Τεχνολογική Στρατηγική

Η ιστορική εξέλιξη των αεροδρομίων. Τεχνολογία, οικονομία, κοινωνία σε αλληλεπίδραση.

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• πώς αλλάζουν οι κανόνες του παιχνιδιού;
• πώς η τεχνολογία επηρεάζει την αξία και την ανταγωνιστικότητα των προϊόντων;
• πως επιδρούν διαφορετικές τεχνολογίες (ψηφιακή, βιοτεχνολογία, υλικά κλπ.);

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“Digitization is important but we are not prepared enough,”—this is one of the key findings from a survey among more than 300 industrial decision-makers in the US, Japan, and Germany on the status of digitization, their expectations on productivity within this field, and the challenges they see. Along with these results, the report discusses the different options company leaders can choose from to make the best out of their companies’ current starting position.

Modularization excels in high-volume industries such as automotive, but does it offer tangible benefits for companies that tackle just a few, extremely complicated projects each year? The builders of steel plants, chemical plants, paper mills, wind parks, packaging lines, or power plants fall into this category, completing a handful of highly specialized solutions every year that feature very specialized components. New research—laid out in our report Smart platforms: Cracking the complexity challenge of project industries—affirms that, if done right, a modular platform strategy can deliver significant value quickly in these situations to fix the complexity challenge

We present a framework, called the Risk-Reward Nexus, to study the relationship between innovation and inequality. We ask the following question: What types of economic actors (workers, taxpayers, shareholders) make contributions of effort and money to the innovation process for the sake of future, inherently uncertain, returns? Are these the same types of economic actors who are able to appropriate  returns from the innovation process if and when they appear? That is, who takes the risks and who gets the rewards? We argue that it is the collective, cumulative, and uncertain characteristics of the innovation process that make this disconnect between risks and rewards possible. We conclude by sketching out key policy implications of the Risk-Reward Nexus approach.

What can we learn from the history of technological revolutions? Why is there so much populism now? Why do we experience major financial bubbles? And how to move towards a green global golden age of the information revolution? Carlota Perez, one of the world’s foremost experts on the impact of technical change on the economy, discusses these questions in the first episode of TheOtherSchool series. Carlota Perez is a Professor at TalTech, Estonia, and an Honorary Professor at University College London, UK.

Perez, C. and Soete L. (1988) "Catching up in technology: entry barriers and windows of opportunity". In G.Dosi et al. eds. Technical Change and Economic Theory, London: Francis Pinter, pp. 458-479.

Creative destruction plays a key role in entrepreneurship and economic development.

Coined by economist Joseph Schumpeter in 1942, the theory of “creative destruction” suggests that business cycles operate under long waves of innovation. Specifically, as markets are disrupted, key clusters of industries have outsized effects on the economy.

Take the railway industry, for example. At the turn of the 19th century, railways completely reshaped urban demographics and trade. Similarly, the internet disrupted entire industries—from media to retail.

The infographic shows how innovation cycles have impacted economies since 1785, and what’s next for the future.

If the future of computing is anything like its past, then its trajectory will depend on things that have little to do with computing itself. 

Technology does not appear from nowhere. It is rooted in time, place, and opportunity. No lab is an island; machines’ capabilities and constraints are determined not only by the laws of physics and chemistry but by who supports those technologies, who builds them, and where they grow. 

Cognitive technologies are increasingly being used to solve business problems; indeed, many executives believe that AI will substantially transform their companies within three years. But many of the most ambitious AI projects encounter setbacks or fail.

A survey of 250 executives familiar with their companies’ use of cognitive technology and a study of 152 projects show that companies do better by taking an incremental rather than a transformative approach to developing and implementing AI, and by focusing on augmenting rather than replacing human capabilities.

Broadly speaking, AI can support three important business needs: automating business processes (typically back-office administrative and financial activities), gaining insight through data analysis, and engaging with customers and employees. To get the most out of AI, firms must understand which technologies perform what types of tasks, create a prioritized portfolio of projects based on business needs, and develop plans to scale up across the company.

• Why Every Organization Needs an Augmented Reality Strategy by Michael E. Porter and James E. Heppelmann

• How Does Augmented Reality Work? - The key is a digital twin.

• Augmented Reality in the Real World - Companies are investing and testing.

• One Company’s Experience with AR - A conversation with ABB’s chief digital officer, Guido Jouret by Gardiner Morse

• The Battle of the Smart GlassesMoney is pouring into development

Approximately 150 million people in North America and Western Europe now work as independent contractors, most of them in knowledge-intensive industries and creative occupations. The authors studied 65 of them in depth and learned that although they feel a host of personal, social, and economic anxieties without the cover and support of a traditional employer, they also say they chose independence and wouldn’t give up the benefits that come with it.

Many of these workers have created a “holding environment” for themselves by establishing four connections: (1) place, in the form of idiosyncratic, dedicated workspaces that allow easy access to the tools of their owners’ trades; (2) routines that streamline workflow and incorporate personal care; (3) purpose, to create a bridge between personal interests and motivations and a need in the world; and (4) people to whom they turn for reassurance and encouragement. These connections help independent workers sustain productivity, endure their anxieties, and even turn those feelings into sources of creativity and growth.

Why do some transformative technologies dominate the market quickly, while others take decades to catch on? It’s a function not just of the technologies themselves, say the authors, but also of their broader ecosystems (electric cars, for example, need a network of charging stations). The ecosystems of the legacy technologies matter too—they can sometimes be improved enough to prolong the life of the old technology.

http://digitalstrategies.tuck.dartmouth.edu/wp-content/uploads/2016/12/Adner-Kapoor-HBR-2016-RIght-Tech-Wrong-Time-how-to-make-sure-your-ecosystem-is-ready-for-the-newest-technologies.pdf

Baldwin & von Hippel, (2011) Modeling a Paradigm Shift: From Producer Innovation to User and Open Collaborative Innovation, Organization Science 22(6):1399-1417

In this paper, we assess the economic viability of innovation by producers relative to two increasingly important alternative models: innovations by single-user individuals or firms and open collaborative innovation. We analyze the design costs and architectures and communication costs associated with each model. We conclude that both innovation by individual users and open collaborative innovation increasingly compete with and may displace producer innovation in many parts of the economy. We explain why this represents a paradigm shift with respect to innovation research, policy making, and practice. We discuss important implications and offer suggestions for further research.

A lot of positive hype has built up around Industry 4.0 over the last few years, creating aware-ness of the topic within many companies and contributing significantly to the rejuvenation of “good old industry” in the public mind. In its aftermath, industry leaders remain optimistic overall, but a degree of disillusionment has also crept in as the actual implementation results so far are mixed.

On the one hand, we still see high uncertainty among manufacturers regarding what implement-ing Industry 4.0 really requires of them – and many are still struggling to even get started. On the other hand, most technology suppliers have moved relatively fast in adjusting their portfolios towards Industry 4.0. We are also seeing a growing number of manufacturers report substantial progress, especially when moving beyond the Industry 4.0 umbrella term and focusing on valuable, business-specific applications. To get there, many clients have told us they have even renamed their “Industry 4.0” projects to shake off an initial sense of disillusion-ment while keeping the elements that created true value.

To take stock of these complex and diverse developments and shed light on why some players are making progress while others are not, McKinsey has repeated its Industry 4.0 Global Expert Survey, exploring changes in attitudes towards Industry 4.0 and progress made in its implemen-tation. In the first part of this publication, we draw upon the survey results to present and discuss the status quo of the implementation of Industry 4.0 along three dimensions:

• Perception. To what extent have attitudes towards Industry 4.0 changed over the last year?
• Progress. How much progress have companies made in implementing Industry 4.0? Which Industry 4.0 applications have companies had the most success implementing?
• Problems. What are the key barriers to implementation that held back manufacturers?

In the second part of the publication, we will build on these insights, as well as on selected case studies and our own experience from client work, to outline five pragmatic steps that manu-facturers can take to unlock value from Industry 4.0.

Modular platform strategies – originally developed and used by high-volume automotive players – can drive value in complex, project-based industries as well.

Modularization excels in high-volume industries such as automotive, but does it offer tangible benefits for companies that tackle just a few, extremely complicated projects each year? The builders of steel plants, chemical plants, paper mills, wind parks, packaging lines or power plants fall into this category, completing a handful of highly specialized solutions every year that feature very specialized components. McKinsey & Company research affirms that, if done right, a modular platform strategy can deliver significant value quickly in these situations to fix the complexity challenge.

Twelve emerging technologies—including the mobile Internet, autonomous vehicles, and advanced genomics—have the potential to truly reshape the world in which we live and work. Leaders in both government and business must not only know what’s on the horizon but also start preparing for its impact.

In a study of innovations developed by mountain bikers, we find that user-innovators almost always utilize "local" information - information already in their possession or generated by themselves - to assess the need for and to develop solutions for their innovations. We argue that this finding fits the economic incentives operating on users. Local need information is the most relevant to user-innovators, since the bulk of their innovation-related rewards typically come from in-house use. Local solution information that is already "in stock" is preferred because it can be applied to innovation-related problem-solving at a relatively low cost. Our findings suggest that innovation development is distributed among users in an economical way: user-innovations tend to be developed by "low-cost providers." It also suggests that the likely function and solution type employed in most user innovations can be predicted on the basis of preexisting user activity patterns and stocks of solution-related information. This in turn opens the way to new methods for efficiently screening user populations for the presence of innovations of any specified type

Advances in science and technology have created promising new opportunities for industries and economies to create value, which also have made them more complex as innovations can contain specialized knowledge from various disciplines. The chapter presents a general discussion pointing to the increased distribution of innovation activities in society due to digitalization and IT advances.The purpose of this case is to explore how generativity relates to open innovation ecosystems. More specifically we address the question of how generative capacity attracts external actors to contribute with extensive value. The casesets out to explore the proposed shift in power relations among actors in such value ecosystems, and investigate the role of suppliers and complementors within distributed and innovation processes. To discuss these areas, we will draw on a comparative case study of two smartphone platforms ±theiPhoneandAndroid.The smartphone industry, as well as the two cases, was selected to highlight new forms of external involvement. The two cases have similarities but also differences in how they approach generativity.

The process of user-centered innovation: how it can benefit both users and manufacturers and how its emergence will bring changes in business models and in public policy.Innovation is rapidly becoming democratized. Users, aided by improvements in computer and communications technology, increasingly can develop their own new products and services. These innovating users—both individuals and firms—often freely share their innovations with others, creating user-innovation communities and a rich intellectual commons. In Democratizing Innovation, Eric von Hippel looks closely at this emerging system of user-centered innovation. He explains why and when users find it profitable to develop new products and services for themselves, and why it often pays users to reveal their innovations freely for the use of all.The trend toward democratized innovation can be seen in software and information products—most notably in the free and open-source software movement—but also in physical products. Von Hippel's many examples of user innovation in action range from surgical equipment to surfboards to software security features. He shows that product and service development is concentrated among "lead users," who are ahead on marketplace trends and whose innovations are often commercially attractive.Von Hippel argues that manufacturers should redesign their innovation processes and that they should systematically seek out innovations developed by users. He points to businesses—the custom semiconductor industry is one example—that have learned to assist user-innovators by providing them with toolkits for developing new products. User innovation has a positive impact on social welfare, and von Hippel proposes that government policies, including R&D subsidies and tax credits, should be realigned to eliminate biases against it. The goal of a democratized user-centered innovation system, says von Hippel, is well worth striving for. An electronic version of this book is available under a Creative Commons license.