July 2018

Authors: Paula Garnero, Ana Inés Basco, Gustavo Beliz, and Diego Coatz.

Main Findings

1. The Algorithmic Factory. The Fourth Industrial Revolution (Industry 4.0) generates a cyber-physical amalgam that connects everything in real time: machine-to-machine, machine-to-product, and product-to-person.

This new era is characterized by the coexistence of a wide variety of technologies that blur the boundaries between the physical, digital, and biological worlds, creating a fusion among these three dimensions and driving a paradigm shift. It entails a transition toward new cyber-physical systems that operate through increasingly complex networks built upon the infrastructure established during the previous digital revolution (Klaus Schwab, 2016). The technological pillars of Industry 4.0 include cyber-physical integration systems; autonomous machines and systems (robots); the Internet of Things (IoT); additive manufacturing (3D printing); big data and advanced analytics; cloud computing; virtual environment simulation; artificial intelligence; cybersecurity; and augmented reality. The most profound transformation stems from digitalization and the ability to connect all social actors in real time through the Internet. Connectivity now extends to consumers, businesses, governments, and civil society organizations through devices such as smartphones, computers, sensors, and wearables, as well as information systems and digital platforms including e-commerce, e-government, and social networks.The defining feature of this era is that connectivity now extends to objects as well, enabling multiple forms of interaction: machine-to-machine (M2M), machine-to-product, machine-to-human, and product-to-human.

2. The Predictive Smart Factory. Companies integrate into networks and collaborate with other ecosystem stakeholders, establishing predictive models through high levels of automation, digitalization, and connectivity.

Organizations generate enormous amounts of data that, thanks to new computational systems and advanced algorithms, can be processed and analyzed with minimal human effort. This enables decentralized decision-making and a shift from preventive to predictive models that can be applied across all areas of the organization. These applications include supply chains, by adjusting input delivery times and minimizing inventory requirements; equipment failure detection systems, by eliminating preventive shutdowns and anticipating malfunctions; and logistics systems, by forecasting the demand for inputs and finished products and optimizing distribution and delivery. Furthermore, through integration systems and digital platforms, companies achieve both vertical and horizontal integration, improving individual productivity and the performance of the value chains in which they participate. They form dynamic networks and collaborate with other companies and ecosystem actors to strengthen innovation processes.

3. The Reinvention of Global Production Geography Has Uncertain Effects on International Trade.

Emerging technologies may encourage global firms to relocate production back to their home countries (reshoring) or decentralize production through distributed manufacturing, bringing manufacturing closer to consumption centers. New opportunities arise for SMEs, which, through small infrastructures distributed across urban areas, can manufacture intelligently and participate in decentralized manufacturing networks. Automation and robotics erode the traditional competitive advantages of countries based on low-cost labor, while the spread of ICTs and technologies such as cloud computing, IoT, and big data further reduce global coordination costs. Consequently, other competitiveness factors—including infrastructure, logistics, digital connectivity, energy costs, and a workforce equipped with Industry 4.0 skills—once again play a central role in global companies’ location decisions. In this context, some firms are reshoring production to their country or region of origin, while others are adopting distributed manufacturing models that enable them to produce closer to the end customer. In addition, broader access to technologies such as 3D printers, circuit printers, and Computer Numerical Control (CNC) systems reduces the importance of economies of scale in certain cases, allowing supply chain relationships to be reconfigured and opening new opportunities for SMEs. Although still in their early stages, these trends could soon alter the geography of global value chains (GVCs), as well as the volume and direction of international trade flows.

4. Disintermediated 360-Degree Business Models. Personalized products, platform products, smart products with embedded services, on-demand production, immediate response, production close to consumption centers, online stores, and open innovation platforms define the new business landscape.

Markets expand through e-commerce platforms, shortening the distance between manufacturers and consumers while creating a direct communication channel that previously did not exist. Intermediaries are reduced, and opportunities to create value through inventory accumulation are minimized. Customers become the focal point, and products are increasingly personalized. For manufacturing industries, the challenge is no longer simply to “produce more with fewer resources” or “sell more to increase market share.” The cycle is no longer limited to designing, producing, and selling; instead, interaction with future users allows products to be sold before they are manufactured. The new challenge is to capture the value generated through product use by transitioning from traditional products to “platform products.” The trend is toward manufacturing smart products that incorporate services. Access to products is increasingly prioritized over ownership. Through open innovation platforms, companies establish cooperative mechanisms that accelerate R&D&I outcomes.

5. Managing Improvisation and Innovation. In the “blind” transition toward the smart factory, companies manage their activities amid high levels of uncertainty. They often lack the capabilities required to analyze data and make decisions in a competitive and constantly changing environment.

The technological landscape evolves rapidly and continuously. Product life cycles are becoming significantly shorter; some goods quickly become obsolete while entirely new markets for goods and services emerge. The digitalization of the economy changes the rules of the game: companies have more information about their customers than ever before, but digitalization also enables new competitors to enter markets unexpectedly. As a result, businesses face growing, scalable competition and must make decisions based on vast amounts of data they often lack the capacity to interpret. Among 2,000 executives from nine industrial sectors across 26 countries, only 20% of industrial companies reported having advanced data analytics capabilities. Meanwhile, 51% believe it is necessary to develop these skills among their workforce to improve decision-making and reduce uncertainty.

6. Three-Dimensional Robotic Inequality. Robotics creates, destroys, and displaces jobs. The adoption of industrial robots is increasing, but it remains concentrated in a small number of countries and large companies.

Production automation is a growing global trend. Between 2010 and 2016, industrial robot production grew at an average annual rate of 12%, while the number of industrial robots per 10,000 workers increased from 66 to 74 units. Robotic capital is concentrated in a few countries and large enterprises, with the automotive industry being the leading adopter worldwide. Seventy-five percent of industrial robots are located in five countries: China, the United States, South Korea, Japan, and Germany, which are also the primary producers of this technology. The recent expansion of machines’ cognitive capabilities means that medium-complexity tasks can now be automated, leading to job losses and the displacement of workers into new occupations. However, the most automated economies also show positive rates of job creation, which may be explained by productivity gains generated through the adoption of new technologies.

7. Hybrid Soft-Hard Skills. Digitalization and technological intensity across industrial sectors affect both the skills demanded from workers and the wages they receive.

A study conducted by the G20 Digital Economy Task Force examined demand for nine cognitive, non-cognitive, and social skills: literacy, numeracy, ICT-related skills, STEM skills (science, technology, engineering, and mathematics), marketing and accounting, management and communication, problem-solving, self-organization, and willingness to learn. The study found that workers in digitally intensive industrial sectors possess higher levels of these skills on average than workers in less technology-intensive sectors and receive higher returns for their work. ICT skills, numeracy, quantitative STEM skills, self-organization, and management and communication skills appear to be especially valued and rewarded in the most digitalized sectors. Other studies also show increasing demand for engineering, software development, computer science, electronics, and data analytics, as well as non-technical skills such as critical thinking and creativity.

8. Collaborative Platforms as Spaces for Future Jobs. Entrepreneurs and startups are emerging within innovation ecosystems to accelerate projects, scale operations, and position themselves in the market.

The decomposition of work into tasks and the rise of the collaborative economy are reducing traditional salaried employment and creating new forms of work organization. As industries strive to digitalize their operations, companies increasingly interact with actors from the ICT sector. Through these interactions, technology providers gain access to valuable information related to businesses, production, and operations, combining it with their own expertise to develop targeted market solutions. Automation applied to administration and human resource management reduces the time and costs associated with hiring, facilitating task outsourcing. New business models, collaborative economy opportunities, and independent service-based work arrangements are reshaping the organization of work and labor relations. Remote software developers, IT professionals, and specialists from various disciplines working under freelance and gig economy arrangements are examples of these changes.

9. Multidimensional Challenges and the Reinvention of Models. Digital transformation challenges all social actors across multiple dimensions.

Technological challenges include standardizing interfaces, improving autonomous decision-making systems, developing infrastructure capable of handling large volumes of data, and strengthening cybersecurity. Socioeconomic challenges include preventing the concentration of new technologies among a few firms, ensuring universal digital literacy, developing workforce skills aligned with new demands, monitoring labor market impacts—particularly income inequality between men and women—and reducing the gender digital divide. Regulatory challenges include establishing new governance frameworks for data security and ownership, new markets and forms of work, intellectual property, national security, digital currencies, and bioethics.

10. From Comparative and Competitive Advantages to Innovative Advantages. The Fourth Industrial Revolution poses particular challenges for emerging economies. It shifts competitiveness away from low labor costs and natural advantages while increasing the importance of productive ecosystems and human capital.

The widespread adoption of new technologies challenges established patterns of comparative advantage, reducing the relative importance of wage competitiveness. The need for more sophisticated ecosystems in terms of infrastructure, logistics, human resources, regulatory frameworks, supplier networks, and related factors increases the challenges faced by most developing countries. Trade is increasingly shifting toward digital goods and services, while knowledge-intensive trade flows are growing approximately 30% faster than capital- and labor-intensive trade flows (OECD, 2016). Labor markets are being affected, while providers of intellectual and robotic capital—primarily concentrated in developed countries—benefit disproportionately. Key challenges for emerging economies include reducing the digital gap with developed countries, promoting the adoption of Industry 4.0 technologies, establishing new strategies for integration into global value chains, improving collaboration between scientific communities and productive sectors, strengthening local innovation ecosystems, and fostering the emergence of new actors and markets.

11. From “Made in Argentina” to “Created in Argentina”. The adoption of new technologies is on corporate agendas, although implementation remains limited and varies according to company size.

Thirty-four percent of Argentine companies plan to adopt all Industry 4.0 technologies within the next five years, compared with more than 70% in Germany and France. Nevertheless, 76% of respondents acknowledge that their company’s transition toward Industry 4.0 is a topic of discussion among senior management. The main barriers to implementation are: (1) a shortage of qualified personnel (70% of responses); (2) uncertainty regarding the return on investment (65%); and (3) resistance to change and innovation (64%). In contrast, companies such as Tenaris and Sinteplast demonstrate significant levels of new technology adoption. Tenaris exemplifies vertical information exchange and collaboration within a value chain through supplier-customer integration.

Sinteplast promotes horizontal information exchange and collaboration by integrating with other leading paint manufacturers to develop new products.

12. Multi-Speed Industry 4.0 Immersion. Argentina’s most competitive and export-oriented sectors show higher levels of Industry 4.0 technology adoption, widening productivity gaps with non-tradable sectors.

Experts emphasize that industrial digitalization represents a new opportunity for intelligent integration into international trade flows. Industry could regain leadership by generating employment, adding value, participating in global value chains, and driving innovation processes.

Achieving this requires a new synthesis among the three pillars of the economic structure—natural resources, industrial capabilities, and the scientific and technological system—while maintaining a stable macroeconomic environment. Argentina should not limit itself to being a user of new technologies; it can become a producer of specialized technological solutions. Biotechnology and targeted industrial policies, such as the State Supplier Development Program and the recent “Buy Argentine” Law, stand out as drivers of industrial transformation. At the regional level, Brazil offers several examples of companies and sectors evolving toward Industry 4.0 and demonstrates the importance of corporate leadership in identifying innovation opportunities and developing new business models.

13. Exponential Examples. The case studies of Tenaris and Sinteplast demonstrate significant adoption of Industry 4.0 technologies, customer-oriented business models, and successful innovations achieved through collaborative strategies.

For more than twenty years, Tenaris has worked collaboratively with YPF to provide just-in-time pipe supply solutions. Building on this experience, the company developed Rig Direct in 2015, a platform product offered globally that reduces working capital requirements across the sector.

Tenaris exemplifies vertical information exchange and collaboration within a value chain through supplier-customer integration. In its effort to reduce inventories and delivery times, Sinteplast operates with high levels of automation and digitalization. The company also participates in various global organizations within the paint manufacturing industry, enabling it to accelerate innovation processes. Sinteplast exemplifies horizontal information exchange and collaboration through integration with other leading paint manufacturers to develop new products.

14. A-Squared (A2): Automated Automotive. The automotive sector exemplifies, in every dimension, how traditional industry is evolving toward Industry 4.0.

The sector has a long tradition of early adoption of new technologies and accounts for the largest stock of robotic capital worldwide, with a recent and significant shift toward collaborative robots.

The global value chain of the automotive industry demonstrates historically high levels of vertical integration and extensive collaboration among stakeholders—features that have been further strengthened through digitalization. The Fourth Industrial Revolution challenges automakers to become “mobility service providers,” leaving behind the traditional Industry 3.0 business model.

Flexible production lines and connected, customized vehicles are becoming standard trends among manufacturers. At the same time, automotive companies face the challenge of competing or cooperating with new players, including telematics providers, content providers, big data firms, telecommunications companies, and insurers. Looking ahead, the sector’s most significant transformations are expected to arise from business models centered on access rather than ownership, together with the growing adoption of highly disruptive technologies such as machine learning and big data analytics. These developments could lead to entirely new driving experiences and, ultimately, autonomous driving. This transition will reshape profit distribution within the industry: the share of digital services in automotive industry profits is expected to increase from 4% in 2015 to 36% by 2030.

15. Industry 4.0 Remains an Emerging and Fragmented State Matter. Globally, governments are increasingly developing strategies to promote the transition toward Industry 4.0, although most initiatives remain focused on expanding access to and dissemination of ICTs.

Governments face the challenge of ensuring universal access to new technologies, reducing undesirable effects related to economic concentration and social inequality, and establishing standards and regulatory frameworks that encourage the emergence of new actors and markets.

However, because these technologies are still emerging, there are no proven formulas that guarantee success, especially given the different starting points among countries. Only a limited number of countries have redefined their industrial policies in response to the new context of the Fourth Industrial Revolution; many more focus primarily on promoting access to ICTs.

This study examined the policies adopted by Germany and Mexico. Germany was the first country to recognize the impact of digitalization and develop a long-term strategy to strengthen competitiveness in this new environment, becoming a global benchmark for Industry 4.0.

Mexico was the first Latin American country to outline a strategy in this direction. In 2016, it developed a roadmap to guide the digitalization of its industrial sector.

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