HBR's annual ideas collection, compiled in cooperation with the World Economic Forum, offers 10 fresh solutions with the potential for a huge positive impact on business and the world. Teresa M. Amabile and Steven J. Kramer reveal what their research shows is the true key to employee motivation-and it's not what most managers focus on providing. Ronald Dixon proposes that the real performance breakthrough in health care will come when the medical community adopts the everyday communications technologies patients already use. Lawrence M. Candell asks why the U.S. has a Lincoln Laboratory to put public-spirited experts across the table from profit-motivated defense contractors, but no such entity to do the same in the financial sector. Eric Bonabeau, Alpheus Bingham, and Aaron Schacht urge players in the pharmaceutical industry to treat drugs as information assets; big pharma could orchestrate drug-development networks to promote innovation. Jack D. Hidary describes a market solution to achieve what no government handout can in the greening of existing buildings. Robert E. Litan and Lesa Mitchell advocate that universities' technology transfer offices loosen their monopolistic grip on their scientists' taxpayer-funded discoveries. Bill Jensen and Josh Klein urge frustrated professionals to "hack work" by adopting the mind-set and tool kit of the hacker to achieve the positive outcomes their employers want but make difficult to achieve. Sendhil Mullainathan notes that we have the tools to spot bubbles about to burst, but individual firms have little incentive to sound the alarm. Why not appoint a "bubbles committee"? Paul Romer proposes that "charter cities" be established to show the citizens of failed and languishing states the merits of market economies and to provide an option for change. Carne Ross questions why only nation-states are allowed to shape international affairs and reveals the need for independent diplomacy.
This is an MIT Sloan Management Review article. Companies have long used teams to solve problems: focus groups to explore customer needs, consumer surveys to understand the market and annual meetings to listen to shareholders. But the words "solve," "explore," "understand" and "listen" have now taken on a whole new meaning. Thanks to recent technologies, including many Web 2.0 applications, companies can now tap into "the collective" on a greater scale than ever before. Indeed, the increasing use of information markets, wikis, crowdsourcing, "the wisdom of crowds" concepts, social networks, collaborative software and other Web-based tools constitutes a paradigm shift in the way that many companies make decisions. Call it the emerging era of "Decisions 2.0." But the proliferation of such technologies necessitates a framework for understanding what type of collective intelligence is possible (or not), desirable (or not) and affordable (or not) -- and under what conditions. At a minimum, managers need to consider the following key issues: loss of control, diversity versus expertise, engagement, policing, intellectual property and mechanism design. By understanding such important issues, companies like Affinnova, Google, InnoCentive, Marketocracy and Threadless have successfully implemented Decisions 2.0 applications for a variety of purposes, including research and development, market research, customer service and knowledge management. The bottom line is this: For many problems that a company faces, there could well be a solution out there somewhere, far outside of the traditional places that managers might search, within or outside the organization. The trick, though, is to develop the right tool for locating that source and then tap into it.
Companies often treat new-product development as a monolithic process, but it can be more rationally divided into two parts: an early stage that focuses on evaluating prospects and eliminating bad bets, and a late stage that maximizes the remaining candidates' market potential. Recognizing the value of this approach, Eli Lilly designed and piloted Chorus, an autonomous unit dedicated solely to the early stage. This article demonstrates how segmenting development in this way can speed it up and make it more cost-effective. Two classes of decision-making errors can impede NPD, the authors say. First, managers often ignore evidence challenging their assumptions that projects will succeed. As a result, many projects go forward despite multiple red flags; some even reach the market, only to fail dramatically after their introduction. Second, companies sometimes terminate projects prematurely because people fail to conduct the right experiments to reveal products' potential. Most companies promote both kinds of errors by focusing disproportionately on late-stage development; they lack the early, truth-seeking functions that would head such errors off. In segmented NPD, however, the early-stage organization maintains loyalty to the experiment rather than the product, whereas the late-stage organization pursues commercial success. Chorus has significantly improved NPD efficiency and productivity at Lilly. Although the unit absorbs just one-tenth of Lilly's investment in early-stage development, it delivers a substantially greater fraction of the molecules slated for late Phase II trials--at almost twice the speed and less than a third of the cost of the standard process, sometimes shaving as much as two years off the usual development time.
This is an MIT Sloan Management Review article. In the past, companies have tried to manage risks by focusing on potential threats outside the organization: competitors, shifts in the strategic landscape, natural disasters, or geopolitical events. They are generally less adept at detecting internal vulnerabilities that creep into organizations and other human-designed systems. Indeed, as companies increase the complexity of their systems they often fail to pay sufficient attention to the introduction and proliferation of loopholes and flaws. A crucial thing to remember is that the possibility of random failure rises as the number of combinations of things that can go wrong increases, while the opportunity for acts of malicious intent also goes up. Build new applications on top of legacy systems and errors creep in between the lines of code. Merge two companies and weaknesses sprout between the organizational boundaries. Build Byzantine corporate structures and processes and obscure pockets are created where bad behavior can hide. Furthermore, the enormous complexity of large systems like communications networks means that even tiny glitches can cascade into catastrophic events. In fact, catastrophic events are almost guaranteed to occur in many complex systems, much like big earthquakes are bound to happen. So, without the benefit of perfect foresight, how can businesses uncover and forestall the fatal flaws lurking within their organizations? There are three complementary strategies: (1) Assess the risk to make better-informed decisions, such as purchasing an insurance policy to cover the risk; (2) spot vulnerabilities and fix them before catastrophic events occur; and (3) design out weaknesses through resilience. These ideas have been around for years, but researchers have recently had to reinvent them in the context of extremely complex, interconnected, cascade-prone systems.
The List is HBR's annual attempt to capture ideas in the state of becoming--when they're teetering between what one person suspects and what everyone accepts. Roderick M. Kramer says it isn't bad when leaders flip-flop. Julia Kirby describes new efforts to redefine the problem of organizational performance. Joseph L. Bower praises the "Velcro organization," where managerial responsibilities can be rearranged. Jeffrey F. Rayport argues that companies must refocus innovation on the "demand side." Eric Bonabeau describes a future in which computer-generated sound can be used to transmit vast amounts of data. Roger L. Martin says highly reliable corporate systems such as CRM tend to have little validity. Kirthi Kalyanam and Monte Zweben report that marketers are learning to contact customers at just the right moment. Robert C. Merton explains how equity swaps could help developing countries avoid some of the risk of boom and bust. Thomas A. Stewart says companies need champions of the status quo. Mohanbir Sawhney suggests marketing strategies for the blogosphere. Denise Caruso shows how to deal with risks that lack owners. Thomas H. Davenport says personal information management--how well we use our PDAs and PCs--is the next productivity frontier. Leigh Buchanan explores workplace taboos. Henry W. Chesbrough argues that the time is ripe for services science to become an academic field. Kenneth Lieberthal says China may change everyone's approach to intellectual property. Jochen Wirtz and Loizos Heracleous describe customer service apps for biometrics. Mary Catherine Bateson envisions a midlife sabbatical for workers. Jeffrey Rosen explains why one privacy policy won't fit everyone. Tihamer von Ghyczy and Janis Antonovics say firms should embrace parasites. And Jeffrey Pfeffer warns business-book buyers to beware. Additionally, HBR offers a list of intriguing business titles due out in 2005.
Imitation exerts enormous influence over society--and business and finance in particular. And its influence has grown as the avenues by which people imitate--and are imitated--have multiplied and the process has gotten faster. Thousands of communications channels make it possible for virtually anyone in the developed world to know, almost instantaneously, what others do, think, believe, claim, or predict. More significantly, we can and do act upon such knowledge. The resulting fads and fashions, bubbles, and crashes are ever more frequent, severe, and complex. The information age has cast up more than its share of paradoxes, including this one: When information is plentiful, we often use it not to make better decisions but to imitate others--and their mistakes. In consumer purchases, financial markets, and corporate strategy, what others do matters more to us than the facts. When there's too much information, imitation becomes a convenient heuristic. This is the basis for a self-referential society. Imitation has its virtues, but it also promotes instability and unpredictability. That's because, by definition a multiplier, it can swell a single opinion into a mass movement or catapult the smallest player to the forefront of a market. Mastering the dynamics of self-reference won't ensure mastery of its consequences. But businesses that understand how imitation works can at least attempt to gird themselves against its worst effects--by accounting for it in their forecasts and risk management plans, by becoming more sensitive to unexpectedly changing circumstances, and by avoiding mindless imitation of other companies' moves.
Making high-stakes business decisions has always been hard. But in recent decades, it's become tougher than ever. The choices facing managers and the data requiring analysis have multiplied even as the time for analyzing them has shrunk. One simple decision-making tool, human intuition, seems to offer a reliable alternative to painstaking fact gathering and analysis. Encouraged by scientific research on intuition, top managers feel increasingly confident that, when faced with complicated choices, they can just trust their gut. The trust in intuition is understandable. But it's also dangerous. Intuition has its place in decision making--you should not ignore your instincts any more than you should ignore your conscience--but anyone who thinks that intuition is a substitute for reason is indulging in a romantic delusion. Detached from rigorous analysis, intuition is a fickle and undependable guide. And although some have argued that intuition becomes more valuable in highly complex and changeable environments, the opposite is actually true. The more options you have to evaluate, the more data you have to weigh, and the more unprecedented the challenges you face, the less you should rely on instinct and the more on reason and analysis. So how do you analyze more in less time? The answer may lie in technology. Powerful new decision-support tools can help executives quickly sort through vast numbers of alternatives and pick the best ones. When combined with the experience, insight, and analytical skills of a good management team, these tools offer companies a way to make consistently sound and rational choices even in the face of bewildering complexity--a capability that intuition will never match.
The collective behavior of people in crowds, markets, and organizations has long been a mystery. Why, for instance, do employee bonuses sometimes lead to decreases in productivity? Why do some products generate a tremendous buzz, seemingly out of nowhere, whereas others languish despite multimillion-dollar marketing campaigns? How could a simple clerical error snowball into a catastrophic loss that bankrupts a financial institution? Traditional approaches like spreadsheet and regression analyses have failed to explain such "emergent phenomena," says Eric Bonabeau, because they work from the top down, trying to apply global equations and frameworks to a particular situation. But the behavior of emergent phenomena, contends Bonabeau, is formed from the bottom up--starting with the local interactions of individuals who alter their actions in response to other participants. Together, the myriad interactions result in a group behavior that can easily elude any top-down analysis. But now, thanks to "agent-based modeling," some companies are finding ways to analyze--and even predict--emergent phenomena. This article discusses emergent phenomena in detail and explains why they have become more prevalent in recent years. In addition to providing real-world examples of companies that have improved their business practices through agent-based modeling, Bonabeau also examines the future of this technology and points to several fields that may be revolutionized by its use.
What do ants and bees have to do with business? A great deal, it turns out. Individually, social insects are only minimally intelligent, and their work together is largely self-organized and unsupervised. Yet collectively they're capable of finding highly efficient solutions to difficult problems and can adapt automatically to changing environments. Over the past 20 years, the authors and other researchers have developed rigorous mathematical models to describe this phenomenon, which has been dubbed "swarm intelligence," and they are now applying them to business. Their research has already helped several companies develop more efficient ways to schedule factory equipment, divide tasks among workers, organize people, and even plot strategy. Emulating the way ants find the shortest path to a new food supply, for example, has led researchers at Hewlett-Packard to develop software programs that can find the most efficient way to route phone traffic over a telecommunications network. Southwest Airlines has used a similar model to efficiently route cargo. To allocate labor, honeybees appear to follow one simple but powerful rule--they seem to specialize in a particular activity unless they perceive an important need to perform another function. Using that model, researchers at Northwestern University have devised a system for painting trucks that can automatically adapt to changing conditions. In the future, the authors speculate, a company might structure its entire business using the principles of swarm intelligence. The result, they believe, would be the ultimate self-organizing enterprise--one that could adapt quickly and instinctively to fast-changing markets.