Quantum computers can solve problems exponentially faster than classical computers can. They will bring about two huge changes: an end to our current infrastructure for cybersecurity over public networks and an explosion of algorithmic power that holds the promise to reshape our world. Scientists face myriad challenges in developing commercially relevant quantum computers. But once they are overcome, the disruption caused by postquantum cryptography will eclipse that of Y2K, which cost the United States and its businesses more than $100 billion to mitigate. This article examines the way quantum computers will not only upend digital security but spur investment, reshape industries, and spark innovation.
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).
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.
Cloud computing is a sea change in the way companies use technology; it's as inevitable and significant as the shift from steam power to electricity on the factory floor. Because criticisms of the cloud have gotten a lot of hype, however, many companies are hesitant to explore it. In this article, McAfee, a principal research scientist at MIT's Center for Digital Business, debunks commonly cited concerns about the cloud. When it comes to cost, reliability, and security, he says, the cloud promises to equal or better on-premise computing. Moreover, as the experiences of companies like 3M, the global contractor Balfour Beatty, and the consulting firm CSC show, cloud computing offers sizable benefits, such as improved productivity, easier collaboration, the ability to mine data for insights, and higher capacity without major capital investment. Here, McAfee walks readers through the three basic categories of cloud computing: "infrastructure-as-a-service" (the leasing of raw computing capacity), "platform-as-a-service" (the leasing of computers ready for software development), and "software-as-a-service" (the hosting of applications for users). Arguing that CEOs and senior managers need to take the lead on the shift to the cloud, he then outlines how companies can get started.
In this conversation with HBR senior editor Anand P. Raman, McAfee, a principal research scientist at the MIT Sloan School of Management's Center for Digital Business, explains why Enterprise 2.0 tools - wikis, tags, Twitter, Google searches, and the like - are transforming companies' innovation processes. Procter & Gamble, for instance, uses its Connect + Develop website not only to publicize what it knows and what it can do but to highlight what it needs. That's radical, says McAfee. And the communities that form around innovation challenges can help sift the ideas, so the best ones quickly rise to the top.
Web 2.0 technologies are now a staple of social collaboration on the internet. In 2006 Andrew McAfee, of the MIT Center for Digital Business, coined the term Enterprise 2.0 to describe how organizations use emergent social software platforms, or ESSPs, to pursue their goals. However, some organizations don't achieve the many collaboration-related benefits that internal ESSPs can offer. After studying both successful and unsuccessful E2.0 initiatives, McAfee attributes most of the failures to five misconceptions. The first two myths crop up before an E2.0 initiative is launched. One is that the risks of ESSPs, most notably from inappropriate use, will greatly outweigh the rewards. McAfee makes the case that those dangers rarely manifest in practice. The other pre-launch myth is that the ROI of an E2.0 initiative should be calculated in monetary terms. McAfee shows how Enterprise 2.0 can deliver valuable benefits in terms of developing human, organizational, and information capital - without a numerical ROI yield. The final three myths arise after an E2.0 project is deployed. One holds that people will flock to a collaboration platform once it is built. Success actually requires various types of top-down support, including active participation by senior leaders. Another is that E2.0's primary worth is in helping close colleagues work together better. In reality, the value extends to networks of expertise well beyond a user's inner circle. The importance of those far-reaching interpersonal connections also debunks the last myth: that E2.0 should be judged by the information it generates. Information is indeed useful, but E2.0's greatest advantage lies in transforming potential ties between people into actual ones.
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.
Cambrian House builds internet-based products and services by relying entirely on its user community for all aspects of its innovation and new product development process. Users suggest ideas for new products and services and also participate in a monthly voting process to select the best ideas. The company is now considering the deployment of a prediction market to deepen user involvement and commitment in its innovation; however, it is not sure if it is an appropriate strategy for its community.
In its eight quarters of operation, Google's internally developed prediction market has delivered accurate and decisive predictions about future events of interest to the company. Google must now determine how to increase participation in the market, and how to best use its predictions.
The information age has brought with it a host of new technologies--and an overabundance of choices. Managers are hard-pressed to figure out what all those innovations do, let alone which ones to adopt and how to implement them. Furthermore, many so-called advancements haven't lived up to expectations: Frustration, delays, and even outright failures tempt many executives to avoid dealing with IT altogether. But those who turn away are selling their companies short. Executives have three critical responsibilities when it comes to IT: They must help choose technologies, using an inside-out approach that keeps the true needs of the business in mind; smooth the adoption of those technologies, taking into account that they may encounter strong resistance; and encourage their exploitation by leveraging already standardized data and work flows. What's most important, though, is that they look beyond the individual IT projects they select to the broader picture of how IT is likely to affect the organization. Information technology can be classified into three types, each of which provides companies with a particular level of change. Function IT encompasses technologies--such as spreadsheet and word-processing applications--that streamline individual tasks. Network IT includes capabilities like e-mail, instant messaging, and blogs and helps people communicate with one another. Enterprise IT brings with it approaches such as customer resource management and supply chain management and lets companies re-create interactions between groups of workers or with business partners. Different types of technology bring about different types of organizational change, and managers should tailor their own roles accordingly. Categorizing IT in this manner can help leaders determine which technologies to invest in and how they can assist organizations in making the most of them.
Engineer John Harrison must determine why motorcycle racer Marco Presto does not feel that his motorcycle is providing enough power as it comes out of corners. Harrison uses engine simulation software to help him in his work.
This is an MIT Sloan Management Review article. There is a new wave of business communication tools, including blogs, wikis, and group messaging software (which the author collectively calls "Enterprise 2.0") that allow for more spontaneous, knowledge-based collaboration. These new tools, the author contends, may well supplant other communication and knowledge management systems with their superior ability to capture tacit knowledge, best practices, and relevant experiences from throughout a company and make them readily available to more users. This article offers a paradigm that highlights the salient characteristics of these new technologies. The resulting organizational communication patterns can lead to highly productive and highly collaborative environments by making both the practices of knowledge work and its outputs more visible. Drawing on case studies and survey data, the article offers managers a set of ground rules for implementing the new technologies. First, create a receptive culture to prepare the way for new practices. Second, create a common platform to allow for a collaboration infrastructure. Third, plan an informal rollout of the technologies rather than a more formal procedural change. And fourth, secure managerial support and leadership. Even when implanted and implemented well, these new technologies will certainly bring with them new challenges. These tools may well reduce management's ability to exert unilateral control and to express some level of negativity. Whether a company's leaders really want this to happen and will be able to resist the temptation to silence dissent is an open question. Leaders will have to play a delicate role if they want Enterprise 2.0 technologies to succeed.