Digital media consumes a large and growing share of our waking lives, but these goods and services go largely uncounted in GDP. That's because the measure is based on what people pay for goods and services. If something has a price of zero, then it typically contributes zero to GDP. Policy makers use GDP data to make decisions about how to invest in everything from infrastructure and R&D to education and cyberdefense, and regulators use economic data to set policy. Because the benefits of digitization are dramatically underestimated, those decisions and policies are being made with a poor understanding of reality. GDP-B is an alternate metric that supplements the traditional GDP framework by quantifying contributions to consumer well-being from new and free goods.
Exponential improvement in computer gear is one of three fundamental forces enabling what the authors call 'The Second Machine Age'. They describe how innovation is being propelled by vast numbers of powerful-but-cheap devices (smartphones), each equipped with an array of processors, sensors and transmitters. They describe how services like Waze only became feasible in the past few years because of accumulated digital power increases and cost declines. Data are the lifeblood of science, they argue, and as a result, the second force powering the Second Machine age is digitization, which increases understanding by making huge amounts of data readily accessible. Thanks to the first two forces, a new style of innovation has emerged that adds social and sensor data to an existing system, greatly increasing its power and usefulness. This approach to innovation is the third and last of the forces shaping the Second Machine Age.
Today's digital innovations are doing for brainpower what the steam engine, and related, technologies did for muscle power during the Industrial Revolution. They're allowing us to rapidly overcome limitations and open up new frontiers, say Erik Brynjolfsson and Andrew McAfee, who have studied the impact of technologies on economies for years. The two MIT professors believe this transformation will create abundance. But they warn that there may be a dark side: Though the pie will get bigger, not everyone will benefit equally. As computers get more powerful, companies have less need for some kinds of workers. That shift is contributing to a phenomenon the two academics call the Great Decoupling: For decades, per capita GDP, productivity, private employment, and median family income rose in almost perfect lockstep. But in the 1980s, growth in income began to sputter and then began to drop. Adjusting for inflation, the median U.S. household today earns less than the median in 1998 did. Job growth has also slowed. Similar trends are emerging in most developed countries. In this interview, Brynjolfsson and McAfee explore the implications: who will win (workers with tech and creative skills), who will lose (the middle class), and how business should respond to the coming tech surge (develop ways to race with machines, not against them).
This is an MIT Sloan Management Review article. Recent technology advances in mobile computing and augmented reality are blurring the boundaries between traditional and Internet retailing, enabling retailers to interact with consumers through multiple touch points and expose them to a rich blend of offline sensory information and online content. In the past, brick-and-mortar retail stores were unique in allowing consumers to touch and feel merchandise and provide instant gratification; Internet retailers, meantime, tried to woo shoppers with wide product selection, low prices and content such as product reviews and ratings. But as the retailing industry evolves toward a seamless "omnichannel retailing"experience, the distinctions between physical and online will vanish, the authors suggest, turning the world into a showroom without walls. This will push retailers and their supply-chain partners in other industries to rethink their competitive strategies The growing prevalence of location-based applications on mobile devices is a critical enabler. Mobile technology is well on its way to changing consumer behavior and expectations, the authors argue. By giving consumers more accurate information about product availability in local stores, retailers can draw people into stores who might otherwise have only looked for products online. The enhanced search capability is especially helpful with niche products, which are not always available in local stores. The availability of product price and availability information, the ability of consumers to shop online and pick up products in local stores, and the aggregation of offline information and online content have combined to make the retailing landscape increasingly competitive. Retailers used to rely on barriers such as geography and customer ignorance to advance their positions in traditional markets. However, technology is removing these barriers.
Big data, the authors write, is far more powerful than the analytics of the past. Executives can measure and therefore manage more precisely than ever before. They can make better predictions and smarter decisions. They can target more effective interventions in areas that so far have been dominated by gut and intuition rather than by data and rigor. The differences between big data and analytics are a matter of volume, velocity, and variety: More data now cross the internet every second than were stored in the entire internet 20 years ago. Nearly real-time information makes it possible for a company to be much more agile than its competitors. And that information can come from social networks, images, sensors, the web, or other unstructured sources. The managerial challenges, however, are very real. Senior decision makers have to learn to ask the right questions and embrace evidence-based decision making. Organizations must hire scientists who can find patterns in very large data sets and translate them into useful business information. IT departments have to work hard to integrate all the relevant internal and external sources of data. The authors offer two success stories to illustrate how companies are using big data: PASSUR Aerospace enables airlines match their actual and estimated arrival times. Sears Holdings directly analyzes its incoming store data to make promotions much more precise and faster.
Investments in certain technologies do confer a competitive edge-one that has to be constantly renewed, as rivals don't merely match your moves but use technology to develop more potent ones and leapfrog over you. That's the conclusion of a comprehensive analysis that Harvard Business School professor McAfee and MIT professor Brynjolfsson conducted of all publicly traded U.S. companies in all industries over the past few decades. They found a clear correlation between levels of IT spending and a new competitive dynamic: Since the mid-1990s, when the rate of spending on IT began to rise sharply, the spread between the leaders and laggards in an industry has widened. There are more winner-take-all markets. But the increased concentration has ramped up, rather than dampened, churn among the remaining players. And these dynamics are greatest in those industries that are more IT intensive. This pattern is already familiar to the makers of digital products, but it has now spread to traditional industries, the authors contend, not because more products are becoming digital but because more processes are. Enterprise software like ERP and CRM systems, coupled with cheap networks, is allowing companies to replicate their unique business processes quickly, widely, and faithfully, in the same way that a digital photo can be endlessly reproduced. In this new environment, top managers must pay careful attention to which processes to make consistent and which to vary locally. And while standardizing some ways of working, they must also encourage employees to come up with creative process improvements to outdo competitors' innovations. Competing at such high speeds isn't easy, and not everyone will be able to keep up-but the companies that do may realize vastly improved business processes as well as higher market share and increased market value.
This is an MIT Sloan Management Review article. Dozens of markets of all types are in the early stages of a revolution as the Internet and related technologies vastly expand the variety of products that can be produced, promoted, and purchased. Although this revolution is based on a simple set of economic and technological drivers, the authors argue that its implications are far-reaching for managers, consumers, and the economy as a whole. Looks at what has been dubbed the "Long Tail" phenomenon, examining how customers derive value from an important characteristic of Internet markets: the ability of online merchants to help consumers locate, evaluate, and purchase a far wider range of products than they can typically buy via the traditional brick-and-mortar channels. The article examines the Long Tail from both the supply side and the demand side and identifies several key drivers. On the supply side, the authors point out how e-tailers' expanded, centralized warehousing allows for more offerings, thus making it possible for them to cater to more varied tastes. On the demand side, tools such as search engines, recommender software, and sampling tools are allowing customers to find products outside of their geographic area. The authors also look toward the future to discuss second order amplified effects of Long Tail, including the growth of markets serving smaller niches.
BroadVision develops software that allows Internet-based businesses to gather information about their online customers and deliver customized information to them in return. The firm was founded in May 1993 by a successful entrepreneur with a track record of two previous successful startups. The case discusses the role of "rules-based systems" in delivering personalized information directly to the consumer and allowing one-to-one marketing to happen on the Internet. Trust and privacy issues related to the use of this "mass-customization" technology are discussed. Related personalization technologies, such as "collaborative filtering" are analyzed as well. Finally, the case deals with the growth strategy and business model of BroadVision, as a young Internet software company competing with software giants such as Microsoft, Netscape, and Oracle.
Collaborative filtering is explained. Collaborative filters leverage the online community to make personalized recommendations to each end-user by comparing their preferences with those of other users with similar profiles.