Trends Identified
The Rise of Messaging
Say hello to a new age of conversation with Facebook Messenger.
2018
Most contagious report 2018
Contagious
Master the new logic of competition
Internet and mobile technology ushered in the information age and profoundly affected technology-intensive and consumer-facing industries such as electronics, communications, entertainment, and retail. But the emerging wave of technology—including sensors, the Internet of Things, and artificial intelligence—will turn every business into an information business. The combination of an exponential increase in data, better tools to mine insights from that data, and a fast-changing business environment means that companies will increasingly need to, and be able to, compete on the rate of learning. Scale will take on a new significance in the learning economy. Instead of the “economies of scale” that today’s leaders grew up with—based on a predictable reduction of marginal production costs across a relatively uniform offering—tomorrow’s leaders will pursue “economies of learning,” based on identifying and fulfilling each customer’s changing needs by leveraging data and technology. The arenas of competition will also look different in the 2020s, requiring new perspectives and capabilities. The familiar picture of a small number of companies producing a common end product and competing within well-defined industry boundaries will be replaced by one where competition and collaboration occur within and between ecosystems. Because ecosystems are fluid and dynamic, and not perfectly controllable even by the orchestrator, companies will need to be much more externally oriented, to deploy influence indirectly through platforms and marketplaces, and to coevolve with ecosystem partners. Orchestrators of ecosystems can leverage the assets of other participants, and ecosystem-based competition tends to have a winner-take-all nature. These factors are already causing rapidly rising valuations relative to tangible assets for the top companies, as well as an increasing gap between the profitability of high and low performers. But there is not yet any playbook for how to harness this premium: practice is racing ahead of theory, and pioneers who can crack the code on ecosystems will be greatly advantaged. Finally, companies will increasingly compete on resilience. Accelerating technological change, political gridlock, a shifting geopolitical power map, the increased scrutiny of business, and the polarization of society all point to an era of protracted uncertainty, in which corporate life cycles are likely to continue shrinking. Companies will therefore need to worry not only about the competitiveness of their immediate game but also about the durability of that game and their ability to weather unanticipated shocks. Most of today’s incumbents—designed for relatively stable, classical business environments—are not well adapted for this more dynamic environment. Therefore, today’s leaders need to fundamentally reinvent the organizational model in order to become future winners.
2018
Winning the ’20s: A Leadership Agenda for the Next Decade
Boston Consulting Group (BCG)
Design the organization of the future
Big data and deep learning have transformed our ability to learn, and the next generation of technologies will undoubtedly bring even more possibilities. History has shown, however, that applying new technologies to existing processes and structures generally yields only incremental gains. To unlock the learning potential of new technologies, leaders need to reinvent the enterprise as a next-generation learning organization.Merely applying AI to individual process steps is not enough: To increase the ability of organizations to learn in aggregate, they must build integrated learning loops that gather information from data ecosystems, continuously derive insights using machine learning, and act on those insights autonomously, all at the speed of algorithms rather than the speed of human hierarchies. But organizations must not learn only on algorithmic timescales—they must also better understand and position themselves for the slow-moving forces, such as social and political shifts, that are increasingly transforming business. To learn on multiple timescales, leaders will need to design organizations that synergistically combine humans and machines. Algorithms should be trusted to recognize patterns in data and act on them autonomously, while humans should focus on higher-order tasks like validating algorithms, imagining new possibilities, and designing and updating the hybrid “human + machine” organization itself. This division of labor also requires rethinking human–machine interfaces so that humans can trust and productively interact with machines. Collectively, these imperatives demand a massive evolution of organizational capabilities and the creation of new “learning contracts” between employees and enterprises. Many of these principles are already being implemented in isolated domains, such as the operations of digital marketplaces. But to win the ’20s, the same principles must be applied to all parts of the organization in order to create a “self-tuning enterprise” that constantly learns and adapts to the environment. Such organizations must be designed with flexible backbone systems, evolving business models, and, above all, a new model of management—one based on biological principles such as experimentation and co-evolution, rather than traditional top-down decision making and slow cycle planning. Management needs to shift its emphasis from designing hardwired structures and procedures to orchestrating flexible and dynamic systems.
2018
Winning the ’20s: A Leadership Agenda for the Next Decade
Boston Consulting Group (BCG)
Apply the science of organizational change
Reinventing organizations to compete in the 2020s will not be a trivial task. Whether because of risk aversion or complacency stemming from today’s increasingly concentrated industries and elevated profitability levels, leading companies may be understandably reluctant to unleash fundamental change preemptively. But our research shows that the single biggest factor influencing the success of major change programs is how early they are initiated. It is therefore critical to create a sense of urgency within the organization to ensure that everyone truly understands the need for change. Even for companies that are committed to such transformation, it can be a risky endeavor: our research shows that most large-scale change efforts fail. Therefore, leaders need to employ evidence-based transformation—understanding empirically what works and why, rather than relying on plausible assertions and rules of thumb. In an era when many powerful forces are revolutionizing how organizations function, building repeatable transformation capabilities will be more important than ever. Leaders also need to de-average and differentiate their approaches to change. Large-scale transformation programs comprise multiple change challenges, from exploring new fields and approaches, to adaptively refining new models, to implementing structured change with clear objectives and means. Leaders will need to diversify their approaches to change accordingly, moving beyond the monolithic programs centered only on PMOs and Gantt charts. By adopting continuous change as the default, episodic change programs will give way to change as an ongoing operating imperative.
2018
Winning the ’20s: A Leadership Agenda for the Next Decade
Boston Consulting Group (BCG)
Achieve innovation and resilience through diversity
Diversity is not only a moral imperative—it can also make businesses more effective in the long run. Our study of more than 1,700 companies around the world shows that diversity increases the capacity for innovation by expanding the range of a company’s ideas and options. And as the speed of change accelerates, innovation and reinvention are increasingly necessary to stay on top. The most obvious sources of diversity, such as gender, ethnicity, and sexual orientation, are indeed important in driving innovation, but variety of work experience and educational background is also meaningful. Importantly, these factors are mostly additive, so companies that are diverse on multiple dimensions are even more innovative. Structural diversity alone, however, is insufficient. Organizations also need an environment conducive to embracing new ideas, and they must install open communication practices, participative leadership, commitment to building diversity in top management, openness to testing multiple ideas, and other measures to unlock the full potential of diversity. Diversity also increases resilience. Like biological communities and organisms, companies that encompass more heterogeneity are likely to withstand unanticipated changes better. Enterprises that embrace diverse talent, ideas, and sources of growth will have an advantage in understanding and adapting to external shocks—which increasingly threaten the survival of individual businesses.
2018
Winning the ’20s: A Leadership Agenda for the Next Decade
Boston Consulting Group (BCG)
Optimize for both social and business value
Several trends are fueling resentment toward business. The climate crisis and other negative externalities are increasingly visible, automation is sparking fear about the future of work, trust in technology is falling, inequality has risen markedly within many countries, and the most successful companies are becoming larger, more visible, and more powerful. As a result, the role of business in society is coming under question, risking the sustainability of the current model of corporate capitalism. Political institutions are not likely to address these concerns effectively in the foreseeable future. Demographics that portend lower global growth, massive public debts that limit investment, tensions resulting from international migration, and a social media landscape that amplifies extreme voices are all likely to continue fueling divisive, populist politics. The rise of China, and the growing US response, challenge the stability of multinational institutions that businesses rely on. In an era characterized by polarization, everything in business will likely become “political.” To keep the game of business going, business needs to be part of the solution. All stakeholders increasingly expect companies to play a more prominent role in addressing social challenges, which will be reinforced as newly adopted metrics and standards make their efforts and impacts more transparent. Leaders need to focus on their companies’ total societal impact—in other words, they need to make sure that their businesses create social as well as economic value. Not only can this increase financial performance in the long run, but it can strengthen the social contract between business and society, ensuring that the relationship is able to endure. Leaders will need to master the art of corporate statesmanship, proactively shaping the critical societal issues that will increasingly change the game of businesses.
2018
Winning the ’20s: A Leadership Agenda for the Next Decade
Boston Consulting Group (BCG)
Deep learning accelerators
Deep learning accelerators such as GPUs, FPGAs, and more recently TPUs. More companies have been announcing plans to design their own accelerators, which are widely used in data centers. There is also an opportunity to deploy them at the edge, initially for inference and for limited training over time. This also includes accelerators for very low power devices. The development of these technologies will allow machine learning (or smart devices) to be used in many IoT devices and appliances.
2018
IEEE Computer Society Predicts the Future of Tech: Top 10 Technology Trends for 2019
IEEE Computer Society
Assisted transportation
While the vision of fully autonomous, self-driving vehicles might still be a few years away, increasingly automated assistance is taking place in both personal and municipal (dedicated) vehicles. Assisted transportation is already very useful in terms of wide recognition and is paving the way for fully autonomous vehicles. This technology is highly dependent on deep learning accelerators (see #1) for video recognition.
2018
IEEE Computer Society Predicts the Future of Tech: Top 10 Technology Trends for 2019
IEEE Computer Society
The Internet of Bodies (IoB)
IoT and self-monitoring technologies are moving closer to and even inside the human body. Consumers are comfortable with self-tracking using external devices (such as fitness trackers and smart glasses) and with playing games using augmented reality devices. Digital pills are entering mainstream medicine, and body-attached, implantable, and embedded IoB devices are also beginning to interact with sensors in the environment. These devices yield richer data that enable more interesting and useful applications, but also raise concerns about security, privacy, physical harm, and abuse.
2018
IEEE Computer Society Predicts the Future of Tech: Top 10 Technology Trends for 2019
IEEE Computer Society
Social credit algorithms
These algorithms use facial recognition and other advanced biometrics to identify a person and retrieve data about that person from social media and other digital profiles for the purpose of approval or denial of access to consumer products or social services. In our increasingly networked world, the combination of biometrics and blended social data streams can turn a brief observation into a judgment of whether a person is a good or bad risk or worthy of public social sanction. Some countries are reportedly already using social credit algorithms to assess loyalty to the state.
2018
IEEE Computer Society Predicts the Future of Tech: Top 10 Technology Trends for 2019
IEEE Computer Society