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After failing to make the basketball, baseball, and football teams in high school, the author persuaded the administration to start a lacrosse team, figuring that no one would know any more than he did about how to play. Eventually he got good at the game and became team captain. He took a valuable lesson from that experience: Opportunity is something you manufacture, not something you wait for. That lesson has informed his career ever since. For example, while he had a part-time job moving boxes as part of a relocation for Little, Brown, he happened across an assignment to create a book jacket. Familiarity with Photoshop and Quark enabled him to quickly come up with a design and slip it into the pile of submissions. When the editors and the sales team chose it as the best, he was offered a full-time job. A couple of start-ups and a stint at Google later, Stone and a close friend came up with the idea for Twitter. His job at the company was to "bring humanity to the technology" and to help "shape our story for the outside world." (He drew the bird logo.) His latest venture is Jelly Industries, a seven-person company of which he's the CEO. There he has learned that the chief executive's most important job is to constantly communicate.

Why is it so hard to build and maintain the capacity to innovate? The reason is not simply a failure to execute but a failure to articulate an innovation strategy that aligns innovation efforts with the overall business strategy. Without such a strategy, companies will have a hard time weighing the trade-offs of various practices-such as crowdsourcing and customer co-creation-and so may end up with a grab bag of approaches. They will have trouble designing a coherent innovation system that fits their competitive needs over time and may be tempted to ape someone else's system. And they will find it difficult to align different parts of the organization with shared priorities. As Corning, a leader in glass and materials science, has found, an innovation strategy must address how innovation will create value for potential customers, how the company will capture a share of that value, and what types of innovation to pursue. Critics tend to discount "routine" innovation that leverages a company's existing technical capabilities and business model and extol "disruptive" innovation, but that is a simplistic view. A company's unique competitive circumstances should dictate the innovation portfolio it pursues. Because innovation cuts across functions, only senior leaders can set an innovation strategy. In doing so, they must recognize that the strategy, like the process of innovation itself, requires continual experimentation and adaptation. HBR Reprint R1506B

People in all walks of life are rightly concerned about advancing automation: Unless we find as many tasks to give humans as we find to take away from them, all the social and psychological ills of joblessness will grow, from economic recession to youth unemployment to individual crises of identity. What if, the authors ask, we were to reframe the situation? What if we were to uncover new feats that people might achieve if they had better thinking machines to assist them? We could reframe the threat of automation as an opportunity for augmentation. They have been examining cases in which knowledge workers collaborate with machines to do things that neither could do well on their own--and they've found that smart people will be able to take five approaches to making their peace with smart machines. Some will "step up" to even higher levels of cognition, where machines can't follow. Some will "step aside," drawing on forms of intelligence that machines lack. Some will "step in," to monitor and adjust computers' decision making. Some will "step narrowly" into very specialized realms of expertise. And, inevitably, some will "step forward," by creating next-generation machines and finding new ways for them to augment the human strengths of workers.

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).

Wouldn't it be great if there were an algorithm that could tell you when to develop a new business model or enter an emerging market? Unfortunately, one doesn't exist. However, it is possible to use the principles behind algorithms to continually retune your strategy and your organization. In online enterprises, algorithms constantly readjust the products and content shown to customers. They do this by operating three learning loops: experimentation, modulation, and shaping. Algorithms keep generating new options and testing reactions to them. But over time the algorithms modulate the rate of experimentation, scaling it back as they learn more about people's likes and dislikes. Algorithms shape preferences too, by introducing customers to products they might not have otherwise discovered. Critically, they do this all in a self-directed manner, without any human intervention. Now some internet companies have begun to regularly readjust their business models, allocation processes, and structures using the same self-directed learning loops. This approach works especially well in rapidly changing markets, like China. In this article, the authors look at how China's Alibaba grew from an 18-person start-up to an $8 billion empire by regularly resetting its vision, testing out new models, shaping opportunities, and building adaptive structures.

As machines evolve from tools to teammates, the author writes, accepting them will be more than a matter of simply adopting some new technology. The first challenge will be recognizing when computers know more than we do. "Algorithm avoidance," for instance, makes people prefer human judgment over that of machines and can lead to worse decisions, from diagnosing patients to predicting political outcomes. The message for managers is that helping humans to trust thinking machines will be essential. One way to encourage that trust is to make robots more humanoid. Researchers at Carnegie Mellon explored this idea with an autonomous robot named Snackbot, which had wheels, arms, a male voice, and an LED mouth that could smile and frown. People in the office made conversation with it and treated it with kindness. But this approach may lead us to put too much faith in the machines' abilities. How we work with thinking machines will vary according to the work we're doing, how it's framed, and how the machines are designed. But under the right conditions, people are surprisingly open to a robotic colleague.

Companies may want to shift a brand's position--to exploit less crowded territory, for example, or grow sales. Companies have long used perceptual mapping to understand how consumers feel about their brands relative to competitors', to find gaps in the marketplace, and to develop brand positions. But the business value of these maps is limited because they fail to link a brand's market position to business performance metrics such as pricing and sales. Other marketing tools measure brands on yardsticks such as market share, growth rate, and profitability but fail to take consumer perceptions into consideration. In this article, Ivey Business School's Niraj Dawar and Charan K. Bagga present a new type of map that links a brand's position to competitors according to its perceived "centrality" (how representative it is of the company) and "distinctiveness" (how much it stands out from other brands) with its business performance along a given metric. Using the tool, marketers can determine a brand's current and desired position, predict its marketplace performance, and devise and track marketing strategy and execution. In-depth examples of the car and beer markets demonstrate the value of this tool to managers of brands in any category.

Fifty years ago fashion and luxury goods were all about family businesses and entrepreneurial designers. Today most of the best-known brands belong to a diversified group like LVMH, Richemont, or Kering. The success of such groups contradicts the management notion that a focus on one core leads to superior returns--and that diversification adds little value. An analysis of the performance of 350 fashion houses suggests that group affiliation does add value, say INSEAD's Andrew Shipilov and Frederic Godart. They found that the fashion collections of group brands were more successful, and judged more creative by industry buyers, than those of independent brands over a 10-year period. How do luxury groups get this edge? Through the way they groom their designers and managers. The groups exploit the variety of their businesses by setting up internal talent markets that offer rich learning opportunities. Rising stars are thus less tempted to leave the organization, and cross-group job moves help spread knowledge and best practices. Group watchmaking companies, for instance, have been able to boost their sales by hiring experts in marketing and CRM from their groups' fashion and cosmetics firms. Worldwide operations give groups another advantage, because spending time overseas is critical to executive development. This is especially true in the luxury field, where international experience exposes designers to creative influences and executives to new but fast-growing customer segments. However, it isn't just in their approach to internal talent that groups excel. They prime the entry-level pipeline by sponsoring educational programs and offering apprenticeships to promising students, as well as recruit external functional know-how more effectively than the independent brands do.

Many people today regard their computers, tablets, and smartphones as indispensable, both professionally and personally. But they can also be dangerous: Research shows that spending too much time on e-mail and social media reduces your productivity and engagement at home and at work. So how can you avoid digital overload? In this article, two experts offer dramatically different strategies. Larry Rosen, a psychologist, advocates pulling away from technology in order to refocus. His advice: Limit the time you spend with your devices, using behavioral techniques to gradually wean yourself away; when you are using technology, take periodic breaks to exercise, meditate, or otherwise recharge; and avoid on-screen activities before bedtime to ensure that you get proper rest. Alexandra Samuel, a pioneer in electronic engagement, recommends the opposite tack: Embrace technology and make smarter use of digital tools to manage information overload. She suggests filtering your e-mail and using a newsreader app to customize the stream of articles and blog items you receive. You can also automate your postings to social networks. The author's approaches needn't be mutually exclusive. Indeed, combining them may be the best way to combat digital distraction.

The politician and peace negotiator on starting a dialogue, getting people to listen, and the importance of public service.

In May 2013, Jack Russo, a Chicago-based tech entrepreneur, had to choose one of four possible product concepts to use as the starting point for his new K-8 educational learning company, TabletTeach LLC. At the time, the K-12 education market in the United States was experiencing major disruption due to print-to-digital transformation, new Common Core State Standards (CCSS), new standardized tests aligned to the Common Core (rolling out in most states in the 2014-2015 school year), and increasing pressure from parents for schools to incorporate technology in their children's learning. Based on his first-hand experience and research, Russo knew there was a significant opportunity for a company that brought to market a tablet-enabled learning solution focusing on grades K-8, which made learning Common Core math and/or language arts fun for every student and engagingly simple for all teachers. This case provides an interesting example of something typically hard to teach: transitioning from the fuzzy front end of a market opportunity analysis to a specific product opportunity. The case bounds the problem by outlining four potential product concepts, which students will then evaluate and rank using their own sets of criteria.

In August 2013, the research director of Superb Trucks LP, a large Ontario-based trucking transportation company, is expected to prepare a recommendation to top management on how to improve the efficiency of the company's trucks. He had made a decision that an innovative fuel additive might serve this purpose and subsequently conducted two studies to assess its effectiveness. What considerations should be made when designing such a field experiment? How can these considerations affect interpretation of study findings and inform business decisions?

Kingfisher Airlines, a leading airline company in India, had incurred substantial losses and its net worth had been eroded. This news was widely covered by Indian and international press. Analysts and media were of the opinion that Kingfisher needed equity infusion to steer it through the distress. Because of its financial difficulties, the company's stock was trading at near-historic lows and its equity value was, in fact, negative. Yet company management was emphatic that Kingfisher was on the road to recovery although it was negotiating a second debt restructuring with banks. Would this restructuring prove more successful than the last? Could anything save Kingfisher from this dire financial situation?

A homeowner and his family finally have an offer on their residence. The terms negotiated with the buyers require the homeowner to build a detached garage on the property before the closing date on August 30, 2013, which is in 16 weeks. The homeowner's family has also made a conditional offer on another home, and the condition must be removed in two days if they would like to finalize that purchase. Although proficient at construction, the homeowner has encountered a major addition to his timeline on May 1. The city is requiring that he obtain a variance approval before the building department issues the building permit, thereby delaying the start of construction by between nine and ten weeks. The homeowner must decide whether to go ahead or cancel the sale of the residence and the purchase of a new home.

This document is one of three available case-based simulations used as the basis for a multisession course on design thinking. The course emphasizes deep user understanding, iteration, and a focus on the possibilities as a way to enhance value creation for stakeholders. Please refer to the course teaching guide to view the additional essential pedagogical tools available to the course instructor-including several hours of video content and a set of posters that summarize ethnographic interview findings for each simulation scenario. In this case, the CEO of Great Lakes (GL), a Fortune 200 company and one of the world's largest dairy cooperatives, reflects on the challenges and opportunities the company faces as it considers how to tap into a bigger slice of the lucrative market for snack foods for Millennials, an area GL's research had identified as a promising first target. Students play the role of members of a handpicked innovation team chartered to explore and develop profitable revenue growth opportunities.

In an effort to save his business, Paul Marciano, the owner of Italian family restaurant Maria's Ristorante, runs a number of experiments focused on improving the customer experience around his target customer segment. These experiments lead to a better understanding about his business and cause him to make specific changes to his business model that ultimately improve things across the board. The experiments are based on research from the academic literature on the use of behavioral variables to manage customer perceptions.

Dr. Felton Wayne, the chief medical officer for North Carolina operations at Valley Health (VH), had been working incredibly hard for the past nine months trying to motivate and empower his medical staff, who had become disillusioned by VH's management practices. But he had little to show for his efforts. He felt unappreciated and ineffective in his role. After a tense meeting with his director, during which Wayne was called a "cowboy," he wondered whether he should just go back to doing what he was good at-taking care of patients. This A case is accompanied by a B case.

In response to his meeting with his corporate director, Dr. Felton Wayne considered resigning. He had been chief medical officer at a hospital owned by Valley Health (VH) for 12 months, and it had been a tough year. But after he implemented a few important changes, Wayne started to see results. This case is a continuation of the A case.

Trionym Systems, a designer and manufacturer of 3-D printers, was enjoying soaring sales. Trionym's chief executive officer (CEO) presented a plan for acquiring a new production facility to address the expected demand for the firm's latest 3-D printer, the RB-5000, which was presently under beta testing. He expressed reservations with respect to considerable uncertainty both in terms of market size and production costs. Accordingly, he wished to use the latest prescriptive analytics techniques to ensure that the decision to expand was the right one. The chief analytics officer was tasked with assessing the proposed project and had to report his findings at the next board meeting.

This case describes the financial and non financial performance of Starbucks, a large organisation provided as on 2007. Howard Schultz, the promoter and chairman of the corporation is disturbed by the decline in the performance of Starbucks, especially the dilution of customer experience. He is required to analyse what happened and adopt a course of action to strengthen Starbucks' performance vis a vis competitive attacks. The participants are required to analyse the situation, generate options for Starbucks and make recommendations for the future, including whether Jim Donald, the current incubent, needs to retained as the CEO of Starbucks.