個案總覽

Most companies already have plenty of creativity and technology. What they don’t have is the managerial skill to convert that creativity and technology into earth-shattering innovation. So how do they harness innovation? The first step is to understand what they need—the managerial skills, abilities, and traits that enable digital innovation. We need to not only acknowledge digital innovators, but promote their role as creators of economic and social value. In this article, S. Somasegar, a former senior executive at Microsoft, and Michael Volpe, former chief marketing officer at HubSpot, discuss the ideal digital innovator’s profile. Key excerpts, arranged under six major themes, deal with what an industry expert looks for in a potential digital innovator: 1) a playful attitude toward technology; 2) agile experimentation (including the use of minimum viable products); 3) mastery of the digital domain; 4) technological innovativeness; 5) a strong online identity; and 6) reliance on an extensive social network for expertise and advice. Entrepreneurs have historically taken one of two approaches to defining IT: it’s either a necessary evil or the product itself. Today there is a third approach, one that will become the dominant path for most innovators and entrepreneurs, especially those building information products.

Thanks to new technologies and innovative new ways of doing business, established incumbents across all industries have never been more vulnerable to attack by agile challengers with relatively little capital or resources. A triad of forces favours today’s disrupters: virtualization, digitalization, and capital superabundance. The half-life of business models has been shrinking and incumbents have been disappearing at an increasingly rapid rate—swallowed up in mergers, taken over by activist investors, or broken up. However, the rise of disrupters does not fully explain the ever-shorter lifespans of incumbents. When executives were asked what they believe are the obstacles to growth, 85 per cent of the reasons cited were internal barriers. Large, long-established companies suffer from “incumbency sclerosis,” which leads to strategic rigidity and an inability to adapt. Mergers and acquisitions (M&A) constitute one prescription, but their effectiveness depends on providing a catalyst for change in the acquirer’s business model, organizational model, and culture—if the acquired company is not destroyed in the process. The cure for incumbency sclerosis more often includes M&A along with other efforts to root out complexity, simplify the company, and build flexible operating models.

Amazon Go—grocery shopping without lineups and checkouts—is the latest in Amazon’s pursuit of new shopping experiences. Scheduled to open in 2017, Amazon Go will provide Seattle customers with the opportunity to shop for groceries without standing in line and then waiting while a clerk checks out groceries item by item. Instead, with a smartphone app and advanced technology, shoppers can take their items from the shelf and “Just Walk Out.” Amazon Go is a major step for the e-commerce giant, in both pursuing brick-and-mortar retail and creating an innovative shopping experience. The absence of checkout lanes and cashiers at these stores has captured media attention, but what’s more important for e-commerce merchants is understanding Amazon’s motives for opening a retail space, which are 1) to drive growth in new markets, 2) to tap into the common desire for in-store shopping (where 90 per cent of all retail sales still occur), and 3) to achieve more powerful technical innovation, such as through the use of beacons—in-store apps that connect with the customer’s smartphone to make fine-tuned suggestions—and hyperspecialization—understanding exactly what the customer is looking for, based on past purchases.

Companies worldwide spent US$1 trillion on digital technology in 2016. Unfortunately, for many businesses, this investment is not corresponding with financial returns. While some companies excel at adopting innovative digital technologies, many are only achieving incremental business improvements. Organizations need to radically rethink their approaches and develop bold digital strategies to harness technologies and unlock new sources of growth. Only 6 per cent of companies that invested in digital managed to translate those investments into sustained financial gains. We identified these as Digital High Performers. To make the leap from Digital Leaders to Digital High Performers, Digital Leaders must master using digital to drive revenue growth and increase investor confidence. Their overemphasis on efficiency and profitability indicates that Digital Leaders might be making trade-offs they cannot afford, putting their growth potential at risk. Four strategies are critical to organizations that want to get the most out of their digital investments: 1) get immersed in new ecosystems; 2) unlock opportunities to commercialize innovative ideas; 3) move beyond purely transactional customer relationships; and 4) embrace cultural and structural shifts. Digital Leaders must continuously assess the effectiveness of their digital investments and pursue overhauls and organizational designs, even if the initial efforts are risky. Commitment to digital alone does not guarantee financial success. New, bold strategies that leverage digital technology as an enabler and a driver of change in a legacy organization are vital for companies that wish to move beyond the verge of high performance. Digital Leaders don’t need greater investment; they need greater follow-through and the courage to lead transformation with tenacity.

Though some organizations recognize that learning from failure often leads directly to innovative products, processes, and services, discussing failure is often avoided in today’s business world. Failure is not just overlooked; it is routinely covered up. And when organizations are preoccupied with error avoidance, instead of error acceptance, innovation suffers because creative processes are inherently error-prone. Organizations have a choice. Instead of fearing failure, they can create a culture that accepts it, encouraging innovation through prudent risk-taking and exploration. So, how do you create a culture that “fails well”? Firms should: 1) create a culture of experimentation and creativity; 2) encourage risk-taking from the top; 3) celebrate failures like wins; 4) stimulate creativity and experimentation; and 5) hire entrepreneurs who are eager to learn. As innovation leaders, managers and organizations need to build a culture that removes the fear of failure and directs employees to learn, avoid mistakes, and pursue innovation through failing smart (maximizing learning with the expectation that failure will occur) and failing forward (taking the next step forward in the most efficient manner possible).

In 2019, Fitbit lost its leadership in the wearable sensor market to Apple and to cheaper alternatives. Why did it lose its market position? How will the proposed acquisition affect it and Google?

In October 2013, future prospects for TransCanada’s pipeline project were uncertain, as the company had to find ways to establish and manage relationships with Aboriginal communities along the proposed Energy East pipeline in Canada, particularly in the province of New Brunswick. Following Supreme Court rulings that reinforced the duty to consult and accommodate, Aboriginals came to have a powerful voice in the development of energy infrastructure, creating new requirements for companies wishing to expand into areas subject to Aboriginal title and treaty claims.

In the workplace, the very mention of Millennials can strike fear into the heart of the most seasoned manager. After all, we are talking about the “me” generation of employees who feel entitled and expect their opinion to be valued above all others, while also apparently being unwilling to work as hard as their parents. But, alas, broad generalizations are wrong a great deal of the time. We recognize this, and go out of our way to reject it in most cases. But how do we apply this same sensibility to Millennials? The first step is to recognize three important principles that apply to working with any individual or group: 1) Don’t assume that you know what motivates another person based solely on knowing his or her birthdate. 2) What motivates you is not necessarily what motivates others. 3) There are only two ways to find out what motivates another individual: asking and observing. We need to take this knowledge and incorporate it into our performance management process, aligning the individual’s rewards with their objectives, and with the objectives of the team. The process is simple but not easy. The biggest barrier is the time it takes. Ultimately, it’s much more expensive to have unproductive team members, high turnover on your team, and a demotivated workforce than to invest in how you manage performance.

Gathering the evidence required to back up a corporate claim has always been important, but the case for effective evidence gathering has never been greater than today. Unfortunately, while the data that organizations ordinarily collect can be useful, it is often insufficient to answer relevant questions. In other words, the evidence required typically isn’t ready to be analyzed and often must be developed using real-world experimentation. This paper examines how businesses can perform randomized controlled trials. To help you conduct better testing for your own business, we also address three questions: What if you can’t run a randomized controlled trial in a lab? Which organizations should conduct tests? How should you conduct your testing? The potential for confusing correlation and causation only becomes greater in a world of big data. Determine if an outcome is significant by using a simple statistical test such as the T-test, and specify your required level of significance before running the test. One way to achieve the best of both worlds is to use a field experiment—an experiment run in the real world but with as many confounding influences as possible removed. Although messier than lab tests, field experiments inspire greater confidence that the results will be relevant. Whenever it is feasible to randomize what you offer your customers, you have the potential to gain a better idea of what works best. Testing can save your organization money, make your actions more effective, and improve outcomes for your customers.

This is an MIT Sloan Management Review Article. South Africa's Nedbank is a leader in its market - but to stay in that position, it needed to identify new ways to serve its existing business clientele as well as attract new customers. Its solution: use the extensive transaction data the bank collects to help customers improve their service.

This is an MIT Sloan Management Review Article. Organizations across the business spectrum are awakening to the transformative power of data and analytics. They are also coming to grips with the daunting difficulty of the task that lies before them. It's tough enough for many organizations to catalog and categorize the data at their disposal and devise the rules and processes for using it. It's even tougher to translate that data into tangible value. But it's not impossible, and many organizations, in both the private and public sectors, are learning how.

This is an MIT Sloan Management Review Article. Companies have yet to apply analytics to human resources - but that's about to change. And lessons learned in applying analytics to customer-focused areas can help avoid mistakes in strategic workforce decisions.

This is an MIT Sloan Management Review Article. Multinational companies have invested heavily in emerging economies - over $3 trillion since 1998, by one estimate. Many of these companies, however, have not adapted their products and operations sufficiently to succeed in these markets, and returns have often been mediocre. Even when managers think they are performing well in emerging markets, they often are not because they have set low expectations. Adapting products and operations requires obtaining and using good market intelligence, which is difficult in emerging markets due to the paucity and unreliability of information. Another factor is the wide heterogeneity of emerging markets compared to developed markets. A third common problem is a lack of shared responsibility for market intelligence between headquarters and country managers, so market intelligence that is collected either is dismissed as not credible or is not updated often enough to keep pace with the rate of change in emerging markets. The authors argue that companies can overcome these difficulties by (1) treating market intelligence as a strategic asset; (2) organizing differently for market intelligence in emerging markets; and (3) using a wide range of sources and methods for market intelligence in emerging markets. They also recommend that market intelligence be organized as a shared responsibility between the corporate office and emerging-market business executives, with shared decision rights and shared resources. The article includes examples illustrating how companies such as Wrigley, Unilever, and Procter & Gamble obtain market intelligence in emerging markets.

This is an MIT Sloan Management Review Article. Companies must make important decisions about which features to include in the goods and services they offer to customers. Understanding the return on investment for a feature is essential to increasing profitability. Although tadding features increases costs, it may also increase revenues, either by attracting new customers or retaining existing customers. Yet the features that retain customers, the authors argue, may be different from the features that initially attract them. The authors provide insights from their research on how to calculate the return on investment for features. Working with a global hotel company, the authors developed a model to assess how features produce financial returns by attracting new customers and/or by retaining existing customers. The model integrates three kinds of data: the revenue increase due to the effect the feature has on attracting new customers; the revenue increase due to the effect the feature has on retaining existing customers; and the costs associated with adding the feature. They tested the model using three features, or "amenities of interest," in the hotel industry: bottled water, free internet access, and a fitness center. Not surprisingly, the authors found that free wireless internet was much more likely to attract customers than free bottled water. However, the picture changed when the authors switched from looking at features that attracted guests to features that retained them. Offering free bottled water during a stay led to a bigger boost in customer retention than offering wireless internet access.

This is an MIT Sloan Management Review Article. As "big data" becomes increasingly integrated into many aspects of our lives, we are hearing more calls for revolutionary changes in how researchers work. To save time in understanding the behavior of complex systems or in predicting outcomes, some analysts say it should now be possible to let the data "tell the story" rather than having to develop a hypothesis and go through painstaking steps to prove it. The success of companies such as Google Inc. and Facebook Inc., which have transformed the advertising and social media worlds by applying data mining and mathematics, has led many to believe that traditional methodologies based on models and theories may no longer be necessary. Among young professionals (and many MBA students), there is almost a blind faith that sophisticated algorithms can be used to explore huge databases and find interesting relationships independent of any theories or prior beliefs. The assumption is: The bigger the data, the more powerful the findings. As appealing as this viewpoint may be, authors Sen Chai and Willy Shih think it's misguided - and potentially risky for businesses that involve scientific research or technological innovation. For example, the data might appear to support a new drug design or a new scientific approach when there isn't actually a causal relationship. Although the authors acknowledge that data mining has enabled tremendous advances in business intelligence and in the understanding of consumer behavior - think of how Amazon.com Inc. figures out what you might want to buy, or how content recommendation engines such as those used by Netflix Inc. work - applying this approach to technical disciplines, they argue, is different. The authors studied several fields where massive amounts of data are available and collected:

This is an MIT Sloan Management Review Article. When it comes to putting data to use, communication - or rather, lack of it - between the data scientists and the executive decision makers can cause problems. The two sides often don't speak the same language and may differ in their approach to and respect for data-based decisions. Given these challenges, organizations may need to call upon a "data translator" to improve how data is incorporated into decision making processes.

This is an MIT Sloan Management Review Article. Competition for digitally savvy talent has never been higher, but companies' methods for acquiring and keeping the skilled employees they need are outmoded. Whether they want to develop capabilities in employees or tap on-demand talent markets - or some mix of both - human resources directors need to experiment with new talent management models.

In surveys of 106 C-suite executives representing 91 private- and public-sector companies from 17 countries, the author found that a full 85% agreed that their organizations were bad at problem diagnosis, and 87% agreed that this flaw carried significant costs. Fewer than one in 10 said they were unaffected by the issue. What they struggle with, it turns out, is not solving problems but figuring out what the problems are. And creative solutions nearly always come from an alternative explanation for--or a reframing of--your problem. The point of reframing is not to find the "real" problem but, rather, to see if there is a better problem to solve. The author outlines seven practices for effective reframing: (1) Establish legitimacy. (2) Bring outsiders into the discussion. (3) Get people's definitions in writing. (4) Ask what's missing. (5) Consider multiple categories. (6) Analyze positive exceptions. (7) Question the objective.

The young CEO of a Turkish bank wants to experiment with a new way of reaching customers and doing business--but she's meeting with resistance from employees and worries that they have had enough. Expert commentary comes from Mitch Krebs, President and CEO of Coeur Mining, and Pinar Abay, CEO of ING Bank Turkey.

The comedian on innovating, humor as a leadership tool, and ending a run while atop the ratings.