Thomas Davenport

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pages: 242 words: 245

The New Ruthless Economy: Work & Power in the Digital Age by Simon Head

Asian financial crisis, business cycle, business process, call centre, conceptual framework, deskilling, Erik Brynjolfsson, Ford paid five dollars a day, Frederick Winslow Taylor, informal economy, information retrieval, medical malpractice, new economy, Panopticon Jeremy Bentham, shareholder value, Shoshana Zuboff, Silicon Valley, single-payer health, supply-chain management, telemarketer, Thomas Davenport, Toyota Production System, union organizing

Thus, Professor Paul David, writing in 2000 about the impact of IT 39 40 THE NEW RUTHLESS ECONOMY investment on the whole economy, could use language very similar to the language used by the MIT Commission in its 1989 study of U.S. manufacturing: "a process of transition to ... new organizational forms . . . with new kinds of workforce skills . . . which would accomplish the abandonment or extensive transformation . . . of the technological regime identified with Fordism."5 The leading practitioners of service sector reengineering also used the language of the new workplace. Thomas Davenport wrote of how reengineering created "a more empowered and diversified work force, eliminating levels of hierarchy, creating self-managing work teams, combining jobs and assigning broader responsibility, and upgrading skills."6 Few would want to oppose a workplace revolution that could enhance the role of employee judgment and skill. Employees so empowered can command good wages, are well placed to form unions, and can have a real say in how technologies are used in the workplace. But has such a revolution really taken place? The use of "new workplace" rhetoric by a leading reengineer such as Thomas Davenport should have given us pause. Similarly, the prevailing view of Japanese production methods espoused by (among others) the MIT and Magaziner Commissions, and the whole body of theory derived from this account were both deeply flawed.

For a discussion of this wider definition of technology, see Paul Krugman, "Technology's Revenge," p. 195. 11. For a discussion of reengjneering see, for example, Michael Hammer and James Champy, Reengineering the Corporation: A Manifesto for Business Revolution (New York, 1993); Michael Hammer, The Reengineering Revolution (New York, 1995); James Champy, Reengineering Management (New York, 1995); Thomas Davenport, Process Innovation, Reengineering Work through Technology (Cambridge, Mass., 1993). For a discussion of enterprise resource planning (ERP), see Thomas Davenport, Mission Critical, Realizing the Promise of Enterprise Systems (Cambridge, Mass., 2000). See also Financial Times (London), .FTSurveys: Enterprise Resource Planning, May 26,1999; Enterprise Resource Planning, December 15, 1999; E-Business: ERP and Beyond, July 19,2000. 12. Michael Hammer, The ReengineeringRevolution, p. xi. 13.

SAP E-Business Solutions, "SAP Business Workflow: What is Workflow?" Undated, downloaded from www.sap.com/solutions/technology/ workfl__users.htm, July 2001. No longer available at SAP's website but can be obtained from the author at sihead@aol.com. 14. Ibid. 15. Keller and Teufel, SAP R/3 Process-Oriented Implementation, $. 105. 16. Thomas Davenport, "The Fad that Forgot People," Fast Company, November 1995, p. 1. Available at www.fastcompany.com/online/01/ reenging.html. 17. Thomas Davenport, Mission Critical, Realizing the Promise of Enterprise Systems (Cambridge, Mass., 2000). 18. Ibid., p. 143; also pp. 137-42. 19. Keller and Teufel, SAP R/3 Process-Oriented Implementation, p. 56. 20. Philip Manchester, "Rich Rewards Yet to be Unlocked," Financial Times Survey: E-Business and Beyond, July 19, 2000, p. i. 21.


pages: 472 words: 117,093

Machine, Platform, Crowd: Harnessing Our Digital Future by Andrew McAfee, Erik Brynjolfsson

"Robert Solow", 3D printing, additive manufacturing, AI winter, Airbnb, airline deregulation, airport security, Albert Einstein, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, backtesting, barriers to entry, bitcoin, blockchain, British Empire, business cycle, business process, carbon footprint, Cass Sunstein, centralized clearinghouse, Chris Urmson, cloud computing, cognitive bias, commoditize, complexity theory, computer age, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, Daniel Kahneman / Amos Tversky, Dean Kamen, discovery of DNA, disintermediation, disruptive innovation, distributed ledger, double helix, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Ethereum, ethereum blockchain, everywhere but in the productivity statistics, family office, fiat currency, financial innovation, George Akerlof, global supply chain, Hernando de Soto, hive mind, information asymmetry, Internet of things, inventory management, iterative process, Jean Tirole, Jeff Bezos, jimmy wales, John Markoff, joint-stock company, Joseph Schumpeter, Kickstarter, law of one price, longitudinal study, Lyft, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, Marc Andreessen, Mark Zuckerberg, meta analysis, meta-analysis, Mitch Kapor, moral hazard, multi-sided market, Myron Scholes, natural language processing, Network effects, new economy, Norbert Wiener, Oculus Rift, PageRank, pattern recognition, peer-to-peer lending, performance metric, plutocrats, Plutocrats, precision agriculture, prediction markets, pre–internet, price stability, principal–agent problem, Ray Kurzweil, Renaissance Technologies, Richard Stallman, ride hailing / ride sharing, risk tolerance, Ronald Coase, Satoshi Nakamoto, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Skype, slashdot, smart contracts, Snapchat, speech recognition, statistical model, Steve Ballmer, Steve Jobs, Steven Pinker, supply-chain management, TaskRabbit, Ted Nelson, The Market for Lemons, The Nature of the Firm, Thomas Davenport, Thomas L Friedman, too big to fail, transaction costs, transportation-network company, traveling salesman, Travis Kalanick, two-sided market, Uber and Lyft, Uber for X, uber lyft, ubercab, Watson beat the top human players on Jeopardy!, winner-take-all economy, yield management, zero day

., Fordham University, 2014). 53 There’s an old joke: Mark Fisher, The Millionaire’s Book of Quotations (New York: Thorsons, 1991), quoted in Barry Popik, “The Factory of the Future Will Have Only Two Employees, a Man and a Dog,” Barrypopik.com (blog), December 2, 2015, http://www.barrypopik.com/index.php/new_york_city/entry/the_factory_of_the_future. 54 “broken leg role”: Paul E. Meehl, Clinical versus Statistical Prediction (Minneapolis: University of Minnesota Press, 1954). 54 “distinct, unanticipated factors”: Ibid. 54 “look out of the window”: Stuart Lauchlan, “SPSS Directions: Thomas Davenport on Competing through Analytics,” MyCustomer, May 14, 2007, http://www.mycustomer.com/marketing/strategy/spss-directions-thomas-davenport-on-competing-through-analytics. 55 This practice earned the company: “Uber ‘Truly Sorry’ for Price Surge during Sydney Siege,” BBC News, December 24, 2014, http://www.bbc.com/news/technology-30595406. 55 “We didn’t stop surge pricing immediately”: “Uber ‘Truly Sorry’ for Hiking Prices during Sydney Siege,” Telegraph, December 24, 2014, http://www.telegraph.co.uk/news/worldnews/australiaandthepacific/australia/11312238/Uber-truly-sorry-for-hiking-prices-during-Sydney-siege.html. 55 Within thirty minutes of the first one: Andrew J.

As soon as we’re born, we start learning important things about how the world works, and we learn them reliably and quickly. Despite decades of research, however, we still don’t understand very much about how we acquire our common sense, and our attempts to instill it in computers have so far been impressive failures, as we’ll discuss more in the next chapter. In many cases, therefore, it’s a good idea to have a person check the computer’s decisions to make sure they make sense. Thomas Davenport, a longtime scholar of analytics and technology, calls this taking a “look out of the window.” The phrase is not simply an evocative metaphor. It was inspired by an airline pilot he met who described how he relied heavily on the plane’s instrumentation but found it essential to occasionally visually scan the skyline himself. This approach can be highly beneficial, not only for preventing errors, but also for managing a company’s reputation.


pages: 304 words: 82,395

Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schonberger, Kenneth Cukier

23andMe, Affordable Care Act / Obamacare, airport security, barriers to entry, Berlin Wall, big data - Walmart - Pop Tarts, Black Swan, book scanning, business intelligence, business process, call centre, cloud computing, computer age, correlation does not imply causation, dark matter, double entry bookkeeping, Eratosthenes, Erik Brynjolfsson, game design, IBM and the Holocaust, index card, informal economy, intangible asset, Internet of things, invention of the printing press, Jeff Bezos, Joi Ito, lifelogging, Louis Pasteur, Mark Zuckerberg, Menlo Park, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, obamacare, optical character recognition, PageRank, paypal mafia, performance metric, Peter Thiel, post-materialism, random walk, recommendation engine, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, smart grid, smart meter, social graph, speech recognition, Steve Jobs, Steven Levy, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Thomas Davenport, Turing test, Watson beat the top human players on Jeopardy!

Everything is run by the numbers,” explained Ken Rudin, then Zynga’s analytics chief, before jumping ship to head analytics at Facebook. Harnessing data is no guarantee of business success but shows what is possible. The shift to data-driven decisions is profound. Most people base their decisions on a combination of facts and reflection, plus a heavy dose of guesswork. “A riot of subjective visions—feelings in the solar plexus,” in the poet W. H. Auden’s memorable words. Thomas Davenport, a business professor at Babson College in Massachusetts and the author of numerous books on analytics, calls it “the golden gut.” Executives are just sure of themselves from gut instinct, so they go with that. But this is starting to change as managerial decisions are made or at least confirmed by predictive modeling and big-data analysis. For instance, The-Numbers.com uses lots of data and mathematics to tell independent Hollywood producers how much income a film is likely to earn long before the first scene is shot.

Zynga data analytics—Nick Wingfield, “Virtual Products, Real Profits: Players Spend on Zynga’s Games, but Quality Turns Some Off,” Wall Street Journal, September 9, 2011 (http://online.wsj.com/article/SB10001424053111904823804576502442835413446.html). [>] Ken Rudin quotation—From interview of Rudin by Niko Waesche, cited in Erik Schlie, Jörg Rheinboldt, and Niko Waesche, Simply Seven: Seven Ways to Create a Sustainable Internet Business (Palgrave Macmillan, 2011). p. 7. Auden quotation—W. H. Auden, “For the Time Being,” 1944. Thomas Davenport quotation—Cukier interview with Davenport, December 2009. The-Numbers.com—Cukier interviews with Bruce Nash, October 2011 and July 2012. [>] Brynjolfsson study—Erik Brynjolfsson, Lorin Hitt, and Heekyung Kim, “Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance?” working paper, April 2011 (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1819486). [>] On Rolls-Royce—See “Rolls-Royce: Britain’s Lonely High-Flier,” The Economist, January 8, 2009 (http://www.economist.com/node/12887368).


pages: 502 words: 107,657

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel

Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, butter production in bangladesh, call centre, Charles Lindbergh, commoditize, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil, en.wikipedia.org, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, job satisfaction, Johann Wolfgang von Goethe, lifelogging, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, mass immigration, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, Norbert Wiener, personalized medicine, placebo effect, prediction markets, Ray Kurzweil, recommendation engine, risk-adjusted returns, Ronald Coase, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, Shai Danziger, software as a service, speech recognition, statistical model, Steven Levy, text mining, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra, zero-sum game

Better yet, “I predict you will buy these button-fly jeans and this snazzy hat” is actionable, to a salesperson. Launching PA into action delivers a critical new edge in the competitive world of business. One sees massive commoditization taking place today, as the faces of corporations appear to blend together. They all seem to sell pretty much the same thing and act in pretty much the same ways. To stand above the crowd, where can a company turn? As Thomas Davenport and Jeanne Harris put it in Competing on Analytics: The New Science of Winning, “At a time when companies in many industries offer similar products and use comparable technology, high-performance business processes are among the last remaining points of differentiation.” Enter predictive analytics. Survey results have in fact shown that “a tougher competitive environment” is by far the strongest reason why organizations adopt this technology.

(Note that in this project a positive response actually entailed an opt-in and click, rather than just a click as with most online advertisements.) www.predictiveanalyticsworld.com/casestudy.php. To view Malcolm Gladwell’s entire speech, “Choice, Happiness and Spaghetti Sauce,” visit: Malcolm Gladwell, “Choice, Happiness and Spaghetti Sauce,” TEDTalks Online. www.ted.com/talks/malcolm_gladwell_on_spaghetti_sauce.html. Video file: www.ted.com/talks, February 2006. Davenport and Harris quote: Thomas Davenport and Jeanne Harris, Competing on Analytics: The New Science of Winning (Harvard Business School Press, 2007). “Survey results have in fact shown that a tougher competitive environment is by far the strongest reason organizations adopt this technology”: David White, “Predictive Analytics: The Right Tool for Tough Times,” Aberdeen Group White Paper, February 2010. www.aberdeen.com/aberdeen-library/6287/RA-predictive-analytics-customer-retention.aspx and www.targusinfo.com/files/PDF/outside_research/PredictiveAnalyticsReport.pdf.


pages: 181 words: 52,147

The Driver in the Driverless Car: How Our Technology Choices Will Create the Future by Vivek Wadhwa, Alex Salkever

23andMe, 3D printing, Airbnb, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, Bernie Sanders, bitcoin, blockchain, clean water, correlation does not imply causation, distributed ledger, Donald Trump, double helix, Elon Musk, en.wikipedia.org, epigenetics, Erik Brynjolfsson, Google bus, Hyperloop, income inequality, Internet of things, job automation, Kevin Kelly, Khan Academy, Kickstarter, Law of Accelerating Returns, license plate recognition, life extension, longitudinal study, Lyft, M-Pesa, Menlo Park, microbiome, mobile money, new economy, personalized medicine, phenotype, precision agriculture, RAND corporation, Ray Kurzweil, recommendation engine, Ronald Reagan, Second Machine Age, self-driving car, Silicon Valley, Skype, smart grid, stem cell, Stephen Hawking, Steve Wozniak, Stuxnet, supercomputer in your pocket, Tesla Model S, The Future of Employment, Thomas Davenport, Travis Kalanick, Turing test, Uber and Lyft, Uber for X, uber lyft, uranium enrichment, Watson beat the top human players on Jeopardy!, zero day

Symantec, for example, has a software product, Clearwell, that does legal discovery. Legal discovery is the laborious process of sifting through boxes of documents, reams of e-mails, and numerous other forms of information submitted to the court by litigants. Such tasks used to necessitate armies of junior associates. Clearwell does a far better job and has begun to obliterate an entire class of junior lawyers. As Thomas Davenport, a distinguished professor at Babson University, wrote in a column titled “Let’s Automate All the Lawyers,” in The Wall Street Journal: There are a variety of other intelligent systems that can take over other chunks of legal work. One system extracts key provisions from contracts. Another decides how likely your intellectual property case is to succeed. Others predict judicial decisions, recommend tax strategies, resolve matrimonial property disputes, and recommend sentences for capital crimes.


pages: 204 words: 58,565

Keeping Up With the Quants: Your Guide to Understanding and Using Analytics by Thomas H. Davenport, Jinho Kim

Black-Scholes formula, business intelligence, business process, call centre, computer age, correlation coefficient, correlation does not imply causation, Credit Default Swap, en.wikipedia.org, feminist movement, Florence Nightingale: pie chart, forensic accounting, global supply chain, Hans Rosling, hypertext link, invention of the telescope, inventory management, Jeff Bezos, Johannes Kepler, longitudinal study, margin call, Moneyball by Michael Lewis explains big data, Myron Scholes, Netflix Prize, p-value, performance metric, publish or perish, quantitative hedge fund, random walk, Renaissance Technologies, Robert Shiller, Robert Shiller, self-driving car, sentiment analysis, six sigma, Skype, statistical model, supply-chain management, text mining, the scientific method, Thomas Davenport

There are various types of analytics that serve different purposes for researchers: Statistics: The science of collection, organization, analysis, interpretation, and presentation of data Forecasting: The estimation of some variable of interest at some specified future point in time as a function of past data Data mining: The automatic or semiautomatic extraction of previously unknown, interesting patterns in large quantities of data through the use of computational algorithmic and statistical techniques Text mining: The process of deriving patterns and trends from text in a manner similar to data mining Optimization: The use of mathematical techniques to find optimal solutions with regard to some criteria while satisfying constraints Experimental design: The use of test and control groups, with random assignment of subjects or cases to each group, to elicit the cause and effect relationships in a particular outcome Although the list presents a range of analytics approaches in common use, it is unavoidable that considerable overlaps exist in the use of techniques across the types. For example, regression analysis, perhaps the most common technique in predictive analytics, is a popularly used technique in statistics, forecasting, and data mining. Also, time series analysis, a specific statistical technique for analyzing data that varies over time, is common to both statistics and forecasting. a. Thomas Davenport and Jeanne G. Harris, Competing on Analytics (Boston: Harvard Business School Press, 2007), 7. * * * The type of transactional data mentioned above for human resource decisions is structured (easily captured in rows and columns), quantitative, and in relatively small volumes (a terabyte or two even in large corporations). It’s a traditional environment for analytics, so let’s call it small data.


Big Data at Work: Dispelling the Myths, Uncovering the Opportunities by Thomas H. Davenport

Automated Insights, autonomous vehicles, bioinformatics, business intelligence, business process, call centre, chief data officer, cloud computing, commoditize, data acquisition, disruptive innovation, Edward Snowden, Erik Brynjolfsson, intermodal, Internet of things, Jeff Bezos, knowledge worker, lifelogging, Mark Zuckerberg, move fast and break things, move fast and break things, Narrative Science, natural language processing, Netflix Prize, New Journalism, recommendation engine, RFID, self-driving car, sentiment analysis, Silicon Valley, smart grid, smart meter, social graph, sorting algorithm, statistical model, Tesla Model S, text mining, Thomas Davenport

Becher, Chief Marketing Officer, SAP “Big Data at Work provides a terrific foundation for thoughtful planning to exploit the business opportunities created by diverse and vast sources of information. Davenport’s clear approach will enlighten managers about the need to carefully mine these resources to improve operations and products while driving new and competitive strategies.” — Gary L. Gottlieb, MD, MBA, President and CEO, Partners HealthCare System, Inc.; Professor of Psychiatry, Harvard Medical School “Thomas Davenport has supplied a smart, practical book for anyone looking to unlock the opportunities—and avoid the pitfalls—of big data.” —Rob Bearden, CEO, Hortonworks “Conversational, engaging, and an exceptional guide for decision making in the big data world. Big Data at Work offers insight to the business and technology components of a big data strategy, a path to success, and best practices from across industry sectors.”


pages: 252 words: 78,780

Lab Rats: How Silicon Valley Made Work Miserable for the Rest of Us by Dan Lyons

Airbnb, Amazon Web Services, Apple II, augmented reality, autonomous vehicles, basic income, bitcoin, blockchain, business process, call centre, Clayton Christensen, clean water, collective bargaining, corporate governance, corporate social responsibility, creative destruction, cryptocurrency, David Heinemeier Hansson, Donald Trump, Elon Musk, Ethereum, ethereum blockchain, full employment, future of work, gig economy, Gordon Gekko, greed is good, hiring and firing, housing crisis, income inequality, informal economy, Jeff Bezos, job automation, job satisfaction, job-hopping, John Gruber, Joseph Schumpeter, Kevin Kelly, knowledge worker, Lean Startup, loose coupling, Lyft, Marc Andreessen, Mark Zuckerberg, McMansion, Menlo Park, Milgram experiment, minimum viable product, Mitch Kapor, move fast and break things, move fast and break things, new economy, Panopticon Jeremy Bentham, Paul Graham, paypal mafia, Peter Thiel, plutocrats, Plutocrats, precariat, RAND corporation, remote working, RFID, ride hailing / ride sharing, Ronald Reagan, Rubik’s Cube, Ruby on Rails, Sam Altman, Sand Hill Road, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, Skype, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, Stanford prison experiment, stem cell, Steve Jobs, Steve Wozniak, Stewart Brand, TaskRabbit, telemarketer, Tesla Model S, Thomas Davenport, Tony Hsieh, Toyota Production System, traveling salesman, Travis Kalanick, tulip mania, Uber and Lyft, Uber for X, uber lyft, universal basic income, web application, Whole Earth Catalog, Y Combinator, young professional

During the early days of the personal computer and then the dawn of the Internet, a lot of people believed the growing use of technology would be good for workers. Technology would empower us and give us more autonomy and freedom. It could democratize the workplace and give rank-and-file workers a greater voice in how the company was run. But some started to worry—including some who had invented the new ways of working. In the 1990s Babson College business professor Thomas Davenport helped create something called business process reengineering. This was a strategy for using computer technology to restructure organizations. It was supposed to be a good thing, but when corporations embraced “reengineering,” they just used it as an excuse to fire lots of people. Davenport, who was seen as the father of reengineering, was appalled. He decried the mass firings as “mindless bloodshed” carried out by managers who “treated the people inside companies as if they were just so many bits and bytes.”


pages: 286 words: 95,372

The Fields Beneath: The History of One London Village by Gillian Tindall

ghettoisation, Jane Jacobs, means of production, New Urbanism, profit motive, Right to Buy, The Death and Life of Great American Cities, Thomas Davenport, urban sprawl

About 1780 its landlord, Thomas Wood, was advertising: A good trap-ball ground, skittle ground, pleasant summer house, extensive gardens, and every accomodation for the convenience of those who may think it proper to make an excursion to the above house during the summer months … A good ordinary on Sundays at two o’clock. Several years later Wood was still advertising his ‘larder’ in glowing terms, but appending this advertisement to a public protestation of his innocence in a recent court case. In 1785 a Sir Thomas Davenport, who had suffered a highway robbery near the Assembly House, accused Wood of having been the highwayman, on the identification evidence of his coachman. Wood was arrested, remanded in gaol tried but eventually acquitted, and two other men were hanged in his stead. However Davenport was apparently so convinced that the true villain had escaped him that he continued what amounted to a persecution campaign against Wood, who is said to have ‘died raving mad’ (in 1787) as a result of it.


pages: 336 words: 92,056

The Battery: How Portable Power Sparked a Technological Revolution by Henry Schlesinger

Albert Einstein, animal electricity, Any sufficiently advanced technology is indistinguishable from magic, British Empire, Copley Medal, Fellow of the Royal Society, index card, invention of the telegraph, invisible hand, Isaac Newton, James Watt: steam engine, Livingstone, I presume, Menlo Park, Metcalfe’s law, popular electronics, Ralph Waldo Emerson, RFID, Robert Metcalfe, Stephen Hawking, Thales of Miletus, the scientific method, Thomas Davenport, transcontinental railway, Upton Sinclair, Vannevar Bush, Yogi Berra

Yet for nine years Congress squabbled over just what “…for the increase and diffusion of knowledge among men” really meant, maneuvering politically and consulting with the best minds they could find, including Faraday and Henry. John Quincy Adams wanted the money to go to an observatory while others argued for a national library or a college. In the end, Congress decided on a library, museum, and art gallery. Henry proved instrumental in laying the foundation of the Smithsonian, ensuring that it would endure. LONG BEFORE HENRY ARRIVED AT the Smithsonian, his work caught the attention of Thomas Davenport, a blacksmith from Brandon, Vermont. Born in 1802 into modest circumstances, Davenport was apprenticed at an early age. The apprenticeship apparently “took,” since he went into the trade and by most accounts made a good living. However, he also maintained a lifelong habit of reading and self-improvement, supplementing his spotty education, which included just three years of formal schooling.


pages: 372 words: 94,153

More From Less: The Surprising Story of How We Learned to Prosper Using Fewer Resources – and What Happens Next by Andrew McAfee

back-to-the-land, Bartolomé de las Casas, Berlin Wall, bitcoin, Branko Milanovic, British Empire, Buckminster Fuller, call centre, carbon footprint, clean water, cleantech, cloud computing, Corn Laws, creative destruction, crony capitalism, David Ricardo: comparative advantage, decarbonisation, dematerialisation, Deng Xiaoping, Donald Trump, Edward Glaeser, en.wikipedia.org, energy transition, Erik Brynjolfsson, failed state, Fall of the Berlin Wall, Haber-Bosch Process, Hans Rosling, humanitarian revolution, hydraulic fracturing, income inequality, indoor plumbing, intangible asset, James Watt: steam engine, Jeff Bezos, job automation, John Snow's cholera map, joint-stock company, Joseph Schumpeter, Khan Academy, Landlord’s Game, Louis Pasteur, Lyft, Marc Andreessen, market fundamentalism, means of production, Mikhail Gorbachev, oil shale / tar sands, Paul Samuelson, peak oil, precision agriculture, profit maximization, profit motive, risk tolerance, road to serfdom, Ronald Coase, Ronald Reagan, Scramble for Africa, Second Machine Age, Silicon Valley, Steve Jobs, Steven Pinker, Stewart Brand, telepresence, The Wealth of Nations by Adam Smith, Thomas Davenport, Thomas Malthus, Thorstein Veblen, total factor productivity, Uber and Lyft, uber lyft, Veblen good, War on Poverty, Whole Earth Catalog, World Values Survey

In 1885, Daimler and his colleague Wilhelm Maybach demonstrated their Petroleum Reitwagen, a clunky motorcycle-like machine that was the world’s first vehicle powered by internal combustion. There would be many more of them, more than a few built by the company that became Daimler-Benz, the home of Mercedes. Electric power started small, got big, then shrank again. In 1837 the Vermont blacksmith and tinkerer Thomas Davenport received a US patent for an “Improvement in Propelling Machinery by Magnetism and Electro-Magnetism.” We now call such devices for propelling machinery motors. Unfortunately for Davenport, the batteries of his time were too primitive to supply the electrical energy his device needed, and power lines, utilities, and the grid did not yet exist. Davenport was apparently bankrupt when he died in 1851.


The Future of Money by Bernard Lietaer

agricultural Revolution, banks create money, barriers to entry, Bretton Woods, business cycle, clean water, complexity theory, corporate raider, dematerialisation, discounted cash flows, diversification, fiat currency, financial deregulation, financial innovation, floating exchange rates, full employment, George Gilder, German hyperinflation, global reserve currency, Golden Gate Park, Howard Rheingold, informal economy, invention of the telephone, invention of writing, Lao Tzu, Mahatma Gandhi, means of production, microcredit, money: store of value / unit of account / medium of exchange, Norbert Wiener, North Sea oil, offshore financial centre, pattern recognition, post-industrial society, price stability, reserve currency, Ronald Reagan, seigniorage, Silicon Valley, South Sea Bubble, The Future of Employment, the market place, the payments system, Thomas Davenport, trade route, transaction costs, trickle-down economics, working poor

However, all computer applications were really being built around the existing organisational structure and management procedures. One day someone thought to reverse the process by asking the simple question: 'how should we organise ourselves to best take advantage of the available information technologies. Re-engineering was born. So were 'strategic layoffs'. In all fairness, such layoffs were not the intent of the original re- engineering inventors. One of the earlier pioneers was Thomas Davenport, research VP at CSC Index (the 'home' of re-engineering). In an article in First Company, Davenport reported that: 'Re-engineering did not start out as a code word for mindless corporate bloodletting. It wasn't supposed to be the last gasp of Industrial Age management. I know because I was there at the beginning. I was one of the creators ... But the fact is, once out of the bottle, the re-engineering genie quickly turned Ugly.'


pages: 1,073 words: 314,528

Strategy: A History by Lawrence Freedman

Albert Einstein, anti-communist, Anton Chekhov, Ayatollah Khomeini, barriers to entry, battle of ideas, Black Swan, British Empire, business process, butterfly effect, centre right, Charles Lindbergh, circulation of elites, cognitive dissonance, coherent worldview, collective bargaining, complexity theory, conceptual framework, corporate raider, correlation does not imply causation, creative destruction, cuban missile crisis, Daniel Kahneman / Amos Tversky, defense in depth, desegregation, Edward Lorenz: Chaos theory, en.wikipedia.org, endogenous growth, endowment effect, Ford paid five dollars a day, framing effect, Frederick Winslow Taylor, Gordon Gekko, greed is good, information retrieval, interchangeable parts, invisible hand, John Nash: game theory, John von Neumann, Kenneth Arrow, lateral thinking, linear programming, loose coupling, loss aversion, Mahatma Gandhi, means of production, mental accounting, Murray Gell-Mann, mutually assured destruction, Nash equilibrium, Nelson Mandela, Norbert Wiener, Norman Mailer, oil shock, Pareto efficiency, performance metric, Philip Mirowski, prisoner's dilemma, profit maximization, race to the bottom, Ralph Nader, RAND corporation, Richard Thaler, road to serfdom, Ronald Reagan, Rosa Parks, shareholder value, social intelligence, Steven Pinker, strikebreaker, The Chicago School, The Myth of the Rational Market, the scientific method, theory of mind, Thomas Davenport, Thomas Kuhn: the structure of scientific revolutions, Torches of Freedom, Toyota Production System, transaction costs, ultimatum game, unemployed young men, Upton Sinclair, urban sprawl, Vilfredo Pareto, War on Poverty, women in the workforce, Yogi Berra, zero-sum game

This one is about an access of freedom. Slowly, or suddenly, corporate managers all over the world are learning that free enterprise these days really is free.”26 Speaking of the virtues of “radical change,” Champy described to managers the “secret satisfaction” of learning to do “what other managers in your industry thought to be impossible.” They would not only “thrive” but would also “literally redefine the industry.”27 Thomas Davenport, who had been director of research at the Boston-based Index Group, which was eventually turned into the CSC Index, was one of those closely associated with the development of the original concept. He later described how a “modest idea had become a monster” as it created a “Reengineering Industrial Complex.” This was an “iron triangle of powerful interest groups: top managers at big companies, big-time management consultants, and big-league information technology vendors.”

Michael Hammer and James Champy, Reengineering the Corporation: A Manifesto for Business Revolution (London: HarperBusiness, 1993), 49. 18. Peter Case, “Remember Re-Engineering? The Rhetorical Appeal of a Managerial Salvation Device,” Journal of Management Studies 35, no. 4 (July 1991): 419–441. 19. Michael Hammer, “Reengineering Work: Don’t Automate, Obliterate,” Harvard Business Review, July/August 1990, 104. 20. Thomas Davenport and James Short, “The New Industrial Engineering: Information Technology and Business Process Redesign,” Sloan Management Review, Summer 1990; Keith Grint, “Reengineering History: Social Resonances and Business Process Reengineering,” Organization 1, no. 1 (1994): 179–201; Keith Grint and P. Case, “The Violent Rhetoric of Re-Engineering: Management Consultancy on the Offensive,” Journal of Management Studies 6, no. 5 (1998): 557–577. 21.


pages: 460 words: 131,579

Masters of Management: How the Business Gurus and Their Ideas Have Changed the World—for Better and for Worse by Adrian Wooldridge

affirmative action, barriers to entry, Black Swan, blood diamonds, borderless world, business climate, business cycle, business intelligence, business process, carbon footprint, Cass Sunstein, Clayton Christensen, cloud computing, collaborative consumption, collapse of Lehman Brothers, collateralized debt obligation, commoditize, corporate governance, corporate social responsibility, creative destruction, credit crunch, crowdsourcing, David Brooks, David Ricardo: comparative advantage, disintermediation, disruptive innovation, don't be evil, Donald Trump, Edward Glaeser, Exxon Valdez, financial deregulation, Frederick Winslow Taylor, future of work, George Gilder, global supply chain, industrial cluster, intangible asset, job satisfaction, job-hopping, joint-stock company, Joseph Schumpeter, Just-in-time delivery, Kickstarter, knowledge economy, knowledge worker, lake wobegon effect, Long Term Capital Management, low skilled workers, Mark Zuckerberg, McMansion, means of production, Menlo Park, mobile money, Naomi Klein, Netflix Prize, Network effects, new economy, Nick Leeson, Norman Macrae, patent troll, Ponzi scheme, popular capitalism, post-industrial society, profit motive, purchasing power parity, Ralph Nader, recommendation engine, Richard Florida, Richard Thaler, risk tolerance, Ronald Reagan, science of happiness, shareholder value, Silicon Valley, Silicon Valley startup, Skype, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, Steven Levy, supply-chain management, technoutopianism, The Wealth of Nations by Adam Smith, Thomas Davenport, Tony Hsieh, too big to fail, wealth creators, women in the workforce, young professional, Zipcar

Collins lives an ascetic life in Boulder, Colorado, where he has a private management “laboratory” staffed by five assistants and spends as much time as he can spare climbing mountains.1 But even these professional gurus were conceived in the womb of the management theory industry. Covey has an MBA from Harvard Business School and a PhD in business studies; Collins started his life as a professor at Stanford Business School. However, since the turn of the century we have seen a striking new development in the world of business gurus: the rise of a subspecies of guru who have no background in either business schools or consultancies. In 2008, Thomas Davenport, a management professor at Babson College, compiled a list of the world’s most influential management thinkers for the Wall Street Journal on the basis of Google hits, media mentions, and academic citations. Only one member of the top five was a certified management guru with a PhD in business and a perch in a business school: Gary Hamel (who was ranked number one). The other four were journalists (Thomas Friedman and Malcolm Gladwell), a retired CEO (Bill Gates), and an academic from a department of education rather than business (Howard Gardner).2 Bill Gates’s position on the list is hardly surprising: he is arguably the world’s most thoughtful businessman as well as one of its most successful entrepreneurs.


pages: 511 words: 132,682

Competition Overdose: How Free Market Mythology Transformed Us From Citizen Kings to Market Servants by Maurice E. Stucke, Ariel Ezrachi

affirmative action, Airbnb, Albert Einstein, Andrei Shleifer, Bernie Sanders, Boeing 737 MAX, Cass Sunstein, choice architecture, cloud computing, commoditize, corporate governance, Corrections Corporation of America, Credit Default Swap, crony capitalism, delayed gratification, Donald Trump, en.wikipedia.org, George Akerlof, gig economy, Goldman Sachs: Vampire Squid, Google Chrome, greed is good, hedonic treadmill, income inequality, income per capita, information asymmetry, invisible hand, job satisfaction, labor-force participation, late fees, loss aversion, low skilled workers, Lyft, mandatory minimum, Mark Zuckerberg, market fundamentalism, mass incarceration, Menlo Park, meta analysis, meta-analysis, Milgram experiment, mortgage debt, Network effects, out of africa, payday loans, Ponzi scheme, precariat, price anchoring, price discrimination, profit maximization, profit motive, race to the bottom, Richard Thaler, ride hailing / ride sharing, Robert Bork, Robert Shiller, Robert Shiller, Ronald Reagan, shareholder value, Shoshana Zuboff, Silicon Valley, Snapchat, Social Responsibility of Business Is to Increase Its Profits, Stanford prison experiment, Stephen Hawking, The Chicago School, The Market for Lemons, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, Thomas Davenport, Thorstein Veblen, Tim Cook: Apple, too big to fail, transaction costs, Uber and Lyft, uber lyft, ultimatum game, Vanguard fund, winner-take-all economy

Otherwise, as Smith noted, “You don’t have to be a rocket scientist to figure out that the junior analyst sitting quietly in the corner of the room hearing about ‘muppets,’ ‘ripping eyeballs out’ and ‘getting paid’ doesn’t exactly turn into a model citizen.” Ethical concerns have continued to overshadow Goldman Sachs and other financial institutions.42 Such a corporate culture is toxic not only to the “muppets,” but ultimately to the company itself. Compare, for example, Goldman Sachs and Vanguard Group Inc., whose business culture the business professor Thomas Davenport found from his research represents the “anti-Goldman Sachs.” Whereas Goldman’s managing directors refer to their clients as “muppets,” Vanguard does the opposite: “People there are constantly reminding themselves that the idea is to help clients make better investment decisions at the lowest possible cost.”43 Whereas Goldman people “care only about making money,” Vanguard people “don’t seem hung up on the fact that people in other firms are more highly compensated on average; they seem to find it rewarding to know they’ve done the right thing for their customers.


pages: 807 words: 154,435

Radical Uncertainty: Decision-Making for an Unknowable Future by Mervyn King, John Kay

"Robert Solow", Airbus A320, Albert Einstein, Albert Michelson, algorithmic trading, Antoine Gombaud: Chevalier de Méré, Arthur Eddington, autonomous vehicles, availability heuristic, banking crisis, Barry Marshall: ulcers, battle of ideas, Benoit Mandelbrot, bitcoin, Black Swan, Bonfire of the Vanities, Brownian motion, business cycle, business process, capital asset pricing model, central bank independence, collapse of Lehman Brothers, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, demographic transition, discounted cash flows, disruptive innovation, diversification, diversified portfolio, Donald Trump, easy for humans, difficult for computers, Edmond Halley, Edward Lloyd's coffeehouse, Edward Thorp, Elon Musk, Ethereum, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, fear of failure, feminist movement, financial deregulation, George Akerlof, germ theory of disease, Hans Rosling, Ignaz Semmelweis: hand washing, income per capita, incomplete markets, inflation targeting, information asymmetry, invention of the wheel, invisible hand, Jeff Bezos, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Snow's cholera map, John von Neumann, Kenneth Arrow, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, market bubble, market fundamentalism, Moneyball by Michael Lewis explains big data, Nash equilibrium, Nate Silver, new economy, Nick Leeson, Northern Rock, oil shock, Paul Samuelson, peak oil, Peter Thiel, Philip Mirowski, Pierre-Simon Laplace, popular electronics, price mechanism, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, railway mania, RAND corporation, rent-seeking, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Shiller, Ronald Coase, sealed-bid auction, shareholder value, Silicon Valley, Simon Kuznets, Socratic dialogue, South Sea Bubble, spectrum auction, Steve Ballmer, Steve Jobs, Steve Wozniak, Tacoma Narrows Bridge, Thales and the olive presses, Thales of Miletus, The Chicago School, the map is not the territory, The Market for Lemons, The Nature of the Firm, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Thomas Malthus, Toyota Production System, transaction costs, ultimatum game, urban planning, value at risk, World Values Survey, Yom Kippur War, zero-sum game

As Obama in a different context would find later in his meeting in the Oval Office, the expressions of probabilities within NASA disguised uncertainty rather than resolved it. Feynman’s excoriation of NASA’s bureaucracy provides an unmatched account of the misuse of pseudoscience to rationalise administrative decisions made in the face of radical uncertainty. This misuse of models was common to analysing spacecraft in Houston, fish stocks in Newfoundland, trams in Edinburgh and migration in Europe. Sadly, the misuse is widespread and continues. Thomas Davenport and Brook Manville constructed a series of case studies on how good decisions had been made in large organisations. 24 They begin with an analysis of how in 2009 NASA, chastened by the Challenger disaster, first postponed the launch of space shuttle STS-119 and then successfully executed it. They stress features of the agency’s revised procedures: commitment to tracking small failures, ability to recognise and understand complex issues, real attention to front-line workers, the ability to learn from and rebound from errors, and the ability to improvise effective response to crisis . . . the overarching culture was one of open exchange, honouring of diverse opinions, and the embrace of the right to dissent.


Smart Grid Standards by Takuro Sato

business cycle, business process, carbon footprint, clean water, cloud computing, data acquisition, decarbonisation, demand response, distributed generation, energy security, factory automation, information retrieval, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Iridium satellite, iterative process, knowledge economy, life extension, linear programming, low earth orbit, market design, MITM: man-in-the-middle, off grid, oil shale / tar sands, packet switching, performance metric, RFC: Request For Comment, RFID, smart cities, smart grid, smart meter, smart transportation, Thomas Davenport

The organization of this subsection is as follows: Section 4.4.2 gives an introduction of the history of the PEV and issues related to vehicle deployment; Section 4.4.3 introduces the various types of EVs; Section 4.4.4 introduces various kinds of EV batteries; Section 4.4.5 introduces the issues related to the integration of EVs with electric grid. Section 4.4.6 introduces the standardization projects and efforts of various international/national SDOs. 4.4.2 The Rise and Fall of Electric Vehicles Several inventers are being credited as the first EV inventors. In 1828, Hungarian engineer, Ányos Jedlik, invented the EV model car. Between 1834 and 1835, Thomas Davenport, an American inventor, built a battery-powered EV, a small locomotive that was operated on a short section of tracks. Other electric car inventors around this early period include Robert Anderson of Scotland and Sibrandus Stratingh of the Netherlands. By the twentieth century, EVs were commonplace and took the majority of the market. At that time, the light, powerful Internal Combustion Engines (ICEs) had not been developed yet.


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WTF?: What's the Future and Why It's Up to Us by Tim O'Reilly

4chan, Affordable Care Act / Obamacare, Airbnb, Alvin Roth, Amazon Mechanical Turk, Amazon Web Services, artificial general intelligence, augmented reality, autonomous vehicles, barriers to entry, basic income, Bernie Madoff, Bernie Sanders, Bill Joy: nanobots, bitcoin, blockchain, Bretton Woods, Brewster Kahle, British Empire, business process, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, Chuck Templeton: OpenTable:, Clayton Christensen, clean water, cloud computing, cognitive dissonance, collateralized debt obligation, commoditize, computer vision, corporate governance, corporate raider, creative destruction, crowdsourcing, Danny Hillis, data acquisition, deskilling, DevOps, Donald Davies, Donald Trump, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, Filter Bubble, Firefox, Flash crash, full employment, future of work, George Akerlof, gig economy, glass ceiling, Google Glasses, Gordon Gekko, gravity well, greed is good, Guido van Rossum, High speed trading, hiring and firing, Home mortgage interest deduction, Hyperloop, income inequality, index fund, informal economy, information asymmetry, Internet Archive, Internet of things, invention of movable type, invisible hand, iterative process, Jaron Lanier, Jeff Bezos, jitney, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, Kevin Kelly, Khan Academy, Kickstarter, knowledge worker, Kodak vs Instagram, Lao Tzu, Larry Wall, Lean Startup, Leonard Kleinrock, Lyft, Marc Andreessen, Mark Zuckerberg, market fundamentalism, Marshall McLuhan, McMansion, microbiome, microservices, minimum viable product, mortgage tax deduction, move fast and break things, move fast and break things, Network effects, new economy, Nicholas Carr, obamacare, Oculus Rift, packet switching, PageRank, pattern recognition, Paul Buchheit, peer-to-peer, peer-to-peer model, Ponzi scheme, race to the bottom, Ralph Nader, randomized controlled trial, RFC: Request For Comment, Richard Feynman, Richard Stallman, ride hailing / ride sharing, Robert Gordon, Robert Metcalfe, Ronald Coase, Sam Altman, school choice, Second Machine Age, secular stagnation, self-driving car, SETI@home, shareholder value, Silicon Valley, Silicon Valley startup, skunkworks, Skype, smart contracts, Snapchat, Social Responsibility of Business Is to Increase Its Profits, social web, software as a service, software patent, spectrum auction, speech recognition, Stephen Hawking, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, strong AI, TaskRabbit, telepresence, the built environment, The Future of Employment, the map is not the territory, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Davenport, transaction costs, transcontinental railway, transportation-network company, Travis Kalanick, trickle-down economics, Uber and Lyft, Uber for X, uber lyft, ubercab, universal basic income, US Airways Flight 1549, VA Linux, Watson beat the top human players on Jeopardy!, We are the 99%, web application, Whole Earth Catalog, winner-take-all economy, women in the workforce, Y Combinator, yellow journalism, zero-sum game, Zipcar

CHAPTER 8: MANAGING A WORKFORCE OF DJINNS 155 breakthroughs and business processes: Steve Lohr, “The Origins of ‘Big Data’: An Etymological Detective Story,” New York Times, February 1, 2013, https://bits.blogs.nytimes.com/2013/02/01/the-origins-of-big-data-an-etymological-detective-story/. 155 speech recognition and machine translation: Alon Halevy, Peter Norvig, and Fernando Pereira, “The Unreasonable Effectiveness of Data,” IEEE Intelligent Systems, 1541–1672/09, retrieved March 31, 2017, https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/35179.pdf. 156 “the sexiest job of the 21st century”: Thomas Davenport and D. J. Patil, “Data Scientist: The Sexiest Job of the 21st Century,” Harvard Business Review, October 2012, https://hbr.org/2012/10/data-scientist-the-sexiest-job-of-the-21st-century. Hal Varian had used this same phrase about statistics in 2009. See “Hal Varian on How the Web Challenges Managers,” McKinsey & Company, January 2009, http://www.mckinsey.com/industries/high-tech/our-insights/hal-varian-on-how-the-web-challenges-managers. 157 “the right values for these parameters is something of a black art”: Sergey Brin and Larry Page, “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” Stanford University, retrieved March 31, 2017, http://infolab.stanford. edu/~backrub/google.html. 158 as many as 50,000 subsignals: Danny Sullivan, “FAQ: All About the Google RankBrain Algorithm,” Search Engine Land, June 23, 2016, http://searchengine land.com/faq-all-about-the-new-google-rankbrain-algorithm-234440. 158 “new synapses for the global brain”: Tim O’Reilly, “Freebase Will Prove Addictive,” O’Reilly Radar, March 8, 2007, http://radar.oreilly.com/2007/03/free base-will-prove-addictive.html. 158 “10 experiments for every successful launch”: Matt McGee, “BusinessWeek Dives Deep into Google’s Search Quality,” Search Engine Land, October 6, 2009, http://searchengineland.com/businessweek-dives-deep-into-googles-search-quality-27317. 159 the manual that they provide: Search Quality Evaluator Guide, Google, March 14, 2017, http://static.googleusercontent.com/media/www.google.com/en//inside search/howsearchworks/assets/search qualityevaluatorguidelines.pdf. 160 “Another big difference”: Brin and Page, “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” Section 3.2.


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The Meritocracy Trap: How America's Foundational Myth Feeds Inequality, Dismantles the Middle Class, and Devours the Elite by Daniel Markovits

"Robert Solow", 8-hour work day, activist fund / activist shareholder / activist investor, affirmative action, Anton Chekhov, asset-backed security, assortative mating, basic income, Bernie Sanders, big-box store, business cycle, capital asset pricing model, Capital in the Twenty-First Century by Thomas Piketty, carried interest, collateralized debt obligation, collective bargaining, computer age, corporate governance, corporate raider, crony capitalism, David Brooks, deskilling, Detroit bankruptcy, disruptive innovation, Donald Trump, Edward Glaeser, Emanuel Derman, equity premium, European colonialism, everywhere but in the productivity statistics, fear of failure, financial innovation, financial intermediation, fixed income, Ford paid five dollars a day, Frederick Winslow Taylor, full employment, future of work, gender pay gap, George Akerlof, Gini coefficient, glass ceiling, helicopter parent, high net worth, hiring and firing, income inequality, industrial robot, interchangeable parts, invention of agriculture, Jaron Lanier, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, knowledge economy, knowledge worker, Kodak vs Instagram, labor-force participation, longitudinal study, low skilled workers, manufacturing employment, Mark Zuckerberg, Martin Wolf, mass incarceration, medical residency, minimum wage unemployment, Myron Scholes, Nate Silver, New Economic Geography, new economy, offshore financial centre, Paul Samuelson, payday loans, plutocrats, Plutocrats, Plutonomy: Buying Luxury, Explaining Global Imbalances, precariat, purchasing power parity, rent-seeking, Richard Florida, Robert Gordon, Robert Shiller, Robert Shiller, Ronald Reagan, savings glut, school choice, shareholder value, Silicon Valley, Simon Kuznets, six sigma, Skype, stakhanovite, stem cell, Steve Jobs, supply-chain management, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, Thomas Davenport, Thorstein Veblen, too big to fail, total factor productivity, transaction costs, traveling salesman, universal basic income, unpaid internship, Vanguard fund, War on Poverty, Winter of Discontent, women in the workforce, working poor, young professional, zero-sum game

“silver-haired industry experience”: Kiechel, The Lords of Strategy, 9. “break an organization down”: John Micklethwait and Adrian Wooldridge, The Witch Doctors: Making Sense of the Management Gurus (New York: Random House, 1996), 26. Hereafter cited as Micklethwait and Wooldridge, The Witch Doctors. responsible for their downsizings: See Micklethwait and Wooldridge, The Witch Doctors, 29–31; Thomas Davenport, “The Fad That Forgot People,” Fast Company, October 31, 1995, accessed November 19, 2018, www.fastcompany.com/26310/fad-forgot-people. “Overhead Value Analysis”: Terrence Deal and Allan A. Kennedy, The New Corporate Cultures (New York: Perseus, 1999), 64. excessive embrace of middle management: McKinsey argued that the midcentury approach had allowed “the number of nonproduction employees in manufacturing industry, for example, [to] increase six times as fast as that of production workers [between 1950 and 1970].”