The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies (16 page)

In contrast to leisure, where more time is a good thing, value at work is created by saving time. Hal Varian, the chief economist at Google, looked specifically at time savings gained from Google searches.
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He and his team gathered a random sample of Google queries, such as: “In making cookies, does the use of butter or margarine affect the size of the cookie?” The team then did their best job to answer the questions without using Google—by looking answers up in the library, for instance. On average it took about twenty-two minutes to answer a query without Google (not counting travel time to the library!) but only seven minutes to answer the same query with Google. Google saved an average of fifteen minutes per query. When you multiply that time difference out across all the queries that the average American makes using the average hourly wage of Americans ($22), that works out to about $500 per adult worker per year.

As anyone who has been caught up in the pleasures of surfing the Web (perhaps while ‘doing research’ for a book) can attest, though, the strict distinction between work and play or input and output that economists make is not always so clear. The billions of hours that people spend uploading, tagging, and commenting on photos on social media sites like Facebook unquestionably creates value for their friends, family, and even strangers. Yet at the same time these hours are uncompensated, so presumably the people doing this ‘work’ find it more intrinsically rewarding than the next best use of their time. To get a sense on the scale of this effort, consider that last year users collectively spent about 200 million hours each day just on Facebook, much of it creating content for other users to consume.
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That’s ten times as many person-hours as were needed to build the entire Panama Canal.
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None of this is counted in our GDP statistics as either input or output, but these kinds of zero-wage and zero-price activities still contribute to welfare. Researchers like Luis von Ahn at Carnegie Mellon are working on ways of motivating and organizing millions of people to create value via collective projects on the Internet.
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New Goods and Services

In the early days of the 1990s Internet boom, venture capitalists used to joke that there were only two numbers in the new economy: infinity and zero. Certainly, a big part of the value in the new economy has come from the reduction in the price of many goods to zero. But what about the other end of that spectrum, price drops from infinity down to some finite number? Suppose Warner Bros. makes a new movie and you can watch it for nine dollars. Has your welfare increased? Before the movie was conceived, cast, filmed, and distributed, you couldn’t buy it at any price, even infinity. In a sense, paying just nine bucks is a pretty large price reduction from infinity, or whatever the maximum price was that you would have been willing to pay. Similarly, we now have access to all sorts of new services that never existed before, some of which we saw in earlier chapters. Much of the increase in our welfare over the past century comes not just from making existing goods more cheaply but from expanding the range of goods and services available.

Seventy-seven percent of software companies report the introduction of new products each year, and Internet retailing has vastly expanded the set of goods available to most consumers.
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With a few clicks, over two million books can be found and purchased at Amazon.com. By contrast, the typical physical bookstore has about 40,000 titles and even the largest Barnes & Noble store in New York City stocks only 250,000 titles. As documented in a research paper that Erik wrote with Michael Smith and Jeffrey Hu, there have been similar increases in the online selection for other categories such as videos, music, electronics, and collectibles. Every time a new product is made available, it increases consumer surplus.

One way to think of the value created is to imagine that the new product always existed, but only at such a high price that no one could buy it. Making it available is like lowering the price to a more reasonable level. There have even been substantial increases in the number of stock keeping units (SKUs) in most physical stores as computerized inventory management systems, supply chains, and manufacturing have become more efficient and flexible. For the overall economy, the official GDP numbers miss the value of new goods and services added to the tune of about 0.4 percent of additional growth each year, according to economist Robert Gordon.
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Remember that productivity growth has been in the neighborhood of 2 percent per year for most of the past century, so contribution of new goods is not a trivial portion.

Reputations and Recommendations

Digitization also brings a related but subtler benefit to the vast array of goods and services that already exist in the economy. Lower search and transaction costs mean faster and easier access and increased efficiency and convenience. For example, the rating site Yelp collects millions of customer reviews to help diners find nearby restaurants in the quality and price ranges they seek, even when they are visiting new cities. The reservation service OpenTable then lets them book a table with just a few mouse clicks.

In aggregate, digital tools like these make a large difference. In the past, ignorance protected inefficient or lower-quality sellers from being unmasked by unsuspecting consumers, while geography limited competition from other sellers. With the introduction of structured comparison sites like FindTheBest.com and Kayak, airline travel, banking, insurance, car sales, motion pictures, and many other industries are being transformed by consumers’ ability to search for and compare competing sellers. No longer can a seller of substandard services expect to feed on a continuing stream of naïve or ill-informed consumers. No longer can the seller expect to be insulated from competitors in other locations who can deliver a better service for less. Research by Michael Luca of Harvard Business School has found that the increased transparency has helped smaller independent restaurants compete with bigger chains because customers can more quickly find quality food via rating services like Yelp, reducing their reliance on brand names’ expensive marketing campaigns.
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The intangible benefits delivered by the growing sharing economy—better matches, timeliness, customer service, and increased convenience—are exactly the types of benefits identified by the 1996 Boskin Commission as being poorly measured in our official price and GDP statistics.
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This is another way in which our true growth is greater than the standard data suggest.

Intangible Assets

Just as free goods rather than physical products are an increasingly important share of consumption, intangibles also make up a growing share of the economy’s capital assets. Production in the second machine age depends less on physical equipment and structures and more on the four categories of intangible assets: intellectual property, organizational capital, user-generated content, and human capital.

Intellectual property includes patents and copyrights. The rate of patenting by American inventors has been increasing rapidly since the 1980s,
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and other types of intellectual assets have also grown.
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In addition, a lot of research and development (R&D) is never formalized as intellectual property but is still very valuable.

The second—and even larger—category of intangibles is organizational capital like new business processes, techniques of production, organizational forms, and business models. Effective uses of the new technologies of the second machine age almost invariably require changes in the organization of work. For instance, when companies spend millions of dollars on computer hardware and software for a new enterprise resource planning system, they typically also include process changes that are three to five times as costly as the original investments in hardware and software. Yet, while the hardware and software spending generally shows up as additions to the nation’s capital stock, the new business processes, which often outlast the hardware, are generally not counted as capital. Our research suggests that a correct accounting for computer-related intangible assets would add over $2 trillion to the official estimates of the capital assets in the United States economy.
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User-generated content is a smaller but rapidly growing third category of intangible assets. Users of Facebook, YouTube, Twitter, Instagram, Pinterest, and other types of online content not only consume this free content and gain the consumer surplus discussed above but also produce most of the content. There are 43,200 hours of new YouTube videos created each day,
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as well as 250 million new photos uploaded each day on Facebook.
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Users also contribute valuable but unmeasured content in the form of reviews on sites like Amazon, TripAdvisor, and Yelp. In addition, user-generated content includes the simple binary information used to sort reviews and present the best content first (e.g., when Amazon asks “Was this review helpful to you?”). Hardware and software companies now compete to improve the productivity of user-generated content activities. For example, smartphones and apps for smartphones now include easy or automatic tools for posting photos on Facebook. This content has value to other users and can be thought of as yet another type of intangible capital asset that is being added to our collective wealth.

The fourth and biggest category is the value of human capital. The many years that we all spend in schools learning skills like reading, writing, and arithmetic—as well as the additional learning that happens on the job and on our own—makes us more productive and, in some cases, is intrinsically rewarding. It is also a contribution to the nation’s capital stock. According to Dale Jorgenson and Barbara Fraumeni, the value of human capital in the United States is five to ten times larger than the value of all the physical capital in the United States.
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Human capital has not always been this important to the economy. The great economist Adam Smith understood that one of the great drawbacks of the first machine age was the way it forced workers to do repetitive tasks. In 1776, he noted, “The man whose whole life is spent in performing a few simple operations, of which the effects are perhaps always the same, or very nearly the same, has no occasion to exert his understanding.”
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As we’ll discuss further later in the book, investments in human capital will be increasingly important as routine tasks become automated and the need for human creativity increases.

Important as these intangible assets are, the official GDP ignores them. User-generated content, for example, involves unmeasured labor creating an unmeasured asset that is consumed in unmeasured ways to create unmeasured consumer surplus. In recent years, however, there have been some efforts to create experimental ‘satellite accounts.’ They track some of these categories of intangible assets in the U.S. economy. For instance, the new satellite accounts created by the Bureau of Economic Analysis estimate that investment in R&D capital accounted for about 2.9 percent of GDP and has increased economic growth by about 0.2 percent per year between 1995 and 2004.
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It’s hard to say exactly how large the bias is from miscounting all the types of intangible assets, but we are reasonably confident the official data underestimate their contribution.
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New Metrics Are Needed for the Second Machine Age

It’s a fundamental principle of management: what gets measured gets done. Modern GDP accounting was certainly a huge step forward for economic progress. As Paul Samuelson and Bill Nordhaus put it, “While the GDP and the rest of the national income accounts may seem to be arcane concepts, they are truly among the great inventions of the twentieth century.”
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But the rise in digital business innovation means we need innovation in our economic metrics. If we are looking at the wrong gauges, we will make the wrong decisions and get the wrong outputs. If we measure only tangibles, then we won’t catch the intangibles that will make us better off. If we don’t measure pollution
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innovation, then we will get too much pollution and not enough innovation. Not everything that counts can be counted, and not everything that can be counted, counts.

As Nobel Prize winner Joe Stiglitz put it:

The fact that GDP may be a poor measure of well-being, or even of market activity, has, of course, long been recognized. But changes in society and the economy may have heightened the problems, at the same time that advances in economics and statistical techniques may have provided opportunities to improve our metrics.
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The new metrics will differ both in conception and execution. We can build on some of the existing surveys and techniques researchers have been using. For instance, the human development index uses health and education statistics to fill in some of the gaps in official GDP statistics
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; the multidimensional poverty index uses ten different indicators—such as nutrition, sanitation, and access to water—to assess well-being in developing countries.
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Childhood death rates and other health indicators are recorded in periodic household surveys like the Demographic and Health Surveys.
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There are several promising projects in this area. Joe Stiglitz, Amartya Sen, and Jean-Paul Fitoussi have created a detailed guide for how we can do a comprehensive overhaul of our economic statistics.
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Another promising project is the Social Progress Index that Michael Porter, Scott Stern, Roberto Loria, and their colleagues are developing.
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In Bhutan, they’ve begun measuring “Gross National Happiness.” There is also a long-running poll behind the Gallup-Healthways Well-Being Index.
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These are all important improvements, and we heartily support them. But the biggest opportunity is in using the tools of the second machine age itself: the extraordinary volume, variety, and timeliness of data available digitally. The Internet, mobile phones, embedded sensors in equipment, and a plethora of other sources are delivering data continuously. For instance, Roberto Rigobon and Alberto Cavallo measure online prices from around the world on a daily basis to create an inflation index that is far timelier and, in many cases, more reliable, than official data gathered via monthly surveys with much smaller samples.
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Other economists are using satellite mapping of nighttime artificial light sources to estimate economic growth in different parts of the world, and assessing the frequency of Google searches to understand changes in unemployment and housing.
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Harnessing this information will produce a quantum leap in our understanding of the economy, just as it has already changed marketing, manufacturing, finance, retailing, and virtually every other aspect of business decision-making.