empire, business process, California gold rush, carbon footprint, Cass Sunstein, cloud computing, collateralized debt obligation, collective bargaining, computer age, disintermediation, 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, 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, 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.
23andMe, Affordable Care Act / Obamacare, Albert Einstein, big data - Walmart - Pop Tarts, bioinformatics, 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, John von Neumann, Mark Zuckerberg, market bubble, meta analysis, meta-analysis, 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?”
The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone
3D printing, airport security, AltaVista, Amazon Mechanical Turk, Amazon Web Services, bank run, Bernie Madoff, big-box store, Black Swan, book scanning, Brewster Kahle, call centre, centre right, 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, 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?
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.
Business Lessons From a Radical Industrialist by Ray C. Anderson
Albert Einstein, banking crisis, 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, intermodal, invisible hand, late fees, Mahatma Gandhi, market bubble, music of the spheres, Negawatt, new economy, oil shale / tar sands, oil shock, 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.
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, Bretton Woods, BRICs, business climate, capital asset pricing model, 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, laissez-faire capitalism, land reform, liquidity trap, Long Term Capital Management, McMansion, moral hazard, mortgage tax deduction, naked short selling, 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, 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.”
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, disintermediation, distributed generation, double helix, experimental economics, full employment, hydrogen economy, industrial robot, informal economy, interchangeable parts, job satisfaction, labour market flexibility, 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, capital asset pricing model, Carmen Reinhart, carried interest, Celtic Tiger, clean water, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, 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, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, eurozone crisis, Fall of the Berlin Wall, financial independence, financial innovation, 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, interest rate swap, invention of the wheel, invisible hand, Isaac Newton, job automation, Johann Wolfgang von Goethe, joint-stock company, Joseph Schumpeter, Kenneth Rogoff, Kevin Kelly, labour market flexibility, 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, merger arbitrage, Mikhail Gorbachev, Milgram experiment, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, mutually assured destruction, Naomi Klein, Network effects, new economy, Nick Leeson, Nixon shock, Northern Rock, nuclear winter, oil shock, Own Your Own Home, pets.com, 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 Feynman, Richard Thaler, 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, 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, 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 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
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.
Top Dog: The Science of Winning and Losing by Po Bronson, Ashley Merryman
Asperger Syndrome, Berlin Wall, conceptual framework, crowdsourcing, delayed gratification, deliberate practice, Edward Glaeser, experimental economics, Fall of the Berlin Wall, fear of failure, game design, Jean Tirole, knowledge worker, loss aversion, Mark Zuckerberg, meta analysis, meta-analysis, Mikhail Gorbachev, phenotype, Richard Feynman, Richard Feynman, risk tolerance, school choice, shareholder value, Silicon Valley, six sigma, Steve Jobs
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?”
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, Baxter: Rethink Robotics, business intelligence, business process, call centre, carbon-based life, Clayton Christensen, clockwork universe, conceptual framework, dark matter, David Brooks, deliberate practice, deskilling, Edward Lloyd's coffeehouse, Elon Musk, Erik Brynjolfsson, estate planning, follow your passion, Frank Levy and Richard Murnane: The New Division of Labor, Freestyle chess, game design, general-purpose programming language, 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 Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Khan Academy, knowledge worker, labor-force participation, 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, Richard Feynman, risk tolerance, Robert Shiller, Robert Shiller, Rodney Brooks, Second Machine Age, self-driving car, Silicon Valley, six sigma, Skype, 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.
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, connected car, corporate social responsibility, crowdsourcing, Elon Musk, financial innovation, global supply chain, income inequality, industrial robot, Internet of things, job satisfaction, Khan Academy, Kickstarter, late fees, Lean Startup, 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, ride hailing / ride sharing, 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, Steve Jobs, supply-chain management, TaskRabbit, The Fortune at the Bottom of the Pyramid, The Nature of the Firm, transaction costs, 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.
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, 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.
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.
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, Corn Laws, corporate governance, corporate social responsibility, credit crunch, crony capitalism, double entry bookkeeping, Etonian, hiring and firing, 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.
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, margin call, Moneyball by Michael Lewis explains big data, 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
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.
Airbnb, business intelligence, cloud computing, financial independence, Google Glasses, hiring and firing, Isaac Newton, Jeff Bezos, Mark Zuckerberg, 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 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, 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
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.
Antifragile: Things That Gain From Disorder by Nassim Nicholas Taleb
Air France Flight 447, Andrei Shleifer, banking crisis, Benoit Mandelbrot, Berlin Wall, Black Swan, credit crunch, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, discrete time, double entry bookkeeping, Emanuel Derman, epigenetics, financial independence, Flash crash, Gary Taubes, Gini coefficient, Henri Poincaré, high net worth, 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, knowledge economy, Lao Tzu, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, meta analysis, meta-analysis, microbiome, moral hazard, mouse model, Norbert Wiener, pattern recognition, 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, Silicon Valley, six sigma, spinning jenny, statistical model, Steve Jobs, Steven Pinker, Stewart Brand, stochastic process, stochastic volatility, The Great Moderation, The Wealth of Nations by Adam Smith, Thomas Malthus, too big to fail, transaction costs, urban planning, 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.
3D printing, barriers to entry, call centre, Clayton Christensen, clean water, cloud computing, continuous integration, corporate governance, experimental subject, Frederick Winslow Taylor, Lean Startup, Mark Zuckerberg, minimum viable product, Network effects, payday loans, Peter Thiel, pets.com, Ponzi scheme, pull request, risk tolerance, 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.
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, 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, Isaac Newton, Long Term Capital Management, Menlo Park, mental accounting, meta analysis, meta-analysis, 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, 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.
Joel on Software by Joel Spolsky
barriers to entry, c2.com, George Gilder, index card, Jeff Bezos, knowledge worker, Metcalfe's law, 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 Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson, Andrew McAfee
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, Baxter: Rethink Robotics, British Empire, business intelligence, business process, call centre, clean water, combinatorial explosion, computer age, computer vision, congestion charging, corporate governance, crowdsourcing, David Ricardo: comparative advantage, 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, game design, global village, happiness index / gross national happiness, illegal immigration, immigration reform, income inequality, income per capita, indoor plumbing, industrial robot, informal economy, inventory management, James Watt: steam engine, Jeff Bezos, jimmy wales, job automation, 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, Mark Zuckerberg, Mars Rover, 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, payday loans, 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.
3D printing, Airbnb, Albert Einstein, Berlin Wall, Black Swan, clean water, collapse of Lehman Brothers, Credit Default Swap, crony capitalism, crowdsourcing, Danny Hillis, declining real wages, demographic dividend, 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, Joseph Schumpeter, Kickstarter, lone genius, manufacturing employment, Mark Zuckerberg, Martin Wolf, new economy, Paul Graham, Peter Thiel, 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.
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, crony capitalism, cross-subsidies, en.wikipedia.org, Fall of the Berlin Wall, fear of failure, Flynn Effect, income per capita, invisible hand, Jeff Bezos, job satisfaction, lone genius, Mahatma Gandhi, microcredit, Occupy movement, profit maximization, Ralph Waldo Emerson, shareholder value, six sigma, 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, women in the workforce
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.
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 process, business process outsourcing, call centre, Carmen Reinhart, clean water, collapse of Lehman Brothers, collateralized debt obligation, 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, illegal immigration, index fund, intermodal, inventory management, Kenneth Rogoff, labor-force participation, LNG terminal, low skilled workers, Mark Zuckerberg, Martin Wolf, Maui Hawaii, McMansion, 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, 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.
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, Capital in the Twenty-First Century by Thomas Piketty, Celtic Tiger, central bank independence, collapse of Lehman Brothers, collective bargaining, 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, 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, Richard Feynman, road to serfdom, Ronald Reagan, Satoshi Nakamoto, security theater, shareholder value, Silicon Valley, six sigma, South Sea Bubble, sovereign wealth fund, Steve Jobs, The Chicago School, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, trickle-down economics, Washington Consensus, 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.
3D printing, Airbnb, Amazon Web Services, Andy Kessler, banking crisis, barriers to entry, bitcoin, blockchain, Burning Man, business climate, call centre, car-free, cloud computing, collaborative consumption, collaborative economy, collective bargaining, congestion charging, crowdsourcing, cryptocurrency, decarbonisation, don't be evil, Elon Musk, en.wikipedia.org, ethereum blockchain, Ferguson, Missouri, Firefox, frictionless, Gini coefficient, hive mind, income inequality, index fund, informal economy, 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 lending, 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 Nature of the Firm, transaction costs, Turing test, Uber and 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!
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, Plutocrats, plutocrats, Ronald Reagan, six sigma, sovereign wealth fund, technology bubble, too big to fail, 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.
Albert Einstein, asset allocation, Atul Gawande, Bernie Madoff, business process, Cass Sunstein, choice architecture, clean water, 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, loss aversion, medical residency, meta analysis, meta-analysis, Monroe Doctrine, Richard Thaler, risk tolerance, Robert Shiller, Robert Shiller, school vouchers, six sigma, 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.
Gnuplot in Action: Understanding Data With Graphs by Philipp Janert
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.
Affordable Care Act / Obamacare, AI winter, Airbnb, Atul Gawande, Captain Sullenberger Hudson, Checklist Manifesto, Clayton Christensen, collapse of Lehman Brothers, computer age, crowdsourcing, deskilling, 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, knowledge worker, medical malpractice, medical residency, Menlo Park, minimum viable product, natural language processing, Network effects, Nicholas Carr, obamacare, pattern recognition, 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, Toyota Production System, Uber for X, 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.
Connectography: Mapping the Future of Global Civilization by Parag Khanna
1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 3D printing, 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, complexity theory, 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, diversification, Doha Development Round, edge city, Edward Snowden, Elon Musk, energy security, ethereum blockchain, European colonialism, eurozone crisis, failed state, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, 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 robot, informal economy, Infrastructure as a Service, interest rate swap, Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, labour market flexibility, labour mobility, LNG terminal, low cost carrier, manufacturing employment, mass affluent, megacity, Mercator projection, microcredit, mittelstand, Monroe Doctrine, mutually assured destruction, New Economic Geography, new economy, New Urbanism, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Peace of Westphalia, peak oil, Peter Thiel, 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, 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.
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 process, buy low sell high, capital asset pricing model, centre right, collateralized debt obligation, corporate governance, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, discounted cash flows, disintermediation, diversification, 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, Nick Leeson, P = NP, pattern recognition, 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 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.
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, credit crunch, 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, Joseph Schumpeter, Lean Startup, meta analysis, meta-analysis, minimum viable product, quantitative easing, randomized controlled trial, 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, 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.
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, butterfly effect, capital asset pricing model, cellular automata, central bank independence, citizen journalism, clockwork universe, collective bargaining, complexity theory, correlation coefficient, 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, Fractional reserve banking, full employment, Henri Poincaré, housing crisis, Hyman Minsky, income inequality, invisible hand, iterative process, John von Neumann, 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, open economy, 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
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.
Valuation: Measuring and Managing the Value of Companies by Tim Koller, McKinsey, Company Inc., Marc Goedhart, David Wessels, Barbara Schwimmer, Franziska Manoury
air freight, barriers to entry, Basel III, BRICs, business climate, business process, capital asset pricing model, capital controls, cloud computing, compound rate of return, conceptual framework, corporate governance, corporate social responsibility, credit crunch, Credit Default Swap, discounted cash flows, distributed generation, diversified portfolio, energy security, equity premium, index fund, iterative process, Long Term Capital Management, market bubble, market friction, meta analysis, meta-analysis, 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, 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.