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The Most Innovative Companies 2019

This article is a chapter from the BCG report, The Most Innovative Companies 2019: The Rise of AI, Platforms, and Ecosystems.

Users of Google’s email software recently discovered that Gmail was offering to finish their sentences for them. This new Smart Compose feature relies on Google’s expertise in artificial intelligence (AI) and machine learning (ML), along with billions of training examples and the company’s cloud-based Tensor Processing technology, to intuit what Gmail users want to say—often faster than the users can complete their own thoughts.

In a world where computers can compose notes to your friends, it’s hardly surprising that the theme of BCG’s 13th annual global innovation survey and report is the rising importance of AI and of platforms that support innovation. This is not an out-of-the-blue development. Our last few reports have highlighted the crucial role of science and technology in innovation, the impact of digital technologies on both digital natives and more traditional industries, and strong innovators’ increasing use of various internal and external vehicles to uncover new ideas. This year’s survey shows that AI use is rapidly expanding and that many companies are relying more on platforms and their cousin, ecosystems, to support their innovations efforts.

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Two New Forces

Most companies are at least exploring the use of AI, and strong innovators are seeing positive results. Nine out of ten respondents in our current survey say that their companies are investing in AI, and more than 30% expect AI to have the greatest impact of any innovation area on their industry over the next three to five years. (See Exhibit 2.) Four in ten self-described strong innovators report receiving more than 15% of their sales from AI-enabled products, compared with less than one in ten weak innovators. In a companion article, we take an in-depth look at the widening gap in where and how AI is affecting innovation. (See the companion article “AI Powers a New Innovation Machine.”)

Platforms and ecosystems serve multiple functions, including facilitating (and sometimes profiting from) the innovation of others, expanding reach and collaboration, and enabling new multiparty solutions and offerings. Again, strong innovators are more likely than weak ones to expect a significant impact within three to five years and to be actively targeting these areas. (See Exhibit 3.) Strong innovators also show other signs of being focused on external innovation. For example 75% report using incubators, 81% leverage academic partnerships, and 83% partner with other companies. Weak innovators lag consistently in all of these areas.

Platforms are technologies that provide a foundation for developing other business offerings. Numerous industrial goods companies, including Siemens (number 16) and Boeing (number 11), have built substantial platform businesses in predictive maintenance to complement their traditional engineering and manufacturing endeavors. Amazon, Microsoft, and IBM, among others, offer a range of software and services from their cloud platforms.

Ecosystems go a step further and leverage a range of partners that pull together the underlying technologies, applications, software platforms, and services needed to produce an integrated solution. (See “The Emerging Art of Ecosystem Management,” BCG article, January 2019.) The two main mobile operating systems—Google’s Android and Apple’s iOS—have grown into complex ecosystems of telcos, device manufacturers, service providers, and app developers, among others. Rapidly changing technologies and growing customer demand for a highly customized user experience further amplify the need for partnerships.

The opportunity to innovate entirely new revenue streams, business models, and sources of continuing advantage is particularly strong for B2B businesses, thanks to the masses of data that devices connected to the Internet of Things (IoT) generate. Data ecosystems will play a critical role in defining the future of competition in many B2B industries. (See “How IoT Data Ecosystems Will Transform B2B Competition,” BCG article, July 2018.)

Authors: Michael Ringel, Senior Partner & Managing Director, Boston; Florian Grassl, Partner & Managing Director, Munich; Ramón Baeza, Senior Partner & Managing Director, Madrid

More: www.bcg.com

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How Diverse Leadership Teams Boost Innovation

“Hire a chief innovation officer.” “Change the culture.” “Look outside your industry.” There’s no shortage of advice about how companies can become more innovative. The catch is that most of that advice is based on anecdotal evidence. But there’s one step companies can take that does have some data behind it.

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A recent BCG study suggests that increasing the diversity of leadership teams leads to more and better innovation and improved financial performance. In both developing and developed economies, companies with above-average diversity on their leadership teams report a greater payoff from innovation and higher EBIT margins. Even more persuasive, companies can start generating gains with relatively small changes in the makeup of their senior teams.

For company leaders, this is a clear path to creating a more innovative organization. People with different backgrounds and experiences often see the same problem in different ways and come up with different solutions, increasing the odds that one of those solutions will be a hit. In a fast-changing business environment, such responsiveness leaves companies better positioned to adapt. (See “Diversity at Work,” BCG article, July 2017.) This argument has always made intuitive sense, and now we have some convincing correlations to add to the case.

Diversity Gaining Momentum Worldwide

We surveyed employees at more than 1,700 companies in eight countries (Austria, Brazil, China, France, Germany, India, Switzerland, and the US) across a variety of industries and company sizes. (This was a followup study to one we reported on last year in The Mix That Matters: Innovation Through Diversity, BCG Focus, April 2017, and discussed in an accompanying TED talk.) We looked at perceptions of diversity at the management level across six dimensions—gender, age, nation of origin (meaning employees born in a country other than the one in which the company is headquartered), career path, industry background, and education (meaning employees’ focus of study in college or graduate school). To gauge a company’s level of innovation, we looked at the percentage of total revenue from new products and services launched over the past three years.

Broadly, 75% of respondents said that diversity is gaining momentum in their organizations. Employees at companies in emerging markets (China, Brazil, and India) reported greater progress over the past several years than companies in developed markets.  The biggest takeaway we found is a strong and statistically significant correlation between the diversity of management teams and overall innovation. Companies that reported above-average diversity on their management teams also reported innovation revenue that was 19 percentage points higher than that of companies with below-average leadership diversity—45% of total revenue versus just 26%

 

. (See Exhibit 1.) In other words, nearly half the revenue of companies with more diverse leadership comes from products and services launched in the past three years. In an increasingly dynamic business environment, that kind of turbocharged innovation means that these companies are better able to quickly adapt to changes in customer demand.  Not surprisingly, these organizations also reported better overall financial performance: EBIT margins that were 9 percentage points higher than those of companies with below-average diversity on their management teams.

More: www.bcg.com

Authors: Rocío Lorenzo, Partner & Managing Director, Munich; Nicole Voigt, Partner & Managing Director, Düsseldorf; Miki Tsusaka, Senior Partner & Managing Director, Chief Marketing Officer, Tokyo; Matt Krentz, Senior Partner & Managing Director, Chicago

 

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Competing on the Rate of Learning

New technologies, particularly artificial intelligence, have the potential to propel the rate of learning in business to new heights—the volume and velocity of data have exploded, and algorithms can unlock complex patterns and insights with unprecedented speed. In an era of shrinking product life cycles and rapidly changing business models, the companies that are the first to decode new trends or emerging needs have the best chance to take advantage of them.

But learning at the speed of algorithms requires more than algorithms themselves. New technology can accelerate learning in individual process steps, but to create aggregate organizational learning and competitive advantage it must be complemented by organizational innovation. Moreover, slow-moving contextual shifts, driven by social, political, and economic forces, are becoming just as important to business as fast-moving technologies. To compete on the ability to learn, therefore, leaders must reinvent their organizations to leverage both human and machine capabilities synergistically in order to expand learning to both faster and slower timescales.

A Brief History of Learning Organizations

In first-generation learning organizations, businesses learned how to execute existing processes more efficiently—best exemplified by the “experience curve.” As Bruce Henderson observed half a century ago, firms tend to reduce their costs at a constant and predictable rate as their cumulative experience increases. For example, in the early 20th century costs of the Model T consistently fell by about 25% every time the cumulative product volume doubled.

In this model, learning was a game of continuous improvement aimed at reducing marginal costs. Competing on learning was essentially about building volume, and therefore experience, faster than competitors. This permitted a strategy of pricing for the anticipated value of learning and pursuing cost reductions systematically, using mechanisms such as statistical process control, kaizen, Six Sigma, and quality circles.

In recent years, a second-generation concept of learning came to the forefront: learning how to envision and create new products. In other words, companies must learn not only to descend experience curves but also to “jump” from one curve to another.

This second dimension of learning has always existed in business, but its importance has grown. Technological innovation has compressed product life cycles, so new learning curves appear before old ones have fully played out—and firms must balance both dimensions of learning at the same time. For example, Netflix jumped from a DVD rental business to a streaming service to in-house content creation, while expanding to 190 countries, in less than a decade.

Today, a third phase of the learning game is beginning to unfold. Modern technologies, such as sensors, digital platforms, and AI, promise to massively accelerate the rate at which information is generated, gathered, and processed. This potentially enables companies to operate at superhuman speed, learning about the market and reacting in seconds or even milliseconds.

At the same time, however, companies must also expand their learning abilities to consider longer timescales, as social, political, and economic shifts gradually reshape the business context. Most businesses have woken up to the reality of time compression, but this is only half the picture. The range of timescales that need to be considered is being stretched in both directions. A third-generation learning organization is one that can embrace this new reality—adopting algorithmic principles over shorter timescales while adapting to nonbusiness forces that operate over longer ones.

To make this leap, businesses cannot rely on technological sophistication alone. Repeating a well-established historical pattern, evolution of the organizational model is needed to unlock the potential of new technologies. The original experience curve could be exploited only when new industrial technologies were complemented by organizational innovations like new factory layouts, redefined roles for workers (such as the assembly line), and new managerial approaches like quality circles and kanban. In the same way, to build the third generation of learning organizations, leaders must reinvent the enterprise not only to unlock the potential of new technologies but also to synergistically combine the unique learning capabilities and timescale advantages of both humans and technology—in other words, to build effective “human + machine” machines.

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The third generation of learning organizations presents an enormous opportunity. Companies can unleash both the power of technology for rapid learning and human ingenuity on longer timescales. But this will require leaders first to reimagine the organization and how it is managed.

More: BCG By Martin Reeves and Kevin Whitaker

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BCG – How Complicated Is Your Company?

  

Around the world, economic growth is slowing down. In developed and emerging economies alike, growth rates have declined considerably from their peaks, and there is little evidence that they will rise substantially any time soon. Anemic expansion of labor productivity is largely to blame. As Nobel Prize winner Paul Krugman wrote in The Age of Diminished Expectations, “Productivity isn’t everything, but in the long run it is almost everything. A country’s ability to improve its standard of living over time depends almost entirely on its ability to raise its output per worker.”

True, many factors can affect the rise and fall of labor productivity in the short term, including political instability, changing regulations, business cycles, technology investment, and the difficulty of improving the service sector’s productivity. But we believe that the underlying cause of the recent slowdown has been the ongoing, long-term rise of complicatedness, a phenomenon we first measured in one of our previous publications on Smart Simplicity, “Smart Rules: Six Ways to Get People to Solve Problems Without You.”1 We define complicatedness as the increase in organizational structures, processes, procedures, decision rights, metrics, scorecards, and committees that companies impose to manage the escalating complexity of their external business environment.

We recently surveyed executives and employees at more than 1,000 companies about their perceptions of the nature and degree of complicatedness at their organizations. The results highlight the strong connection between complicatedness and performance and indicate where companies should concentrate their efforts to simplify.

By Reinhard Messenböck , Yves Morieux , Jaap Backx , and Donat Wunderlich

More: www.bcg.com

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EY – Engineering the engineering org

How can companies design their engineering functions to strike the right balance between market responsiveness and operational efficiency?

Harnessing and optimizing engineering talent is paramount to success in the technology sector, but our experience has shown that there is no single way to accomplish this when it comes to designing an engineering organizational structure. Some structures optimize solution time-to-market, while others optimize operational efficiency. If an organization leans too far in either direction, it risks falling behind competitors in cost structure, innovation or speed-to-market. How can companies design their engineering functions to strike the right balance between market responsiveness and operational efficiency? It is worth noting that what is right for one company in its current form (stage in the product life cycle, competitive landscape, etc.) may not be right for another or for that same company five years from now. In short, there is no right structure — only the right structure at the right time for a given company.

Know your options. There are a wide variety of options when it comes to engineering organizational structures. For this analysis we have grouped them into three categories: vertically oriented, horizontally oriented and hybrid.

  1. Vertically oriented structure where engineering is part of each business unit (BU)
  2. Horizontally oriented structure where engineering is a stand-alone organization
  3. Hybrid structures that use hard and dotted lines to matrix engineers between an engineering organization and BUs

To assess where their company lies on this spectrum, executives can ask themselves questions such as:

  • Who is responsible for meeting customer demands and anticipating market trends?
  • Who owns the product line P&L? Who is responsible for prioritizing engineering investments?
  • Who is responsible for attracting, developing and retaining engineering talent?

by: Barak Ravid, Managing Director, EY Co-head of Technology; Contributors: Barak Ravid
Managing Director, Co-head of Technology, EY-Parthenon, Ernst & Young LLP; Spencer Lee, Vice President
EY-Parthenon, Ernst & Young LLP; Nina Lapachet, Senior Manager, Transaction Advisory Services, Ernst & Young LLP

More: EY

About EY. EY is a global leader in assurance, tax, transaction and advisory services. The insights and quality services we deliver help build trust and confidence in the capital markets and in economies the world over. We develop outstanding leaders who team to deliver on our promises to all of our stakeholders. In so doing, we play a critical role in building a better working world for our people, for our clients and for our communities. EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. For more information about our organization, please visit ey.com.